Precise gene regulation through transcriptional repression is essential for Plasmodium berghei asexual blood stage development

Domain: biology
Published: 2026-01-03
Editorial outcome: accept

Abstract
Malaria is caused by the proliferation of Plasmodium parasites in the vertebrate bloodstream through repeated cycles of asexual multiplication inside erythrocytes. During these cycles, parasites dynamically change their transcriptome at each developmental step to express genes exactly when required; however, the mechanisms regulating these transcriptomic changes remain unclear. In this study, we reveal that the AP2-family transcription factor PbAP2-TR is essential for the asexual blood stage development of the rodent malaria parasite Plasmodium berghei, as a transcriptional repressor. Conditional knockout of pbap2-tr causes developmental arrest at the trophozoite stage, i.e., the cell growth phase of asexual blood stage development. The expression of PbAP2-TR target genes is upregulated in pbap2-tr-knockout parasites, and introduction of mutations into the binding motifs increases the promoter activity of the target genes. Time-course transcriptome analysis shows that PbAP2-TR is largely responsible for the transcriptional down-regulation from early to late trophozoite development. Furthermore, our data demonstrate that PbAP2-TR recruits a putative chromatin remodeler, PbMORC, as a co-factor. These results indicate that transcriptional repression by PbAP2-TR-PbMORC complex contributes on precise control of transcription peak patterns during the asexual blood stage development.

Introduction
Plasmodium is the causative agent of malaria, which is one of the most serious infectious diseases worldwide1. The parasite proliferates in host blood through repeated cycles of red blood cell (RBC) invasion by a specific invasive stage called the merozoite and asexual replication inside host RBCs2–4. Intraerythrocytic asexual development can be divided into three stages: ring, trophozoite, and schizont5. The ring stage, which is the first developmental stage formed after merozoite invasion, is characterized by a biconcave disc shape6. At the ring stage, the expression of exported proteins is upregulated to modify the host cell into a parasite-favorable environment7. The next developmental stage, trophozoite, grows rapidly with an elevated uptake of host-derived nutrients, including hemoglobin, which is a source of amino acids8,9. For rapid cell growth, gene transcription becomes considerably more active during the trophozoite stage than during the ring stage10. The parasite then develops into the schizont stage, which undergoes a unique mode of cell division called schizogony11,12. In schizonts, several rounds of asynchronous nuclear division occur while merozoite components, such as the rhoptry and inner membrane complex (IMC), are generated13. Finally, multiple progeny merozoites are formed through segmentation simultaneously with a final round of nuclear division.

As the asexual blood stage development proceeds, the parasite dynamically alters gene expression. Time-course transcriptome analyses using microarray and steady-state RNA sequencing (RNA-seq) have shown that the transcript levels of genes that have a common functional role show similar peak patterns in the course of the intraerythrocytic developmental cycle (IDC)14–16. Such temporal changes in gene transcription largely appear as the cascade of transcriptional activation to express genes just when they are required, i.e., “just-in-time” transcription. Concordant with the transcription peak patterns, nucleosome-free or nucleosome-depleted regions, which indicate active transcription sites, are also periodically established17. Furthermore, a recent study indicated the essentiality of chromatin remodelers for the “just-in-time” regulation of gene expression during the asexual blood stage development18. These suggest that regulation at the transcriptional level is important for IDC progression; thus, investigating the mechanisms that underlie this periodic transcriptional regulation is very important to obtain a deep understanding of parasite asexual proliferation in the host blood.

Plasmodium spp. have a limited number of sequence-specific transcription factors encoded in their genome. These transcription factors are mainly AP2 family proteins, which are homologues of the plant APETALA2/Ethylene Response Factor (AP2/ERF) and contain one to three DNA-binding domains called AP2 domains19. In previous studies, several stage-specific transcription factors have been explored, and extensive progress has been particularly made regarding the development of invasive and sexual stages20. At these stages, transcriptional activation of stage-specific genes is controlled by a few sequence-specific transcription factors and their corresponding binding motifs. For the asexual blood stage development, two transcriptional activators have been reported, PfAP2-I and PbSIP221,22. PfAP2-I is expressed from trophozoites to early schizonts, and targets invasion-related genes during the schizont stage. PbSIP2 functions as a master regulator essential for merozoite formation, comprehensively activating genes related to merozoite formation, such as genes related to the rhoptry, microneme, and IMC. Meanwhile, transcription factors that control transcriptomic changes during the other stages of the IDC, i.e. ring and trophozoite stages, have not been identified, and the mechanism regulating the transcription peak patterns for each gene remains largely unknown.

To advance our knowledge of transcriptional regulation during the IDC, we focused on AP2 transcription factor genes that could not be knocked out during the IDC of P. berghei. Here, we demonstrate that the AP2 family transcription factor, PbAP2-TR (Trophozoite Repressor, PBANKA_0909600), functions as a transcriptional repressor essential for trophozoite development. Our data reveal that PbAP2-TR represses the transcription of its target genes during trophozoite development and controls their transcriptional profiles. Furthermore, we show that PbAP2-TR recruits a putative chromatin remodeler, PbMORC, as a possible co-factor for the transcriptional repression of target genes.

Results
PbAP2-TR is an AP2 transcription factor expressed in trophozoites
PbAP2-TR is an AP2-family transcription factor that possesses three conserved AP2 domains (Fig S1A). The first (position 182–235) and second (position 279–325) AP2 domains are located in tandem near the N-terminus, and the third (position 1474–1522) domain is located towards the C-terminus. When the amino acid (AA) sequences of the tandem AP2 domains were aligned among PbAP2-TR orthologs in Plasmodium species, both the AP2 domains and the linker between them were found to be highly conserved (96% and 87% for the first and second AP2 domains, respectively; 81% for the linker) (Fig S1B). For the third AP2 domain of PbAP2-TR, the AA sequences were completely conserved within Plasmodium (Fig S1C). In addition to these AP2 domains, PbAP2-TR contains a conserved AP2-coincident domain mostly at the C-terminus (ACDC) and a putative nuclear localization signal (NLS) at position 1139–1151 (Fig S1A).

We first attempted to generate pbap2-tr-knockout parasites using conventional homologous recombination23 but failed to obtain mutant parasites. This was consistent with previous knockout screening studies on rodent malaria parasites24–26. These results indicate that pbap2-tr is essential for asexual blood stage development. To evaluate at which cell-stage PbAP2-TR functions during intraerythrocytic development, we assessed the PbAP2-TR expression pattern. We generated a parasite line expressing GFP-fused PbAP2-TR (PbAP2-TR::GFP, Fig S2) using the Cas9-expressing parasite, PbCas927, and performed a time-course fluorescent analysis. The cell cycle was synchronized to mature schizonts by incubating PbAP2-TR::GFP-infected blood in culture for 16 h, and the cultured schizonts were then intravenously injected into mice. A nuclear-localized GFP signal was first observed in early trophozoites at 8 h post-injection (hpi) (Fig. 1A). The signal continued to be observed for the late trophozoites in the peripheral blood (Fig. 1A). As late asexual blood stages are rarely observed in peripheral blood owing to sequestration, we further performed fluorescence analysis on cultured PbAP2-TR::GFP. In the culture, mononuclear parasites showed nuclear-localized GFP signals, as observed in peripheral blood; however, the signal was considerably weaker in schizonts with two nuclei. Furthermore, later schizonts showed no GFP signal (Fig. 1A). These results indicate that PbAP2-TR is a trophozoite-specific transcription factor.

Disruption of pbap2-tr results in developmental arrest at the trophozoite stage
As gene disruption of pbap2-tr was unsuccessful, we performed a conditional knockout of pbap2-tr to assess the role of PbAP2-TR. We employed a previously reported dimerizable Cre (DiCre) system28,29 using a parasite line that constitutively expressed Cas9 and DiCre (PbCas9DiCre)22. Two loxP sequences were each introduced to the 5′ and 3′ sides of pbap2-tr, arranged in the same direction (pbap2-tr-DiCre, Fig S3A), for removing the pbap2-tr locus in a rapamycin-dependent manner (Fig. 1B). For the conditional knockout, whole blood was harvested from mice infected with pbap2-tr-DiCre and split into two cultures (Fig. 1C). At the beginning of the culture, rapamycin was added to one culture (final concentration, 30 nM) (pbap2-tr-DiCreRapa+), and dimethyl sulfoxide (DMSO) was added to the other (pbap2-tr-DiCreRapa-) as a control (Fig. 1C). After 16 h of culture, genotyping PCR confirmed that the pbap2-tr locus was almost completely excised from the genome of pbap2-tr-DiCreRapa+, with only a subtle signal for the wild-type (WT) pbap2-tr locus (Fig. 1D). To assess the effect of pbap2-tr-disruption, mature schizonts of pbap2-tr-DiCreRapa+ and pbap2-tr-DiCreRapa- were inoculated into mice (Fig. 1C). The parasites were then cultured at 10 hpi, and parasite development was assessed by Giemsa-staining every four hours (Fig. 1C). In the cultures, pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ showed similar ring-to-trophozoite ratios until 18 hpi (Fig. 1E). In addition, the average size of trophozoites at 18 hpi was comparable between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ with a diameter of approximately 4.4 μm (Fig. 1F). However, at 22 hpi, the schizont ratio reached 20% in pbap2-tr-DiCreRapa-, whereas most of the pbap2-tr-DiCreRapa+ parasites remained as mononuclear cells (schizont ratio: 0.6%) (Fig. 1E). Furthermore, the ratio of schizonts in pbap2-tr-DiCreRapa+ was still less than 3% at 26 hpi, whereas that in pbap2-tr-DiCreRapa- was higher than 60% (Fig. 1E). This suggests that PbAP2-TR functions during trophozoite development before the beginning of nuclear division.

To further confirm the essentiality of pbap2-tr in asexual blood stage development, we assessed the parasite growth of pbap2-tr in vivo. After inducing rapamycin-dependent knockout and inoculating the schizonts of pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ into mice, parasitemia was determined through daily Giemsa staining. Parasite infectivity immediately after inoculation was comparable between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ as their parasitemia was not significantly different on day 0 (6 hpi), suggesting that pbap2-tr-disruption did not affect the ability of schizonts/merozoites to infect host RBCs (Fig. 1G). On day 1, the parasitemia of pbap2-tr-DiCreRapa+ decreased from that on day 0 and was significantly lower than that of pbap2-tr-DiCreRapa- (Fig. 1G). In the following days, parasitemia of pbap2-tr-DiCreRapa+ increased with a growth rate comparable to that of pbap2-tr-DiCreRapa- (Fig. 1G). However, genotyping on day 3 did not detect pbap2-tr-disrupted parasites but only parasites with the WT pbap2-tr locus (Fig. 1H). This result confirms that pbap2-tr plays an essential role in parasite development during the IDC.

Previously, Shang et al. reported that in P. falciparum, disruption of the pbap2-tr ortholog, named pfap2-g5, resulted in upregulation of PfAP2-G and increased the rate of differentiation into gametocytes, consequently causing a significant reduction in the parasite asexual growth rate30. Thus, they concluded that PfAP2-G5 is important for suppressing commitment to the gametocyte fate. To evaluate whether PbAP2-TR plays a similar role, we assessed the number of gametocytes in pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ on day 1 (24 hpi) of the above in vivo growth assays (because gametocyte maturation takes approximately 24 h in P. berghei) through Giemsa-staining. Gametocytemia (gametocyte/RBC) was comparable between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+, demonstrating that the rate of commitment to gametocyte fate was not significantly affected by whether pbap2-tr was disrupted (Fig S3B). Next, to further confirm that the loss of asexual proliferation in pbap2-tr-DiCreRapa+ was not due to the parasite commitment to gametocyte fate, we disrupted pbap2-g in pbap2-tr-DiCre using the CRISPR/Cas9 system [pbap2-tr-DiCre pbap2-g(-), Fig S3C]. DiCre-mediated disruption of pbap2-tr was induced in cultures (pbap2-tr-DiCre pbap2-g(-)_Rapa+ and pbap2-tr-DiCre ap2-g(-)_Rapa-) (Genotyping 1, Fig S3D left), and after inoculating pbap2-tr-DiCre pbap2-g(-)_Rapa- and pbap2-tr-DiCre ap2-g(-)_Rapa+ into mice, parasitemia was assessed daily. The result was similar to that of the phenotype analysis for pbap2-tr-DiCre; in pbap2-tr-DiCre ap2-g(-)_Rapa+, parasitemia decreased from day 0 to day 1 and later increased (Fig S3E), but the day-3 parasites possessed the WT pbap2-tr locus (Genotyping 2, Fig S3D right). Collectively, these results suggest that PbAP2-TR is indeed essential for asexual blood stage development and does not play any evident role in the sexual commitment unlike PfAP2-G5.

PbAP2-TR recognizes two DNA motifs using different AP2 domains
To investigate the target genes regulated by PbAP2-TR, we performed chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) of PbAP2-TR at the trophozoite stage. In P. falciparum, PfAP2-G5 also plays a role in the early gametocyte development. Thus, to specifically assess the role of PbAP2-TR in asexual development, we disrupted pbap2-g in PbAP2-TR::GFP using the CRISPR/Cas9 system [PbAP2-TR::GFP pbap2-g(-), Fig S4A]. ChIP-seq analyses were performed in duplicate using PbAP2-TR::GFP pbap2-g(-) at 12 hpi. Experiments 1 and 2 detected 1086 and 1259 peaks, respectively (by macs2 with the thresholds of fold enrichment > 3.0 and q-value < 0.01, using sequence data of input DNA as a control), and 1017 peaks overlapped (93% of the peaks in experiment 1) (Fig. 2A, Supplementary Data 1). Genome-wide comparison of ChIP/input enrichment between the replicates resulted in Pearson correlation coefficient of 0.96, and IDR1D analysis revealed rank of peaks in each replicate to be largely consistent, showing high reproducibility of the data (Fig. 2A, S4B, and S4C). From the common peaks, we first explored the putative binding motifs of PbAP2-TR by DNA motif enrichment analysis using Fisher’s exact test. The analysis revealed GTTGTA as the most enriched motif (p-value = 5.2 × 10−72) and several motifs containing GTTGT in the 20 most enriched motifs (Supplementary Data 1). Furthermore, the analysis detected the enrichment of motifs containing GTTGC. Thus, the most enriched motif was considered as GTTGY (Fig. 2B). Among the 1017 ChIP-seq peaks, 872 peaks contained the GTTGY motif within 300 bp of the summit, and most were found within 100 bp (Fig. 2C). In addition to GTTGY, motifs containing GTTCT were highly enriched (Fig. 2D). This motif was found in 514 peaks, mostly close to the summit (Fig. 2E). Similar motifs were also enriched in the ChIP-seq analysis of PfAP2-G530. Hereafter, the GTTGY and GTTCT motifs are referred to as Motif 1 and 2, respectively. In total, 90% of the ChIP-seq peaks (934 peaks) contained at least either Motif 1 or 2, and nearly half of the peaks (452 peaks) contained both of the motifs. Among the peaks containing both Motifs 1 and 2, the distance between these two motifs was not constant, i.e. these motifs are not arranged in a specific positional relationship (Fig. 2F).

To further evaluate the DNA-binding properties of PbAP2-TR, we performed DNA immunoprecipitation followed by high-throughput sequencing (DIP-seq) analysis using recombinant PbAP2-TR AP2 domains fused with maltose-binding protein (MBP) and fragmented P. berghei genomic DNA. First, DIP-seq was performed on two N-terminal tandem AP2 domains. Because these two AP2 domains likely function together owing to their proximity and the conserved amino acids between them (Fig S1B), we generated a recombinant protein containing both AP2 domains. In this analysis, 3038 peaks were detected throughout the genome (Supplementary Data 2). Motif enrichment analysis of these DIP peaks detected GTTCT and GATCT as the two most enriched motifs (Fig. 2G and Supplementary Data 2), which was consistent with the previously identified binding motif for the first AP2 domain of PfAP2-G531. Among the 3038 DIP peaks, 2502 peaks (82.3%) contained GWTCT (W = A or T) within 100 bp of their summit (Fig. 2H), suggesting that GWTCT, which is analogous to Motif 2, is the binding motif of the N-terminal tandem AP2 domains of PbAP2-TR. Next, DIP-seq was performed on the third AP2 domain of PbAP2-TR. In this analysis, 2980 peaks were detected (Supplementary Data 2), and the most enriched motif in these peak regions was GTTGT (Supplementary Data 2). The following enriched motifs were one-base-shifted motifs of GTTGT (TGTTG, AGTTG, and TTGTA) and GTTGC (Supplementary Data 2). Thus, the enriched motifs were related to Motif 1 (GTTGY) (Fig. 2G). Motif 1 was contained within 100 bp from the summit of 2888 peaks (97%) (Fig. 2I). Collectively, these results suggest that PbAP2-TR binds to Motif 1 and 2 each by different AP2 domains.

