Mapping cis- and trans-regulatory target genes of human-specific deletions

Domain: biology
Published: 2025-12-20
Editorial outcome: major_revision

Abstract
Deletion of functional sequence is predicted to represent a fundamental mechanism of molecular evolution. Comparative genetic studies of primates have identified thousands of human-specific deletions (hDels), and the cis-regulatory potential of short (≤31 base pairs) hDels has been assessed using reporter assays. However, how structural variant-sized (≥50 base pairs) hDels influence molecular and cellular processes in their native genomic contexts remains unexplored. Here, we design genome-scale libraries of single-guide RNAs targeting 7.2 megabases of sequence in 6358 hDels and present a systematic CRISPR interference (CRISPRi) screening approach to identify hDels that modify cellular proliferation in chimpanzee pluripotent stem cells. By intersecting hDels with chromatin state features and performing single-cell CRISPRi (Perturb-seq) to identify their cis- and trans-regulatory target genes, we discovered 20 hDels controlling gene expression. We highlight two hDels, hDel_2247 and hDel_585, with tissue-specific activity in the brain. Our findings reveal a molecular and cellular role for sequences lost in the human lineage and establish a framework for functionally interrogating human-specific genetic variants.

Introduction
Millions of single-nucleotide and structural variants (SVs)—deletions, duplications, insertions, and inversions ≥50 base pairs (bp) in length—have accumulated in the human lineage since divergence from non-human primates1–4. Contained within this genetic variation are alterations to functional sequences that distinguish humans from nonhuman primates5,6. However, the overwhelming majority of variants are predicted to be selectively neutral7. Among polymorphic variants, deletions are enriched for driving splicing and expression quantitative trait loci8 and noncoding deletions predicted to be deleterious exhibit levels of purifying selection comparable to loss-of-function coding alleles9. Noncoding deletions removing cis-regulatory elements may also underlie instances of adaptive evolution10,11. Recent studies have identified noncoding deletions in the human genome and assessed their capacity for driving reporter gene expression1,6,12. We reasoned that inactivating human-specific deletions (hDels) using tiling CRISPRi-based genetic screens in chimpanzee cells would enable systematic genome-scale interrogation of the effect of this class of genomic alterations on cellular proliferation and gene expression.

Results
We focused on 7278 SV-sized (≥50bp) hDels previously identified through comparison of long-read great ape genomes1 (“Methods”). hDels span 12.7 megabases (Mb) of the chimpanzee reference genome (panTro6), are a median of 626bp (range 50–262,923bp), and primarily intersect noncoding regions (52.4% of hDel base pairs are intronic, 47.4% are intergenic, and 0.2% are exonic). Compared with matched genomic sequences13, hDels are enriched for repeat elements (p<10−3, 63.2% of hDel base pairs are repetitive) and intergenic regions (p<10−3) and depleted from introns (p=7×10−3) and exons (p<10−3). While hDels are depleted for overlap with conserved sequences, 2177 hDels remove sequences under purifying selection at levels comparable to exonic sequence (116,828bp, depletion p<10−3). To characterize the epigenetic state of chromatin at hDels present in the chimpanzee reference genome, we performed Omni ATAC-seq14 (Supplementary Fig. 1) in chimpanzee induced pluripotent stem (iPS) cells from four individuals (C3624K, C3651, C8861, Pt5-C) and profiled H3K4me1, H3K4me3, H3K27ac, and H3K27me3 histone modifications using CUT&Tag15 (Supplementary Fig. 2). Although hDels are depleted from Tn5-accessible and H3K4me1-, H3K4me3-, H3K27ac-, and H3K27me3-modified chromatin (p<10−3), we identified 290 hDels intersecting at least one of these epigenetic features, revealing sequences lost in the human lineage harboring candidate cis-regulatory elements.

To evaluate the functions of hDels in their native genomic contexts using a CRISPRi-based genetic screening approach, we first introduced dCas9-KRAB into the CLYBL safe harbor locus16 in iPS cells from two male chimpanzees (Supplementary Fig. 3a, C3624K, Pt5-C). We then designed a library of sgRNAs tiling across all hDels (hDel-v1) and separately, a library targeting hDels intersecting epigenetic features associated with cis-regulatory elements (hDel-v4).

To probe the effect of hDels as a class of human-specific SVs on a quantitative cellular phenotype, we designed a library of 170,904 sgRNAs tiling across 7.2 Mb of sequence within 6358 hDels (Supplementary Fig. 3b, hDel-v1). We considered hDels independent of evolutionary conservation or epigenetic state, as these features may not be predictive of all classes of cis-regulatory elements17. To tile across all uniquely targetable hDels, sgRNAs were assigned to 50-bp genomic windows and the sgRNA with the highest predicted activity18 per window was selected for inclusion in hDel-v1 (Fig. 1a, median 52bp between sgRNAs, median 14 sgRNAs per hDel). We reasoned that iPS cells would be a useful model for studying hDels because of their transcriptionally permissive chromatin structure19 and sensitivity to proliferation-modifying perturbations. We transduced chimpanzee CRISPRi iPS cells (C3624K, Pt5-C) with the lentiviral hDel-v1 sgRNA library, selected for sgRNA-expressing cells with puromycin, cultured cells for 10 days, and quantified sgRNA enrichment and depletion by high-throughput sequencing (Fig. 1a–c).

Analysis of technical and biological replicates revealed that sgRNAs were highly correlated between replicates of the same cell line (Fig. 1d and Supplementary Fig. 3, Pearson’s r=0.78 to 0.88) and between cell lines (r=0.69). As expected, sgRNAs targeting the promoters of essential or proliferation-suppressor genes were depleted or enriched, respectively (Fig. 1d). Using DESeq220 to model sgRNA counts from hDel-v1 and compute sgRNA false discovery rates (FDRs), we identified 1851 hDel-targeting sgRNAs modifying cellular proliferation (FDR<0.01, Fig. 1e). Because sgRNAs exhibit variable CRISPRi activity depending on their genomic position, we assigned hDel-targeting sgRNAs to overlapping 500-bp genomic windows (250-bp step size) and computed hDel FDRs using alpha-robust rank aggregation (α-RRA). Genome-wide, we identified 16 hDels modifying cellular proliferation (FDR<0.1, Fig. 1f), including hDel_6304, a 382 bp deletion located within the first intron of the nucleosome remodeling and deacetylase (NuRD) complex subunit MBD3, which increases cellular proliferation upon CRISPRi (Fig. 1g).

To fine-map functional sequence within proliferation-modifying hDels identified using hDel-v1, we designed a second tiling library (hDel-v2) with reduced spacing between proximal sgRNAs. Because reduced spacing supports the discovery of hDels that may not have been detected using hDel-v1, we included hundreds of hDels with a single proliferation-modifying sgRNA. We omitted a genomic window strategy for sgRNA selection to maximize tiling density, resulting in a library of 78,270 sgRNAs targeting 558 hDels (Fig. 2a, b, median 7bp between sgRNAs, median 119 sgRNAs per hDel). As with hDel-v1, we transduced chimpanzee CRISPRi iPS cells (C3624K) with the lentiviral hDel-v2 sgRNA library, selected and cultured sgRNA-expressing cells, and quantified sgRNA enrichment and depletion by high-throughput sequencing.

hDel-targeting sgRNAs screened in both hDel-v1 and hDel-v2 were highly correlated (r=0.73, Fig. 2c), as were technical replicates (Supplementary Fig. 4, r=0.82). We discovered 38 hDels modifying cellular proliferation (FDR<0.1, Fig. 2d), including 14 hDels intersecting Omni ATAC-seq, H3K4me1, H3K4me3, H3K27ac, or H3K27me3, epigenetic features associated with cis-regulatory elements (Fig. 2e). For example, hDel_7051, a 2,602 bp deletion of a long interspersed nuclear element element within an intronic region of the SWI/SNF family chromatin remodeler ATRX, intersects Omni ATAC-seq, H3K4me1, and H3K27ac, and reduces cellular proliferation upon CRISPRi (Fig. 2f). Together, hDel-v1 and hDel-v2 identify cellular phenotypes for select hDels and indicate that despite the predicted phenotypic importance of SV-sized noncoding deletions9, hDels as a class of human-specific SVs are largely dispensable for iPS cell proliferation.

We next sought to map the cis- and trans-regulatory targets of proliferation-modifying hDels using single-cell CRISPRi. To facilitate hDel-gene mapping, we designed a compact library of sgRNAs (hDel-v3) targeting hDels identified using hDel-v2 (122 sgRNAs targeting 19 hDels, FDR<0.05). As positive and negative controls, we included transcription start site (TSS)-targeting sgRNAs, putative cis-regulatory element-targeting sgRNAs21, and non-targeting sgRNAs (Supplementary Fig. 5a). We transduced chimpanzee CRISPRi iPS cells (C3624K) with the lentiviral hDel-v3 sgRNA library, selected and cultured sgRNA-expressing cells for 7 days, and performed single-cell RNA sequencing (Fig. 3a, Direct-capture Perturb-seq). After filtering, we recovered 16,810 sgRNA-expressing cells (Supplementary Fig. 5b–d, median 15,366 UMIs per cell, median 151 cells per sgRNA).

To identify the transcriptional consequences of hDel-v3 sgRNAs, we summed gene expression counts across cells containing each sgRNA and negative-control sgRNAs and performed a likelihood-ratio test using DESeq2. TSS-targeting sgRNAs mediated efficient target gene repression (Fig. 3b, 52.9 to 93.4%, median 85.0%, FDR<0.1), demonstrating the performance of CRISPRi and the accuracy of sgRNA-cell assignments. As expected, we observed an enrichment of significant sgRNA-gene pairs for hDel-targeting, but not non-targeting, sgRNAs (Fig. 3c). We identified 4 hDel-gene pairs within 100kb (FDR<0.1), including hDel_6012-RPL26, hDel_349-MRPS14, and hDel_6304-MBD3.

Targeting of hDel_6012 (Fig. 3d) reduced the expression of the 60S ribosomal protein L26 RPL26 (Fig. 3e, 33.0 to 49.8%, median 41.3%, FDR<0.1), and we observed a highly correlated relationship between the effect of hDel_6012-targeting sgRNAs on cellular proliferation and RPL26 expression (Fig. 3f, r=0.97). hDel_6012 does not intersect epigenetic features associated with cis-regulatory elements (Fig. 3d), highlighting the value of evaluating hDels independent of chromatin profiling. Genome-wide, we identified 636 differentially expressed genes upon hDel_6012 CRISPRi, including 35 genes encoding S and L ribosomal proteins, 32 of which (91.4%) were up-regulated (Fig. 3g, FDR<0.1). As expected, sgRNAs targeting hDel_6012 elicited correlated genome-wide transcriptional responses (Supplementary Fig. 6a, r=0.57 to 0.68, FDR<0.1).

sgRNAs targeting hDel_349 (Supplementary Fig. 6b) reduced the expression of the mitochondrial ribosomal 28S subunit MRPS14 (Supplementary Fig. 6c, 60.3 to 88.3%, median 74.7%, FDR<0.1), and we observed a highly correlated relationship between the effect of hDel_349-targeting sgRNAs on cellular proliferation and MRPS14 expression (Supplementary Fig. 6d, r=0.73). Genome-wide, we identified 11 differentially expressed genes upon hDel_349 CRISPRi, all of which correspond to mitochondrial or nuclear-mitochondrial transcripts (Supplementary Fig. 6e, FDR<0.1), indicating that mitochondrial dysfunction underlies reduced proliferation. While we cannot exclude the possibility that hDel_349-targeting sgRNAs interfere with transcription at the MRPS14 promoter, the sgRNAs reducing MRPS14 expression are located −302 to −658 bp relative to the TSS, outside of the optimal range of CRISPRi22, and sgRNAs targeting MRPS14 in human K562 cells22 do not exhibit proliferation-modifying effects at similar distances (Supplementary Fig. 6f), suggesting that the observed effects are specific to hDel_349. MRPS14 variants in humans are associated with muscle hypotonia, cognitive delay, and midface retrusion23, providing evidence that loss of a MRPS14 cis-regulatory element may alter the development of multiple tissues.

