Convergent evolutionary shifts in AGT targeting between mitochondria and peroxisomes across mammal transitions to herbivory

Domain: chemistry
Published: 2026-03-04
Editorial outcome: minor_revision

Abstract
Herbivory has evolved multiple times during mammalian diversification, playing a key role in the success of this globally distributed clade. A central metabolic challenge for herbivores is the detoxification of glyoxylate. The enzyme alanine:glyoxylate aminotransferase (AGT) converts glyoxylate to glycine, preventing the formation of harmful calcium oxalate crystals. AGT localizes to mitochondria and peroxisomes based on the mitochondrial targeting sequence (MTS) and the peroxisomal targeting signal (PTS1), respectively. While most studies focused on MTS, MTS variation alone does not fully explain AGT localization patterns. To assess the relative importance of the PTS1 motif, we combined comparative sequence analyses with functional assays. We find that multiple herbivorous lineages underwent independent mutations resulting in disrupted or truncated MTS regions, whereas the PTS1 motif remains functional. Immunofluorescence assays revealed more efficient peroxisomal localization of AGT in herbivores, with PTS1 often overriding mitochondrial signals even when the MTS is intact. Additionally, transcriptomic analyses show that several herbivorous lineages preferentially use downstream transcriptional start sites, producing AGT isoforms lacking the MTS. Together, our findings reveal a central role of AGT peroxisomal targeting in evolution of plant-based diets, and demonstrate how increased targeting efficiency has evolved convergently via the interplay of transcriptional regulation and targeting signals.

Introduction
The independent evolution of plant-based diets has occurred multiple times throughout the diversification of mammals, and is a key factor contributing to the evolutionary and ecological success of this group1. Fossil evidence indicates that early mammals were primarily insectivorous, as inferred from their jaw and dental morphology, and that these formed the foundation for numerous subsequent shifts into novel dietary niches2,3. Herbivory in mammals likely originated ~260 million years ago in groups such as Eleutherodontidae, which fed on non-flowering plants4, with further diversification of herbivorous lineages coinciding with angiosperm evolution in the Cretaceous5. For successful transitions to plant-based diets, mammals evolved multiple traits for finding, ingesting, breaking down, and metabolizing plant tissues6. Adaptations for hosting symbiotic bacteria for the breakdown of cellulose7,8, as well as processing simple and complex carbohydrates9–11, have evolved convergently in multiple groups. One of the major challenges for mammals that subsist on plants is overcoming toxins and secondary compounds, many of which have evolved as defences against herbivory12,13.

The enzyme alanine:glyoxylate aminotransferase (AGT) is primarily located in the mitochondria of liver cells, where it converts glyoxylate to glycine14. Glyoxylate is a byproduct of metabolism and is otherwise converted into oxalate, which can accumulate and lead to the formation of toxic calcium oxalate crystals in the body14. In carnivores, the precursor of glyoxylate is hydroxyproline, which is broken down in the mitochondria15, whereas in herbivores, it is glycolate, which is produced in peroxisomes16. As a consequence, in some species, AGT has also evolved to target peroxisomes via distinct protein domains and post-translational modifications17. The tendency for AGT to localize in mitochondria in carnivores, and peroxisomes in herbivores, is supported by immunoelectron microscopy studies across over 70 mammalian species18,19.

AGT’s subcellular localization is directed by a mitochondrial targeting sequence (MTS) of ~22 amino acids at the N-terminus, and a peroxisomal targeting signal (PTS1), a C-terminal tripeptide within the mature protein14,20–22. To date, most studies relating AGT to diet have focused on the dominant role of the MTS in mitochondrial targeting18,19,23. However, independent MTS losses have been reported in several lineages, including bats and primates23,24. Many such losses arise from mutations affecting the 5′ start site of the AGXT, which disrupt MTS function and impair mitochondrial import25–27. Yet despite these results, MTS integrity alone cannot fully explain the AGT distribution across mammals. In many species, AGT localization exists along a continuum between mitochondria and peroxisomes. Moreover, in some species with intact MTS—such as herbivorous domestic horse (Equus ferus) and omnivorous olive baboon (Papio anubis)—AGT predominantly targets peroxisomes18.