PbAP2-TR targets are downregulated during early to late trophozoite development
Based on ChIP-seq data, we identified 619 target genes of PbAP2-TR, which were defined as genes with a ChIP-seq peak within 1200 bp of the start codon (Supplementary Data 3). Among these targets, only 88 genes overlapped with those of PfAP2-G5 at the trophozoite stage (517 genes reported by Shang et al.) (Supplementary Data 3). To examine the role of PbAP2-TR in transcriptional regulation, we investigated the changes in the transcript levels of these target genes from the beginning (8 hpi) to the end (16 hpi) of PbAP2-TR expression using high-throughput RNA sequencing (RNA-seq). To obtain asexual transcriptomic data, RNA-seq analyses were conducted using gametocyte-less mutant parasites, i.e., the ap2-g-knockout line, in biological triplicate (quality check results were shown in Fig S5A–C). Among the genes significantly downregulated at 16 hpi compared with those at 8 hpi (799 genes in total, log2(fold change) < −1, p-value adjusted for multiple testing with the Benjamini-Hochberg procedure (p-value adj) < 0.05), 180 genes were PbAP2-TR targets whereas only 55 target genes were included in the significantly upregulated genes (702 genes in total, log2(fold change) > 1, p-value adj < 0.05) (Fig. 3A and Supplementary Data 4). Overall, the average log2(fold change) value of the PbAP2-TR target genes was significantly lower than that of the other genes (p-value = 2.3 × 10−26 by two-tailed Student’s t-test). In addition, in the upstream region (200–1000 bp from the start codon) of the downregulated genes, GTTGT (Motif 1) was the second most significantly enriched with a p-value of 1.0 × 10−34 by Fisher’s exact test (Fig. 3B). The other binding motifs, GTTGC (Motif 1) and GTTCT (Motif 2), were also enriched with p-values of 1.3 × 10−4 and 6.3 × 10−3, respectively (Fig. 3B). These results suggest that PbAP2-TR is the major transcriptional repressor responsible for gene downregulation during early to late trophozoite development.

PbAP2-TR functions as a transcriptional repressor
To verify that PbAP2-TR is a transcriptional repressor, we performed a differential expression analysis between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ at 12 hpi (quality check results were shown in Fig S6A–C). The analysis revealed that 70 and 111 genes were significantly upregulated and downregulated, respectively, in pbap2-tr-DiCreRapa+ compared with those in pbap2-tr-DiCreRapa- (Fig. 4A, S6D, and Supplementary Data 5). Of note, pbap2-g was not differentially expressed in pbap2-tr-DiCreRapa+ (log2(fold change) = 0.075 and p-value adj = 0.79) consistent with the comparable sexual commitment rate between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ (Fig S3B). Among the upregulated genes, 47 PbAP2-TR target genes were detected, showing significant enrichment with a p-value of 4.2 × 10−21 by Fisher’s exact test (Fig. 4A). In contrast, the downregulated genes included only nine target genes (Fig. 4A). Furthermore, the average log2(fold change) value for the PbAP2-TR target genes was significantly higher than that for the other genes with a p-value of 2.6 × 10−67 by two-tailed Student’s t-test (Fig S1D). Motif enrichment analysis showed enrichment of both Motif 1 and 2 in the upstream sequences (200–1000 bp from the start codon) of the upregulated genes compared with those of the other genes (Fig. 4B). These results confirm that PbAP2-TR functions as a transcriptional repressor during trophozoite development.

Binding motifs of PbAP2-TR function as cis-regulatory repressing elements
To evaluate the functions of Motif 1 and 2 as cis-regulatory elements, we performed dual luciferase assays using a centromere plasmid containing firefly and Renilla luciferase genes (pCen-luc, Fig. 4C). Expression of the Renilla luciferase (R-luci) gene in pCen-luc was controlled by the P. berghei elongation factor 1-alpha promoter as an internal control, and the target gene promoters were inserted upstream of the firefly luciferase (f-luci) gene (Fig. 4C). We selected two PbAP2-TR target genes, dihydrolipoamide acyltransferase (dlat, PBANKA_0505000) and biotin--protein ligase 1 (bpl-1, PBANKA_0511000), for the reporter assays, as these were significantly upregulated upon pbap2-tr-disruption (Supplementary Data 5). The upstream regions of dlat and bpl-1 both contained one of Motif 1 and two of Motif 2 (Fig. 4D), and we introduced mutations to alter either or both of these motifs from GTTGY and GTTCT to tTTGY and tTTCT, respectively. These pCen-luc plasmids were then introduced into the wild-type P. berghei ANKA strain, and dual luciferase assays were performed at 14 hpi in biological triplicate.

In the assay for the dlat promoter, the relative expression of f-luci against R-luci was significantly increased by 23- and 7-fold through mutations into Motif 1 and 2, respectively (p-value < 0.01, two-tailed Student’s t-test) (Fig. 4E). Furthermore, f-luci/R-luci expression was the highest with mutations into both Motifs 1 and 2 (49-fold higher than that without mutations) (Fig. 4E). In the assay for bpl-1, a similar result was obtained; promoter activity significantly increased with mutations into either Motif 1 or 2 (by 54- and 5-fold, respectively), and mutations into both motifs induced the highest f-luci/R-luci expression level (83-fold higher than that without mutations) (Fig. 4E). Thus, for both reporters, Motifs 1 and 2 both functioned as cis-regulatory elements for transcriptional repression, and Motif 1 contributed more to transcriptional repression than Motif 2.

Next, we evaluated whether the functional difference between Motifs 1 and 2 was also observed in the differential expression analysis between pbap2-tr-DiCreRapa+ and pbap2-tr-DiCreRapa-. We divided the target genes into three groups: targets of a peak with both motifs, only Motif 1, and only Motif 2, within 300 bp of the summit (Supplementary Data 5). The average log2(fold change) value of the “both motifs” group was significantly higher than that of the other two groups with p-values less than 0.05 by two-tailed Student’s t-test (Fig. 4F). This suggests that transcriptional repression by PbAP2-TR is strong in regions containing both binding motifs. For targets with either motif, the average log2(fold change) value was significantly higher in the Motif 1 group than in the Motif 2 group (Fig. 4F). These results verify that Motif 1 is a stronger cis-regulatory element for transcriptional repression by PbAP2-TR than Motif 2. Collectively, these results suggest that a single transcription factor can generate variations in the transcript levels of target genes through combinations of different cis-regulatory elements. In a previous study, we described a similar mechanism for transcriptional activation by PbSIP222. These cis-element dependent variations in the level of transcriptional activation and repression may be important for the parasite to regulate its complex lifecycle with a small number of sequence-specific transcription factors19.

PbAP2-TR mainly targets ribosome biogenesis-related genes and exported protein genes and contributes toward establishing their transcription peak patterns
PbAP2-TR targets included 458 genes that were functionally annotated in the PlasmoDB (https://plasmodb.org/plasmo/app)32 (Supplementary Data 3). To explore deeper insights into the role of transcriptional repression by PbAP2-TR in asexual blood stage development, we classified these annotated genes into characteristic groups. Among 13 groups, the “protein biogenesis” group was the largest, containing 94 target genes (Fig. 5A). These mainly included ribosome-related genes, such as 40S and 60S ribosomal protein genes and nucleolar protein genes. The target genes also included many genes belonging to “metabolism,” “exported protein,” and “mitochondria” (Fig. 5A). In any of these groups, no significant enrichment of targets associated with Motif 1 or 2 was detected, suggesting that difference in the binding motifs was not related to enrichment of characteristic groups in PbAP2-TR targets (Fig S7A and Supplementary Data 3). We further performed gene ontology (GO) analysis of the PbAP2-TR targets to explore the enriched genesets. The analysis revealed that the term “ribosome biogenesis” was most enriched in the target genes with a p-value of 2.1 × 10−6, consistent with the significant number of ribosome-related genes found in the targets (Supplementary Data 6). Furthermore, several terms related to ribosomes, such as “ribonucleoprotein complex biogenesis,” “rRNA processing,” and “nucleolus,” were included in the 20 most enriched terms (Supplementary Data 6). Other enriched terms include some related to parasite proteins exported into the host cell (such as “host cellular component” and “symbiont-containing vacuole”) and two IMC-related terms (“pellicle” and “inner membrane pellicle complex”) (Supplementary Data 6).

In the course of the Plasmodium IDC, the expression of most genes changes with cell stage progression rather than being constantly expressed, and genes of the same functional group mostly show similar expression patterns10,14,33. To investigate whether PbAP2-TR contributes to the establishment of unique expression peak patterns for each functional gene group, we assessed the transcript levels of target-enriched group genes at 4 (ring, before PbAP2-TR expression), 8 (early trophozoite, beginning of PbAP2-TR expression), and 16 hpi (late trophozoite, end of PbAP2-TR expression) (Supplementary Data 7). For most genes with the GO term “ribosome biogenesis” and “nucleolus,” their transcript per million (TPM) values peaked at 8 hpi when PbAP2-TR expression began (Figs. 5B and S7B). Similarly, the expression peaks for most Plasmodium exported protein genes (including exp1–3 and ibis1) were also observed at 8 hpi (Figs. 5B and S7B). The “pellicle” genes mostly showed no notable change or a slight decrease from 4 to 8 hpi, but similar to ribosome-related genes, their expression decreased towards 16 hpi (Figs. 5B and S7B). Collectively, gene groups enriched in PbAP2-TR targets commonly showed patterns of downregulation from 8 to 16 hpi, during which PbAP2-TR is expressed. Notably, expression of targets in these groups was mostly upregulated in pbap2-tr-DiCreRapa+ compared to pbap2-tr-DiCreRapa- (Fig S7C). Thus, these results suggest that PbAP2-TR contributes to the establishment of transcription peak patterns in its target genes by repressing their transcription during the IDC.

PbAP2-TR recruits PbMORC as a co-factor
To further investigate the mechanism of transcriptional repression by PbAP2-TR, we performed rapid immunoprecipitation mass spectrometry (MS) of endogenous proteins (RIME), which involves ChIP, followed by MS analysis, and explored its co-factors. ChIP was conducted using PbAP2-TR::GFP pbap2-g(-) and WT (as controls) parasites at 12 hpi, as described for the ChIP-seq analyses. IPed proteins were harvested by on-bead digestion with trypsin and subjected to liquid chromatography-tandem MS (LC-MS/MS) analysis. MS data obtained from four biologically independent experiments were compared between PbAP2-TR::GFP pbap2-g(-) and WT. Through this analysis, we identified ten proteins that were unique to PbAP2-TR::GFP pbap2-g(-) ChIP (detected in at least three of four replicates) and one protein that was more than five-fold enriched in PbAP2-TR::GFP pbap2-g(-) ChIP compared to WT ChIP, with a p-value less than 0.01 by a two-tailed Student’s t-test (Fig. 6A and Supplementary Data 8). Among these, PbAP2-TR itself and PbMORC had average quantitative values (aveQVs) higher than 20, whereas the values for the others were lower than 3, suggesting that PbMORC is a strong candidate for a PbAP2-TR co-factor (Fig. 6A and Supplementary Data 8). This result is consistent with the previous studies in P. falciparum, which detected PbAP2-TR ortholog, PfAP2-G5 through the co-IP with PfMORC34,35.

Plasmodium parasites possess a single MORC, which has a conserved GHKL (gyrase, Hsp90, histidine kinase, and MutL)-ATPase domain and several Kelch motifs (Fig. 6B)34. To verify that PbMORC is a PbAP2-TR co-factor, we performed the reciprocal RIME analysis at 12 hpi. To conduct this experiment on the pbap2-g knockout background as with the above RIME analysis, a parasite line expressing GFP-fused PbMORC was generated, and pbap2-g was disrupted in this parasite [PbMORC::GFP pbap2-g(-), Fig S8A]. The RIME analysis using PbMORC::GFP pbap2-g(-) detected 146 proteins that were unique or more than five-fold enriched (Fig. 6C and Supplementary Data 8). These proteins included PbMORC and PbAP2-TR with the first and third highest aveQVs of 121.3 and 47.5, respectively (Fig. 6C and Supplementary Data 8), which supports the notion that PbMORC acts as a major co-factor of PbAP2-TR. Next, to confirm that PbAP2-TR recruits PbMORC to the upstream regions of target genes as a co-factor, we performed ChIP-seq analysis using PbMORC::GFP pbap2-g(-) at 12 hpi. Duplicate experiments identified 1864 and 1984 peaks, of which 1436 peaks (77% of the experiment 1 peaks) overlapped (Pearson correlation coefficient = 0.94) (Fig. 6D and S8B, and Supplementary Data 9). Among these common peaks, 547 peaks overlapped with those of PbAP2-TR, accounting for 54% (547/1017 peaks) of the PbAP2-TR peaks. Consistently, Motifs 1 and 2 were significantly enriched in the PbMORC peak regions with p-values of 1.5 × 10−52 and 0.035, respectively, by Fisher’s exact test (Supplementary Data 9). Furthermore, the PbMORC ChIP-seq coverage showed clear enrichment patterns around the summits of most PbAP2-TR peaks (Fig. 6E), including those that were classified as non-overlapping with the PbMORC peaks under the thresholds of fold enrichment > 3 and q-value < 0.01 in macs2 peak calling (Fig S8C and S8D). These results indicate that PbAP2-TR genome-widely recruits PbMORC to the upstream regions of its target genes.

Importantly, while ChIP-seq showed co-localization in the PbAP2-TR binding regions, only 38% (547/1436 peaks) of the PbMORC peaks overlapped with the PbAP2-TR peaks (Fig. 6F). Motif enrichment analysis of the remaining PbMORC peaks (889 peaks) detected ACACA, TGCAY, and YGTCT, along with their related motifs (Fig. 6G and Supplementary Data 9). These results imply that PbMORC is recruited to the genome not only by PbAP2-TR but also through other factors. In the PbMORC RIME, two other AP2 family members, PBANKA_0521700 and PbAP2-P (PBANKA_0939100), were identified with the second and fourth highest aveQVs of 69.3 and 27.8, respectively (Fig. 6C and Supplementary Data 8) while they were not detected in the PbAP2-TR RIME (Supplementary Data 8). These findings may suggest that PbMORC functions as a co-factor of PBANKA_0521700 and PbAP2-P during the IDC, independently of PbAP2-TR. Notably, in P. falciparum, the orthologs of these transcription factors, PF3D7_0420300 and PfAP2-P (PF3D7_1107800), were also detected in the co-IP with PfMORC34,35. In addition, PF3D7_0420300 and PfAP2-P have been reported to bind to ACACA and TGCATG, respectively31,36, which were analogous to those enriched in the PbMORC peaks.

RIME analyses of PbAP2-TR and PbMORC additionally identified several putative transcriptional regulators. The proteins commonly detected in the two RIME analyses included EELM2 (PBANKA_1234600) and ISWI (PBANKA_1123500) (Figs. 6A, C, Supplementary Data 8). Furthermore, other putative transcriptional regulators, such as CHD1 (PBANKA_0907200), ELM2 (PBANKA_0205000), and HDAC1 (PBANKA_0826500), were uniquely identified in the PbMORC RIME (Fig. 6C and Supplementary Data 8). While their aveQVs in the RIME were relatively low compared to those of PbAP2-TR and PbMORC, these proteins might also contribute to the transcriptional regulation during the IDC as potential interaction partners of PbAP2-TR and/or PbMORC.

Methods
Ethics statement
All experiments were performed in accordance with the recommendations of the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health to minimize animal suffering and were approved by the Animal Research Ethics Committee of Mie University (permit number 23–29).

Parasite preparation
The parasites were inoculated into female ddY mice (Mus musculus, an outbred strain purchased from Japan SLC Inc., 5–6-week-old), which were kept in a temperature-controlled room (22–24°C) under a 16:8 h light/dark cycle with relative humidity within 40–60%. All parasites used in this study were derived from the wild-type (WT) P. berghei ANKA strain. Transgenic parasites generated using the CRISPR/Cas9 method were derived from the WT-originated Cas9-expressing parasite, PbCas9, which has a Cas9 expression cassette at the p230p locus39. The pbap2-tr-DiCre parasite was generated from PbCas9DiCre, which constitutively expresses Cre59 (Thr19–Asn59) fused with FKBP12 and Cre60 (Asn60–Asp343) fused with FRB in addition to Cas922.

In vitro cultures of whole blood from infected mice were performed using RPMI1640 medium supplemented with 25% fetal calf serum and penicillin/streptomycin at 37°C in 5% CO2 and 10% O2. For cell cycle synchronization, infected blood was cultured for 16 h, and mature schizonts produced in the cultures were harvested by density gradient centrifugation using an iodixanol solution (Optiprep), whose density was adjusted to 1.077 g/mL by mixing with tricine solution. The harvested schizonts were then intravenously injected into mice. Parasitemia and parasite morphology were assessed on Giemsa-stained blood smears.

Generation of transgenic parasites via the CRISPR/Cas9 system
For gene editing with the CRISPR/Cas9 system using PbCas9 and PbCas9DiCre, donor DNAs and single guide RNA (sgRNA) vectors were constructed according to the previously developed protocol27. Briefly, templates for donor DNAs were constructed using overlap PCR and cloned into pBluescript KS(+) by In-Fusion cloning (Takara) at the XhoI and BamHI sites. Donor DNAs were then amplified by PCR from the constructed plasmid. The target sequences of the sgRNAs were designed using CHOPCHOP. sgRNA templates were constructed by annealing DNA oligos and were cloned into the sgRNA vector using the DNA Ligation Kit (Takara).

Transfection was performed using cultured schizonts and DNA constructs described above. Briefly, recipient parasites were cultured for 16 h, and schizonts were harvested by density gradient centrifugation. The harvested schizonts were then washed once with RPMI1640, transfected with DNA constructs using the Amaxa Basic Parasite Nucleofector Kit 2 (LONZA), and immediately inoculated into mice. All transfectants were selected by treating the infected mice with 70 μg/mL pyrimethamine in their drinking water from 30 h after transfection. For CRISPR/Cas9 gene editing, recombination was confirmed using PCR and/or Sanger sequencing, and clonal parasites were obtained by limiting dilution. All the primers used in this study are listed in Supplementary Data 10.

Fluorescence microscopic analysis
Fluorescence analysis was performed using the Olympus BX51 microscope with Olympus DP74 camera. For nucleus detection, parasites were stained with 1 ng/mL Hoechst 33342 for 10 min at 37°C.