Targeting of hDel_6304 (Fig. 3h) reduced the expression of the NuRD complex subunit MBD3 (Fig. 3i, 35.5 to 51.7%, median 47.2%, FDR<0.1). We observed an inverse relationship between the effect of hDel_6304-targeting sgRNAs on cellular proliferation and MBD3 expression (Fig. 3j, r=−0.94), consistent with depletion of MBD3–NuRD inhibiting the differentiation of highly proliferative pluripotent cells24. Genome-wide, we identified 83 differentially expressed genes upon hDel_6304 CRISPRi, including transcription factors controlling meso-endoderm differentiation (EOMES, GATA6, LHX1, MIXL1), all of which were down-regulated (Fig. 3k, FDR<0.1). hDel_6304 is also accessible in chimpanzee neural progenitor cells25, suggesting that loss of hDel_6304 in the human lineage may contribute to increased neural stem and progenitor cell proliferation26 by delaying terminal differentiation.

We next examined RPL26, MRPS14, and MBD3 expression in human and chimpanzee cells. To quantify cis-regulatory divergence, we compared the expression of human and chimpanzee alleles in an identical trans environment. As expected, human alleles drove reduced MRPS14 expression compared to chimpanzee alleles in human-chimpanzee allotetraploid iPS cells (cis contribution 13.1%, FDR<0.05), explaining cross-species differences in gene expression (Supplementary Fig. 6h, 14.3%, FDR<0.005)27. Similarly, MBD3 expression is reduced in human, compared to chimpanzee, iPS cells (31.7%, FDR<0.001)28, and human alleles drove reduced MBD3 expression (Supplementary Fig. 6i, cis contribution 34.7%, FDR<0.15)27. Surprisingly, RPL26 expression from human alleles is increased compared to chimpanzee alleles (Supplementary Fig. 6j, cis contribution 21.6%, FDR<0.05)27, indicating that additional RPL26 cis-regulatory alterations occurred in the human and chimpanzee lineages. Together, these findings suggest that hDel_349 and hDel_6304 remove cis-regulatory elements contributing to reduced MRPS14 and MBD3 expression in human cells, with trans-regulatory target genes controlling mitochondrial function and differentiation, respectively.

We also investigated potential sources of sgRNA off-target activity for proliferation-modifying hDels lacking cis-regulatory target genes. Because hDels are enriched for repeat elements, we focused on nucleotide homopolymers in hDel-targeting sgRNAs. Grouping hDel-v2 sgRNAs by the presence and position of N4 homopolymers (AAAA, GGGG, CCCC) revealed that sgRNAs containing guanine (G4) and cytosine (C4) homopolymers exhibited pervasive off-target activity (Supplementary Fig. 7a, b). Off-target activity was dependent on the position of the homopolymer within the sgRNA, with the greatest toxicity observed for sgRNAs containing G4 or C4 near the center of the spacer sequence: sgRNAs containing G4 at spacer position 9 were 5.0-fold more likely to have significant effects on cellular proliferation compared to all hDel-v2 sgRNAs (Supplementary Fig. 7c, d, 28.6%, FDR<0.05), while sgRNAs containing C4 at spacer position 11 were 2.4-fold more likely to have proliferation-modifying effects (Supplementary Fig. 7e, f, 13.7%, FDR<0.05). Consequently, we excluded G4/C4 containing sgRNAs from hDel-v2 and hDel-v3 analysis. In hDel-v3, we did not observe correlated genome-wide transcriptional responses for homopolymer-containing sgRNAs, revealing no single transcriptional basis for proliferation-modifying effects. We also identified G4-associated toxicity for sgRNAs tiling across GATA1 and MYC in human K562 cells29 (Supplementary Fig. 7g, h), providing evidence that sgRNA nucleotide homopolymers are an unappreciated source of off-target activity in CRISPRi-based genetic screens.

As hDels may control gene expression without directly modifying cellular proliferation, we focused on nonessential hDels intersecting epigenetic features associated with cis-regulatory elements. We designed a library of sgRNAs (hDel-v4) targeting hDels intersecting Omni ATAC-seq, H3K4me1, or H3K27ac (Fig. 4a, 888 sgRNAs targeting 163 hDels), including putative cis-regulatory element-targeting sgRNAs21 and non-targeting sgRNAs as positive and negative controls, respectively (Supplementary Fig. 8a). To facilitate hDel-gene mapping using a larger library of sgRNAs, we transduced chimpanzee CRISPRi iPS cells (C3624K) with the lentiviral hDel-v4 sgRNA library at a high multiplicity of infection, selected and cultured sgRNA-expressing cells for 7 days, and performed single-cell RNA sequencing (Fig. 4a, Direct-capture Perturb-seq). After filtering, we recovered 18,571 sgRNA-expressing cells, detecting multiple sgRNAs per cell (Fig. 4b, Supplementary Fig. 8, median 7 sgRNAs per cell, median 495 UMIs per sgRNA per cell, median 26,989 UMIs per cell, median 195 cells per sgRNA).

To identify the transcriptional consequences of hDel-v4 sgRNAs, we summed gene expression counts across cells containing each sgRNA and all other cells and performed a likelihood-ratio test using DESeq2. As expected, sgRNAs targeting a putative inhibitor of DNA binding ID1 cis-regulatory element21 reduced the expression of ID1 (Supplementary Fig. 8d, 23.6 to 37.2%, FDR<0.1). As with hDel-v3, we observed an enrichment of significant sgRNA-gene pairs for hDel-targeting, but not non-targeting, sgRNAs (Fig. 4c). We identified 16 hDel-gene pairs within 100kb (Fig. 4d and Supplementary Fig. 8e, FDR<0.1), including hDel_585-HADHA, hDel_1608-C4orf48, and hDel_2247-PLPP1.

hDel_585, a 207bp intronic deletion located within the alpha subunit of the mitochondrial trifunctional protein HADHA, intersects Omni ATAC-seq (Fig. 4e). Although hDel_585 did not modify cellular proliferation (Fig. 4e), sgRNAs targeting hDel_585 reduced the expression of HADHA (Fig. 4f, 20.7 to 24.8%, FDR<0.1). Because sequences within hDel_585 are not conserved to mice, we examined chromatin accessibility in additional nonhuman primates as a measure of cis-regulatory activity during development. Analysis of single-nucleus ATAC sequencing (snATAC-seq) of post-conception day 80 (PCD80) rhesus macaque prefrontal cortex (Supplementary Fig. 9, PFC) revealed that hDel_585 was accessible in radial glia, intermediate progenitor cells, and excitatory and inhibitory neurons (Fig. 4g). As deletions can increase cis-regulatory activity by removing transcriptional repressors or creating transcription factor binding sites12, we performed Omni ATAC-seq of human, chimpanzee, and orangutan neuroepithelial cells to examine evolutionary differences in chromatin accessibility at the HADHA gene body. While hDel_585 was accessible in chimpanzee and orangutan neuroepithelial cells, we did not observe accessibility at the boundaries of hDel_585 in human neuroepithelial cells (Fig. 4h), consistent with the loss of cis-regulatory sequence. These results provide evidence that the loss of hDel_585 in the human lineage removed a cis-regulatory element active in the forebrain regulating HADHA.

hDel_1608, a 3.2 kb deletion located within the predicted lncRNA LOC104005955, intersects Omni ATAC-seq, H3K4me1, H3K4me3, and H3K27me3 (Fig. 4i). Targeting of hDel_1608 increased the expression of the Wolf-Hirschhorn Syndrome-associated30 lumicrine factor31 C4orf48 (Fig. 4j, 16.2 to 19.8%, FDR<0.1), which shares a bidirectional promoter with LOC104005955. This finding is consistent with the negative regulation of mRNA by a divergently transcribed lncRNA32, although other mechanisms, including interference with repressive transcription factors could underlie increased expression following CRISPRi.

Several hDels linked to cis-regulatory target genes removed evolutionarily conserved sequences6. hDel_1273, linked to the GTP-specific beta subunit of succinyl-CoA synthetase SUCLG2 (Supplementary Fig. 8g, 30.1%, FDR<0.1), is partially conserved to platypus, and is predicted to be active in the developing mouse heart, limb, midbrain33. Additionally, sgRNAs targeting hDel_3779, as well as complete genomic deletion of hDel_3779 using a pair of Cas9 ribonucleoproteins (RNPs), reduced the expression of the RAC1 effector FAM49B (Supplementary Fig. 8h and j, 14.2 to 23.6%, FDR<0.1), a regulator of mitochondrial fission and cytoskeletal remodeling34,35. Finally, hDel_6842 intersects a mouse ENCODE proximal enhancer-like signature and is linked to the ceramide kinase CERK (Fig. 4k, 23.7 to 27.7%, median 26.2%, FDR<0.1). CERK converts ceramide to ceramide 1-phosphate (C1P), a sphingolipid metabolite hydrolyzed by PLPP136, the cis-regulatory target of hDel_2247 (Fig. 4d), raising the possibility of epistasis between hDel_2247 and hDel_6842.

We also examined the relationship between hDels and human-chimpanzee cis-regulatory divergence. For CERK, FAM49B, GRTP1, and SUCLG2, human alleles drove reduced expression compared to chimpanzee alleles in allotetraploid iPS cells27 (Fig. 4l, FDR<0.1), consistent with the human-specific loss of cis-regulatory sequence. However, in certain cases, hDels removing cis-regulatory elements did not account for cross-species cis-regulatory divergence. For example, ATRX was expressed at similar levels from human and chimpanzee alleles, and HADHA was expressed at higher levels from human alleles, suggesting that additional cis-regulatory alterations in the human and chimpanzee lineages attenuate or even reverse the cis-regulatory effects of select hDels, consistent with compensatory evolution within human-accelerated regions37.

To further explore the functions of hDels with cis-regulatory activities, we focused on hDel_2247, a 6.8 kb intergenic deletion linked to the phospholipid phosphatase PLPP1. hDel_2247 is located between PLPP1 (71kb to TSS) and the lysosomal amino acid transporter38 SLC38A9 (107kb to TSS) and intersects Omni ATAC-seq, H3K4me1, H3K27ac (Fig. 5a). Although hDel_2247 did not modify cellular proliferation (Fig. 5a), 8 sgRNAs targeting hDel_2247 reduced the expression of PLPP1 (Fig. 5b, 17.9 to 28.8%, median 23.2%, FDR<0.1). Moreover, complete genomic deletion of hDel_2247 using a pair of Cas9 RNPs resulted in a more pronounced reduction in PLPP1 expression (65.0% to 75.9%; Fig. 5c and Supplementary Fig. 8j). To more closely examine the ancestral function of hDel_2247 in the human-chimpanzee last common ancestor, we synthesized a 1557 bp chimpanzee sequence intersecting Omni ATAC-seq, H3K4me1, and H3K27ac, and assessed its capacity to drive expression of a lacZ reporter gene in vivo. We found that the chimpanzee sequence drove consistent lacZ expression in the olfactory bulb and anterior neocortex (n=4/5 embryos, Fig. 5d, e and Supplementary Fig. 10b, c), two structures that have undergone morphological alterations in the human lineage. Reduced expression of PLPP1 increases extracellular LPA in vivo39, which may have cell-extrinsic effects, including on olfactory ensheathing cell migration40 and neural stem and progenitor cell differentiation41. Together, these findings indicate that the loss of hDel_2247 in the human lineage removed a conserved cis-regulatory element regulating PLPP1 with tissue-specific activity in the brain.