Compared to the MTS region, the role of AGT’s PTS1 motif is less well understood. Some have suggested that PTS1 might only function when the MTS is weak or inactive21; however, the finding that enhancing AGT peroxisomal targeting leads to reduced mitochondrial localization implies that AGT distribution is controlled by a balance between mitochondrial and peroxisomal import systems28. Studies of other peroxisome targeting proteins have identified a so-called consensus PTS1 motif, [S/A/C]-[K/R/H]-[L/M] that confers high peroxisomal targeting efficiency28. However, while comparisons of AGT across vertebrate groups have recorded this consensus motif in some taxa, its relationship to diet in mammals is unclear. Indeed, the human AGT PTS1 sequence, KKL, is unique among human peroxisomal proteins and is necessary but insufficient for efficient peroxisomal import27,29–31.

In addition to amino acid variation in targeting regions, subcellular localization of AGT across mammals can also reflect differential use or loss of alternative transcription start sites. The complete AGXT has two transcription start sites: one upstream of the first translation start codon, and another located between two translation start codons14. In cats, mitochondrial AGT derives from the longer transcript, whereas in rabbits, peroxisomal AGT originates from the shorter one21. More omnivorous species, such as marmosets and rats have been shown to express both transcript variants21, suggesting a link between transcriptional regulation and dietary strategy.

In this work, we conduct the large-scale comparative study of AGT across mammals. By combining cell-based immunofluorescence assays of natural and mutant proteins with analyses of transcripts and regulatory regions, we demonstrate that variation in PTS1 sequences and alternative transcription initiation contribute to differences in AGT localization and dietary adaptation across species.

Results
Using tBLASTn32, we searched publicly available genome assemblies from 685 mammal species and retrieved 505 hits, with the remaining 180 genomes showing no hit due to low quality. Of the 505 hits, we recorded 472 AGT orthologues with an MTS region. In 33 species, the sequence was incomplete due to gaps in either the mature region and/or PTS1 targeting region.

Nonfunctional MTS and high-conserved PTS1 occur mostly in herbivores
We examined the 472 MTS regions and found that 429 were complete and thus considered putatively functional. MTS sequences showed significant variation between Eutheria (22 amino acids) and Prototheria/Metatheria (33 amino acids), indicating a lack of sequence homology.

In 43 species (Supplementary Fig. 1), the MTS was inferred to be non-functional due to the presence of a single non-canonical start codon (n=21), premature stop codon (n=6), or frameshift mutation (n=3), or a combination of these (n=13). Of these species, 35 (81.40%) are herbivores including 28 strict herbivores, four are omnivores (9.30%), and four are carnivores (9.30%) including three hypercarnivores (species with a diet comprising >70% animal tissue; e.g., Iberian mole, Talpa occidentalis) (Supplementary Fig. 2). Examples of herbivores with functional losses caused by frameshift mutations include the common wombat (Vombatus ursinus) from the order Diprotodontia, representing the first such case from the Metatheria. Losses arising from nonsense mutations were seen in lagomorphs, primates, bats, and several rodents. For example, we identified a shared premature stop codon (TGA) at nucleotide positions 43–45 in the MTS of five squirrel species (alpine marmot, Himalayan marmot, Vancouver Island marmot, woodchuck, and yellow-bellied marmot) and the mountain beaver (Aplodontia rufa), and a different stop (TAA) at the same site in the dormouse (Glis glis), Similarly, among the primates, the MTS of the white-faced saki (Pithecia pithecia) contained a premature stop codon at nucleotide positions 55–57 which can also be found in nutrias (Myocastor coypus). Other cases of loss of function involved missense mutations in the upstream translation start site of the AGXT, seen in diverse groups such as bats (e.g., Rousettus aegyptiacus) and primates (e.g., Cercopithecus mona) (Supplementary Fig. 1).

In contrast to the MTS, we recorded no cases of loss-of-function mutations in the PTS1 motif. A total of 498 complete orthologues contained a PTS1 motif, although the residues varied among species. We examined in detail the PTS1 motif composition and found that the consensus motif ([S/A/C]-[K/R/H]-[L/M]) was present in 106 species, comprising 75 (70.75%) herbivores and 69 (65.09%) strict herbivores (Figs. 1 and S2 and Supplementary Data 1). Additionally, the PTS1 in 330 species (66.27%) contained the [N/K]-K-L motif, which partially matches the consensus sequence (Supplementary Data 1). Interestingly, we recorded an overrepresentation of the motifs SRL (n=17), SKL (n=66), and SKM (n=23), with most examples of the former two (94.12% and 86.36%, respectively) seen in herbivores, whereas cases of the latter motif were more common (91.30%) in carnivores (Supplementary Data 1).