Conditional knockout of pbap2-tr
Whole blood from mice infected with pbap2-tr-DiCre (or pbap2-tr-DiCre pbap2-g(-)) parasites was cultured. The cultures were then split into two parts; a 3/20 volume of rapamycin (Wako) solution (200 μM DMSO stock) was added to one part (final concentration of 30 nM), and the same volume of DMSO was added to the other as a control. The parasites were cultured for 16 h, and schizonts were harvested and inoculated into mice. For in vitro phenotype analysis, the parasites were cultured again at 10 hpi. For in vivo phenotype analysis, parasites were grown in mice for 3 days, and parasitemia was assessed daily by Giemsa staining. Genotyping PCR to confirm recombination at the pbap2-tr locus was performed at 16 h after starting the cultures before schizont harvest and on day 3 of the in vivo phenotype analysis. The primers used for genotyping are listed in Supplementary Data 10.

ChIP-seq and sequencing data analysis
ChIP-seq was performed without using spike-in normalization. Infected blood was passed through a Plasmodipur filter, and formalin solution was immediately added to a final concentration of 1% for cell fixation. After 1 h of fixing at 30°C, RBCs were lysed in ice-cold 1.5 M NH4Cl solution, and residual cells were lysed in SDS lysis buffer (50 mM Tris-HCl, 1% SDS, 10 mM EDTA). The cell lysate was sonicated using the Bioruptor (Cosmo Bio), and immunoprecipitation was performed at 4°C using anti-GFP polyclonal antibodies (Abcam, ab290, Rabbit polyclonal, reactive against all variants of Aequorea victoria GFP, GR19413-1, 1:250) conjugated to Protein A Magnetic Beads (Invitrogen). After overnight incubation with rotation, the beads were washed five times with low-salt wash buffer (20 mM Tris-HCl, 0.1% SDS, 2 mM EDTA, 1% Triton X, 150 mM NaCl) and three times with high-salt wash buffer (20 mM Tris-HCl, 0.1% SDS, 2 mM EDTA, 1% Triton X, 500 mM NaCl). The beads were then resuspended in extraction buffer (10 mM Tris-HCl, 1% SDS, 5 mM EDTA, 300 mM NaCl) and were incubated for 15 min at room temperature to extract the immunoprecipitated chromatin. DNA fragments were purified from the chromatins after treatment with RNase A and proteinase K. Libraries were constructed from the DNA fragments using the KAPA HyperPrep Kit (Kapa Biosystems). Next-generation sequencing (NGS) was performed using the MGI DNBSEQ-G400. DNA fragments purified from cell lysates before immunoprecipitation were also sequenced as input sequence data. Two biologically independent experiments were performed for each ChIP-seq experiment.

Reads in the sequence data were mapped onto the reference genome sequence of P. berghei (v3.0, downloaded from PlasmoDB) using Bowtie2. Those aligned onto more than two sites in the genome were removed from the mapping data, and peaks were called by the macs2 callpeak using the input sequence data as control (fold enrichment > 3.0, q-value < 0.01, and setting --call-summit option on). The ChIP-seq enrichment on the genome was visualized as raw read coverage normalized by library size using bamCoverage (-bs 10, --normalizeUsing RPKM) or log2-transformed ChIP/input ratio using bamCompare (-bs 10). The replicated data were compared using IDR1D (https://idr2d.mit.edu/)61 (maxgap = 100) and multiBigwigSummary bins (-bs 1000) to assess their reproducibility. Fraction of reads in peaks (FRiP) was calculated using plotEnrichment, and normalized strand cross-correlation coefficient (NSC) and relative strand cross-correlation coefficient (RSC) were assessed using phantompeakqualtools for quality check of each ChIP and input data. The parameters for all programs were set as default unless otherwise indicated. Common peaks in duplicates were defined as those with a distance less than 150 bp between their peak summits.

The enrichment of motifs within 50 bp of the peak summits was analyzed using Fisher’s exact test. For this motif enrichment analysis, peaks located within 1 kb of the end of each chromosome were excluded to avoid detection of the telomeric repeat sequence TTYAGGG (Y = T or C). In the P. berghei reference genome, 13 of 28 chromosome end sequences are fully resolved, and these include less than 1-kb telomeric repeat sequences. Repeats of TTYAGGG are also found within subtelomeric 2.3-kb repeat units. Genes with peaks within 1200 bp of their start codons were identified as target genes. The 1200-bp threshold was determined based on the previous observations that binding motifs of AP2-O and AP2-Sp were detected within 1200 bp from the start codons of the major ookinete and sporozoite-specific genes, respectively62,63. The gene ontology analysis was performed using GSEABase and GOstats programs.

DIP-seq analysis
DIP-seq was performed as previously described64. Briefly, the sequences for the AP2 domains of PbAP2-TR (164–336 for AP2 domains 1–2 and 1458–1527 for AP2 domain 3) were cloned into the MBP fusion vector pMal-c5X (NEB). E. coli transformed with the plasmids was cultured for 12 h at 37°C, and the expression of MBP-fused proteins was then induced with isopropyl β-D-thiogalactopyranoside (Wako, final concentration of 200 nM). Recombinant AP2 domains fused with MBP were purified using amylose resin (NEB) and were mixed with P. berghei ANKA genomic DNA fragments. After 30 min of incubation at room temperature, the recombinant proteins and bound DNA fragments were purified using amylose resin. DNA fragments were then subjected to library preparation and NGS using the Illumina NextSeq 500, as described for the ChIP-seq analysis. Genomic DNA fragments were sequenced as inputs before use in the DIP. Sequence data were analyzed similar to that in ChIP-seq, except for the parameters of peak calling (fold enrichment > 2.5, q-value < 0.01). Motif enrichment analyses were performed separately for three chromosome sets (chromosomes 1–8, 9–12, and 13–14) because the analysis using all DIP-seq peaks detected several motifs with p-values less than 5.0 × 10−324, which is the smallest positive real number on the R platform.

RNA-seq and sequence data analysis
For RNA-seq analysis using pbap2-g-knockout parasites, parasite cell cycles were synchronized as described in the parasite preparation method. For RNA-seq analysis using pbap2-tr-DiCre, rapamycin-dependent disruption of pbap2-tr was induced, and schizonts of pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ were inoculated into mice, as described for the conditional knockout of pbap2-tr. Whole blood was harvested at 4, 8, and 16 hpi for pbap2-g-knockout parasites and at 12 hpi for pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ parasites. The blood was then passed through a Plasmodipur filter. RBCs were lysed in ice-cold 1.5 M NH4Cl solution, and total RNA was extracted from the residual parasites using the Isogen II reagent (Nippon Gene). RNA-seq libraries were prepared using the KAPA mRNA HyperPrep Kit (Kapa Biosystems) and were sequenced using the MGI DNBSEQ-G400. Three biologically independent experiments were performed for each sample. The sequence data were mapped onto the reference P. berghei ANKA genome sequence using HISAT2, with the maximum intron length set as 1000. The number of reads mapped to each gene was calculated using featureCounts and compared between samples using DESeq2. To evaluate the replicate consistency, principal component analysis plots, sample-to-sample distance heatmaps, and dispersion plots were produced using DESeq2 plotPCA, dist, and plotDispEsts, respectively. For differential expression analyses, DESeq2 apeglm shrinkage65 was applied to the log2(fold change) to accurately evaluate the effect sizes without arbitrarily filtering out genes with low counts. Subtelomeric multigene families (pir and fam) were removed from the differential expression analysis. Default parameters were set for all programs unless indicated otherwise.

Dual-luciferase reporter assay
Plasmids were constructed to generate luciferase reporter lines as previously described37. Briefly, the upstream regions of dlat and bpl-1 were amplified from P. berghei genomic DNA by PCR and inserted upstream of the firefly luciferase gene in the reporter plasmid pCen-luc using the KpnI and NheI sites. In addition to the firefly luciferase gene, pCen-luc contain the Renilla luciferase gene expression cassette as an internal control and the human dhfr gene as a drug-selectable marker. The expression of these two genes under the control of the bi-directional P. berghei elongation factor 1-alpha gene promoter. The plasmid also contains the centromere sequence from the P. berghei chromosome 566. Mutations within dlat and bpl-1 promoters were introduced using overlap PCR before integration of their upstream sequences into the reporter plasmid.

Parasites carrying pCen-luc were synchronized as described in the parasite preparation method and were harvested from the tail vein of infected mice at 14 hpi. RBCs were lysed in ice-cold lysis solution (1.5 M NH4Cl, 10 mM EDTA, and 0.1 M KHCO3) for 5 min, and the residual cells were subjected to dual-luciferase reporter assays using the Dual-Luciferase Reporter Assay System (Promega). The assays were performed according to the manufacturer’s instructions. Firefly and Renilla luciferase expression was assessed using the GloMax 96 Microplate Luminometer (Promega). The assays were performed in biological triplicate for each sample.

RIME
ChIP was performed as described for ChIP-seq analysis. The beads with immunoprecipitated chromatins were washed twice with 100 mM ammonium hydrogen carbonate (AMBIC) solution. Proteins on the washed beads were digested with 10 μl of trypsin (Promega) in 100 mM AMBIC at an enzyme-to-protein ratio of 1:100 (wt/wt) for overnight at 37°C and were further incubated for 4 h at 37°C with additional 10 μl of trypsin. The peptides released from the beads through digestion were then purified using a C18 tip (GL-Science, Tokyo, Japan) and then subjected to nanocapillary reversed-phase LC-MS/MS analysis using a C18 column (12 cm × 75 μm, 1.9 μm, Nikkyo Technos, Tokyo, Japan) on a nanoLC system (Bruker Daltoniks, Bremen, Germany) connected to a timsTOF Pro mass spectrometer (Bruker Daltoniks) and a modified nano-electrospray ion source (CaptiveSpray; Bruker Daltoniks). From the MS/MS data, IPed proteins were identified using DataAnalysis version 5.2 (Bruker Daltoniks) and MASCOT version 2.7.0 (Matrix Science, London, UK) against the Uniprot_Plasmodium_berghei_ANKA_strain database (4948 sequences; 3412795 residues). Protease specificity was set for trypsin (C-term, KR; Restrict, P; Independent, no; Semispecific, no; two missed and/or nonspecific cleavages permitted); conversion of the N-terminal Gln to pyro-Glu and oxidation of methionine were considered as possible modifications. The mass tolerance for precursor ions and fragment ions were ±15 ppm and ±0.05 Da, respectively. The threshold score/expectation value for accepting individual spectra was P < 0.05. Quantitative values were determined using Scaffold5 version 5.1.2 (Proteome Software, Portland, OR, USA). Four biologically independent experiments were performed for each sample. Fold change and p-value (two-tailed Student’s t-tests) were calculated using Microsoft Excel.

Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability
All ChIP-sequencing, RNA-sequencing and DIP-sequencing data generated in this study have been deposited in the Gene Expression Omnibus database under accession numbers GSE290541, GSE290542, GSE290544, and GSE290545. All MS/MS data for RIME have been deposited in the ProteomeXchange Consortium under dataset PXD067426. Source data are provided with this paper.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This manuscript describes the function of the Plasmodium berghei transcription factor the authors name Pb-TR.\nThe authors convincingly show that this AP2 domain-containing protein is essential for parasite development during the\nasexual replication cycle through a conditional KO. They go on to analyze its targets in the genome through both ChIP-Seq\nand DIP-Seq and convincingly identify candidate motifs. Interestingly, two independent motifs are identified and specify\neither the first two AP2 domains or the last single AP2 domain. The authors go on to determine that Pb-TR is more\nassociated with genes identified in the ChIP-Seq analysis that are markers of early stages rather than late stages, leading to\nthe hypothesis that Pb-TR is a repressor. They then further establish a phenotype using their conditional KO RNA-Seq, and\nshow in a luciferase assay that the motifs identified can lead to higher reporter luciferase bioluminescence when mutated.\nFinally, they identify MORC as an interactor using both MS and by comparing ChIP-Seq profiles.\nThe data is overall compelling, and this is a useful addition to the understanding of transcription in the rodent model of\nmalaria.\nThere are a some limitations of the study.\n• Given the strength of the phenotype, I found it surprising that the transcriptional changes in the RNA-Seq data following\nexcision were somewhat limited and wondered whether 12 hpi was indeed the right time point to conduct this assay. Only a\nminute number of genes with peaks are found to be upregulated. Is this low proportion expected, and is it sufficient to\nconclude that Pb-TR is a transcriptional repressor?\n• Some of the analysis and the interpretations in the paper could be deeper. For instance, it would be interesting to dissect\nand discuss further the contribution of the different AP2 domains and whether they may be associated with different targets.\nThe discussion around the functional enrichment of Pb-TR targets is perhaps not deserving of a main figure, as it doesn’t\nreally enhance the understanding of the phenotype, and no attempt is made to use the RNA-Seq in tandem. Another\nexample is the other proteins identified by RIME, which include several chromatin-associated proteins, but no attempt is\nmade at discussing whether they may also be present at Pb-TR sites and how that could play into the transcriptional\nregulation.\n• An interrogation arising from the paper is the contrast with the phenotype of the Plasmodium falciparum ortholog of Pb-TR.\nThe authors contrast this in the discussion, but this could be really enhanced; a divergent role of an AP2 in different spp. is\nan interesting observation, and the authors could do more comparative analysis to establish whether there is a possible\ndivergence. For instance, comparing targets of the APG5 and Pb-TR may be an interesting first step. Truly establishing a\ndivergence between the two species would really enhance the impact of the paper.\nMinor points:\nA citation of a VEuPathDB publication should be included.", "reviewer_2": "Summary: The study identifies PbAP2-TR (Trophozoite Repressor) as a trophozoite-stage AP2 transcription factor that\nfunctions as a transcriptional repressor essential for Plasmodium berghei asexual blood-stage development. Using DiCre\nconditional knockout, ChIP-seq/DIP-seq, time-course RNA-seq, motif mutagenesis luciferase reporters, and RIME/ChIP-seq\nfor PbMORC, the authors show that PbAP2-TR binds two motifs (GTTGY and GTTCT) via distinct AP2 domains, represses\ntarget genes (notably ribosome biogenesis and exported proteins) from 8-16 hpi, and recruits PbMORC as a co-factor; only\n~38% of MORC peaks overlap with PbAP2-TR, implying additional recruiters.\nOriginality and field context: Prior work in Toxoplasma gondii established a MORC–HDAC3–ApiAP2 repression axis, and\nrecent P. falciparum studies show PfMORC is essential, associates with heterochromatin, and co-IPs with multiple ApiAP2\nproteins (including PfAP2-G5). The present study moves beyond association to a cis-encoded, stage-bounded mechanism\nin malaria parasites: a specific trophozoite ApiAP2 repressor (PbAP2-TR) with dual-motif/domain logic that recruits\nPbMORC to enforce a precise 8-16 hpi repression program. Notably, while PfAP2-G5 co-purifies with PfMORC, it is non-\nessential across the IDC and primarily linked to restraining gametocyte commitment, whereas PbAP2-TR is essential for\nasexual progression—underscoring a mechanistic advance rather than a mere extension of Pf co-IP observations. In short,\nthe present story extends the Toxoplasma paradigm and fills a key mechanistic gap left by the PfMORC literature, making it\na substantive, field-moving advance rather than an incremental confirmation.\nMajor strengths\n• Clear stage specificity and genetic essentiality. PbAP2-TR is expressed in trophozoites and DiCre excision causes a\ntrophozoite-stage developmental arrest with careful staging controls.\n• Cohesive multi-omics mechanism. ChIP-seq and DIP-seq define two motifs and assign them to different AP2 domains;\nluciferase mutagenesis shows cis-repressive function with Motif 1 > Motif 2 effect sizes.\n• Biological coherence. Target-enriched functional categories (ribosome biogenesis, exported proteins, pellicle/IMC) decline\nfrom 8-16 hpi, matching the proposed repressive window.\nA) Key concerns about Transcriptomics (analysis & visualization)\nThe transcriptomic component is central to your mechanistic claim and is, overall, well integrated with the genetics and ChIP\ndata. The authors analyze (i) an 8-16 hpi progression in an ap2-g- background to align with the trophozoite window of\nPbAP2-TR expression, and (ii) an acute pbap2-tr DiCre ± rapamycin contrast at 12 hpi with three biological replicates,\nmapped with HISAT2/featureCounts and modeled in DESeq2—good choices that match the biology and enable clear cross-\nvalidation between time course and inducible loss of function. At present, results are primarily visualized with volcano plots\n(Fig. 3A, Fig. 4A), and gene-set summaries are shown as TPM-scaled line plots across 4/8/16 hpi (Fig. 5B).\n• Use MA plots with shrunken log2FC values instead of volcano plots. The current volcanoes (Figs. 3A and 4A) \noveremphasize extreme p-values, which hides the role of expression strength and gives undue weight to low-count, highly\nsignificant genes. MA plots (mean expression vs shrunken log2FC, e.g. with DESeq2 apeglm/ashr) make effect sizes at\nbiologically relevant expression levels clearer. Please re-render Figs. 3A and 4A as MA plots, marking FDR and |LFC|\ncutoffs directly; a simplified volcano can remain in the supplement if desired.\n• Show full QC and replicate information. For the 12 hpi DiCre contrast (n = 3 per condition), include in the Supplement a\nPCA plot, a sample-to-sample distance heatmap, and the standard DESeq2 dispersion–mean plot to document replicate\nconsistency and treatment separation. Clearly state the number of replicates for the 8/16 hpi time points and provide the\nsame QC panels, so readers can be confident that the time-course results are robust.\n• Clarify the gene-set expression patterns. Fig. 5B’s line plots (TPM normalized to 4 hpi) are informative but overcrowded.\nReplace or supplement them with row-z-scored heatmaps of the main gene sets (“ribosome biogenesis,” “nucleolus,”\n“exported proteins/pellicle”) across 4/8/16 hpi, annotated with PbAP2-TR target status and Motif 1/Motif 2 presence near the\nTSS. This format will make the coordinated 8–16 hpi down-regulation immediately visible and directly link expression\nchanges to cis-regulatory logic.\nB) Key concerns about MORC/AP2-TR\n• In Fig. 6C, the IGV snapshots don’t convincingly demonstrate co-localization: the two PbMORC replicates are shown on\nchromosome 1 with their own y-axis scales, and the PbAP2-TR track is plotted separately below, making direct, like-for-like\nvisual comparison difficult; several MORC peaks appear without an obvious AP2-TR peak in the same view. This\nimpression actually matches your own quantification that only 38% of MORC peaks overlap AP2-TR (Fig. 6E), so the panel,\nas drawn, tends to undercut the text’s claim of “genome-wide co-localization.” Consider (i) replotting matched loci with\nidentical y-axis scaling and a single, aligned multi-track view (MORC rep1/rep2 and AP2-TR together), (ii) adding zoom-ins\non representative overlap and non-overlap sites, and (iii) emphasizing the more appropriate summary evidence (the heat\nmap of MORC signal centered on AP2-TR peaks in Fig. 6D and the 38% overlap in Fig. 6E) while softening the wording\nfrom “genome-wide co-localization” to “co-localized at a subset of AP2-TR sites.”\n• To move beyond correlative evidence of MORC co-recruitment, perform reciprocal co-IP or BioID to confirm direct complex\nformation and reinforce the central model.\nC) Minor comments\n• Your RIME list (Table S8) includes a protein bearing an ELM2 domain—precisely the class of ELM2–SANT co-repressors\nthat scaffold MORC–HDAC3 complexes in Toxoplasma—yet the manuscript concludes that no chromatin regulators were\ndetected and emphasizes MORC acting alone; please acknowledge this candidate and, ideally, test its\nassociation/functon(reciprocal IP).\n• ChIP-seq robustness: strengthen the ChIP-seq methods and reporting by providing replicate concordance and quality\nmetrics (IDR, FRiP, NSC, RSC) for both AP2-TR and MORC datasets, clarifying how peaks were called and thresholds\ndefined. Explicitly justify the use of the ±1200 bp promoter window in P. berghei, state whether spike-in normalization was\napplied, and include antibody validation details (lot, specificity) for the GFP ChIP. Finally, define the exact criteria for calling\n“targets” directly in the main text, not only in tables.\nD) Optional but valuable additions\n• Consider performing ATAC-seq in the PbAP2-TR KD context to directly link transcriptional repression with chromatin\ncompaction at target loci.", "reviewer_3": "The authors described the function of PbAP2-TR, an AP2-domain containing transcriptional factor, in the regulation of\nmalaria parasite asexual development. When this gene was conditionally knocked out, parasite growth was arrested at the\ntrophozite stage. ChIP-seq analysis revealed PbAP2-TR-regulated genes and their binding motifs. Differential expression\nanalysis by RNA-seq indicated that PbAP2-TR is a transcriptional repressor, and this conclusion was confirmed by an\nepisomal expression cassette with PbAP2-TR binding motifs. ChIP followed by mass spectrometry analysis revealed that\nPbMORC was associated with PbAP2-TR.\nThis work revealed the novel functions of PbAP2-TR, which is significant in the field. Authors put a great effort to provide\ndetailed information by advanced technologies such as Dicre-based conditional KO, ChIP-seq, and RNA-seq. The overall\nstudy is excellent and innovative. However, authors need to address quite a few questions to completely cover the whole\nstory of this gene.\n1. First of all, this study revealed the potential hidden function of PfAP2-G5, the ortholog of PbAP2-TR in P. falciparum. That\nis AP2-G5 is also involved in regulating asexual development. However, on the other hand, this study did not provide\nenough data on the function of PbAP2-TR in the regulation of AP2-G, which was shown in the PfAP2-G5 study. The authors\ndid not mention whether AP2-G was changed or not, whether gametocytegenesis and gemetocyte development were\nchanged. Based on the RNA-seq data (Table S5), AP2-G was slightly increased after PbAP2-TR was deleted at 12 hpi;\nmeanwhile, AP2-G2 was significantly increased after PbAP2-TR KO (this may indicate that gametocyte development was\nchanged).\n2. If PbAP2-TR is involved in regulating AP2-G, the ChIP-seq and RNA-seq analysis after PbAP2-TR KO in AP2-G KO\nparasites may hide important information related to AP2-G. For example, PbAP2-TR binding sites in the AP2-G promoter\n(PfAP2-G5 was found to bind the AP2-G promoter) may be omitted.\n3. The authors did not compare PbAP2-TR-regulated genes and binding motifs with the PfAP2-G5-regulated genes and\nbinding motifs. At least, PbAP2-TR binding motif 2 is shared with PfAP2-G5 binding motif.\n4. There is no \"C\" in fig. 4. The \"D\" to \"G\" should be \"C\" to \"F\".\n5. Some critical data should be included in the manuscript. For example, the authors did not mention the number of\nbiological replicates for RNA-seq.", "reviewer_4": "The authors clearly present an interesting and thorough study with largely compelling evidence that PbAP2-tr regulates\nasexual stage parasite genes by binding to two motifs at their promoters and by recruiting PbMORC to these sites where the\ncomplex acts to repress expression of these genes. This is an important and interesting finding. There are some issues with\nthe way the data is presented, particularly the chip data, which hinders critical assessment and which could be altered to\nfacilitate assessing the conclusions. The differential expression data should also be shown to not be affected by\ndevelopmental delays which might have confounded the analyses.\nSpecific comments\nFor clarity I will use -/- to indicate a KOd allele throughout this review although I am aware that these parasites are haploid.\nPage 5 line 166 “This result suggests that in P. berghei, PbAP2-TR is essential for asexual blood stage development and\nthat repression of ap2-g transcription is not a common function of PbAP2-TR orthologs .”\nThis argument doesn’t make sense to me, ap2-tr is Kod on a ap2-g -/- background and asexual ap2-tr -/- parasites are not\nrecovered. This shows that AP2-tr is required for asexual growth as per the experiment performed on AP2-G +/+ \nbackground. How do these experiments inform understanding of AP2-tr regulation of Ap2-G? gametocyte production would\nneed to be recorded to infer that AP2-tr was not regulating AP2-G. AP2-G is not essential so nothing can really be inferred\nfrom AP2-tr-/- AP2-g-/- parasite experiment.\nPage 5 line 173 “To specifically assess the role of PbAP2-TR in asexual development, we disrupted pbap2-g in PbAP2-\nTR::GFP using the CRISPR/Cas9 system [PbAP2-TR::GFPpbap2-g(-), Fig S4 ].”\nAlthough it does not affect interpretation of AP2-tr chip enrichment, it is unclear here why the chipseq was performed on ap2-\ng-/- parasites. Later in the MS I realised that the authors were likely concerned that because PfAP2-G5 is an ortholog of AP2-\ntr and regulates gametocytogenesis so if AP2-tr also regulated gametocytogenesis then the resulting gametocytes could\nconfound their analyses of asexual development. I think they should make this point explicitly before describing their use of\nAP2-G -/- parasites because the rationale for using the AP2-G -/- was unclear and seemed to relate more to disproving a role\nfor AP2-tr in regulating gametocytogenesis, which was not done. It seems to me that the logical test would have been to\ncompare gam counts between ap2-tr -/- ap2-g -/- and ap2-tr -/-ap2-g+/+ to determine whether ap2-tr does actually regulate\nap2-g. Is it not possible to count gams in Pb?\nFigure 2A\nChipseq traces should include relevant input traces as well with ll traces normalised fro library size. Alternatively chip/input\ncould be shown and the raw traces for both reps chip and input could be provided as suppl figs.\nPage 5 line 186\n“Among the peaks containing both Motifs 1 and 2, the distance between these two motifs was not constant, suggesting that\nMotifs 1 and 2 function independently, rather than cooperatively, as a cis-regulatory element for PbAP2-TR (Fig 2F ).”\nA more cautious interpretation would be appropriate at this stage as it is not proven that ap2-tr binds either or both of the\nmotifs, it is probable that other TFs bind these promoters, potentially within the same complex.\nPage 6 lines 229-241 “PbAP2-TR functions as a transcriptional repressor”\nA common confounder of inducible KO studies in plasmodium is developmental delay in the KO affecting rnaseq diff gene\nexpression comparisons with the non-induced control. Have the matched ko and control rnaseq been assessed for\ndevelopmental stage, e.g. using the mixture model of tonkin-hill et al 2018 plos biol.\nPage 8 line 309 should this read fig 5b?\nFig 6C\nPbmorc and pbap2-tr chip traces should be shown as log2chip/input with both chip and input somehow normlaised for\nlibrary ize eg rpkm by a fixed bin size across the genome.\nFig 6D\nDetails should be provided of what is being shown, coverage is a generic term, it should be pbmorc log2chip/input for rpkm\nby bin size or similar measure that accounts for library size and non specific enrichment ie input or non-specific precipitated\nmaterial.\nIn general the chipseq data could be further explored, it would be interesting to see if Pb MORC and ap2-tr enrichment differ\nbetween heterochromatin and euchromatin and between coding sequence vs intergenic sequence using published datasets\nof heterochromatin marks eg H3K9me3 and input normalised data."}, "author_response": "7/11/2025\nResponses to Reviewers:\nWe would like to thank you for taking your time and effort to review our manuscript,\n“Precise gene regulation through transcriptional repression is essential for Plasmodium\nasexual blood stage development” (NCOMMS-25-48898). We found all of your\ncomments highly constructive and insightful. Thus, we sincerely made revisions\naccording to these comments.\nReviewer #1 (Remarks to the Author):\nThis manuscript describes the function of the Plasmodium berghei transcription factor\nthe authors name Pb-TR.\nThe authors convincingly show that this AP2 domain-containing protein is essential\nfor parasite development during the asexual replication cycle through a conditional\nKO. They go on to analyze its targets in the genome through both ChIP-Seq\nand DIP-Seq and convincingly identify candidate motifs. Interestingly, two independent motifs\nare identified and specify either the first two AP2 domains or the last single AP2 domain.\nThe authors go on to determine that Pb-TR is more associated with genes identified in\nthe ChIP-Seq analysis that are markers of early stages rather than late stages, leading\nto the hypothesis that Pb-TR is a repressor. They then further establish a phenotype\nusing their conditional KO RNA-Seq, and show in a luciferase assay that the motifs\nidentified can lead to higher reporter luciferase bioluminescence when mutated.\nFinally, they identify MORC as an interactor using both MS and by comparing ChIP-\nSeq profiles.\nThe data is overall compelling, and this is a useful addition to the understanding of\ntranscription in the rodent model of malaria.\nThere are a some limitations of the study.\nThank you for your thorough review and constructive comments. Your advice led us to\ntake a deeper look into our data and helped us improve the manuscript. We performed\nadditional experiments and analyses and adjusted statements in the manuscripts according\nto comments made by all reviewers. We hope the changes made in the revised manuscript\nwould satisfy your requirements below.