Methods
Imaging
All imaging was performed at the UCSF Weill Imaging Core using a Leica THUNDER Imager.

Cell lines and cell culture
Chimpanzee iPS cells from two healthy male donors (C3624K and Pt5-C) were cultured in v3.1 medium (65 ng/ml FGF2-G3, 2 ng/ml TGFβ1, 0.5 ng/ml NRG1, 20 μg/ml insulin, 20 μg/ml transferrin, 20 ng/ml sodium selenite, 200 μg/ml ascorbic acid 2-phosphate, 2.5 mg/ml bovine serum albumin (BSA), 30 ng/ml heparin, 15 μM adenosine, guanosine, cytidine, uridine nucleosides, 6 μM thymidine nucleosides in Dulbecco’s Modified Eagle’s Medium (DMEM)/Ham’s F-12 (Corning, 10-092-CM)) supplemented with 100 IU/ml penicillin, and 100 μg/ml streptomycin at 37 °C and 5% CO2. At ≥80% confluency, cultures were dissociated with phosphate-buffered saline (PBS) supplemented with 0.5 mM ethylenediaminetetraacetic acid (EDTA), resuspended in v3.1 medium supplemented with 2 μM thiazovivin (MedChemExpress, HY-13257), and seeded on Matrigel-coated cell culture plates (Corning, 354230). Protocols were approved by the Human Gamete, Embryo, and Stem Cell Research Committee at UCSF.

CRISPRi iPS cell line generation
To establish chimpanzee iPS cell lines expressing dCas9-KRAB (ZNF10/KOX1), 1×106 iPS cells were seeded at a density of 100,000 cells/cm2 and transfected with 3 μg pC13N-dCas9-BFP-KRAB (Addgene, 127968), 0.375 μg pZT-C13-L1 (Addgene, 62196), and 0.375 μg pZT-C13-R1 (Addgene, 62197) using 10 μl Lipofectamine Stem (Invitrogen, STEM00001)53. After 7 days, BFP-positive iPS cells were isolated by single-cell fluorescence-activated cell sorting. Transgene integration at the CLYBL locus was verified by PCR. To assess CRISPRi-mediated transcriptional repression, iPS cells were transduced with non-targeting or SEL1L-targeting sgRNAs54, selected with 1.5 μg/ml puromycin (Gibco, A1113803), and processed for quantitative reverse transcription PCR.

Lentivirus production and titration
Lenti-X HEK293T cells (Takara Bio, 632180) were maintained in DMEM/Ham’s F-12 supplemented with 10% fetal bovine serum, 100 IU/ml penicillin, and 100 μg/ml streptomycin at 37 °C and 5% CO2. To generate lentivirus, 150 mm cell culture dishes were coated with 10 μg/ml poly-D-lysine (Sigma-Aldrich, P7405) and Lenti-X HEK293T cells were seeded at a density of 85,000 cells/cm2. The following day, medium was replaced, and Lenti-X HEK293T cells were transfected with 23.1 μg hDel sgRNA library transfer plasmid, 7.6 μg pMD2.G (Addgene, 12259), and 13.9 μg psPAX2 (Addgene, 12260) using 125 μl Mirus TransIT-293 (Mirus, MIR 2700) in Opti-MEM (Gibco, 31985062). Lentivirus-containing supernatant was harvested two days post-transfection, filtered through a 0.45 μm PVDF membrane (Millipore, SLHV033RS), and concentrated using precipitation solution (Alstem, VC100). To determine functional lentiviral titer, iPS cells were transduced in a dilution series and fluorophore-positive populations were quantified using a flow cytometer three days post transduction.

Human-specific deletions
hDel sequences (Supplementary Data 1–131) were extracted from panTro6 contigs and aligned to the assembled panTro6 reference genome. hDel coordinates were compared to the UCSC hg38-panTro6 net alignment using BEDTools (v. 2.27.1) and discrepancies between hDels, hCONDELs6, and the UCSC hg38-panTro6 net alignment were resolved by reciprocal BLAST-like alignment tool.

hDel enrichment analysis
Intersections between hDels and genomic features were tested for significance using a resampling approach. After discarding all hDel sequences mapped to unplaced contigs and alternate haplotypes, 1000 matched null sets of genomic features were sampled from panTro6 (excluding unplaced contigs and alternate haplotypes) using bootRanges55. Regions were sampled using a block length of 500 kb, excluding approximately 51 Mb of blacklisted sequence (excludeOption=“drop”, withinChrom=FALSE). This blacklist was generated by combining runs of at least 1 kb with less than 100% 50-mer mappability identified using GenMap56 and nuclear mitochondrial insertions (NUMTs) inferred as described previously57.

After sampling matched null features, intersection between each sampled set of features and the featureset of interest (introns, exons, repeat elements, Tn-5 accessible regions, and pA-Tn5-accessible regions) was assessed using BEDTools58. After counting the number of base pairs in each intersection, p-values for enrichment or depletion of intersection were computed as the number of null feature sets for which intersection with the feature set of interest was greater (for enrichment testing) or lower (for depletion testing) than the observed intersection between hDels and features of interest.

Introns, exons, and intergenic regions were extracted from the chimpanzee reference genome (panTro6), annotated with the Comparative Annotation Toolkit59,60. Repeat regions were identified using the UCSC panTro6 RepeatMasker annotations. All features were merged using BEDTools before performing intersections.

Bases under selective constraint were computed using PhyloP61 on an alignment of 241 mammal genomes62, with panTro6 as the reference sequence. Bases with at least 95% probability of purifying selection were taken to be under selective constraint; this corresponded to 25.6% of all exonic bases and resulted in enrichment of constrained bases in exons (p<10−3, using the same resampling approach described above).

hDel sgRNA library design
For all hDel sgRNA libraries (hDel-v1, hDel-v2, hDel-v3, and hDel-v4), candidate hDel-targeting sgRNAs were identified and scored for predicted off-target activity against mismatched target sites in the chimpanzee reference genome (panTro6) using FlashFry63 (v. 1.15; –maxMismatch=3; –scoringMetrics JostandSantos, dangerous, minot). Candidate sgRNAs (GN19) with >1 perfect-match target site, CRISPRi specificity score <0.2, maximal predicted CRISPRi activity at any off-target site >0.8, or TTTT sequences were excluded from all libraries.

To maximize coverage of hDel sequences in the hDel-v1 library, sgRNAs were grouped into non-overlapping 50-bp bins corresponding to the genomic location of their target sequence. Candidate sgRNAs were then scored for predicted on-target activity using DeepHF18, and the sgRNA with the highest DeepHF score in each 50-bp bin was selected for inclusion in the library (n=3121 hDels). For hDels targeted by fewer than 10 sgRNAs after filtering and binning, sgRNAs were ranked by their DeepHF scores and a sequentially increasing number of sgRNAs were selected per 50-bp bin until all hDels were targeted by at least 10 sgRNAs (n=1531 hDels). For the remaining hDels targeted by fewer than 10 sgRNAs, sgRNAs targeting human-conserved sequence flanking either side of each hDel were filtered, binned, and ranked as described above until each hDel ±250bp was targeted by at least 5 sgRNAs (n=1706 hDels). In total, 170,904 sgRNAs tiling 6358 hDels were included in hDel-v1 (median distance between sgRNAs: 52bp; median number of sgRNAs per hDel: 14). Non-targeting sgRNAs (n=3000 sgRNAs) were generated by scoring random GN19NGG sequences against panTro6 and filtering for 0 perfect-match target sites. As protein-coding controls, sgRNAs targeting the promoters of essential genes (n=8068 sgRNAs targeting 2017 genes), proliferation-suppressor genes (n=1692 sgRNAs targeting 423 genes), and chimpanzee organoid-expressed genes (n=15,189 sgRNAs targeting 5063 genes) were selected from hCRISPRi-v2 after off-target scoring against panTro6. The complete hDel-v1 sgRNA library contains 198,718 sgRNAs. All hDel-v1 sgRNAs were screened in a single pool.

Candidate hDel cis-regulatory elements were screened at higher tiling density in the hDel-v2 sgRNA library (n=558 hDels, see hDel CRISPRi screening analysis). For the 50 hDels with the greatest number of sgRNAs passing off-target filters described above, all sgRNAs within ±500bp of MAGeCK- and iAnalyzer-identified hDel genomic windows and DESeq2-identified singleton sgRNAs were selected for inclusion in the library. For all other hDels, all hDel-targeting sgRNAs, as well as sgRNAs targeting human-conserved sequence flanking either side of each hDel (±500bp), were included. In total, 78,270 sgRNAs tiling 558 hDels were included in hDel-v2 (median distance between sgRNAs: 7bp; median number of sgRNAs per hDel: 119). Non-targeting sgRNAs (n=2000 sgRNAs) and sgRNAs targeting the promoters of essential genes (n=600 sgRNAs targeting 98 genes) and proliferation-suppressor genes (n=394 sgRNAs targeting 60 genes) were selected from hDel-v1 and CEV-v1, respectively. The complete hDel-v2 sgRNA library contains 81,264 sgRNAs. All hDel-v2 sgRNAs were screened in a single pool.

Two additional sgRNA libraries were designed for single-cell CRISPRi screening to facilitate mapping hDel cis-regulatory element-gene pairs. For hDel-v3, all essential sgRNAs targeting α-RRA-identifed 250-bp hDel genomic windows (n=122 sgRNAs targeting 19 hDels, see hDel CRISPRi screening analysis) were selected for inclusion in the library. sgRNAs targeting the promoters hDel-proximal genes (n=18 sgRNAs targeting 12 genes), core-control non-targeting sgRNAs (Replogle Cell 2022) (n=10 sgRNAs), and sgRNAs targeting putative cis-regulatory elements (Gasperini Cell 2019) (n=10 sgRNAs targeting 5 cis-regulatory elements) were also included. The complete hDel-v3 sgRNA library contains 160 sgRNAs.