We performed ancestral reconstruction of PTS1 motifs across the mammal tree and identified numerous instances of convergent evolution of known consensus motifs (Fig. 1). Notably, we observed independent evolution of the GKL motif in all Old World fruit bats (Pteropodidae) and sloths (Folivora) examined, and the SKL motif in most members of Artiodactyla and the koala (Phascolarctos cinereus). Similarly, we observed convergent evolution of the NRL motif in several unrelated lineages, including the Hispaniolan solenodon (Solenodon paradoxus) and degu (Octodon degus), the SRL motif in the dama gazelle (Nanger dama), paca (Cuniculus paca), and mouse-deer (Tragulus javanicus), and the HKL motif in carnivorans such as the domestic dog (Canis lupus familiaris) and banded mongoose (Mungos mungo), along with non-carnivorans like the Sumatran rhinoceros (Dicerorhinus sumatrensis) and domestic pig (Sus scrofa). Less common convergent motifs included HRL seen in the South African springhare (Pedetes capensis) and Patagonian mara (Dolichotis patagonum), SKM seen in the kinkajou (Potos flavus) and European hedgehog (Erinaceus europaeus), and GRL in the Indochinese shrew (Crocidura indochinensis) and nectar bat (Macroglossus sobrinus). Interestingly, while the majority of these convergent motif changes occurred in herbivorous mammals, the presence of distinct motifs was also seen in some omnivorous and carnivorous species, and no consensus motifs were recorded in primates (Fig. 1).

AGT peroxisomal targeting efficiency correlates with degrees of herbivory
We conducted cell-based immunofluorescence assays to assess the mitochondrial and peroxisomal targeting efficiency of the mature AGT protein in 37 mammal species for which immunoelectron microscopy data were also available18. Based on co-localization data, we found that mitochondrial targeting efficiencies ranged from 21.43% in the rhesus monkey (Macaca mulatta) to 98.66% in the greater horseshoe bat (Rhinolophus ferrumequinum), while peroxisomal targeting efficiencies ranged from 5.66% in the greater horseshoe bat to 92.61% in the rhesus monkey (Fig. 2a/l and Supplementary Fig. 3). Notably, we observed generally lower peroxisomal targeting efficiencies in species from the Carnivora and Chiroptera orders. Within Carnivora, peroxisomal targeting efficiencies varied from 8.06% in the lion (Panthera leo) to 29.40% in the brown bear (Ursus arctos), and only three species—including the giant panda (Ailuropoda melanoleuca) and the North American raccoon (Procyon lotor)—showed peroxisomal targeting efficiencies exceeding 20%. Similarly, in Chiroptera, peroxisomal targeting efficiencies ranged from 5.66% in greater horseshoe bats to 30.74% in the black flying fox (Pteropus alecto), the only herbivorous bat species in our sample (Fig. 2a).

To investigate the relationship between the AGT subcellular targeting quantified from our cell-based assays with published data on diet, we ran phylogenetic Bayesian mixed models (MCMCglmm)33 and found contrasting effects for peroxisomal and mitochondrial localization. In a model of peroxisomal targeting efficiency as a function of dietary plant content, diet had a significant positive effect (posterior mean=0.28, 95% CI=0.110–0.430, pMCMC=0.0016, Supplementary Table 1), consistent with enhanced peroxisomal localization in herbivorous species. An equivalent model assessing mitochondrial targeting revealed a negative, but non-significant, association with plant-based diets (posterior mean=–0.12, 95% CI=–0.280 to 0.037, pMCMC=0.13, Supplementary Table 1). We also ran phylogenetic generalized least squares (PGLS) regressions34 and obtained consistent findings in which herbivory showed a significant positive association with AGT peroxisomal targeting efficiency (R²=0.30, p=4.09×10−4, Fig. 2b and Supplementary Table 2) but not with mitochondrial targeting efficiency (R²=0.07, p=0.11, Supplementary Table 2). In both models, the phylogenetic signal remained strong (Pagel’s λ=1.00 and 0.97, respectively).