\nGiven the strength of the phenotype, I found it surprising that the transcriptional\nchanges in the RNA-Seq data following excision were somewhat limited and wondered\n1\nwhether 12 hpi was indeed the right time point to conduct this assay. Only a minute\nnumber of genes with peaks are found to be upregulated. Is this low proportion\nexpected, and is it sufficient to conclude that Pb-TR is a transcriptional repressor?\nThank you for your comment. About the gene upregulation in pbap2-tr KO parasites, the\nnumber of PbAP2-TR targets in the significantly upregulated genes (defined as log (fold\n2\nchange) > 1 and p-valueadj < 0.05) were limited (47 genes) as you mention. However, 202\ntarget genes were upregulated with p-valueadj < 0.05, and 73% of the targets had log (fold\n2\nchange) higher than 0 (visualized as a histogram in Fig S6D, right). In addition, we could\nobserve overall upregulation tendency for the target genes with a p-value of 2.6 × 10−67\nby two-tailed Student’s t-test as described in the manuscript. We consider that this overall\nupregulation of target genes caused defects in the transcriptional control and eventually\ndevelopmental arrest. These results are a strong indication that PbAP2-TR is a\ntranscriptional repressor. Meanwhile, given your comment, we noticed that distribution\nof log (fold change) values for target genes was not clear in the volcano plot in the main\n2\nfigure, as also mentioned by reviewer #2. Thus, we replaced the volcano plot in Fig 4A\nwith the MA plot.\nAbout the timing of differential expression analysis, the analysis at later time-\npoint might detect more target genes in the significantly upregulated genes. However,\ndevelopment of pbap2-tr KO parasites is arrested at the trophozoite stage. After the\ndevelopmental arrest, parasites would eventually go on towards cell death; thus, cell\ndeath-related biological processes (e.g. mRNA decay) might affect the transcriptomic\nanalysis at the later time-point. Of note, reviewer #4 was also concerned about the\npossibility that developmental delay in the KO parasites has affected the differential\nexpression analysis. Therefore, we chose 12 hpi, at which obvious developmental delay\nor arrest has not been observed in the pbap2-tr KO parasites (Fig 1E), to minimize such\nconfounding effects in the analysis and to assess the transcriptomic changes directly\ninduced by pbap2-tr-disruption.\nIn addition to the timing of performing the analysis, another factor is involved in\nthe relatively low fold change values of some targets. As discussed in the manuscript, one\nof the major roles of PbAP2-TR is repression of genes that have peak expression during\nring to early trophozoite development (e.g., ribosome biogenesis and exported protein).\nThese target genes are less responsive in the differential expression analysis because\nhighly expressed genes show only modest fold changes when upregulated. Thus, we\nconsider that the limited number of significantly upregulated target genes was due to their\nactive transcription before PbAP2-TR expression.\nit would be interesting to dissect and discuss further the contribution of the different\nAP2 domains and whether they may be associated with different targets.\nThank you for your suggestion. Gene classification in the target genes that were\nassociated with Motifs 1 or 2 was not largely different between them. In addition, no\nenrichment of Motif 1 or 2 targets was detected for any characteristic groups (p-value >\n0.01 by Fisher’s exact test for all characteristic groups). Given these, we added the\nfollowing sentence and supplementary figure (Fig S7A) to describe these results and also\nincluded information of which motifs the targets are associated with in Table S3.\nLine: “In any of these groups, no significant enrichment of targets associated with Motif\n1 or 2 was detected, suggesting that difference in the binding motifs was not related to\nenrichment of characteristic groups in PbAP2-TR targets (Fig S7A and Table S3).”\nMeanwhile, it is noteworthy that having different binding motifs (Motifs 1 and\n2) is important for PbAP2-TR to generate variation in the level of transcriptional\nrepression among its targets as we have shown in the differential expression analysis and\nluciferase reporter assays. Intriguingly, such a cis element-dependent mechanism of\nmodulating the degree of transcriptional regulation was also found for PbSIP2 in our\nprevious study. Thus, we have described these results in the Results section as follows.\nLine: “These results verify that Motif 1 is a stronger cis-regulatory element for\ntranscriptional repression by PbAP2-TR than Motif 2. Collectively, these results suggest\nthat a single transcription factor can generate variations in the transcript levels of target\ngenes through combinations of different cis-regulatory elements. In a previous study, we\ndescribed a similar mechanism for transcriptional activation by PbSIP2 22. These cis-\nelement dependent variations in the levels of transcriptional activation and repression\nmay be important for the parasite to regulate its complex life cycle with a small number\nof sequence-specific transcription factors 19.”\nThe discussion around the functional enrichment of Pb-TR targets is perhaps not\ndeserving of a main figure, as it doesn’t really enhance the understanding of the\nphenotype, and no attempt is made to use the RNA-Seq in tandem.\nThank you for your opinion. We think that it is very important to know what types of\ngenes need to be repressed by PbAP2-TR for facilitating the trophozoite development. As\nwe stated in the manuscript, through target classification, we unraveled that major\n(e.g., ribosome biogenesis and exported protein). The time-course RNA-seq analysis\nfurther revealed their transcription patterns during ring-to-trophozoite development,\nwhich peaked at 8 hpi (Fig 5B and S7B). These results suggest that the major role of\nPbAP2-TR is to establish the transcriptional peak pattern during the ring to early\ntrophozoite development. We consider that defects in controlling such transcriptional\npeak patterns of hundreds of its target genes caused the developmental arrest in the pbap2-\ntr KO parasite. Notably, the expression of these target-enriched gene groups was\nupregulated in the pbap2-tr KO parasites at 12 hpi. We added this result to the Results\nsection with a supplementary figure Fig S7C as follows.\nLine 332–333: “Notably, expression of targets in these groups was mostly upregulated in\npbap2-tr-DiCreRapa+ compared to pbap2-tr-DiCreRapa- (Fig S7C).”\nConsidering these results, we would like to present the characterization of\nPbAP2-TR targets in a main figure.\nAnother example is the other proteins identified by RIME, which include several\nchromatin-associated proteins, but no attempt is made at discussing whether they may\nalso be present at Pb-TR sites and how that could play into the transcriptional\nregulation.\nThank you for your insight. As you mention, our RIME detected some proteins putatively\nrelated to transcriptional regulation in those uniquely IPed with PbAP2-TR::GFP, such as\nEELM2-domain containing protein and ISWI chromatin-remodeling complex ATPase.\nHowever, we were not sure to mention them as an interaction partner of PbAP2-TR\nbecause their average quantitative values (aveQVs) in PbAP2-TR::GFP ChIP samples\nwere less than 3, significantly lower compared to that of PbAP2-TR (aveQV = 25.8) and\nPbMORC (aveQV = 21.7). Meanwhile, we agree that it is important to mention these\nproteins as potential interactors of PbAP2-TR (or PbMORC). In addition, we performed\nreciprocal RIME analysis using PbMORC::GFPpbap2-g(-) (as suggested by reviewer #2)\nand detected several important transcription factors and putative regulators, in addition to\nabove-mentioned factors. Collectively, we modified the Results and Discussion sections\nas follows. Also, we indicated these proteins in Fig 6A and 6C.\n<Results>\nLine 353–362: “Plasmodium parasites possess a single MORC, which has a conserved\nGHKL (gyrase, Hsp90, histidine kinase, and MutL)-ATPase domain and several Kelch\nmotifs (Fig 6B) 34. To verify that PbMORC is a PbAP2-TR co-factor, we performed the\n4\nreciprocal RIME analysis at 12 hpi. To conduct this experiment on the pbap2-g knockout\nbackground as with the above RIME analysis, a parasite line expressing GFP-fused\nPbMORC was generated, and pbap2-g was disrupted in this parasite\n[PbMORC::GFPpbap2-g(-), Fig S8A]. The RIME analysis using PbMORC::GFPpbap2-g(-)\ndetected 146 proteins that were unique or more than five-fold enriched (Fig 6C and Table\nS8B). These proteins included PbMORC and PbAP2-TR with the first and third highest\naveQVs of 121.3 and 47.5, respectively (Fig 6C and Table S8B), which supports the\nnotion that PbMORC acts as a major co-factor of PbAP2-TR.”\nLine 375–397: “Importantly, while ChIP-seq showed co-localization in the PbAP2-TR\nbinding regions, only 38% (547/1436 peaks) of the PbMORC peaks overlapped with the\nPbAP2-TR peaks (Fig 6F). Motif enrichment analysis of the remaining PbMORC peaks\n(889 peaks) detected ACACA, TGCAY, and YGTCT, along with their related motifs (Fig\n6G and Table S9E). These results imply that PbMORC is recruited to the genome not only\nby PbAP2-TR but also through other factors. In the PbMORC RIME, two other AP2\nfamily members, PBANKA_0521700 and PbAP2-P (PBANKA_0939100), were\nidentified with the second and fourth highest aveQVs of 69.3 and 27.8, respectively (Fig\n6C and Table S8B) while they were not detected in the PbAP2-TR RIME (Table S8A).\nThese findings may suggest that PbMORC functions as a co-factor of\nPBANKA_0521700 and PbAP2-P during the IDC, independently of PbAP2-TR. Notably,\nin P. falciparum, the orthologs of these transcription factors, PF3D7_0420300 and PfAP2-\nP (PF3D7_1107800), were also detected in the co-IP with PfMORC 34,35. In addition,\nPF3D7_0420300 and PfAP2-P have been reported to bind to ACACA and TGCATG,\nrespectively 31,36, which were analogous to those enriched in the PbMORC peaks.\nRIME analyses of PbAP2-TR and PbMORC additionally identified several\nputative transcriptional regulators. The proteins commonly detected in the two RIME\nanalyses included EELM2 (PBANKA_1234600) and ISWI (PBANKA_1123500) (Fig\n6A, 6C, Table S8A, and S8B). Furthermore, other putative transcriptional regulators, such\nas CHD1 (PBANKA_0907200), ELM2 (PBANKA_0205000), and HDAC1\n(PBANKA_0826500), were uniquely identified in the PbMORC RIME (Fig 6C and Table\nS8B). While their aveQVs in the RIME were relatively low compared to those of PbAP2-\nTR and PbMORC, these proteins might also contribute to the transcriptional regulation\nduring the IDC as potential interaction partners of PbAP2-TR and/or PbMORC.”\n<Discussion>\nLine 450–464: “In Toxoplasma, MORC functions in a complex with histone deacetylase\n3 (HDAC3) to regulate sexual commitment, suggesting that MORC functions are related\nto histone modifications 54. Comparably, HDAC1 was detected as an interaction partner\nof both PbMORC and PfMORC 34,35, suggesting that the cooperation of MORC proteins\nwith histone deacetylases is common in Apicomplexa. In contrast, RIME analysis with\nPbAP2-TR detected PbMORC as a major co-factor, but no histone-modifying enzymes.\nSimilarly, our previous study revealed PbMORC as the only major co-factor of the\nfemale-specific transcriptional repressor complex, PbAP2-FG2/PbAP2R-2 39. These\nimply that, in Plasmodium, the components of co-factor complexes differ depending on\nthe transcription factor that recruits them; i.e. when PbMORC is recruited by PbAP2-TR\nor PbAP2-FG2, they may repress target gene expression simply by remodeling chromatin\nstates, without the involvement of histone modification. Alternatively, the PbAP2-TR and\nPbAP2-FG2 RIME did not detect histone modifying enzymes perhaps because they may\ninitially act in a complex with MORC and subsequently dissociate from genomic DNA\nwhile MORC remains associated with chromatin. Following this dissociation, MORC\nmay then recruit histone-modifying enzymes to further modulate the downstream gene\nexpression.”\nAn interrogation arising from the paper is the contrast with the phenotype of the\nPlasmodium falciparum ortholog of Pb-TR. The authors contrast this in the discussion,\nbut this could be really enhanced; a divergent role of an AP2 in different spp. is\nan interesting observation, and the authors could do more comparative analysis to\nestablish whether there is a possible divergence. For instance, comparing targets of the\nAPG5 and Pb-TR may be an interesting first step. Truly establishing a divergence\nbetween the two species would really enhance the impact of the paper.\nThank you for your suggestion. As you mention, it would be valuable to discuss a\ndivergence in roles of PbAP2-TR and PfAP2-G5 through comparing their ChIP-seq\nresults. In fact, we have previously downloaded the fastq files of PfAP2-G5 ChIP-seq\ndata at the trophozoite stage and analyzed them using the same method we used in\nthe current manuscript to compare them with our PbAP2-TR ChIP-seq data in detail.\nHowever, as we mapped their sequence data on the P. falciparum genome, their input data\nshowed considerably high ratio of reads on gene bodies (input_1, 90.55%: input_2,\n90.59%). Ideally, input data should show constant distribution of sequence reads across\nthe genome; thus, the ratio of reads mapped on gene bodies should be comparable to the\nratio of these regions on the genome (approximately 60% in P. falciparum). In addition,\nwhile ChIP data for transcription factors should have less sequence reads on gene bodies\n(because transcription factors bind to regulatory regions, which are mainly located on\nintergenic regions), more reads were mapped onto gene bodies for the PfAP2-G5 ChIP\ncompared with their input data (ChIP_1, 92.30%: ChIP_2, 92.40%). Furthermore, we\nnoticed that read coverage of PfAP2-G5 ChIP and input data showed many peak-like\npatterns on gene bodies, unlike our ChIP data (Figure below). This sequence bias in the\nPfAP2-G5 ChIP-seq made us concerned about their data quality. Incidentally, our input\ndata for PbAP2-TR showed 61% of reads on gene bodies, which was comparable to the\nratio of gene body regions on the genome (62%). Furthermore, the ChIP data of PbAP2-\nTR showed smaller ratio of reads on gene bodies (46%).\nThe sequence bias in the PfAP2-G5 ChIP-seq seemed to be derived from GC\nbias (Figure below) and hence was probably caused by too many amplification cycles\nduring the library preparation. (We suspect that amplification of extreme AT-rich\nsequences for the intergenic regions of P. falciparum is less efficient than gene body\nregions.) This bias must affect the peak calling results. In fact, more than half of peaks\ndetected in our macs2 peak-calling for the PfAP2-G5 ChIP-seq were located on gene\nbodies, which was highly unusual for ChIP-seq of transcription factors. Presumably, due\nto such biased data, X Shang et al. defined genes with ChIP-seq peaks within their gene\nbodies as target genes, in addition to those with peaks upstream. This analysis is also\nunusual for ChIP-seq experiments of sequence-specific transcription factors.\nThrough the analysis, we considered that the ChIP-seq data of PfAP2-G5 was\nnot performed with a good quality. This outcome made us hesitate to compare the ChIP-\nseq result with ours in detail and to discuss the roles of PbAP2-TR/PfAP2-G5 based on\nthis comparison because we could not be sure if the results were derived from actual\ndifferences between the roles of PbAP2-TR and PfAP2-G5 or just sequence bias.\nHowever, as you asked (also asked by other reviewers), many readers would be interested\nin the comparison between the functions of PbAP2-TR and PfAP2-G5. Thus, we at least\ncompared the target genes and binding motifs of PbAP2-TR with those of PfAP2-G5\nreported in the study by X Shang et al. (for the target comparison, those with peaks\nupstream were compared). We described these as follows.\nLine 223–225: “Among these targets, only 88 genes overlapped with those of PfAP2-G5\nat the trophozoite stage (517 genes reported by Shang et al.) (Table S3).”\nLine 194–195: “Similar motifs were also enriched in the ChIP-seq analysis of PfAP2-G5\n30.”\nA citation of a VEuPathDB publication should be included.\nsentence in which we mentioned PlasmoDB.\n“Alvarez-Jarreta, J. et al. VEuPathDB: the eukaryotic pathogen, vector and host\nbioinformatics resource center in 2023. Nucleic Acids Res 52, D808–D816 (2024).”\nReviewer #2 (Remarks to the Author):\nSummary: The study identifies PbAP2-TR (Trophozoite Repressor) as a trophozoite-\nstage AP2 transcription factor that functions as a transcriptional repressor essential\nfor Plasmodium berghei asexual blood-stage development. Using DiCre conditional\nknockout, ChIP-seq/DIP-seq, time-course RNA-seq, motif mutagenesis luciferase\nreporters, and RIME/ChIP-seq for PbMORC, the authors show that PbAP2-TR binds\ntwo motifs (GTTGY and GTTCT) via distinct AP2 domains, represses target genes\n(notably ribosome biogenesis and exported proteins) from 8-16 hpi, and recruits\nPbMORC as a co-factor; only ~38% of MORC peaks overlap with PbAP2-TR, implying\nadditional recruiters.\nThank you for your thorough review and constructive comments. Your advice on data\nanalysis and visualization was very clear and helpful for us to improve our manuscript.\nAccordingly, we performed additional experiments and analyses and adjusted statements\nin the manuscripts. We hope the changes made in the revised manuscript would satisfy\nyour requirements below.\nOriginality and field context: Prior work in Toxoplasma gondii established a MORC–\nHDAC3–ApiAP2 repression axis, and recent P. falciparum studies show PfMORC is\nessential, associates with heterochromatin, and co-IPs with multiple ApiAP2 proteins\n(including PfAP2-G5). The present study moves beyond association to a cis-encoded,\nstage-bounded mechanism in malaria parasites: a specific trophozoite ApiAP2\nrepressor (PbAP2-TR) with dual-motif/domain logic that recruits PbMORC to enforce\na precise 8-16 hpi repression program. Notably, while PfAP2-G5 co-purifies with\nPfMORC, it is non-essential across the IDC and primarily linked to restraining\ngametocyte commitment, whereas PbAP2-TR is essential for asexual progression—\nunderscoring a mechanistic advance rather than a mere extension of Pf co-IP\nobservations. In short, the present story extends the Toxoplasma paradigm and fills a\nkey mechanistic gap left by the PfMORC literature, making it a substantive, field-\nmoving advance rather than an incremental confirmation.\nbiology. We are truly grateful with your generous and positive comments.\nMajor strengths\nClear stage specificity and genetic essentiality. PbAP2-TR is expressed in trophozoites\nand DiCre excision causes a trophozoite-stage developmental arrest with careful\nstaging controls.\nCohesive multi-omics mechanism. ChIP-seq and DIP-seq define two motifs and assign\nthem to different AP2 domains; luciferase mutagenesis shows cis-repressive function\nwith Motif 1 > Motif 2 effect sizes.\nBiological coherence. Target-enriched functional categories (ribosome biogenesis,\nexported proteins, pellicle/IMC) decline from 8-16 hpi, matching the proposed\nrepressive window.\nThank you so much for captioning the major strengths in our manuscript. These\nstatements show that you have reviewed our manuscript thoroughly. We really appreciate\nyou taking your time to review our manuscript and provide these comments.\nA) Key concerns about Transcriptomics (analysis & visualization)\nThe transcriptomic component is central to your mechanistic claim and is, overall, well\nintegrated with the genetics and ChIP data. The authors analyze (i) an 8-16 hpi\nprogression in an ap2-g- background to align with the trophozoite window of PbAP2-\nTR expression, and (ii) an acute pbap2-tr DiCre ± rapamycin contrast at 12 hpi with\nthree biological replicates, mapped with HISAT2/featureCounts and modeled in\nDESeq2—good choices that match the biology and enable clear cross-validation\nbetween time course and inducible loss of function. At present, results are primarily\nvisualized with volcano plots (Fig. 3A, Fig. 4A), and gene-set summaries are shown as\nTPM-scaled line plots across 4/8/16 hpi (Fig. 5B).