For hDel-v4, nonessential sgRNAs targeting hDels marked by chromatin state features associated with cis-regulatory elements, including Omni ATAC-seq, H3K4me1, and H3K27ac (see Omni ATAC-seq and CUT&Tag), were selected for inclusion in the library. sgRNAs passing off-target filters described above and lacking AAAA, TTTT, GGGG, or CCCC sequences were scored for predicted on-target activity using DeepHF, and the 5 sgRNAs with the highest DeepHF scores targeting each hDel Tn5- or pA-Tn5-accessible region were included (n=888 sgRNAs targeting 163 hDels). Core-control non-targeting sgRNAs (n=25 sgRNAs), and sgRNAs targeting putative cis-regulatory elements (n=10 sgRNAs targeting 5 cis-regulatory elements) were also included. The complete hDel-v4 sgRNA library contains 923 sgRNAs.

hDel sgRNA library cloning
Oligonucleotide pools were designed with flanking PCR adapter sequences and restriction sites (BstXI, BlpI), synthesized by Agilent Technologies, and cloned into the sgRNA expression vector pCRISPRia-v2 (Addgene, 84832; hDel-v1, hDel-v2) or pJR101 (Addgene, 187241; hDel-v3, hDel-v4) as described previously54. Briefly, oligonucleotide pools were amplified by 8 to 10 cycles of PCR using NEBNext Ultra II Q5 Master Mix (New England Biolabs, M0544X), digested with BstXI and BlpI, size-selected by polyacrylamide gel electrophoresis, ligated into BstXI- and BlpI-digested pCRISPRia-v2 or pJR101, and introduced into MegaX DH10B T1R cells by electroporation (Invitrogen, C640003; Bio-Rad, 1652660).

hDel CRISPRi screening
Chimpanzee CRISPRi iPS cells (C3624K or Pt5-C, hDel-v1; C3624K, hDel-v2) were dissociated with Accutase (Innovative Cell Technologies, AT104-500), resuspended in v3.1 medium supplemented with 2 μM thiazovivin and 5 μg/ml polybrene (Mirus, MIR 6620), transduced with the hDel-v1 or hDel-v2 lentiviral sgRNA library at a target infection rate of 25%, and plated at a density of 85,000 cells/cm2 in Matrigel-coated 5-layer cell culture flasks (Corning, 353144). Two days post-transduction, cells were dissociated with Accutase, resuspended in v3.1 medium supplemented with 2 μM thiazovivin and 1.5 μg/ml puromycin, and plated at a density of 100,000 cells/cm2. Four days post-transduction, 200M cells were harvested (t0) and 300M cells were resuspended in v3.1 medium supplemented with 1.5 μg/ml puromycin and plated (≥1000× sgRNA library representation). Selection efficiency was assessed using a flow cytometer (≥70% BFP+). Every two days, cells were dissociated with Accutase, resuspended in v3.1 medium supplemented with 2 μM thiazovivin, and plated. Technical replicates were maintained separately for the duration of the screen. After 10 days of growth, 200M cells from each technical replicate were harvested (tfinal). Genomic DNA was isolated from pelleted cells by column purification (Macherey-Nagel, 740950.50), and the sgRNA expression cassette was amplified by 22 cycles of PCR using NEBNext Ultra II Q5 Master Mix and primers containing Illumina P5/P7 termini and sample-specific TruSeq indices. Each sample was distributed into individual 100 μl reactions in 96-well plates, each containing 10 μg genomic DNA. Following amplification, reactions from each sample were pooled and a 100 μl aliquot was purified by double-sided SPRI selection (0.65×, 1×). Purified libraries were quantified using Agilent Bioanalyzer, pooled at equimolar concentrations, and sequenced on Illumina HiSeq 4000 using a custom sequencing primer (SE50; AoCRISPRi_seqV5).

hDel CRISPRi screening analysis
Single-end sequencing reads were aligned to hDel-v1 or hDel-v2 and counted using MAGeCK64 (v. 0.5.9.4; count). For hDel-v1 (C3624K, Pt5-C), sgRNAs were assigned to overlapping 500-bp hDel genomic windows (250-bp step size) depending on the genomic location of their target sequence. hDel genomic windows targeted by fewer than 5 sgRNAs were excluded from analysis. hDel genomic windows and sgRNA counts were then used as input for analysis by MAGeCK alpha-robust rank aggregation (α-RRA) (test –paired –gene-test-fdr-threshold 0.05 –norm-method control –gene-lfc-method alphamean), iAnalyzeR (combining sgRNA Z-scores for each genomic window using Stouffer’s method followed by the Benjamini–Hochberg procedure), or DESeq2 (design=~individual+time). The union of the hDel 500-bp genomic windows and hDel-targeting sgRNAs identified using these approaches (n=313 genomic windows MAGeCK α-RRA 10% FDR, n=147 genomic windows iAnalyzeR 5% FDR, n=87 genomic windows MAGeCK α-RRA 10% FDR and iAnalyzeR 5% FDR, n=202 sgRNAs DESeq2 1% FDR) were included in the hDel-v2 sgRNA library (n=558 hDels). For the hDel-v1 Manhattan plot in Fig. 1, sgRNA adjusted p-values from DESeq2 were combined into FDRs corresponding to each 500-bp hDel genomic window using α-RRA (v. 0.5.9; –control).

For hDel-v2 (C3624K), sgRNA counts were used as input for differential analysis by DESeq2 (design=~time). sgRNAs containing GGGG sequences following spacer position 5 or CCCC sequences between spacer positions 10 and 12 were excluded from analysis due to pervasive off-target effects (Supplementary Fig. 7; fraction of significantly enriched or depleted sgRNAs at least two fold greater than all hDel-v2 sgRNAs). Enriched sgRNAs (log2 fold-change ≥1) initially present at low abundance (≤5th percentile) were also excluded from analysis (n=159 sgRNAs). hDel-targeting sgRNAs were assigned to nonoverlapping 250-bp hDel genomic windows, and sgRNA adjusted p-values from DESeq2 were combined into FDRs corresponding to each hDel genomic window using α-RRA (–control).

Single-cell hDel CRISPRi screening
For hDel-v3, chimpanzee CRISPRi C3624K iPS cells were dissociated with Accutase (Innovative Cell Technologies, AT104-500), resuspended in v3.1 medium supplemented with 2 μM thiazovivin and 5 μg/ml polybrene (Mirus, MIR 6620), transduced with the hDel-v3 lentiviral sgRNA library at a target infection rate of 10%, and plated at a density of 100,000 cells/cm2. The following day, v3.1 medium was replaced. Two days post transduction, v3.1 medium was replaced and supplemented with 1.5 μg/ml puromycin. Selection continued until six days post transduction. Seven days post transduction, iPS cells were dissociated with Accutase and resuspended in 1× PBS supplemented with 0.04% BSA for single-cell RNA sequencing (Direct-capture Perturb-seq). iPS cells were partitioned into Gel Beads-in-emulsion (GEMs) across five wells using the 10× Genomics Chromium Controller and cDNA libraries from polyadenylated mRNAs and Feature Barcode-compatible sgRNAs were generated by following the 10× Genomics Chromium Next GEM Single Cell 3′ Reagent Kits v3.1 (Dual Index) User Guide (CG000316 Rev D). cDNA libraries from mRNAs and sgRNAs were quantified using Agilent Bioanalyzer, pooled at a 4:1 molar ratio, and sequenced on Illumina NovaSeq 6000 (28×10×10×90).

For hDel-v4, chimpanzee CRISPRi C3624K iPS cells were transduced with the hDel-v4 lentiviral sgRNA library at a target infection rate of >95% and Direct-capture Perturb-seq was performed as described above.

Single-cell CRISPRi screening analysis
A mismatch map for hDel-v3 and hDel-v4 was generated using kITE65 and indexed using kallisto66 (v. 0.48.0; kb ref –workflow kite). Paired-end sequencing reads from the gene expression and CRISPR screening libraries were then pseudoaligned and error-collapsed using kallisto|bustools (v. 0.42.0; kb count –workflow kite: 10× FB –filter bustools). The chimpanzee reference genome (panTro6), annotated with the Comparative Annotation Toolkit59,60 was used as the reference transcriptome.

To assign sgRNAs to cells, a two-component Poisson-Gaussian mixture model67 was fit for each sgRNA using the log2-transformed UMIs in the bustools-filtered cell by sgRNA matrix. Assignments were made when the posterior probability of a cell belonging to the second component of the mixture model was >0.5.

For hDel-v3, cells with fewer than 2049 genes detected (10th percentile), 5105 UMIs (10th percentile), and greater than 15% mitochondrial UMIs were filtered from the dataset using Scanpy (v. 1.9.1). After intersecting Cell Barcodes in the gene expression and CRISPR screening UMI matrices, 16,810 cells were retained for analysis (median 4564 genes detected per cell; median 15,366 gene UMIs per cell; median 151 cells per sgRNA; median 1597 UMIs per sgRNA per cell).

For hDel-v4, cells with fewer than 1106 genes detected (10th percentile), 2744 UMIs (10th percentile), and less than 1% or greater than 15% mitochondrial UMIs were filtered from the dataset. After intersecting Cell Barcodes in the gene expression and CRISPR screening UMI matrices, 18,571 cells were retained for analysis (median 6143 genes detected per cell; median 26,989 gene UMIs per cell; median 7 sgRNAs per cell; median 195 cells per sgRNA; median 495 UMIs per sgRNA per cell).

To perform differential gene expression testing for hDel-v3, the unnormalized gene expression UMIs were summed across cells containing each sgRNA (+sgRNA “pseudobulk”) and cells containing non-targeting sgRNAs (+non-targeting sgRNA “pseudobulk”) using ADPBulk (https://github.com/noamteyssier/adpbulk) and a likelihood-ratio test was performed individually for each sgRNA using DESeq2 controlling for GEM well (design=~GEM+sgRNA; test=“LRT”, reduced=~GEM).

To perform differential gene expression testing for hDel-v4, the unnormalized gene expression UMIs were summed across cells containing each sgRNA (+sgRNA “pseudobulk”) and all other cells (-sgRNA “pseudobulk”) using ADPBulk and a likelihood-ratio test was performed individually for each sgRNA using DESeq2 controlling for GEM well (design=~GEM+sgRNA; test=“LRT”, reduced=~GEM). Cells containing any sgRNA targeting the same hDel were excluded from the -sgRNA “pseudobulk”.

For hDel-v3 and hDel-v4, genes detected in fewer than 2000 cells (~10% of all cells) were filtered from the dataset prior to differential gene expression testing. To identify differentially expressed genes for hDel-targeting sgRNAs, log2 fold-change was divided by its standard error for each sgRNA-gene pair and then Z-score normalized. Gene-specific null distributions were generated from all sgRNA-gene pairs located ≥100kb from a hDel. For genes within ≤100kb of a hDel, p-values were computed from the survival function of a normal distribution, concatenated across genes, and adjusted for multiple comparisons using the Benjamini–Hochberg procedure applied to sgRNA-gene pairs within ≤100kb.

hDel Cas9 RNP nucleofection
Chimpanzee iPS cells from a male donor (C8861) were cultured in v3.1 iPSC medium supplemented with 5 mg/ml BSA at 37 °C and 5% CO2, as described above. Cells were dissociated with Accutase (Sigma-Aldrich, A6964-500ML), resuspended in P3 solution (Lonza, V4XP-3024), and nucleofected using an Amaxa 4D Nucleofector (CA-137). For each hDel, pairs of RNPs were prepared by complexing sgRNAs (Synthego) with Alt-R S.p. Cas9 Nuclease V3 (IDT, 1081058) and incubating for 15′ at room temperature. Per cuvette, 1×106 cells were electroporated with Cas9 RNPs and pmaxGFP (Lonza). For hDel_2247, crRNA sequences ATGGAGATGTTGTCGGGCA and GGAACTCTGGGTTTGCCAG were used. For hDel_3779, cRNA sequences TGCCTCCAGTGGTAGAGTAG and TCCCCACTAAGACAGAGAAA were used. Matched no-sgRNA controls were nucleofected in parallel with sgRNAs omitted. Nucleofected cells were plated at ~104,000 cells/cm2 on Matrigel-coated 6-well plates. At ~90% confluency, cells were dissociated with PBS containing 0.5 mM EDTA and harvested for analysis. For each hDel, three independent nucleofections and two independent no-sgRNA control nucleofections were performed.

hDel genotyping
Genomic DNA was extracted using the Monarch Genomic DNA Purification Kit (NEB, T3010). Wild-type chimpanzee (C4933) and human (H20961) genomic DNA were included as controls. Reactions contained 0.4 µM forward and reverse primers (hDel_2247 forward: GGTTTAGTATCCAAGACTCCTAT; hDel_2247 reverse: GGAAGGGTAAACAGACTATAGTC; hDel_3779 forward: TTCCTATTTCGAGGTGGGTCAGC; hDel_3779 reverse: CTGAAACAGTTGTTGTGGAGGCC), 1× LongAmp Taq 2× Master Mix (New England Biolabs, M0287S), and genomic DNA in nuclease-free water. For hDel_2247, 50 ng DNA was used with the following cycling conditions: 94 °C for 30s; 30 cycles of 94 °C for 20s, 52 °C for 30s, 65 °C for 9 min 20s; final extension at 65 °C for 10 min. Products were resolved by agarose gel electrophoresis. For hDel_3779, 25 ng DNA was used with the following cycling conditions: 94 °C for 30s; 30 cycles of 94 °C for 15s, 61 °C for 20s, 65 °C for 1 min 40s; final extension at 65 °C for 10 min. Products were resolved by agarose gel electrophoresis.