PTS1 is significant in determining the subcellular localization of full-length AGT
To investigate the impact of PTS1 on peroxisomal targeting ability in mammals, we also constructed AGT plasmids lacking PTS1 for our 37 focal species. These plasmids were then used in immunofluorescence assays to assess the subcellular localization of AGT when only the MTS and mature regions were present. The experimental procedure followed a similar protocol to that described earlier. By comparing the results with previously obtained peroxisomal targeting efficiencies, we observed that the peroxisomal targeting efficiency of AGT in the absence of PTS1 was reduced by over 50% in most species, with the most marked decreases seen in herbivorous mammals, ranging from 73.16% in the strict herbivorous koala to 8.96% in omnivorous olive baboons. In contrast, carnivorous mammals maintained low peroxisomal targeting efficiencies, with the greater horseshoe bats showing almost no change (3.71%) in efficiency (Fig. 2a and Supplementary Fig. 4). Closer examination of these strongly contrasting species showed that, following removal of PTS1, the peak intensity of AGT in koalas no longer overlapped with that of peroxisomes (Fig. 2g/j), whereas AGT in the greater horseshoe bat retained a wild type condition of mitochondrial localization (Fig. 2k/l).

We modeled the reduction in peroxisomal targeting efficiency following PTS1 removal as a function of plant tissue in the diet, and found a significant positive association after controlling for phylogeny (posterior mean=0.20, 95% CI=0.091–0.310, pMCMC=0.0014, Supplementary Table 1). This result was further supported using a PGLS regression (R²=0.41, p=1.88×10−5, Fig. 2c and Supplementary Table 2) with strong phylogenetic signal (Pagel’s λ=0.83). These findings suggest herbivorous species experience a greater loss in targeting efficiency when PTS1 is disrupted.

Because variation in peroxisomal localization among species likely reflects a balance between the relative efficiencies of PTS1 and MTS targeting, we also tested whether the greater targeting in herbivores over carnivores was mainly attributable to their PTS1 sequences, or might instead also reflect adaptive decreases in MTS targeting efficiency, as previously suggested for anthropoid lineages24. We therefore generated AGT constructs lacking the MTS for all focal species and compared their subcellular localization via immunofluorescence assays with those of our first experiment based on vectors containing full AGT sequences. Our results revealed that deletion of the MTS led to substantial reductions of mitochondrial targeting efficiency—over 35% in most mammalian species—ranging from a 31.67% decrease in the crested porcupine (Hystrix cristata) to 71.47% in the African hunting dog (Lycaon pictus) (Supplementary Figs. 3, 5, and 6). Thus, the MTS contributes significantly to mitochondrial localization of AGT, with particularly pronounced effects in members of Laurasiatheria. However, this was not universally the case. For example, in the olive baboon and rhesus monkey, removal of the MTS resulted in only modest (~10%) reduction in mitochondrial localization, suggesting a reduced role for MTS in mitochondrial targeting without a compensatory enhancement of PTS1 function. Together, these findings indicate that the PTS1 motif retains the capacity to direct AGT to peroxisomes even in the presence of a functional MTS, so contradicting earlier suggestions that PTS1 becomes functionally relevant only when the MTS is absent or compromised21.

Tests of molecular adaptation
To investigate whether positive selection has acted on the AGXT—particularly within the MTS and PTS1 regions that govern subcellular localization—we analyzed separate datasets corresponding to the MTS, PTS1, and the mature region excluding PTS1 across all mammals as well within major superorders. For each dataset, we estimated rates of synonymous and nonsynonymous substitutions (dS and dN, respectively) and the dN/dS ratio ω for all branches on the tree under the free-ratio model.

Across all mammals, we recorded ω values >1 in 642 out of 854 branches for PTS1 (Supplementary Fig. 7), compared to 465 branches for the MTS region, and 55 branches for the mature region without PTS1 (Supplementary Fig. 7). Pairwise ω estimates using the modified Nei-Gojobori method35 further supported these results: 62.38% of pairwise comparisons in the PTS1 region showed dN > dS, compared to 12.90% in the MTS region, and none in the mature region without PTS1 (Supplementary Fig. 7). These findings suggest that the PTS1 region of AGXT is subject to more positive selection than both the MTS and the rest of the mature protein sequence. These trends were also seen when analyzing separate superorders and 37 species in experiments with the PTS1 region showing the strongest selection pressure compared to the MTS and the rest of the mature protein sequence in all groups except Monotremata (Fig. 2e/d and Supplementary Fig. 7).