\nUse MA plots with shrunken log2FC values instead of volcano plots. The current\nvolcanoes (Figs. 3A and 4A) overemphasize extreme p-values, which hides the role of\nexpression strength and gives undue weight to low-count, highly significant genes. MA\nplots (mean expression vs shrunken log2FC, e.g. with DESeq2 apeglm/ashr) make\neffect sizes at biologically relevant expression levels clearer. Please re-render Figs. 3A\nand 4A as MA plots, marking FDR and |LFC| cutoffs directly; a simplified volcano can\nremain in the supplement if desired.\nDESeq2 apeglm to shrink the log (fold change) values without filtering out genes with\nMaterials and methods section as follows and also cited A Zhu et al. (2018).\nLine: “For differential expression analyses, DESeq2 apeglm shrinkage 65 was applied to\nthe log (fold change) to accurately evaluate the effect sizes without arbitrarily filtering\n2\nout genes with low counts.”\nNext, we produced MA plots for differential expression analyses of 8 vs 16 hpi\nand WT vs KO and replaced volcano plots in Fig 3A and 4A with these MA plots. For\ndifferential expression analysis between pbap2-tr KO and DMSO-control, we provided\nthe volcano plot as a supplementary figure Fig S6D. For 8 vs 16 hpi, we did not include\nthe volcano plot in a figure because many genes had p-values below 10-300 and were\noveremphasized in the plot as you mentioned.\nAlong with the apeglm application, results of differential expression analyses\nwere slightly changed (e.g. the number of significantly up/downregulated genes, motif\nenrichment, and p-values for Student’s t-test). Accordingly, we modified some texts in\nthe Results section and Fig 3B, 4B, and 4F.\nShow full QC and replicate information. For the 12 hpi DiCre contrast (n = 3 per\ncondition), include in the Supplement a PCA plot, a sample-to-sample distance\nheatmap, and the standard DESeq2 dispersion–mean plot to document replicate\nconsistency and treatment separation. Clearly state the number of replicates for the\n8/16 hpi time points and provide the same QC panels, so readers can be confident that\nthe time-course results are robust.\nThank you for your advice. We provided the PCA plots, the sample-to-sample distance\nheatmaps, and the standard DESeq2 dispersion–mean plots for differential expression\nanalyses of 8 vs 16 hpi and WT vs KO in the supplementary figures (Fig S5A–C and Fig\nS6A–C, respectively). Regarding these, we added the following sentence in the Results\nand Materials and methods sections.\nLine 229–230: “(quality check results were shown in Fig S5A–C)”\nLine 245–246: “(quality check results were shown in Fig S6A–C)”\nLine 617–619: “To evaluate the replicate consistency, principal component analysis plots,\nsample-to-sample distance heatmaps, and dispersion plots were produced using DESeq2\nplotPCA, dist, and plotDispEsts, respectively.”\nIn addition, we modified a sentence as follows to clarify the number of replicates\n11\nfor the RNA-seq analysis of pbap2-g KO parasites at 8 and 16 hpi in the Results section.\nLine 227–229: “To obtain asexual transcriptomic data, RNA-seq analyses were conducted\nusing gametocyte-less mutant parasites, i.e., the ap2-g-knockout line, in biological\ntriplicate”\nAlso, we added the following sentence to the figure caption of Fig 5B to clarify\nthe number of replicates for the RNA-seq analysis of pbap2-g KO parasites at 4, 8, and\n16 hpi.\nLine 927–928: “Transcriptomic analyses were performed in biological triplicate at each\ntime-point.”\nClarify the gene-set expression patterns. Fig. 5B’s line plots (TPM normalized to 4 hpi)\nare informative but overcrowded. Replace or supplement them with row-z-scored\nheatmaps of the main gene sets (“ribosome biogenesis,” “nucleolus,” “exported\nproteins/pellicle”) across 4/8/16 hpi, annotated with PbAP2-TR target status and Motif\n1/Motif 2 presence near the TSS. This format will make the coordinated 8–16 hpi down-\nregulation immediately visible and directly link expression changes to cis-regulatory\nlogic.\nThank you for your useful suggestion for improving our data presentation. Following\nyour comment, we supplemented the Fig 5B with row-z-scored heatmaps, which were\nproduced using Heatmapper (S Babicki et al., 2016) and were shown as a supplement\nfigure Fig S7B. In the figure, we annotated PbAP2-TR targets on the side of heatmaps.\nAbout the motif presence, currently, TSSs in P. berghei have not been elucidated.\nMeanwhile, we think that regarding the cis-regulatory argument, whether these motifs\nexist in the PbAP2-TR binding regions would be a more appropriate criterion. Thus, we\ndecided to categorize the targets according to whether Motifs 1 and 2 are present in the\nupstream ChIP-seq peak regions and to color-code them (those with both Motifs 1 and 2,\nonly Motif 1, only Motif 2, and no motifs by yellow, green, blue, and grey, respectively).\nB) Key concerns about MORC/AP2-TR\nIn Fig. 6C, the IGV snapshots don’t convincingly demonstrate co-localization: the two\nPbMORC replicates are shown on chromosome 1 with their own y-axis scales, and the\nPbAP2-TR track is plotted separately below, making direct, like-for-like visual\ncomparison difficult; several MORC peaks appear without an obvious AP2-TR peak in\nthe same view. This impression actually matches your own quantification that only 38%\nof MORC peaks overlap AP2-TR (Fig. 6E), so the panel, as drawn, tends to undercut\n12\nthe text’s claim of “genome-wide co-localization.” Consider (i) replotting matched loci\nwith identical y-axis scaling and a single, aligned multi-track view (MORC rep1/rep2\nand AP2-TR together), (ii) adding zoom-ins on representative overlap and non-overlap\nsites, and (iii) emphasizing the more appropriate summary evidence (the heat\nmap of MORC signal centered on AP2-TR peaks in Fig. 6D and the 38% overlap in Fig. 6E)\nwhile softening the wording from “genome-wide co-localization” to “co-localized at a\nsubset of AP2-TR sites.”\nThank you for your comment and ideas for improving our data presentation with detailed\ninstructions. Considering these, we made the following modifications.\n(i) We replaced the IGV images of row counts in ChIP-seq data into those of\nlog -transformed ChIP/input and provided them as a single multi-track view (Fig 6D).\n2\n(ii) We added several IGV images at overlap and non-overlap sites as a\nsupplementary figure Fig S8D (rps24, rpl6, and imc1a for overlap sites, dlat, noc2, and\ncyt c for non-overlap sites). In the figure, we also indicated positions of Motifs 1 and 2\nby green and blue bars, respectively.\n(iii) We indicated the 38%-overlap in Fig 6F. Regarding the co-localization of\nPbAP2-TR and PbMORC, we consider that these two factors indeed co-localize genome-\nwidely. Although only 38% of PbMORC peaks overlapped with those of PbAP2-TR,\nthese common peaks accounted for 54% of PbAP2-TR peaks. Given that even replicate\nChIP-seq datasets typically show approximately 80% overlap under stringent peak-\ncalling thresholds (e.g., fold enrichment > 3 and q-value < 0.01 in our study), a 54%\noverlap between two distinct factors can be considered as substantially high. Meanwhile,\nthe genome-wide co-localization cannot be fully demonstrated based on the peak-\noverlaps. Thus, we provided the heatmap of PbMORC ChIP-seq log (ChIP/input) across\n2\nall PbAP2-TR peaks, which showed peak patterns around most PbAP2-TR peak summits\n(Fig 6E), including the regions defined as “non-overlap” sites (Fig S8D). This heatmap\nsuggests that these “non-overlap” regions could not be detected as peaks in the PbMORC\nChIP-seq due to our peak-calling criteria. In fact, when the PbMORC peaks were called\nwith only the q-value threshold, they encompassed 90% of PbAP2-TR peaks. To make\nthis clearer, we provided heatmap showing PbMORC log (ChIP/input) around the summit\n2\nof “non-overlap” PbAP2-TR peaks (470 peaks, upper part of the Venn diagram in Fig\nS8C) as a supplementary figure Fig S8C. In addition, we modified the Results section as\nfollows.\nLine 366–374: “Among these common peaks, 547 peaks overlapped with those of\nPbAP2-TR, accounting for 54% (547/1017 peaks) of the PbAP2-TR peaks. Consistently,\nof 1.5 × 10−52 and 0.035, respectively, by Fisher’s exact test (Table S9D). Furthermore,\nthe PbMORC ChIP-seq coverage showed clear enrichment patterns around the summits\nof most PbAP2-TR peaks (Fig 6E), including those that were classified as “non-\noverlapping” with the PbMORC peaks under the thresholds of fold enrichment > 3 and\nq-value < 0.01 in macs2 peak calling (Fig S8C and S8D). These results indicate that\nPbAP2-TR genome-widely recruits PbMORC to the upstream regions of its target genes.”\nTo move beyond correlative evidence of MORC co-recruitment, perform reciprocal co-\nIP or BioID to confirm direct complex formation and reinforce the central model.\nThank you for your suggestion. Accordingly, we performed RIME experiment using\nPbMORC::GFPpbap2-g(-) and detected PbAP2-TR with the third highest average\nquantitative value (aveQV) (PbMORC being the highest), which strongly supports our\nconclusion that PbMORC is a major co-factor of PbAP2-TR. In addition, we detected two\nother AP2 transcription factors, PBANKA_0521700 and PbAP2-P, with the second and\nfourth highest aveQVs, respectively. Notably, in P. falciparum, these transcription factors\nwere suggested to bind to the ACACA and TGCATG motifs, respectively, which were\nsimilar to those enriched in the PbMORC peak regions. Thus, the result suggests that\nthese factors recruit PbMORC to specific cis-regulatory elements, other than PbAP2-TR\nbinding motifs, on the genome.\nIn addition to these transcription factors, the PbMORC RIME detected several\nother transcriptional regulators (also described in the answer to your next comment). Of\nnote, these included HDAC1, which was also detected previous co-IP with PfMORC in\nP. falciparum, indicating that the function of MORC is related to regulation of histone\ndeacetylation and is conserved within Apicomplexa. Given this result and the RIME with\nPbAP2-TR, which did not detect HDAC1, we set up two hypotheses: 1. in Plasmodium,\nthe components of co-factor complexes, which include MORC, are dependent on the\ntranscription factor that recruits them, and for certain transcription factors, histone-\nmodifying enzymes are not required. 2. transcription factors first recruit MORC and\ntogether regulate the downstream gene expression. After that, transcription factors\ndissociate from genomic DNA, and the remaining MORC subsequently recruits histone\ndeacetylases to further modulate gene expression. Accordingly, we added Fig 6C and\nTable S8B for the PbMORC RIME results and modified the Results and Discussion\nsections as follows.\n<Results>\nGHKL (gyrase, Hsp90, histidine kinase, and MutL)-ATPase domain and several Kelch\nmotifs (Fig 6B) 34. To verify that PbMORC is a PbAP2-TR co-factor, we performed the\nreciprocal RIME analysis at 12 hpi. To conduct this experiment on the pbap2-g knockout\nbackground as with the above RIME analysis, a parasite line expressing GFP-fused\nPbMORC was generated, and pbap2-g was disrupted in this parasite\n[PbMORC::GFPpbap2-g(-), Fig S8A]. The RIME analysis using PbMORC::GFPpbap2-g(-)\ndetected 146 proteins that were unique or more than five-fold enriched (Fig 6C and Table\nS8B). These proteins included PbMORC and PbAP2-TR with the first and third highest\naveQVs of 121.3 and 47.5, respectively (Fig 6C and Table S8B), which supports the\nnotion that PbMORC acts as a major co-factor of PbAP2-TR.”\nLine 375–397: “Importantly, while ChIP-seq showed co-localization in the PbAP2-TR\nbinding regions, only 38% (547/1436 peaks) of the PbMORC peaks overlapped with the\nPbAP2-TR peaks (Fig 6F). Motif enrichment analysis of the remaining PbMORC peaks\n(889 peaks) detected ACACA, TGCAY, and YGTCT, along with their related motifs (Fig\n6G and Table S9E). These results imply that PbMORC is recruited to the genome not only\nby PbAP2-TR but also through other factors. In the PbMORC RIME, two other AP2\nfamily members, PBANKA_0521700 and PbAP2-P (PBANKA_0939100), were\nidentified with the second and fourth highest aveQVs of 69.3 and 27.8, respectively (Fig\n6C and Table S8B) while they were not detected in the PbAP2-TR RIME (Table S8A).\nThese findings may suggest that PbMORC functions as a co-factor of\nPBANKA_0521700 and PbAP2-P during the IDC, independently of PbAP2-TR. Notably,\nin P. falciparum, the orthologs of these transcription factors, PF3D7_0420300 and PfAP2-\nP (PF3D7_1107800), were also detected in the co-IP with PfMORC 34,35. In addition,\nPF3D7_0420300 and PfAP2-P have been reported to bind to ACACA and TGCATG,\nrespectively 31,36, which were analogous to those enriched in the PbMORC peaks.\nRIME analyses of PbAP2-TR and PbMORC additionally identified several\nputative transcriptional regulators. The proteins commonly detected in the two RIME\nanalyses included EELM2 (PBANKA_1234600) and ISWI (PBANKA_1123500) (Fig\n6A, 6C, Table S8A, and S8B). Furthermore, other putative transcriptional regulators, such\nas CHD1 (PBANKA_0907200), ELM2 (PBANKA_0205000), and HDAC1\n(PBANKA_0826500), were uniquely identified in the PbMORC RIME (Fig 6C and Table\nS8B). While their aveQVs in the RIME were relatively low compared to those of PbAP2-\nTR and PbMORC, these proteins might also contribute to the transcriptional regulation\nduring the IDC as potential interaction partners of PbAP2-TR and/or PbMORC.”\n<Discussion>\nLine 450–464: “In Toxoplasma, MORC functions in a complex with histone deacetylase\n3 (HDAC3) to regulate sexual commitment, suggesting that MORC functions are related\nto histone modifications 54. Comparably, HDAC1 was detected as an interaction partner\nof both PbMORC and PfMORC 34,35, suggesting that the cooperation of MORC proteins\nwith histone deacetylases is common in Apicomplexa. In contrast, RIME analysis with\nPbAP2-TR detected PbMORC as a major co-factor, but no histone-modifying enzymes.\nSimilarly, our previous study revealed PbMORC as the only major co-factor of the\nfemale-specific transcriptional repressor complex, PbAP2-FG2/PbAP2R-2 39. These\nimply that, in Plasmodium, the components of co-factor complexes differ depending on\nthe transcription factor that recruits them; i.e. when PbMORC is recruited by PbAP2-TR\nor PbAP2-FG2, they may repress target gene expression simply by remodeling chromatin\nstates, without the involvement of histone modification. Alternatively, the PbAP2-TR and\nPbAP2-FG2 RIME did not detect histone modifying enzymes perhaps because they may\ninitially act in a complex with MORC and subsequently dissociate from genomic DNA\nwhile MORC remains associated with chromatin. Following this dissociation, MORC\nmay then recruit histone-modifying enzymes to further modulate the downstream gene\nexpression.”\nC) Minor comments\nYour RIME list (Table S8) includes a protein bearing an ELM2 domain—precisely the\nclass of ELM2–SANT co-repressors that scaffold MORC–HDAC3 complexes in\nToxoplasma—yet the manuscript concludes that no chromatin regulators were\ndetected and emphasizes MORC acting alone; please acknowledge this candidate and,\nideally, test its association/functon(reciprocal IP).\nThank you for your insight. As you mention, our RIME detected EELM2-domain\ncontaining protein in those uniquely IPed with PbAP2-TR::GFP. However, we were not\nsure to mention this result because its average quantitative value (aveQV) in PbAP2-\nTR::GFP ChIP samples were less than 3, significantly smaller compared to that of PbAP2-\nTR (aveQV = 25.8) and PbMORC (aveQV = 21.7). Meanwhile, we agree that it is\nimportant to discuss EELM2 as potential interactors of PbAP2-TR (or PbMORC) because\nas you mention, EELM2 (or ELM2) was previously identified in co-IP with MORC in P.\nfalciparum and Toxoplasma. In addition, we performed reciprocal RIME analysis using\nPbMORC::GFP (as suggested above) and also detected EELM2. Accordingly, we\nmodified the Results section as described above and indicated EELM2 in Fig 6A and 6C.\nIn addition, we modified the Discussion section regarding MORC acting alone in\nas described in the answer to above comment.\nChIP-seq robustness: strengthen the ChIP-seq methods and reporting by providing\nreplicate concordance and quality metrics (IDR, FRiP, NSC, RSC) for both AP2-TR\nand MORC datasets, clarifying how peaks were called and thresholds defined.\nThank you for your advice. According to your comment, we presented concordance in\nChIP-seq peaks by performing IDR1D analysis (https://idr2d.mit.edu/) and showed the\nresult in Fig S4C for PbAP2-TR and Fig S8B for PbMORC. In addition, to assess\nconsistency in genome-wide ChIP/input values, we calculated Pearson correlation\ncoefficient between the replicates as follows. We produced bigwig file of log (ChIP/input)\n2\nusing bamCompare (deepTools) and then compared the replicate bigwig data at each 1\nkb-bin using multiBigwigSummary bins (deepTools). These analyses yielded the Pearson\ncorrelation coefficient of 0.96 and 0.94 for PbAP2-TR and PbMORC ChIP-seq,\nrespectively. The scatter plot for the comparison data was included in Fig 2A for PbAP2-\nTR and Fig 6D for PbMORC. Regarding these analyses, we modified the Results section\nand figure captions as follows.\n<Results>\nLine 184–186: “Genome-wide comparison of ChIP/input enrichment between the\nreplicates resulted in Pearson correlation coefficient of 0.96, and IDR1D analysis revealed\nrank of peaks in each replicate to be largely consistent, showing high reproducibility of\nthe data (Fig 2A, S4B, and S4C).”\nLine 364–366: “of which 1436 peaks (77% of the experiment 1 peaks) overlapped\n(Pearson correlation coefficient = 0.94) (Fig 6D and S8B, and Table S9A, S9B, and S9C).”\n<Figure captions>\nLine 878–879: “A scatter plot at the right bottom shows comparison of log (ChIP/input)\n2\nin replicate at each 1-kb bin.”\nLine 950–951: “A scatter plot on the right shows comparison of log (ChIP/input) in\n2\nreplicate at each 1-kb bin.”\nIn addition, we calculated FRiP of all ChIP and input data using plotEnrichment\n(deepTools) and NSC and RSC using phantompeakqualtools. We summarized these\nvalues in Table S1C for PbAP2-TR and Table S9C for PbMORC. Accordingly, the\nfollowing sentences were added in Materials and methods section.\nLine 566–573: “The ChIP-seq enrichment on the genome was visualized as log2-\ntransformed ChIP/input ratio using bamCompare setting bin size as 10 bp. The replicate\n17\ndata were compared using IDR1D (https://idr2d.mit.edu/) 61, setting max gap as 100, and\nmultiBigwigSummary bins, setting bin size as 1 kb, to assess their reproducibility.\nFraction of reads in peaks (FRiP) was calculated using plotEnrichment, and normalized\nstrand cross-correlation coefficient (NSC) and relative strand cross-correlation coefficient\n(RSC) were assessed using phantompeakqualtools for quality check of each ChIP and\ninput data.”\nAbout peak calling, we defined the parameters for macs2 in the Materials and\nmethods section as follows.\nLine 564–566: “peaks were called by the macs2 callpeak using the input sequence data\nas control (fold enrichment > 3.0, q-value < 0.01, and setting --call-summit option on).”\nIn addition, we added the following sentence to the Results section.