Reverse transcription quantitative PCR
Total RNA was extracted using the Monarch Total RNA Miniprep Kit (New England Biolabs, T2010). For each sample, 1 µg RNA was used as input for cDNA synthesis (Thermo Fisher, K1671) using the following conditions: 25 °C for 10 min, 50 °C for 60 min, 85 °C for 5 min. RT-qPCR included 1× PowerUp SYBR Green Master Mix (Applied Biosystems, A25742), 0.25 µM forward and reverse primers, cDNA diluted 1:80, and nuclease-free water. For each hDel, three primer pairs were used: GAPDH and POLR2C (reference genes), and PLPP1 or FAM49B (target genes). Reactions were run in quadruplicate in 10 µl volumes on 384-well plates. RT-qPCR was performed on QuantStudio 6 Real-Time PCR System (Applied Biosystems) using the Relative Quantification module in Fast mode with a heated cover at 105 °C. Cycling included a hold stage (50 °C for 2 min, 95 °C for 2 min), followed by 40 cycles (95 °C for 15s, 55 °C for 20s, 60 °C for 30s) with fluorescence collected at each step. Melt curve analysis (95 °C for 15s, 55 °C for 20s, 95 °C for 15s) was performed with continuous acquisition. Cq values were calculated using the ΔΔCT method with GAPDH and POLR2C as reference genes. Technical replicates were averaged, and relative expression (RQ) was calculated per sample and group. Pairwise comparisons were tested using two-sided and one-sided Student’s t-tests to assess both general and directional effects. One-way ANOVA with Tukey’s HSD post-hoc test was used to detect group-wide differences while correcting for multiple comparisons.

Omni ATAC-seq
Chimpanzee iPS cells from four healthy donors (C3624K dCas9-KRAB, Pt5-C dCas9-KRAB, C8861, and C3651) were rinsed with DMEM/Ham’s F-12 and dissociated with PBS supplemented with 0.5 mM EDTA. Cells were washed and resuspended in cold PBS supplemented with 0.04% BSA. Following counting, 100,000 cells were resuspended in 100 μl cold lysis buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.01% digitonin, 0.1% Tween-20, 0.1% NP40, and 1% BSA) by pipetting three times and incubated on ice for 3 min. Following lysis, 1 ml cold wash buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.1% Tween-20, and 1% BSA) was added and nuclei were centrifuged at 500×g for 5 min at 4 °C. Supernatant was removed using P1000, P200, and P20 pipettes, and nuclei were resuspended in 50 μl transposition mix (25 μl 2× transposition buffer (Active Motif), 10 μl transposase (Active Motif), 2 μl 10× PBS, 0.5 μl 0.5% digitonin, 0.5 μl 10% Tween-20, and 12 μl dH2O) by pipetting three times. Transposition reactions were incubated for 30 min at 37 °C while shaking at 1000 rpm and cleaned using DNA Clean & Concentrator-5 (Zymo Research, D4003). Transposed libraries were amplified in 50 μl PCRs (0.5 μl Q5 DNA polymerase, 10 μl 5× Q5 reaction buffer, 1 μl 10 mM dNTP mix, 2.5 μl 25 μM i7 index primer and 2.5 μl 25 μM i5 index primer68) using the following cycling parameters: 72 °C for 5 min; 98 °C for 30s; 10 cycles of 98 °C for 10s, 63 °C for 30s, and 72 °C for 1 min. Amplified transposed libraries were purified by SPRI selection (1.2×), quantified using Agilent Bioanalyzer, and pooled at equimolar concentrations. Purified libraries were sequenced on Illumina HiSeq 4000 (PE100).

Neuroepithelial cell differentiation and Omni ATAC-seq
Chimpanzee (C3624K dCas9-KRAB, C8861), human (H20961), and orangutan (Jos-3C1) iPS cells were seeded at a density of 100,000 cells/cm2 in v4 medium (v3.1 medium with 5 mg/ml BSA) containing CEPT69. The following day (Day 1), medium was replaced with DMEM/Ham’s F-12 differentiation medium (DMEM/Ham’s F-12 containing 1% polyvinyl alcohol, 100 μg/ml 2-Phospho-L-ascorbic acid trisodium salt, 20 ng/ml sodium selenite, 20 μg/ml holo-transferrin, 20 μg/ml insulin, and 0.1 mg/ml Primocin) supplemented with 0.5 μM LDN193189, 10 μM SB431542, and 0.1 μM Wnt-C59. Medium was replaced on Day 3. On Day 5, medium was replaced with DMEM/Ham’s F-12 differentiation medium supplemented with 0.5 μM LDN193189, 10 μM SB431542, and CEPT. On Day 7, cells were dissociated with Accutase and seeded at a density of 800,000 cells/cm2 onto polyethylenimine (0.1%) and Matrigel-coated plates in DMEM/Ham’s F-12 differentiation medium supplemented with a modified 6F70 formulation (1 μM SB431542, 0.1 μM K02288, 0.1 μM AKTi VIII, 0.075 μM MK2006, 0.1 μM LDN193189, 0.5 μM CHIR99021, 0.2 μM NVP-TNKS656, 25 ng/ml SHH), and CEPT. On Day 10, medium was replaced with DMEM/Ham’s F-12 differentiation medium supplemented with 25 ng/ml SHH, 50 ng/ml FGF8, and CEPT. On Day 12, medium was replaced with DMEM/Ham’s F-12 differentiation medium supplemented with 25 ng/ml SHH, and 50 ng/ml FGF8. On Day 15, medium was replaced and cells were rinsed with DMEM/Ham’s F-12 and dissociated with Accutase. Omni ATAC-seq was performed as described above. Purified libraries were sequenced on Illumina NovaSeq X (PE150).

Omni ATAC-seq analysis
Paired-end sequencing reads were trimmed using Cutadapt71 (v. 3.4; -q 20 –minimum-length 20) and aligned to panTro6 using Bowtie 272 (v. 2.2.5; –very-sensitive -X 2000 -k 10). SAM files were converted to BAM format while discarding alignments with MAPQ<15, sorted by position or read name, and indexed using SAMtools73 (v. 1.10, -q 15). Tn5-accessible regions were called following PCR duplicate removal using Genrich (https://github.com/jsh58/Genrich) (v. 0.6.1; -j -r -e chrM -q 0.05). Tn5-accessible regions were intersected using BEDTools multiinter (v. 2.27.1) and only regions common to all four iPS cell lines were retained for analysis (n=94,003). BAM files were converted to bedGraph format using deepTools74 (v. 3.5.1; –binSize 1 –ignoreDuplicates) and visualized using SparK (https://github.com/harbourlab/SparK) (v. 2.6.2). To identify intersections between Omni ATAC-seq and hDels, at least half of a Tn5-accessible region was required to intersect a hDel.

CUT&Tag
Concanavalin A-coated beads (Epicypher, 21-1401) were washed twice and resuspended in binding buffer (20 mM HEPES pH 7.5, 10 mM KCl, 1 mM CaCl2, and 1 mM MnCl2). Chimpanzee iPS cells from two healthy donors (C3624K dCas9-KRAB and C8861) were rinsed with DMEM/Ham’s F-12 and dissociated with PBS supplemented with 0.5 mM EDTA. Following counting, 175,000 cells were washed twice in 1 ml wash buffer (20 mM HEPES pH 7.5, 150 mM NaCl, 0.5 mM spermidine, and 1 tablet cOmplete EDTA-free protease inhibitor cocktail) and incubated with 11 μl concanavalin A-coated beads on an end-over-end rotator for 10 min. The cell and bead mixture was placed on a magnetic stand and unbound supernatant was discarded. Bead-bound cells were resuspended in 50 μl primary antibody buffer (20 mM HEPES pH 7.5, 150 mM NaCl, 0.5 mM spermidine, 1 tablet cOmplete EDTA-free protease inhibitor cocktail, 0.05% digitonin, 2 mM EDTA, and 0.1% BSA) and 0.5 μl primary antibody (1:100 dilution; H3K4me1 (Abcam, ab8895, lot GR3426435-2), H3K4me3 (Abcam, ab8580, lot GR3425199-1), H3K27ac (Abcam, ab4729, lot GR3442878-1), or H3K27me3 (Cell Signaling Technology, 9733S, lot 19)) was added. Bead-bound cells and primary antibody were mixed by pipetting and placed on a nutator overnight at 4 °C. The following day, the primary antibody solution was placed on a magnetic stand and supernatant was discarded. Bead-bound cells were resuspended in 50 μl secondary antibody buffer (goat anti-rabbit IgG (Epicypher, 13-0047) diluted 1:100 in 20 mM HEPES pH 7.5, 150 mM NaCl, 0.5 mM spermidine, 1 tablet cOmplete EDTA-free protease inhibitor cocktail, and 0.05% digitonin) and placed on a nutator at room temperature for 60 min. Bead-bound cells were washed three times in 1 ml digitonin-wash buffer (20 mM HEPES pH 7.5, 150 mM NaCl, 0.5 mM spermidine, 1 tablet cOmplete EDTA-free protease inhibitor cocktail, and 0.05% digitonin), resuspended in 50 μl digitonin-300 buffer (20 mM HEPES pH 7.5, 300 mM NaCl, 0.5 mM spermidine, 1 tablet cOmplete EDTA-free protease inhibitor cocktail, and 0.05% digitonin) containing pAG-Tn5 (Epicypher, 15-1017), and placed on a nutator at room temperature for 60 min. Following pA-Tn5 binding, bead-bound cells were washed three times in 1 ml digitonin-300 buffer, resuspended in 125 μl transposition buffer (10 mM MgCl2 in digitonin-300 buffer), and incubated at 37 °C for 60 min. Following transposition, 4.2 μl 0.5 M EDTA, 1.25 μl 10% SDS, and 1.1 μl 20 mg/ml proteinase K (Invitrogen, AM2546) were added and bead-bound cells were incubated at 55 °C for 60 min. Bead-bound cells were placed on a magnetic stand and DNA-containing supernatant was cleaned using ChIP DNA Clean & Concentrator (Zymo Research, D5201). Transposed libraries were amplified in 50 μl PCRs (25 µl NEBNext HiFi 2× PCR master mix, 2 μl 10 μM i7 index primer and 2 μl 10 μM i5 index primer68) using the following cycling parameters: 58 °C for 5 min; 72 °C for 5 min; 98 °C for 45s; 13 cycles of 98 °C for 15s, 60 °C for 10s; and 72 °C for 1 min. Amplified transposed libraries were purified by SPRI selection (1.3×), quantified using Agilent Bioanalyzer, and pooled at equimolar concentrations. Purified libraries were sequenced on Illumina NovaSeq 6000 (PE150).