Branch-site tests with herbivore lineages marked in Supplementary Fig. 8 as the foreground revealed no evidence for positive selection when applied across mammals as a whole (ω₂=1.0; LRT p=0.92, model A in Supplementary Data 2), nor within Afrotheria or Metatheria (ω₂≈1.0–1.3; LRT p≥0.38, model G/I in Supplementary Data 2). In contrast, analyses restricted to Laurasiatheria and Euarchontoglires detected a strongly supported class of codons with ω >1 on herbivore branches (ω₂≈33 and 32, respectively; LRT p=0.001 in both cases, model C/E in Supplementary Data 2). The inferred proportion of such sites was extremely small (p2a+p2b≈0, model C/E in Supplementary Data 2), indicating that adaptive changes are highly localised. BEB analysis identified a handful of candidate codons in these two clades, including 215 I and 286T in Laurasiatheria (PP≥0.95, model C in Supplementary Data 2), and 20V and 286T in Euarchontoglires (PP>0.8, model E in Supplementary Data 2), whereas no codons had supported ω >1 in Afrotheria or Metatheria.

Dietary adaptation is associated with alternative AGT transcription start site usage
To investigate whether dietary strategies influence the transcriptional regulation of AGT in mammals, we analyzed RNA-sequencing (RNA-seq) data from normal liver tissue across 172 mammalian species. We assessed usage of upstream transcription start sites by quantifying the ratio of read coverage of the upstream versus the downstream translation start site (ATG1 and ATG2 in Fig. 3b, respectively) and found differences between species with plant- versus meat-based diets. Among the 148 species with a complete AGT sequence, 75 species exhibited a low upstream-to-downstream start site usage ratio (ATG1/ATG2≤0.5, Fig. 3a), including 14 carnivorous and 51 herbivorous species (including 12 hypercarnivores and 37 strict herbivores). In contrast, 73 species showed higher upstream usage (ATG1/ATG2>0.5, Fig. 3a), comprising 50 carnivorous and 18 herbivorous species (including 47 hypercarnivores and 9 strict herbivores). An additional 24 species lacked a complete MTS but retained the mature AGT region and the PTS1 motif. Of these, five herbivorous species had an ATG1/ATG2 ratio >0.5, while the remaining 19 species (3 carnivorous and 15 herbivorous, including 1 hypercarnivore and 14 strict herbivores) had lower ratios (≤0.5, Fig. 3a).

For species with an intact MTS, we again ran a Bayesian mixed model to examine upstream AGT transcription start site usage as a function of dietary plant content. A significant negative association (posterior mean=–0.29, 95% CI=−0.420 to −0.110, pMCMC=0.0014, Supplementary Table 1) indicates that herbivorous species are more likely to initiate AGT transcription from the downstream transcription start site, bypassing the upstream start codon that includes the mitochondrial targeting signal. A significant negative relationship between the ATG1/ATG2 ratio and dietary plant content was also supported by the results of PGLS analysis (R²=0.11, p=3.53×10−5, Fig. 3c and Supplementary Table 2) with some remaining phylogenetic signal (Pagel’s λ=0.60). These findings independently corroborate the results of the MCMCglmm model and further support the link between diet and alternative AGT transcriptional regulation, with plant-rich diets associated with reduced usage of the upstream transcript isoform.

Variation in promoter activity across species
We hypothesised that herbivory is associated with reduced usage of the upstream AGXT promoter (ATG1) and compensatory activation of a downstream start region, which should manifest as weaker upstream promoter marks/accessibility and lower upstream promoter activity. To probe the regulatory basis of the start-site shift, we examined liver ChIP-seq profiles for active promoter marks (H3K4me3, H3K27ac)36 across 13 species (Fig. 3d and Supplementary Fig. 9). In multiple herbivores, enrichment was weaker upstream of ATG1 and comparatively stronger near the downstream start region, whereas dog (Carnivora) showed extended upstream signal—patterns consistent with reduced upstream promoter activity in herbivores and greater upstream activity in some non-herbivores. Consistent with these profiles, RNA-seq coverage over the AGXT start-site region was higher in the dog than in the herbivores within this subset (Fig. 3d).