\nLine 181–182: “(by macs2 with the thresholds of fold enrichment > 3.0 and q-value <\n0.01, using sequence data of input DNA as a control)”\nExplicitly justify the use of the ±1200 bp promoter window in P. berghei, state whether\nspike-in normalization was applied, and include antibody validation details (lot,\nspecificity) for the GFP ChIP. Finally, define the exact criteria for calling “targets”\ndirectly in the main text, not only in tables.\nThank you for very helpful point-by-point suggestions. About the 1,200-bp threshold for\ndefining target genes, we have been using the criterion for several previous transcriptional\nregulator studies and found it useful. In the P. berghei genome, average size of intergenic\nregions is ca. 1600, and median is ca. 1400. In addition, in our previous studies of AP2-\nO and AP2-Sp (the master regulator of ookinete and sporozoite development,\nrespectively), their binding motifs were observed within 1200 bp from the start codons of\nthe major stage-specific genes. Based on these, we speculated that 1200 bp threshold for\ndefining target genes would be sufficient to encompass most of the true targets. We think\nit is useful to include as many true targets as possible when evaluating the role of\ntranscription factors based functional enrichment in targets. We added the following\nsentence to the Materials and methods section to describe these criteria in detail.\nLine 582–584: “The 1200-bp threshold was determined based on the previous\nobservations that binding motifs of AP2-O and AP2-Sp were detected within 1200 bp\nfrom the start codons of the major ookinete and sporozoite-specific genes, respectively\n62,63.”\nWe did not use spike-in normalization and thus added the following text to clarify.\nLine 550: “ChIP-seq was performed as previously described without using spike-in\n18\nnormalization”\nAbout anti-GFP antibody, we described the details in the reporting summary but\nforgot to include them in the main manuscript. Thank you for the notification. We added\nthe details in the Materials and methods section as follows.\nLine 555–556: “(Abcam, ab290, Rabbit polyclonal, reactive against all variants of\nAequorea victoria GFP, GR19413-1)”\nCriteria for target genes were described in the Results section as follows.\nLine 222–223: “Based on ChIP-seq data, we identified 619 target genes of PbAP2-TR,\nwhich were defined as genes with a ChIP-seq peak within 1200 bp of the start codon\n(Table S3).”\nD) Optional but valuable additions\nConsider performing ATAC-seq in the PbAP2-TR KD context to directly link\ntranscriptional repression with chromatin compaction at target loci.\nThank you for your suggestion. We agree that ATAC-seq analysis in pbap2-tr KO would\nbe valuable because its co-factor PbMORC is a putative chromatin remodeling ATPase.\nMeanwhile, as our current manuscript and previous studies by others suggest, MORC is\nassociated with several AP2 transcription factors during the Plasmodium asexual blood\nstage development. Hence, we are planning to investigate the chromatin-level regulation\nafter evaluating the functions of other AP2 transcription factors that are associated with\nMORC, which we are currently pursuing, to capture the comprehensive regulatory\nmechanism during the asexual blood stage development. Thus, we would like to perform\nanalyses on chromatin state, including ATAC-seq analysis, on WT and several AP2 gene\nKO parasites in the future.\nReviewer #3 (Remarks to the Author):\nThe authors described the function of PbAP2-TR, an AP2-domain containing\ntranscriptional factor, in the regulation of malaria parasite asexual development. When\nthis gene was conditionally knocked out, parasite growth was arrested at the\ntrophozite stage. ChIP-seq analysis revealed PbAP2-TR-regulated genes and their binding motifs.\nDifferential expression analysis by RNA-seq indicated that PbAP2-TR is a\ntranscriptional repressor, and this conclusion was confirmed by an episomal expression\ncassette with PbAP2-TR binding motifs. ChIP followed by mass spectrometry analysis\nrevealed that PbMORC was associated with PbAP2-TR.\nThis work revealed the novel functions of PbAP2-TR, which is significant in the field.\nsuch as Dicre-based conditional KO, ChIP-seq, and RNA-seq. The overall study is\nexcellent and innovative. However, authors need to address quite a few questions to\ncompletely cover the whole story of this gene.\nThank you for your thorough review and constructive comments. Your insights into the\nconcordance between PbAP2-TR and PfAP2-G5 were especially helpful for us to revise\nour data analysis. We performed additional experiments and analyses and adjusted\nstatements in the manuscripts following comments from all reviewers. We hope the\nchanges made in the revised manuscript would satisfy your requirements below.\n1. First of all, this study revealed the potential hidden function of PfAP2-G5, the\northolog of PbAP2-TR in P. falciparum. That is AP2-G5 is also involved in regulating\nasexual development. However, on the other hand, this study did not provide enough\ndata on the function of PbAP2-TR in the regulation of AP2-G, which was shown in the\nPfAP2-G5 study. The authors did not mention whether AP2-G was changed or not,\nwhether gametocytegenesis and gemetocyte development were changed. Based on the\nRNA-seq data (Table S5), AP2-G was slightly increased after PbAP2-TR was deleted at\n12 hpi; meanwhile, AP2-G2 was significantly increased after PbAP2-TR KO (this may\nindicate that gametocyte development was changed).\nThank you for your important suggestion. Given your comment (and a comment from\nreviewer #4), we assessed the number of gametocytes in the pbap2-tr-DiCreRapa- and\npbap2-tr-DiCreRapa+ on Day 1 (24 hpi) (because gametocyte maturation takes\napproximately 24 h in P. berghei). The result showed no significant difference in\ngametocyte counts between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ (Fig S3B). Thus,\nwe described this result as follows.\nLine 157–162: “we assessed the number of gametocytes in pbap2-tr-DiCreRapa- and\npbap2-tr-DiCreRapa+ on day 1 (24 hpi) of the above in vivo growth assays (because\ngametocyte maturation takes approximately 24 h in P. berghei) through Giemsa-staining.\nGametocytemia (gametocyte/RBC) was comparable between pbap2-tr-DiCreRapa- and\npbap2-tr-DiCreRapa+, demonstrating that the rate of commitment to gametocyte fate was\nnot significantly affected by whether pbap2-tr was disrupted (Fig S3B).”\nAbout the differential expression of pbap2-g in the pbap2-tr KO parasites, the\nlog (fold change) and p-value for pbap2-g in the differential expression analysis were\n2\n0.075 and 0.79, respectively (after applying apeglm shrinkage as suggested by reviewer\n20\n#2). From these values, we cannot conclude that pbap2-g expression increased but rather\nthink that we should state the pbap2-g expression has not been changed upon the pbap2-\ntr-disruption. Thus, we added the following sentence in the Results section.\nLine 248–250: “Of note, pbap2-g was not differentially expressed in pbap2-tr-DiCreRapa+\n(log2(fold change) = 0.075 and p-valueadj = 0.79) consistent with the comparable sexual\ncommitment rate between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ (Fig S3B).”\nAbout the expression of pbap2-g2, its increase seemed to be directly induced by\nthe pbap2-tr-disruption because the PbAP2-TR ChIP-seq peaks were detected in the\nupstream region (at approximately 1.3 kb from the start codon) of pbap2-g2 with PbAP2-\nTR binding motifs around the summit (though pbap2-g2 was not included in the targets\ndue to the 1,200-bp threshold). We consider that the repression of pbap2-g2 could be\nimportant for the asexual blood stage development, and thus, increase of its expression is\nnot necessarily an indication of defects in gametocyte development.\n2. If PbAP2-TR is involved in regulating AP2-G, the ChIP-seq and RNA-seq analysis\nafter PbAP2-TR KO in AP2-G KO parasites may hide important information related to\nAP2-G. For example, PbAP2-TR binding sites in the AP2-G promoter (PfAP2-G5 was\nfound to bind the AP2-G promoter) may be omitted.\nThank you for your comment. We understand your concern about overseeing the possible\nrole of PbAP2-TR in regulating pbap2-g-transcription due to the experiments performed\non the pbap2-g KO background. However, we performed the differential expression\nanalysis in the WT background as described in the manuscript. In this analysis, we did\nnot detect upregulation of pbap2-g in the pbap2-tr KO parasites (as described above),\nconsistent with no increase of gametocyte production in the pbap2-tr KO parasites.\nThis result suggests that PbAP2-TR does not play an important role in pbap2-g regulation.\nAbout the ChIP-seq analysis in the pbap2-g KO background, if PbAP2-TR is\nimportant for the repression of pbap2-g, the ChIP-seq would still show a significant peak\nupstream pbap2-g because such repression should occur during the asexual blood stage\ndevelopment. In addition, we left the upstream region of pbap2-g intact in the pbap2-g\nKO parasites, so ChIP-seq peaks could be detected in this region. In fact, given your\ncomment, we evaluated ChIP-seq peaks upstream pbap2-g and found a peak\napproximately 2.5 kb upstream from the start codon of pbap2-g, which was excluded in\nthe target analysis due to the 1,200-bp threshold. Meanwhile, we detected no binding\nmotifs near the peak summit. Together with that pbap2-g was not upregulated in the\npbap2-tr KO parasites, we speculate that this PbAP2-TR binding is not important for its\n21\nfunction.\n3. The authors did not compare PbAP2-TR-regulated genes and binding motifs with\nthe PfAP2-G5-regulated genes and binding motifs. At least, PbAP2-TR binding motif\n2 is shared with PfAP2-G5 binding motif.\nThank you for your comment. We agree with your suggestion that it would be valuable to\ndiscuss the roles of PbAP2-TR and PfAP2-G5 through comparing their target genes and\nbinding motifs. In fact, we have previously downloaded the fastq files of PfAP2-G5 ChIP-\nseq data at the trophozoite stage and analyzed them using the same method we used in\nthe current manuscript to compare them with our PbAP2-TR ChIP-seq data in detail.\nHowever, as we mapped their sequence data on the P. falciparum genome, their input data\nshowed considerably high ratio of reads on gene bodies (input_1, 90.55%: input_2,\n90.59%). Ideally, input data should show constant distribution of sequence reads across\nthe genome; thus, the ratio of reads mapped on gene bodies should be comparable to the\nratio of these regions on the genome (approximately 60% in P. falciparum). In addition,\nwhile ChIP data for transcription factors should have less sequence reads on gene bodies\n(because transcription factors bind to regulatory regions, which are mainly located on\nintergenic regions), more reads were mapped onto gene bodies for the PfAP2-G5 ChIP\ncompared with their input data (ChIP_1, 92.30%: ChIP_2, 92.40%). Furthermore, we\nnoticed that read coverage of PfAP2-G5 ChIP and input data showed many peak-like\npatterns on gene bodies, unlike our ChIP data (Figure below). This sequence bias in the\nPfAP2-G5 ChIP-seq made us concerned about their data quality. Incidentally, our input\ndata for PbAP2-TR showed 61% of reads on gene bodies, which was comparable to the\nratio of gene body regions on the genome (62%). Furthermore, the ChIP data of PbAP2-\nTR showed smaller ratio of reads on gene bodies (46%).\nThe sequence bias in the PfAP2-G5 ChIP-seq seemed to be derived from GC\nbias (Figure below) and hence was probably caused by too many amplification cycles\nduring the library preparation. (We suspect that amplification of extreme AT-rich\nsequences for the intergenic regions of P. falciparum is less efficient than gene body\nregions.) This bias must affect the peak calling results. In fact, more than half of peaks\ndetected in our macs2 peak-calling for the PfAP2-G5 ChIP-seq were located on gene\nbodies, which was highly unusual for ChIP-seq of transcription factors. Presumably, due\nto such biased data, X Shang et al. defined genes with ChIP-seq peaks within their gene\nbodies as target genes, in addition to those with peaks upstream. This analysis is also\nunusual for ChIP-seq experiments of sequence-specific transcription factors.\nIn the study by X Shang et al., they only used peaks in the upstream regions of genes.\nIn general, after defining peaks with certain criteria (e.g. high fold enrichment, q-values,\nand reproducibility), they should not be further filtered for motif enrichment analysis\nbecause unnecessarily peak filtering may result in missing some true binding motifs. Thus,\nwe analyzed motif enrichment using all macs2-detected peaks (838 common peaks, fold\nenrichment > 3, q-value < 0.01). In the analysis, we detected enrichment of several GC-\nrich motifs (such as GCTGC and GGTGG), which were not detected in the study by X\nShang et al. These motifs were more prevalent in gene bodies than intergenic regions, and\nwhen we assessed motif enrichment using only peaks on intergenic regions, these motifs\nwere no longer enriched. Thus, we speculate that X Shang et al. decided to only use gene-\nupstream peaks because enrichment of these gene body-enriched motifs could be\nconfounding.\nUsing the gene-upstream peaks, X Shang et al. detected five weblogo motifs,\nwhich included both Motifs 1 and 2-related motifs (GT[T/G]GTA and [T/G]GT[T/G]C,\nrespectively). Among these five logos, two were highlighted in their manuscript and\nshown in the main figure. However, other three logos only appear in the supplementary\nfigure, and the most enriched motif [A/G]CATGCA was not mentioned in the main\nmanuscript or displayed in the main figure of the PfAP2-G5 study. Our motif enrichment\nanalysis of PfAP2-G5 ChIP-seq detected several motifs related to four of these five\nweblogo motifs (ATATA was not detected). Among these motifs that are related to the\nfour sequence logos, the most enriched motif was CATGCA (p-value = 3.5 × 10-104)\nconsistent with the analysis by X Shang et al (Table below). Next, GTTGT and GTTGC\n(Motif 1) were enriched with p-values of 6.1 × 10-85 and 1.7 × 10-70, respectively, and\nGTTCT (Motif 2) was detected with relatively moderate enrichment (p-value = 2.5 × 10-\n24) (Table below). Enrichment of these motifs in both PbAP2-TR and PfAP2-G5 ChIP-\nseq analyses is reasonable because these motifs were also detected by our DIP-seq\nanalyses, and amino acid sequences of AP2 domains are highly conserved among PbAP2-\nTR orthologs (96% and 87% for domains 1 and 2, respectively, and 100% for domain 3).\nThese results suggest that PfAP2-G5 ChIP-seq peaks partially include regions that were\nactually bound by PfAP2-G5 through its AP2 domains.\nTable. Motif analysis of PfAP2-G5 ChIP-seq\nMotif by X Shang [A/G]CATGCA GT[T/G]GTA [T/G]GT[T/G]C AA[A/C]AA\n(DREME) (Motif 1-related) (Motif 2-related)\nE-value 3.4 × 10-18 1.2 × 10-3 5.4 × 10-14 2.7 × 10-14\n23\n(DREME)\nMotif in our CATGCA GTTGT and GTTCT AACAA\nanalysis (Fisher) GTTGC (Motif 1) (Motif 2) (TTGTT)\nP-value (Fisher) 3.5 × 10-104 6.1 × 10-85 and 1.7 2.5 × 10-24 1.9 × 10-8\n× 10-70\nAnother reported logo AACAA was enriched with a p-value of 1.9 × 10-8 in our\nanalysis (Table above). However, the enrichment of AACAA (TTGTT) seemed to be\nderived from enrichment of Motifs 1 and 2 because it partially overlaps with both of these\nmotifs. Moreover, in the analysis by X Shang et al., AACAA was detected as AA[A/C]AA\nwith A being slightly larger than C in the sequence logo. Thus, although X Shang et al.\ndefined AACAA as the PfAP2-G5 binding motif and disrupted this motif upstream pfap2-\ng, it is very doubtful that AACAA actually functions as a cis-regulatory element\nrecognized by PfAP2-G5 when it is not a part of Motifs 1 or 2.\nThrough the analysis, we considered that the ChIP-seq data of PfAP2-G5 was\nnot performed with a good quality. This outcome made us hesitate to compare the ChIP-\nseq result with ours in detail and to discuss the roles of PbAP2-TR/PfAP2-G5 based on\nthis comparison because we could not be sure if the differences in the result were derived\nfrom actual differences between the roles of PbAP2-TR and PfAP2-G5 or just sequence\nbias. However, as you asked (also asked by other reviewers), many readers would be\ninterested in the comparison between the functions of PbAP2-TR and PfAP2-G5. Thus,\nwe at least compared the target genes and binding motifs of PbAP2-TR with those of\nPfAP2-G5 reported in the study by X Shang et al (for the target comparison, those with\npeaks upstream were compared). We described these as follows.\nLine 223–225: “Among these targets, only 88 genes overlapped with those of PfAP2-G5\nat the trophozoite stage (517 genes reported by Shang et al.) (Table S3).”\nLine 194–195: “Similar motifs were also enriched in the ChIP-seq analysis of PfAP2-G5\n30.”\n24\n4. There is no \"C\" in fig. 4. The \"D\" to \"G\" should be \"C\" to \"F\".\nThank you for kindly notifying the mislabel. We modified the figure caption accordingly.\n5. Some critical data should be included in the manuscript. For example, the authors\ndid not mention the number of biological replicates for RNA-seq.\nThank you for your comment. We described the number of replicates for RNA-seq\n25\nanalysis in the Materials and methods section as “Three biologically independent\nexperiments were performed”.\nMeanwhile, we realized that the section only described the differential\nexpression analysis between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ but not the\ntranscriptome analyses for ap2-g KO parasites at 4, 8, 16 hpi. Thus, we modified the\nMaterials and methods section “RNA-seq and sequence data analysis” as follows.\nLine 604–614: “For RNA-seq analysis using pbap2-g-knockout parasites, parasite cell\ncycles were synchronized as described in the parasite preparation. For RNA-seq analysis\nusing pbap2-tr-DiCre, rapamycin-dependent disruption of pbap2-tr was induced, and\nschizonts of pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ were inoculated into mice, as\ndescribed for the conditional knockout of pbap2-tr. Whole blood was harvested at 4, 8,\nand 16 hpi for pbap2-g-knockout parasites and at 12 hpi for pbap2-tr-DiCreRapa- and\npbap2-tr-DiCreRapa+ parasites. The blood was then passed through a Plasmodipur filter.\nRBCs were lysed in ice-cold 1.5 M NH Cl solution, and total RNA was extracted from\n4\nthe residual parasites using the Isogen II reagent (Nippon Gene). RNA-seq libraries were\nprepared using the KAPA mRNA HyperPrep Kit (Kapa Biosystems) and were sequenced\nusing the MGI DNBSEQ-G400. Three biologically independent experiments were\nperformed for each sample.”\nReviewer #4 (Remarks to the Author):\nThe authors clearly present an interesting and thorough study with largely compelling\nevidence that PbAP2-tr regulates asexual stage parasite genes by binding to two motifs\nat their promoters and by recruiting PbMORC to these sites where the complex acts to\nrepress expression of these genes. This is an important and interesting finding. There\nare some issues with the way the data is presented, particularly the chip data, which\nhinders critical assessment and which could be altered to facilitate assessing the\nconclusions. The differential expression data should also be shown to not be affected\nby developmental delays which might have confounded the analyses.\nThank you for your thorough review and constructive comments. Your insights on ChIP-\nseq data presentation and potential issues in differential expression analysis were\nespecially helpful for us to improve our manuscript. We performed additional experiments\nand analyses and modified statements in the manuscripts according to comments made\nby all reviewers. We hope the changes made in the revised manuscript would satisfy\nyour requirements below.