CUT&Tag analysis
Paired-end sequencing reads were trimmed using Cutadapt (-q 20 –minimum-length 20) and aligned to panTro6 using Bowtie 2 (–very-sensitive -X 700 -k 10). SAM files were converted to BAM format while discarding alignments with MAPQ<15, sorted by position or read name, and indexed using SAMtools (-q 15). pA-Tn5-accessible regions were called following PCR duplicate removal using Genrich (-j -r -e chrM -q 0.05). For each primary antibody, pA-Tn5-accessible regions were intersected using BEDTools intersect and only regions common to both iPS cell lines were retained for analysis. BAM files were converted to bedGraph format using deepTools (–binSize 1 –ignoreDuplicates) and visualized using SparK. To identify intersections between CUT&Tag and hDels, at least half of a pA-Tn5-accessible region was required to intersect a hDel.

Mouse ENCODE analysis
Mouse ENCODE ATAC-seq and H3K27ac and p300 ChIP-seq datasets from E14.5 forebrain, limb, heart, lung, and liver tissues were downloaded from (https://www.encodeproject.org/). For all datasets, the bigWig file “fold-change over control, isogenic replicates 1, 2” was used. bigWig files were converted to bedGraph format using UCSC bigWigToBedGraph and visualized using SparK.

snATAC-seq of PCD80 rhesus macaque prefrontal cortex
Prefrontal cortex (PFC) was microdissected from post-conception day 80 (PCD80) rhesus macaque cortex75. Tissue was enzymatically dissociated in papain (Worthington, LK003176) containing DNase I for 30 min at 37 °C and gently triturated to form a single-cell suspension. Cells were washed and resuspended in cold PBS supplemented with 0.04% BSA. Following counting, 100,000 cells were resuspended in 100 μl cold lysis buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.01% digitonin, 0.1% Tween-20, 0.1% NP40, and 1% BSA) by pipetting three times and incubated on ice for 3 min. Following lysis, 1 ml cold wash buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2, 0.1% Tween-20, and 1% BSA) was added and nuclei were centrifuged at 500×g for 5 min at 4 °C. Nuclei were partitioned into GEMs using the 10× Genomics Chromium Controller and transposed libraries were generated by following the 10× Genomics Chromium Chromium Next GEM Single Cell ATAC Reagent Kits v1.1 User Guide (CG000209 Rev G). Amplified transposed libraries were quantified using Agilent Bioanalyzer and sequenced on Illumina NovaSeq 6000 (51×12×24×51).

snATAC-seq analysis
Paired-end sequencing reads were aligned to rheMac10 (BSgenome.Mmulatta.UCSC.rheMac10, TxDb.Mmulatta.UCSC.rheMac10.refGene) using Cell Ranger ATAC (v. 2.1.0) and processed with ArchR76 (v. 1.0.2). Cells with fewer than 3000 fragments or a TSS enrichment score less than 20 were filtered from the dataset (n=5166 cells retained, median 9142 fragments per cell, median 31.8 TSS enrichment score). Cellular subsets were identified by iterative latent semantic indexing dimensionality reduction followed by graph-based clustering using ArchR. Fragments were then summed across cells within each cluster using pycisTopic77 (v. 1.0.3) and visualized using SparK.

Transgenic lacZ reporter assay
The chimpanzee sequence contained within hDel_2247 intersecting Omni ATAC-seq, H3K4me1, and H3K27ac (1557 bp; chr5:45194159-45195715, panTro6) was synthesized and cloned into the lacZ reporter vector Hsp68_mini-LacZ-SV40 (VectorBuilder). Transient transgenic mice were produced by pronuclear injections and analyzed for lacZ activity at embryonic day 13 (E13.5) (Cyagen Biosciences).

Data availability
Paired-end sequencing reads (FASTQ) generated in this study have been deposited on SRA under BioProject PRJNA1002791. Source data for all figures is supplied as a source data file. Source data are provided with this paper.