We then assessed chromatin accessibility using liver ATAC-seq (subset of species in Fig. 3d). Herbivores generally showed lower accessibility upstream of ATG1 with more open chromatin nearer the downstream start region, mirroring the ChIP-seq profiles, while the dog showed accessible chromatin extending upstream of ATG1. Taken together, concordant shifts in active promoter marks, chromatin accessibility, and subset RNA-seq coverage support a diet-associated reduction in upstream promoter activity in herbivores, providing a mechanistic link to the ATG1/ATG2 usage patterns described above.

To test whether upstream promoter sequence contributes to these differences, we edited the upstream start codon (ATG1) within the promoter fragment cloned upstream of luciferase (single base-triplet substitution ATG→GCG at ATG1; +1..+3 relative to ATG1). The effect of this mutation on AGT promoter activity was then quantified using dual-luciferase reporter assays across 19 mammalian species. The selection of these species was informed by prior immunofluorescence colocalization data, the availability of complete AGT sequences, and the presence of a functional MTS. When comparing across mammals, we observed no clear association between diet and the magnitude of difference in luciferase activity between ATG1-edited and corresponding wildtype binding sites (p=0.16, Supplementary Fig. 10 and Supplementary Table 2). However, within bats, we recorded lower impacts of ATG1 substitution on promoter activity in the insectivorous species Rhinolophus ferrumequinum and Myotis myotis, and in the blood-feeding Desmodus rotundus, compared to in plant-feeding bats (Supplementary Fig. 10). Striking exceptions were also seen, notably in the donkey (Equus asinus) in which the mutant construct displayed a strong increase in promoter activity.

Finally, we asked whether transcription factor (TF) binding architecture differs among lineages. Using motif prediction in the upstream region for the species with matched RNA-seq/ChIP-seq/ATAC-seq, canonical liver TF motifs (e.g., HNF1A, C/EBP) were conserved in position. By contrast, we observed positional shifts for ZNF454 and VAX2: in ungulates, the predicted ZNF454 motif overlaps the ATG1 codon, whereas in dog and in both rodents it lies downstream; VAX2 shows the opposite pattern (upstream in dog and rodents, downstream in ungulates) (Supplementary Fig. 11). Given that Carnivora and Euungulata are sister clades within Laurasiatheria, these shifts are consistent with lineage-specific regulatory remodeling on the branch leading to ungulates. Functional validation (e.g., TF ChIP or targeted reporter mutagenesis of the predicted sites) will be required to establish causality for liver regulation of AGXT.

Methods
Genome data and gene identification
Genome assemblies for 685 mammal species were obtained from the National Center for Biotechnology Information (NCBI; https://www.ncbi.nlm.nih.gov/, accessed February 2, 2023). Details of the genome assemblies used in this study can be found in the supplementary table (Supplementary Data 1). To identify the gene encoding AGT, we performed tBLASTn searches using the mouse (Mus musculus) AGT protein sequence (NCBI accession number: NC_000067.7) as a query. Coding sequences for each mammal species were determined using GeneWise50 and were manually verified. Mutations in the 5′ translation start site, stop codons, or frameshifts in the mitochondrial targeting signal (MTS) region were considered indicative of a nonfunctional MTS. The genetic identification results are provided in the supplementary table (Supplementary Data 1). The phylogenetic tree topology used in this study was derived from previous research51–54.

Assessment of diet composition
For all mammals in our study, we obtained published dietary information from the PHYLACINE 1.2.1 database55,56. For each species, we calculated the proportion of animal tissue (vertebrate prey and/or invertebrate prey) in the diet. We classified species with diets of ≥70% animal tissue as carnivores, 70%–30% as omnivores, and ≤30% as herbivores57. Within these categories, we also defined species with diets of ≥90% animal tissue as hypercarnivores, and ≤5% as strict herbivores (see Supplementary Data 1).

Plasmid construction for assessing AGT mitochondrial and peroxisomal targeting efficiency
To assess AGT mitochondrial and peroxisome targeting efficiency, we performed cell-based immunofluorescence assays on natural AGT orthologues as well as corresponding mutant that lacked either the MTS or the PTS1. For these assays, we selected 37 mammal species across 11 orders, representing major branches of all three mammalian subclasses. All focal species were selected on the basis of having an available complete AGXT sequence containing an intact MTS, as well as available published immunoelectron microscopy data18.