\nFor clarity I will use -/- to indicate a KOd allele throughout this review although I am\naware that these parasites are haploid.\nThank you for your indication.\nPage 5 line 166 “This result suggests that in P. berghei, PbAP2-TR is essential for\nasexual blood stage development and that repression of ap2-g transcription is not a\ncommon function of PbAP2-TR orthologs .”\nThis argument doesn’t make sense to me, ap2-tr is Kod on a ap2-g -/- background and\nasexual ap2-tr -/- parasites are not recovered. This shows that AP2-tr is required for\nasexual growth as per the experiment performed on AP2-G +/+ background. How do\nthese experiments inform understanding of AP2-tr regulation of Ap2-G? gametocyte\nproduction would need to be recorded to infer that AP2-tr was not regulating AP2-G.\nAP2-G is not essential so nothing can really be inferred from AP2-tr-/- AP2-g-/-\nparasite experiment.\nThank you for your keen insight. In the PfAP2-G5 study, recovery of asexual growth rate\nin pfap2-g5 KO parasites upon additional knockout of pfap2-g was an indication that\nPfAP2-G5 has a role in pfap2-g repression. Thus, to ensure that the loss of asexual\nproliferation in pbap2-tr-DiCreRapa- was not due to such effect and that PbAP2-TR is\nindeed essential for the asexual blood stage development, we performed the conditional\nknockout of pbap2-tr on the pbap2-g KO background. Meanwhile, as you mention, it was\noverinterpreting to conclude that PbAP2-TR does not play any role in pbap2-g regulation\nfrom this result. Thank you for pointing this out clearly. Given your following comments,\nwe counted gametocytes in the pbap2-tr KO and the DMSO-control and observed no\nsignificant difference in the number of gametocytes on Day 1 (24 hpi). Considering your\ncomment and this result, we modified the Result section as follows.\nLine 157–172: “To evaluate whether PbAP2-TR plays a similar role, we assessed the\nnumber of gametocytes in pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ on day 1 (24 hpi)\nof the above in vivo growth assays (because gametocyte maturation takes approximately\n24 h in P. berghei) through Giemsa-staining. Gametocytemia (gametocyte/RBC) was\ncomparable between pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+, demonstrating that the\nrate of commitment to gametocyte fate was not significantly affected by whether pbap2-\ntr was disrupted (Fig S3B). Next, to further confirm that the loss of asexual proliferation\nin pbap2-tr-DiCreRapa+ was not due to the parasite commitment to gametocyte fate, we\n27\ndisrupted pbap2-g in pbap2-tr-DiCre using the CRISPR/Cas9 system [pbap2-tr-\nDiCrepbap2-g(-), Fig S3C]. DiCre-mediated disruption of pbap2-tr was induced in cultures\n(pbap2-tr-DiCrepbap2-g(-)_Rapa+ and pbap2-tr-DiCreap2-g(-)_Rapa-) (Genotyping 1, Fig S3D\nleft), and after inoculating pbap2-tr-DiCrepbap2-g(-)_Rapa- and pbap2-tr-DiCreap2-g(-)_Rapa+\ninto mice, parasitemia was assessed daily. The result was similar to that of the phenotype\nanalysis for pbap2-tr-DiCre; in pbap2-tr-DiCreap2-g(-)_Rapa+, parasitemia decreased from\nday 0 to day 1 and later increased (Fig S3E), but the day-3 parasites possessed the WT\npbap2-tr locus (Genotyping 2, Fig S3D right). Collectively, these results suggest that\nPbAP2-TR is indeed essential for asexual blood stage development and does not play any\nevident role in the sexual commitment unlike PfAP2-G5.”\nPage 5 line 173 “To specifically assess the role of PbAP2-TR in asexual development,\nwe disrupted pbap2-g in PbAP2-TR::GFP using the CRISPR/Cas9 system [PbAP2-\nTR::GFPpbap2-g(-), Fig S4 ].”\nAlthough it does not affect interpretation of AP2-tr chip enrichment, it is unclear here\nwhy the chipseq was performed on ap2-g-/- parasites. Later in the MS I realised that\nthe authors were likely concerned that because PfAP2-G5 is an ortholog of AP2-\ntr and regulates gametocytogenesis so if AP2-tr also regulated gametocytogenesis then the\nresulting gametocytes could confound their analyses of asexual development. I think\nthey should make this point explicitly before describing their use of AP2-G -/-\nparasites because the rationale for using the AP2-G -/- was unclear and seemed to relate\nmore to disproving a role for AP2-tr in regulating gametocytogenesis, which was not\ndone.\nThank you for your comment. In P. falciparum, PfAP2-G5 also plays a role in the early\ngametocyte development. While we could observe morphologically mature gametocytes in\nthe pbap2-tr KO parasites, we were concerned that PbAP2-TR might play a role in early\ngametocyte development like PfAP2-G5 and that it might confound our analysis. Thanks\nto your comment, we realized that this was not clear in the manuscript, and hence, we\nmodified the sentences as follows.\nLine 177–178: “In P. falciparum, PfAP2-G5 also plays a role in the early gametocyte\ndevelopment. Thus, to specifically assess the role of PbAP2-TR in asexual development,”\nIt seems to me that the logical test would have been to compare gam counts between\nap2-tr -/- ap2-g -/- and ap2-tr -/-ap2-g+/+ to determine whether ap2-tr does actually\nregulate ap2-g. Is it not possible to count gams in Pb?\ngametocytes in the pbap2-tr-DiCreRapa- and pbap2-tr-DiCreRapa+ on Day 1 (24 hpi)\n(because gametocyte maturation takes approximately 24 h in P. berghei). The result\nshowed no significant difference in gametocyte counts between pbap2-tr-DiCreRapa- and\npbap2-tr-DiCreRapa+. Consistent with this result, expression of pbap2-g was not\nupregulated in pbap2-tr-DiCreRapa+ compared to pbap2-tr-DiCreRapa-. Thus, we think that\nwe could at least state that the role of PbAP2-TR in pbap2-g repression is not as important\nas that of PfAP2-G5. Accordingly, we modified the Results section as described in the\nanswer to your above comment.\nFigure 2A\nChipseq traces should include relevant input traces as well with ll traces normalised\nfro library size. Alternatively chip/input could be shown and the raw traces for both\nreps chip and input could be provided as suppl figs.\nThank you for your suggestion. We consider that showing raw coverage of ChIP data is\nuseful to visualize the signal-to-noise ratio, which is important to evaluate the qualities\nof ChIP experiment and library preparation. This information would be lost when\nshowing ChIP/input ratio although ChIP/input is useful to visualize the enrichment of\nChIP signals from input data and to compare two different ChIP-seq experiments. In Fig\n2A, we intend to show the ChIP quality of PbAP2-TR ChIP-seq data and reproducibility\nin duplicate. Thus, we would like to show ChIP data alone instead of ChIP/input in the\nmain figure. Meanwhile, as you suggest, it is important to normalize the data by their\nlibrary size and to present the coverage for the input data. Accordingly, we normalized\nthe raw read coverage of ChIP and input data using bamCoverage (deepTools) and added\nfour aligned traces of ChIP and input coverage data for duplicate as a supplementary\nfigure Fig S4B. In addition, we modified the figure caption and Materials and methods as\nfollows.\nLine 876–877: “Histograms show the raw read coverage of ChIP data normalized by\nlibrary size (bin size = 10 bp)”\nLine 566–567: “The ChIP-seq enrichment on the genome was visualized as raw read\ncoverage normalized by library size using bamCoverage (-bs 10, --normalizeUsing\nRPKM)”\nPage 5 line 186\n29\n“Among the peaks containing both Motifs 1 and 2, the distance between these two\nmotifs was not constant, suggesting that Motifs 1 and 2 function independently, rather\nthan cooperatively, as a cis-regulatory element for PbAP2-TR (Fig 2F ).”\nA more cautious interpretation would be appropriate at this stage as it is not proven\nthat ap2-tr binds either or both of the motifs, it is probable that other TFs bind these\npromoters, potentially within the same complex.\nThank you for your suggestion. Given your comment, we realize that this statement\noverestimates the relationship of Motif 1 and 2 in the context of PbAP2-TR functions at\nthis stage. Hence, we modified the sentence as follows.\nLine 199–200: “i.e. these motifs are not arranged in a specific positional relationship (Fig\n2F).”\nPage 6 lines 229-241 “PbAP2-TR functions as a transcriptional repressor”\nA common confounder of inducible KO studies in plasmodium is developmental delay\nin the KO affecting rnaseq diff gene expression comparisons with the non-induced\ncontrol. Have the matched ko and control rnaseq been assessed for developmental stage,\ne.g. using the mixture model of tonkin-hill et al 2018 plos biol.\nThank you for your kind caution. We were also afraid to detect differential gene\nexpressions that occurred due to developmental delay or arrest caused by the conditional\npbap2-tr-disruption. To minimize such confounding effects, we performed the differential\nexpression analysis at 12 hpi, a time point well before any apparent developmental delay\nwas observed in pbap2-tr KO parasites. (As described in the manuscript, ring-to-\ntrophozoite ratio in the KO was comparable to that in the DMSO-control until 18 hpi (Fig\n1E). Furthermore, the average size of trophozoites was also comparable between the KO\nand DMSO-control at 18 hpi (Fig 1F)). Therefore, we consider that differential gene\nexpression detected in pbap2-tr KO at 12 hpi largely reflect the effect of pbap2-tr-\ndisruption but not the effect of developmental delay.\nAlso, thank you for suggesting the use of the mixture model for estimating the\npopulation property in the RNA-seq samples. However, this statistic analysis performed\nby tonkin-hill et al requires template transcriptome data for each stage (e.g., ring,\ntrophozoite, schizont) to profile the parasite cell stage in the samples. In the public data,\nthere are time-course transcriptome data during the asexual blood stage in P. berghei, but\npbap2-tr KO trophozoite would not properly fit to the template trophozoite data because\nPbAP2-TR is a transcription factor, and disruption of its gene causes differential\n30\nexpression of hundreds of genes, especially upregulation of its target genes. Thus, we\nthink that use of the mixture model for our differential expression analysis would not be\nappropriate.\nPage 8 line 309 should this read fig 5b?\nThank you for kindly notifying the mistake. Yes, it should be Fig 5b, and we modified it\naccordingly.\nFig 6C\nPbmorc and pbap2-tr chip traces should be shown as log2chip/input with both chip and\ninput somehow normlaised for library ize eg rpkm by a fixed bin size across the genome.\nThank you for your suggestion. We replaced the ChIP-seq coverage to the log -\n2\ntransformed ChIP/input ratio and modified the figure caption and Materials and methods\nsection as follows.\nLine 948: “Histograms show the log -transformed ChIP/input ratio (bin size = 10 bp).\ncoverage normalized by library size using bamCoverage (-bs 10, --normalizeUsing\nRPKM) or log -transformed ChIP/input ratio using bamCompare (-bs 10).”\nDetails should be provided of what is being shown, coverage is a generic term, it should\nbe pbmorc log2chip/input for rpkm by bin size or similar measure that accounts for\nlibrary size and non specific enrichment ie input or non-specific precipitated material.\nThank you for your comment. We are sorry for the ambiguity we made in the figure.\nFollowing your suggestion, we provided log (ChIP/input) for PbMORC ChIP-seq in the\n2\nheatmap. In addition, we modified the figure caption as follows.\nLine 951–952: “Heatmap showing log (ChIP/input) of PbMORC at the PbAP2-TR peaks.”\nPb MORC and ap2-tr enrichment differ between heterochromatin and euchromatin\nand between coding sequence vs intergenic sequence using published datasets of\nheterochromatin marks eg H3K9me3 and input normalised data.\nPbHP1 (a marker for heterochromatin regions in Plasmodium) reported by K Witmer et\nal. (2020) and defined heterochromatin regions as 500-bp regions with RPMChIP/RPMinput\n> 2, obtaining 1294 regions. Within these regions, only 5 PbAP2-TR ChIP-seq peaks were\ndetected. This number is too small, and thus, comparison of ChIP-seq enrichment within\nthese regions did not seem to be very informative. For coding region vs intergenic region\ncomparison, no significant difference was observed in the ChIP-seq enrichment plot of\nPbAP2-TR vs PbMORC (Figure below). This result was resonable because PbAP2-TR\nand PbMORC genome-widely show similar peak patterns as depicted in the Fig 6E\nheatmap. For regions other than PbAP2-TR peaks, we think that the comparison of\nenrichment of these two factors would not be appropriate because while PbMORC also\ninteracts with other transcription factors on the genome, PbAP2-TR is a sequence-specific\ntranscription factor that directly binds to the genomic DNA.\nORF Intergenic\nR R\nT T\n2- 2-\nP P\nA A\nb b\nP P\nPbMORC PbMORC\n32\n16/12/2025\nResponses to Reviewers:\nWe sincerely thank the reviewers for their careful evaluation of our revised manuscript,\n“Precise gene regulation through transcriptional repression is essential for Plasmodium\nasexual blood stage development” (NCOMMS-25-48898A). We are happy that most of\nthe revisions satisfactorily addressed your previous concerns.\nReviewer #1 (Remarks to the Author):\nThe authors have satisfactorily answered my queries.\nThank you for your evaluation of our revised manuscript. We sincerely appreciate you\ntaking your valuable time for the review process.\nReviewer #2 (Remarks to the Author):\nThe authors have done fine and thorough work in revising their manuscript in response\nto the reviewers’ comments. The study is clearly strengthened by the addition of new\nexperimental data and by the substantial improvements in the analyses, particularly in\nthe transcriptomics and ChIP-seq components. The textual revisions are appropriate\nand the authors have generally clarified their interpretations where needed.\nImportantly, the new figures, controls, and re-analyses (including MA plots, QC metrics,\nreciprocal RIME, and improved visualization of AP2-TR/MORC occupancy) directly\naddress the concerns raised during the first round of review. The expanded discussion\nand comparative analyses also improve the contextualization of the work within the\nbroader ApiAP2/MORC literature.\nOverall, I feel that the authors have adequately addressed all major and minor concerns.\nThis is an interesting and well-executed study that provides the community with a solid\nmechanistic dissection of a trophozoite-stage transcriptional repressor and its\ncooperation with PbMORC during asexual blood-stage development. The manuscript\nnow reaches a standard suitable for publication in its current form.\nThank you for your evaluation of our previous revision. We sincerely appreciate you\ntaking your valuable time to review our manuscript and to provide these comments. Your\ngenerous comments really encouraged us to further pursue our study.\nThe authors addressed all my concerns and comments. However, some responses were\nnot satisfied and raised more questions.\nThank you for your evaluation of our revised manuscript. We sincerely answered your\nfollowing comments and modified the Discussion section.\nIn response to my #1 comment, authors confirmed that the expression of pbap2-G2 was\nincreased and further indicated that PbAP2-TR ChIP-seq peaks were detected in the\nupstream region (at approximately 1.3 kb from the start codon) of pbap2-g2 with\nPbAP2-TR binding motifs around the summit. These data indicate that pbAP2-TR\nrepress pbAP2-G2. Since pbAP2-G2 represses asexual proliferation and enhances\ngametocyte commitment and development, elevation of pbAP2-G2 expression after\ndisrupt apAP2-TR could lead to downregulation of its target genes including many\nasexual genes (?)\nThank you for your comment. The primary role of PbAP2-G2 is to support sexual\ndevelopment after commitment to sexual fate (Yuda M, et al., 2015). Accordingly,\nPbAP2-G2 targets encompass a wide variety of genes, including mosquito- and liver-\nstage–specific genes, not limited to genes promoting asexual replication in the blood.\nGiven this broad spectrum of targets, it is reasonable to assume that the expression of\nPbAP2-G2 has a negative impact on development of the trophozoite, although it remains\nunclear to what extent PbAP2-G2 can function effectively during the trophozoite stage.\nTherefore, repression of pbap2-g2 could be important for asexual development but would\nnot account for the overall functions of PbAP2-TR. We consider that pbap2-g2 as just\none of the PbAP2-TR targets, rather than a dominant factor of the observed phenotypes.\nIn response to my #2 comment, authors indeed identified a pbAP2-TR ChIP-seq peak\nat about 2.5 upstream of pbap2-G . This location is similar to the locations of PfAP-G\nand PfAP2-G5 ChIP-seq peaks at the upstream of PfAP2-G (Josling GA, Russell TJ,\nVenezia J, Orchard L, van Biljon R, Painter HJ, Llinás M. 2020. Dissecting the role of\nPfAP2-G in malaria gametocytogenesis. Nat Commun 11:1503; Shang X, Shen S, Tang\nJ, He X, Zhao Y, Wang C, He X, Guo G, Liu M, Wang L, Zhu Q, Yang G, Jiang C,\nZhang M, Yu X, Han J, Culleton R, Jiang L, Cao J, Gu L, Zhang Q. 2021. A cascade\n2\nof transcriptional repression determines sexual commitment and development in\nPlasmodium falciparum. Nucleic Acids Res 49:9264–9279). More detailed analysis is\nrequired to check the peaks (such as motifs) between pb and pf. I still believe that\nconduction of the ChIP-seq and RNA-seq analysis after PbAP2-TR KO in the wildtype\nparasite but not in AP2-G KO parasites will provide more straightforward results.\nThank you for your comment. As clarified in the previous revision, we performed the\ndifferential expression analysis between pbap2-tr-knockout parasites and DMSO-control\non the WT background (not on the pbap2-tr-knockout background). In addition, we had\nprovided rationale for why the pbap2-g-disruption would not affect the ChIP-seq results\nfor evaluating the role of PbAP2-TR in regulation of pbap2-g, if any.\nIn general, ChIP-seq can detect non-specific signals in regions marked by\nconstitutive heterochromatin. DNA fragments from these regions are poorly sheared by\nsonication and can become insoluble, making them prone to non-specific interaction with\nantibodies or beads. In ENCODE Blacklist for ChIP-seq in human and mouse, such\nregions are defined as regions that are recommended to be excluded from the analysis\n(Amemiya HM, Kundaje A, Boyle AP. The ENCODE Blacklist: Identification of\nProblematic Regions of the Genome. Sci Rep. 2019). Therefore, ChIP-seq peaks detected\nin these regions should be interpretated with caution, particularly when the peaks lack\nbinding motifs. The upstream region of pbap2-g is marked with H3K9 trimethylation in\nasexual stage parasites. In addition, the PbAP2-TR ChIP-seq peaks upstream of pbap2-g\ndid not contain PbAP2-TR binding motifs. Given these, we suspect that the PbAP2-TR\nChIP peak in the upstream region of pbap2-g may be non-specific, and that PbAP2-TR\ndoes not play any role in gametocyte development. In fact, our differential expression\nanalysis between pbap2-tr-knockout parasites and DMSO-control (on the WT\nbackground) showed that pbap2-g expression does not increase in pbap2-tr-knockout\nparasites. Furthermore, we did not detect any increase of gametocyte number in pbap2-\ntr-knockout parasites compared with the DMSO-control.\nReviewer #4 (Remarks to the Author):\nAll of my comments have been addressed satisfactorily.\nThank you for your evaluation of our revised manuscript. We sincerely appreciate you\ntaking your valuable time for the review process.\nReviewer #3 (Remarks to the Author):\n[Editorial Note: See attachment]"}]

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