Code availability
Notebooks implementing analyses are available at https://github.com/tdfair.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript by Fair et al describes their systematic functional tests of human-specific deletions (hDels) on cellular phenotypes using chimpanzee induced pluripotent stem cells (iPSCs). To my knowledge, this represents the first such study focusing on hDels and includes an impressive array of functional genomic experiments. Positing that they may contribute to human-specific traits, they compile a list of hDels via comparisons of human (GRCh38) and chimpanzee (panTro6) reference genomes, building from work by Kronenberg et al that used data from multiple apes to narrow in on these regions. Authors do not find overwhelming evidence that hDels play a major role in iPSC proliferation, using CRISPRi to silence hDel regions, but they are able to describe a handful of interesting examples. In some cases, they also identify target genes using Perturb-seq and connect with species’ differentially-expressed (DE) genes from RNA-seq of chimpanzee-human hybrid cells. Though additional follow-up work is ultimately necessary to verify functional findings, we are left with preliminary evidence that hDels represent an understudied source of species’ divergence. The manuscript is straightforward, well-written, and easy to follow. The experiments are comprehensive, well-designed/controlled, and additionally provide a useful genomic resource of chimpanzee iPSCs (e.g., ATAC-seq, RNA-seq, CUT&TAG).\nBelow are general comments aimed at improving the generalizability of findings and understanding if hDels might contribute to global human-specific traits:\n1. Human-accelerated regions (HARs) and human-specific duplications (HSDs) are enriched for genes important in neural development. Alternatively, in this study, functional hDels seem to disproportionately impact ubiquitously expressed genes with innate cellular functions. Can authors comment on whether this is a product of the assay or a feature of hDels? One idea might be to take nearby associated genes of hDels and test for functional enrichment across all vs. hDels with identified functional impacts.\n2. Further, since we have a set of functional hDels, are there any general rules that can be extracted from their sequence/genomic features? E.g., hConDels vs. non-conserved. Or proximity to genes. Currently, the study narrows in on a few interesting examples, but ideally, generalizable rules of hDels would be useful to the community.\n3. Do authors have details on the population prevalence of identified hDels, particularly the ones they suggest are functional? In Kronenberg, et al they narrow in on ~5000 “fixed” fhDels, but here the study focuses on >7000. It’s not clear where the additional 2000 comes from (polymorphic?). Are fixed hDels more likely to show a function or have defining genomic features?\n4. In the hDel-v3 Perturb-seq, how do authors account for the possible biases introduced by pseudo-bulking across cells when testing functional impacts of hDels impacting proliferation? Might technical artefacts arise from genes with fewer cells (reduced proliferation) vs. more cells (increased proliferation), resulting in systematically fewer transcripts per gene after summing.\nMinor comment:\n1. For hDel-v3 Perturb-seq, only DE genes within 100 kbp of hDel are considered a target. How many hDel/gene combinations fit this criterion in the assay and was this factored into the model when determining statistical significance?", "reviewer_2": "Fair et al developed multiple CRISPRi screening libraries to investigate functions of human-specific deletions during evolution. Using both bulk and single-cell CRISPRi screenings, multiple human-specific deletions either affect cell proliferation in chimpanzee stem cells, or regulate cell gene expression. Studying these regions may reveal how non-coding regions play a role during evolution. In general, the idea is interesting and the approaches are sound. However, the research lacks key validation experiments to evaluate the overall quality of the screening and related conclusions. The authors should also proofread their manuscript, as several main figures were mislabeled.\nMajor\n1.Related to sgRNA and hDel enrichment calculations in Figure 1, it is unclear what is the relationship between DESeq2 analysis on sgRNA and RRA analysis on hDel region enrichment. Would both data were used in later analysis? If a 250-b step size is used, some sgRNAs may be counted multiple times, would this affect the analysis?\n2. It is unclear about the differences between V1 and V2 tiling. The author need to better describe it. Is the V2 library targeting the hits from V1?\n3. Related to Figure 2c, how is it possible to have 18.148 sgRNAs in the scatter plot if the V2 library only contains 78,270 sgRNAs in total? What are compared?\n4. If G4 and C4 would introduce strong off-target effects, why did not exclude these sgRNAs from V1 analysis? Furthermore, experimental evidence would be needed to show these sgRNAs introduce strong off-target effects, for instance, using discovery seq or other methods.\n5. For the V4 analysis, there are multiple different sgRNAs per cell. The authors need to clarify how they correct the effects of these different sgRNAs in individual cells during single-cell RNA-seq analysis.\n6. For the data related to hDel_2247, why mouse tissues were used for the comparison? What would be the results if human tissues were used?\n7. There are no individual cell clones made to validate the screening results related to different phenotypes. As genetics screenings would suffer from false positive hits, these validations are key to show the screenings indeed identified proper hits and deletion regions.\n8. The research aims to study genomic deletions in evolution, the authors would need to use CRISPR editing to delete at least some of the top hits to show the functions of the regions they identified and associated with different genes or phenotypes. Furthermore, non-coding regulatory regions, i.e. enhancer or silencer, may have different functions. CRISPRa may be needed to identify certain types of non-coding deletions, especially loss of silencer activity.\n9. As the authors also agreed that the CRISPRi system has certain effector size limitations, how do the authors consider such an effect in their design of the smaller scale libraries, such as V2, V3, and V4?\n10. The authors concluded that most hDels are dispensable for proliferation. Would this be a strong statement, as the screenings were only done in one cell type?\nMinor\nI am not sure if such mistakes are just minor issues, but a few figures were not labeled properly.\nFigure 1 b and c were not referred to or referred wrongly.\nFigure 2 panels were wrongly labeled.", "reviewer_3": "The manuscript by Fair et al., delves into a pivotal yet underexplored domain within genomics, specifically focusing on human-specific deletions (hDels) and their consequential roles in cellular processes. The study's innovative approach, utilizing cell proliferation and transcriptome changes as a functional readout, provides a fresh perspective in understanding these genomic elements. The authors' application of high throughput CRISPRi screening, executed both at bulk and single-cell levels, stands out as a methodologically robust technique to characterize the role of hDels. Through this screening, the identification of several hDels that influence cell proliferation or gene expression is a significant contribution to the field. Notably, the screening assays have been meticulously designed and executed, demonstrating a high level of scientific rigor. The data are presented with clarity and precision, making the study's findings accessible and comprehensible. The potential implications of these findings in the broader context of genomic research are substantial, indicating that this study, upon addressing specific concerns outlined below, merits timely publication in a prestigious academic journal.\nMajor Concerns:\n1. Validation of hDels Function: The identified hDels from CRISPRi screen require further validation. It is recommended that region-specific deletions be executed using Cas9. This approach would solidify the functional attributions made to these hDels. Alternatively, this concern can also be addressed by analyzing the gene regulatory effects of cis-regulatory hDels in chimpanzee autotetraploids and allotetraploid cells by comparing gene expression between chimpanzee vs human alleles. Such comparative analysis would enhance our understanding of hDels' regulatory function/mechanisms when the sequences are deleted across species rather than epigenetically silenced.\n2. For hDels identified from Perturb-seq and acting as candidate cis-regulatory elements (cCREs), what are the linear distance between these hDes and their target genes? Do these hDels function as distal cCREs? If so, does chromatin looping data in iPSC or hESC support such distal regulation? Given the availability of scRNA-seq data, analyses focusing on both local and distal regulation would deepen our understanding of hDel functions.\n3. The 6.8 kb intergenic deletion hDel_2247 necessitates further elucidation. Since the typical effect size per gRNA in CRISPRi is usually less than 1kb, additional details characterizing the influence of sgRNAs on this larger region are needed. Are there specific motifs or subregions within this 6.8kb area that are critical for its function?\nMinor Concern:\n4. The text within several figures is too small to be easily readable.\n5. There appears to be a discrepancy between the data presented in the figures and the conclusions drawn in the text. For instance, supporting data for the findings discussed in sections such as “We next examined RPL26 MRPS14, and MBD3…” and “sgRNAs targeting a putative inhibitor of DNA binding ID1 cis-regulatory element reduced the expression of ID1…” are not evident. Please include and clearly cite relevant figures or supplementary figures to substantiate these conclusions."}, "author_response": "We thank Reviewer 1 for suggesting testing for enrichment of specific categories of genes near hDels, as well as near hDels that we found to contain cis-regulatory sequence. This analysis allowed us to include the latest Zoonomia conservation scores in our annotation of deletions, revealing that 2177 hDels remove bases under purifying selection at levels comparable to exonic sequence. As expected from human genetics studies, we found that deletions are depleted for removing conserved sequence (p < 10-3), but that in aggregate hDels remove a 116,828 bp of sequence exceeding exon-levels of conservation, highlighting possible functional implications of the class. However, we find no evidence of specific categories of genes being disproportionately affected by cis-regulatory sequences within hDels when controlling for background sets.\nWe performed Gene Ontology (GO) term enrichment testing on genes located near hDels (within 1kb, 5kb, 10kb, or 100kb) using all genes as background and found no significant results.\nWe also tested for enrichment of gene categories near candidate functional elements within hDels, versus candidate functional elements in general. Using iPS cell Tn5-accessible regions as a proxy for functional sequence, we detected no enriched GO terms on genes located near Tn5-accessible regions within hDels versus near all Tn5-accessible regions. Seeking to further narrow the list of candidate functional sequences, we repeated our enrichment testing using runs of conserved bases (at least 8 contiguous bases with phyloP score >= 0.95 from a 240 mammalian genome alignment) within Tn5-accessible regions to model conserved elements. There was no enrichment of genes near runs of conserved bases within Tn5-accessible regions within hDels, using runs of conserved bases within all Tn5-accessible regions as background (we again used maximum distances of 100kb, 10kb, 5kb, and 1kb). Thus, although functional elements are typically observed to be enriched near developmental regulatory genes (e.g., conserved non-coding sequences, including HARs, against a genomic background), deleted functional elements were not enriched in specific categories when controlling for the background set of functional elements.\nTo check whether Tn5-accessible regions might contain binding motifs for specific classes of transcription factors, we located candidate transcription factor binding motifs in hDels (using FIMO with the JASPAR 2020 database). We then tested for enrichment GO terms on transcription factors with predicted binding motifs in hDels, using all transcription factors in the JASPAR 2020 database as background, and again found no enriched terms.\nTo test whether genes found in this experiment to be significantly differently regulated by sequences within hDels were enriched for any functional categories, we tested genes significantly perturbed by hDel CRISPRi for GO enrichment, using both all perturbed genes and all genes within 100 kb of hDels as background. We again found no significant results. This is likely due in part to the small number of genes that passed our significance threshold. But we do note, however, that PLPP1 and CERK are in the same lipid metabolism pathway.\nWe agree that a set of general rules would be useful for the community, but we cannot identify sequence features that make functional hDels (of the type that were linked to genes using Perturb-seq) readily identifiable from other, non-functional hDels. Functional hDels are similar distances to the nearest gene as other hDels (K-S p-value 0.52 and 0.13 for hDel-v3 and hDel-v4 library hits, respectively). Furthermore, as stated above, there are no enriched functional categories of genes near hDels with regulatory potential when controlling for the background set of elements with regulatory potential.\nWe do note that 3 of 20 hDels found to contain at least one run of conserved bases (at least 8 contiguous bp with phyloP score >= 0.95 from a 240 mammalian genome alignment) contained significant CRISPRi guide target sequence (of 26 total significant hDels). This is a significant enrichment (p ~ 6*10-7) and suggests that evolutionary conservation could be an indicator of regulatory potential in other hDels.\nReviewer 1 is correct in highlighting the different sets of hDels reported with evidence of fixation in Kronenberg et al. The Kronenberg et al. main text focused on 5,892 fhDels. The fixed determination involved comparing two new fully assembled human genomes to the reference genome and genotyping of SVs in at least two individuals from each SGDP continental group (N = 16). However, the list of 5,892 hDels further required the deletion to also be a unique structural variant at the locus among apes (11 orangutans, 8 gorillas, 8 chimpanzees, and 2 bonobos). This criterion eliminated fixed deletions in humans that had undergone independent events in other apes. For example, a human-specific hCONDEL near androgen receptor, that removes a penile spine enhancer and previously validated as fixed among humans (McLean et al., Nature 2011) did not pass the multispecies alignment (MSA) determinations as fixed because there is an independent and distinct structural variant involving an inversion in gorilla. However, this hCONDEL still represents a derived and fixed human-specific deletion.\nTo include human-specific deletions that may have independent events in other ape lineages, the Kronenberg paper also includes 1,508 additional fhDels in supplementary table 11.1. We elected to use this broader set as McLean et al. had already shown an intriguing functional example and we aimed for a more comprehensive survey of a class of human-specific variants. We further merged results with 583 hCONDELs, including 76 with evidence for polymoprhism (13%) from McLean et al. to take the union of deletions from these two studies, and we compared all deletions with the UCSC hg38-panTro6 net alignment, resolving any differences by reciprocal BLAT to generate the list of 7,282 for further analysis. After merging hDels and hCONDELs and consolidating deletions separated by <1 kb, our dataset included 1504 hDels that were not previously called as fixed by MSA in Kronenberg (with the requirement for fixed copy number in other apes), and 5774 that were. Identification of functional hDels did not significantly overlap with the categorization of hDels as MSA confirmed. Of 20 hDels linked to target genes, 13 were previously determined as fixed by MSA, which is not a significant enrichment compared to MSA confirmed fixed deletions in the overall set by Fisher’s exact test (p = 0.16). Of these 20 hDels, there is evidence that one, hDel_76, is polymorphic, which is listed in Supplemental table 1.\nWe have used a pseudobulk approach for differential expression testing because methods that compare individual cells frequently have inflated type 1 error rates (Squiar et al., Nature Communications 2021; Zimmerman et al., Nature Communications 2021). Reviewer 1 correctly points out that the number of cells per sgRNA varies in Perturb-seq and presents a challenge for differential expression testing. To account for a variable number of cells in each +sgRNA pseudobulk, DESeq2 uses size factors to make comparisons of gene expression between groups (in this case +hDel-targeting sgRNA vs. +non-targeting sgRNA).\nFor hDel-v3, we identified 4 hDel-gene pairs within 100 kb (FDR < 0.1), including hDel_6012-RPL26, hDel_349-MRPS14, and hDel_6304-MBD3. For multiple hypothesis correction, the Benjamini-Hochberg procedure was applied to all sgRNA-gene pairs separated by ≤100 kb.The approach for assessing statistical significance is outlined below (inspired by Cooper et al., Science 2022):\n● sgRNA-gene pairs were Z-score normalized using the DESeq2 log fold-change divided by the DESeq2 standard error of the log fold-change\n● p-values were calculated from the survival function of a normal distribution for each gene within 100 kb of any hDel, drawing a null distribution from all sgRNA-gene pairs separated by ≥100 kb\n● the Benjamini-Hochberg procedure was applied to all sgRNA-gene pairs separated by ≤100 kb\nsgRNA-level analysis was performed using DESeq2. To aggregate information from adjacent hDel-targeting sgRNAs, sgRNA-level adjusted p-values from DESeq2 were used as input for α-RRA analysis. This approach identifies significant genomic windows by considering multiple sgRNAs and is conceptually similar to MAGeCK, but uses DESeq2 for negative-binomial regression. Yes, as suggested by Reviewer 2, some sgRNAs are included in adjacent overlapping 500-bp windows; p-values corresponding to all 500-bp windows are accounted for in multiple hypothesis correction by α-RRA.\nWe thank Reviewer 2 for requesting this clarification. Yes, hDel-v2 targets hDels that were identified using hDel-v1. Additionally, hDel-v2 features reduced spacing between proximal sgRNAs (median 7 bp between sgRNAs) compared to hDel-v1 (median 52 bp between sgRNAs) and a greater number of sgRNAs per hDel (hDel-v2, median 119 sgRNAs per hDel; hDel-v1, median 14 sgRNAs per hDel).\nWe have revised the main text as follows to clarify the transition between hDel-v1 and hDel-v2:\nTo fine-map functional sequence within proliferation-modifying hDels identified using hDel-v1, we designed a second tiling library (hDel-v2) with reduced spacing between proximal sgRNAs. Because reduced spacing supports the discovery of hDels that may not have been detected using hDel-v1, we included hundreds of hDels with a single proliferation-modifying sgRNA. We omitted a genomic window strategy for sgRNA selection to maximize tiling density, resulting in a library of 78,270 sgRNAs targeting 558 hDels (Fig. 2a, median 7 bp between sgRNAs, median 119 sgRNAs per hDel). As with hDel-v1, we transduced chimpanzee CRISPRi iPS cells (C3624K) with the lentiviral hDel-v2 sgRNA library, selected and cultured sgRNA-expressing cells, and quantified sgRNA enrichment and depletion by high-throughput sequencing.\nFigure 2c shows the correlation in fold-change for the 18,148 sgRNAs that were independently screened in hDel-v1 and in hDel-v2. The remaining targeting sgRNAs in hDel-v2 were not screened in hDel-v1, reflecting the greater tiling density in hDel-v2, and cannot be shown on this scatterplot.\nThe large number of sgRNAs containing G /C homopolymers in hDel-v2 (Figure S7; n = 275 to 404 sgRNAs with G or C homopolymers per spacer position) allowed us to discover position-dependent off-target effects that have been overlooked by previous studies. We organized our presentation of the data based on the order of the experiments, as the design of the hDel-v2 library was based on hDel-v1 as analyzed using state-of-the-art software. We believe that incorporating findings of novel off-target effects discovered using hDel-v2 into analysis of hDel-v1 would have been confusing for the reader, but we ensured that these sgRNAs were removed from hDel-v2 analysis that is presented as validation in Figure 2, controlling for the observed off-target toxicity. We show in Figure S7 that G -associated toxicity is also present in a widely-cited CRISPRi tiling study across GATA1 and MYC in human K562 cells (Fulco et al., Science 2016). Although characterizing the source of sgRNA-mediated off-target effects is not the focus of our study, we agree that it is an important direction for future studies. We believe that sharing the observed sgRNA homopolymer-associated toxicity is of value to the research community.\nWe thank Reviewer 2 for requesting this clarification. For hDel-v4, we transduced cells at a high multiplicity of infection (median 7 sgRNA per cell, median 495 UMIs per sgRNA per cell), consistent with previous single-cell CRISPRi studies (Gasperini et al., Cell 2019; Xie et al., Cell Reports 2019; Morris et al., Science 2023). We knew based on hDel-v1 and hDel-v2 screens that these hDel-targeting sgRNAs were nonessential, motivating us to conduct a high multiplicity of infection screen to increase power to detect differential gene expression and reduce the number of cells needed for scRNA-seq (Gasperini et al., Cell 2019). Because each cell receives a random combination of sgRNAs, no correction was performed for individual sgRNAs. For differential expression testing, we used a pseudobulk approach because methods that compare individual cells frequently have inflated type 1 error rates (Squiar et al., Nature Communications 2021; Zimmerman et al., Nature Communications 2021).\nAs an orthogonal analysis approach, we used SCEPTRE (Barry et al., Genome Biology 2021), software designed for high multiplicity-of-infection single-cell CRISPR screens, to test for hDel-gene associations with hDel-v4. We performed a left-sided test using SCEPTRE to detect a reduction in gene expression in cells harboring hDel-targeting sgRNAs. We found strong concordance between the results of our DESeq2 pseudobulk approach and SCEPTRE: 10 of the 11 hDel-gene pairs with reduced expression using our approach were significant using SCEPTRE (FDR < 0.1). SCEPTRE results:\nWe thank the reviewer for raising this point as further analysis has led to additional information regarding the function of hDel_2247. Human-specific deletion 2247 (hDel_2247) is not present in the human genome. We originally analyzed epigenomic data from the orthologous sequence in mice because there is no comparable ENCODE dataset in nonhuman primates.\nWe agree with Reviewer 2 that analyzing sequences closer to the human-chimpanzee common ancestor would be ideal for characterizing the regulatory activity of the deleted sequence. Therefore, we used an orthogonal approach - transient transgenic lacZ reporter assays in mouse embryos - to analyze the sufficiency of the chimpanzee sequence for driving reporter gene expression in vivo during embryonic mouse development.\nWe found that the chimpanzee sequence (1,557 bp; chr5:45194159-45195715 in panTro6), distinct from epigenomic signatures in mouse, regulates gene expression in the olfactory bulb and anterior neocortex, two structures that have been modified recently in human brain evolution. We thank Reviewer 2 for highlighting the importance of focusing on sequences closer to the ancestral allele lost in recent human evolution, as this led to updated findings regarding the anatomical specificity of hDel_2247.\nWe agree that orthogonal approaches provide additional value. However, we are cautious about experiments involving the generation of isogenic cell lines due to the risk of acquiring unintended genetic changes (Baker et al., Nature Biotechnology 2007; Merkle et al., Nature 2017) and phenotypic variability among individual clones (Westermann et al., Scientific Reports 2022). Instead, we used an orthogonal approach, transient transgenic lacZ reporter assays in mouse embryos, finding that sequences within hDel_2247 drive reporter gene expression specifically in olfactory bulb the anterior neocortex. As hDel_2247’s target gene PLPP1 hydrolyzes LPA, which is a driver of both olfactory ensheathing cell migration and neural progenitor proliferation (Medelnik et al., Stem Cell Reports 2018), this finding may motivate future examination in the context of human brain evolution.\nWe agree that CRISPRi repression of cis-regulatory sequence may not enable detection of all functions of noncoding sequences, and we have now added a sentence to the discussion highlighting this limitation: “For cis-regulatory elements with repressive effects on transcription, such as silencers, CRISPR activation-based approaches may be useful for target gene identification.” In addition, we now highlight an example of an hDel with apparent silencer activity. Targeting of hDel_1608, which intersects multiple epigenetic features results in increased expression of C4orf48 (Fig. 4i,j).\nConsistent with previous studies (Fulco et al., Nature Genetics 2019), we find that CRISPRi has a narrow window of activity at promoter-distal sites. We consider this limitation during the design of hDel-v2, hDel-v3, and hDel-v4 by including at least 5 sgRNAs per targeted hDel. For example, 8 sgRNAs targeting hDel_2247 reduce the expression of PLPP1 in hDel-v4 (Fig. 5a,b).\nWe agree that this statement is overly broad. We have revised the sentence as follows:\nTogether, hDel-v1 and hDel-v2 identify cellular phenotypes for select hDels and indicate that despite the predicted phenotypic importance of SV-sized noncoding deletions, hDels as a class of human-specific SVs are largely dispensable for iPS cell proliferation.\nWe thank Reviewer 2 for raising this concern. We have corrected the panel labels and we apologize for any inconvenience this may have caused.\nWe agree on the importance of orthogonal assays. As suggested by Reviewer 3, we quantified cis-regulatory divergence between human and chimpanzee alleles in human-chimpanzee allotetraploid iPS cells for hDel target genes. We found that the human CERK, FAM49B, GRTP1, SUCLG2, MRPS14, and MDB3 human alleles drove reduced expression compared to chimpanzee alleles in allotetraploid iPS cells (Extended Data Fig. 6h-j, Fig. 4l), consistent with the human-specific loss of cis-regulatory sequence and with our results using CRISPRi. As further validation, we used transient transgenic lacZ reporter assays in mouse embryos, finding that a 1.5 kb sequence within hDel_2247 drives reporter gene expression specifically in the olfactory bulb and anterior neocortex.\nCRISPR-based experiments are complemented by epigenetic characterization of hDel chromatin using Omni ATAC-seq and H3K4me1, H3K4me3, H3K27ac, and H3K27me3 CUT&Tag.\nWe thank Reviewer 3 for requesting this clarification. The linear distance between hDel-targeting sgRNA and TSS for corresponding cis target gene is plotted on a log scale in 10 Fig. 4d. Yes, these hDels function as intergenic or intronic cis-regulatory elements; we provide a table of linear distances between hDel-targeting sgRNAs and their target genes for clarification:\nFor differential expression testing, we first determine whether any hDel alters the expression of any expressed gene within a linear distance of ≤100 kb (to gene body) to establish a cis-regulatory linkage. For hDels with identified cis-regulatory linkages, we then performed a genome-wide trans differential expression test. For example, we identified 83 differentially expressed genes upon hDel_6304 CRISPRi, including transcription factors controlling meso-endoderm differentiation (EOMES, GATA6, LHX1, MIXL1), all of which were down-regulated (Fig. 3k, FDR < 0.1).\nWe have also intersected hDels linked to target genes using Perturb-seq with chimpanzee iPS cell chromatin conformation (Hi-C) from Eres et al., PLoS Genetics 2019. We find that all 20 hDels linked to target genes using Perturb-seq are within regions of 3D genomic interactions in chimpanzee iPS cells. Half of these hDels (10 hDels) are within regions that contact the TSS of the linked gene.\nWe have performed transient transgenic lacZ reporter assays in mouse embryos to characterize the cis-regulatory capacity of sequences within hDel_2247 in vivo. We find that sequences within hDel_2247 intersecting Omni ATAC-seq, H3K4me1, and H3K27ac drive reporter gene expression specifically in the olfactory bulb and anterior neocortex in multiple embryos (n = 4 of 5 transgenic embryos). These results identify a subregion within hDel_2247 that is critical for its cis-regulatory function (1,557 bp; chr5:45194159-45195715 in panTro6) and provide independent validation for the 8 sgRNAs targeting hDel_2247 within this sequence that reduce the expression of PLPP1 in hDel-v4 (Fig. 4f).\nWe thank Reviewer 3 for raising this concern and we apologize for any inconvenience this may have caused. We have adjusted font size throughout the main figures.\nWe thank Reviewer 3 for raising this concern and we apologize for omitting these figures. We have added supporting data for MRPS14, MBD3, and RPL26 in Extended Data Fig. 6h-j. We have also added supporting data for ID1 in Extended Data Fig. 8d."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Authors have suitably addressed my comments and concerns. I look forward to seeing this exciting work published", "reviewer_2": "It is very common to validate some of the top hits from most of the genetic screenings to evaluate the performance of the screening, as both referees 2 and 3 pointed out. Especially that the authors would like to used CRISPRi to study the effects of genomic deletions. Related to that, do the 16 hDels identified from V1 screening overlap with the 38 hDels from V2?\nIt is also puzzling to see CRISPRi (with repressive activity) targeting a silencer (which probably regulated by a repressive TF) will lead to transcriptional activation, as showed by dDel_1608 and C4orf48.", "reviewer_3": "My concerns have been fully addressed.I recommend publication of the revised manuscript."}, "author_response": "We appreciate this reviewer’s helpful comments.\nWe have used pairs of Cas9 RNPs to generate genomic deletions of two hDels (hDel_2247 and hDel_3779) that are linked to gene targets in our hDel-v4 CRISPRi Perturb-seq screen. We find that deletion of hDel_2247 reduces the expression of PLPP1 65.0% to 75.9% in three independent polyclonal populations of chimpanzee iPS cells. Similarly, we find that deletion of hDel_3779 reduces the expression of FAM49B 9.1% to 27.6%.\nWe assigned hDel-targeting sgRNAs to overlapping 500-bp genomic windows (250-bp step size) and combined sgRNAs into hDel FDRs using alpha-robust rank aggregation (α-RRA) from MAGeCK to identify proliferation-modifying hDels. 4 of 16 hDels from hDel-v1 overlap with hDel-v2. This discrepancy is not a matter of data quality: hDel-targeting sgRNAs screened in both hDel-v1 and hDel-v2 were highly correlated (r = 0.73, Fig. 2c). Instead, the addition of new sgRNAs in hDel-v2 did not show similar proliferation-modify effects, partly due to the fact that hDel-v1 sgRNAs were selected for high on-target activity (using DeepHF), whereas hDel-v2 sgRNAs were only filtered for off-target specificity (no on-target activity preference). All major conclusions we draw from the results of our study further depend upon hDel-gene linkages from Perturb-seq (hDel-v3 and hDel-v4).\nhDel_1608 intersects a Tn5-accessible region (panel i) and using conservative pseudobulk and two-tailed statistical tests for analysis of Perturb-seq (hDel-v4), 2 sgRNAs increase the expression of C4orf48 (panel j, 16.2 to 19.8%, FDR < 0.1). This finding is consistent with the negative regulation of mRNA by a divergently transcribed lncRNA (https://pubmed.ncbi.nlm.nih.gov/32777522/). We now acknowledge that other scenarios are also possible, including CRISPRi preventing the binding of repressive transcription factors to target DNA."}, {"round": 3, "reviewer_comments": {"reviewer_2": "Related to comment #1, in the response letter, it indicates \"Similarly, we find that deletion of hDel_3779 reduces the expression of FAM49B 9.1% to 27.6%.\" However, in the main text, it says \"reduced the expression of the RAC1 effector FAM49B (Extended Data Fig. 8h, 8j, 14.2 to 23.6%, FDR < 0.1),\" I am not sure if this is an error, but the authors should clarify this in the manuscript.\nRelated to comment #3, the author may need to include the references related to lncRNAs and silencers in the manuscript."}, "author_response": ""}]

Decision letter