To establish normal targeting, complete orthologues containing both the MTS and PTS1 were synthesized and inserted into the multiple cloning site of the pMSCV-puro vector. Next, to assess MTS- and PTS-mediated targeting, we generated constructs containing either the corresponding non-MTS AGT fused to a N-terminal 3×FLAG-tag peptide, or the non-PTS1 AGT fused to a C-terminal 3×FLAG-tag peptide. Oligonucleotide sequences for these experiments are provided in Supplementary Data 3. The 3×FLAG-tag peptide enables confirmation of the subcellular localization of AGT in subsequent experiments using specific antibodies, and was chosen because its small size and hydrophilic properties allow for normal protein folding and biological activity58,59. Both constructs were produced with Phusion Plus DNA Polymerase (Thermo Scientific, USA, Cat#F630S) and inserted into the pMSCV-puro vector.

We also constructed plasmids for establishing AGT co-localization with mitochondria and peroxisomes. Here we transfected our cells with a retroviral vector containing either the mito-DsRed (a mitochondrial marker), so providing stable expression of red fluorescence, or the consensus tripeptide sequence of the PTS1 (SKL) fused to a green fluorescent protein (GFP), so providing stable expression of green fluorescence. Finally, because we could not record from both stable fluorescent markers in the same cells, for establishing co-localization of intact AGT with peroxisomes, we also labelled background peroxisomes in the cell by using a pEGFP-N1 vector (Miao Ling Plasmid, China, Cat#P0133) in which we fused the consensus tripeptide sequence of the PTS1 (SKL) to the GFP. Oligonucleotide sequences for these experiments are provided in Supplementary Data 3.

In comparisons of peroxisomal targeting efficiency across taxa, the results from the AGT of human and African clawed toad (Xenopus laevis) served as positive and negative controls, respectively. The human AGT protein lacks a functional MTS start codon and has been shown to exclusively target the peroxisome27,60, whereas the Xenopus protein exclusively targets the mitochondria61.

In vitro cell culture and transfection
We transiently transfected HeLa cells (CCTCC, China, Cat#GDC0009), which do not naturally express AGT, with plasmids containing full-length AGT sequences. HeLa cells were cultured in Dulbecco’s Modified Eagle’s Medium (Gibco, USA, Cat#C11995500BT) supplemented with 10% fetal bovine serum (FBS; Excell Bio, China, Cat#FSP500) and 1% penicillin/streptomycin (Gibco, USA, Cat#15140122) at 37°C with 5% CO2. To facilitate subsequent experiments, circular slides were pre-treated with Hanks’ balanced salt solution (Monad, China, Cat#14025-092) and used for cell culture. For transient co-transfection of AGT expression constructs and EGFP-SKL plasmid, we used Lipofectamine 2000 (Thermo Fisher Scientific, USA, Cat#11668019) and Opti-MEM medium (Invitrogen, Carlsbad, CA, USA, Cat#51985-034), following the manufacturer’s instructions.

Immunofluorescence staining for assessing MTS- and PTS1-mediated targeting efficiency
At 24 h post-transfection, the culture medium was removed, and cells were fixed with 4% paraformaldehyde (Aladdin, China, Cat#C104188) for 20 min. To enhance antibody permeability, cells were then incubated with 0.1% Triton X-100 (BioFroxx, Germany, Cat#1139) in phosphate-buffered saline (PBS; Cytiva, USA, Cat#SH3025601) for 20 min. After permeabilization, cells were blocked with 10% FBS in PBS at room temperature for 1 h. For the subcellular localization of AGT, the cells were incubated with a primary antibody against AGT (polyclonal, Proteintech, China, Cat#22394-1-AP, 1:200) diluted in PBS containing 10% FBS for 1 h at room temperature. Subsequently, the cells were incubated with a goat anti-rabbit IgG (H+L) cross-adsorbed secondary antibody conjugated with Alexa Fluor® 647 (Invitrogen, USA, Cat#A-21244, 1:800) for 1 h at room temperature. Fluorescence visualization was then performed to determine the subcellular localization of AGT. Localization data for both positive and negative controls were consistent with previous immunoelectron microscopy findings61,62, validating our approach.

To assess MTS-mediated mitochondrial targeting efficiency and PTS1-mediated peroxisomal targeting efficiency, cells were first incubated with anti-FLAG rabbit polyclonal antibody (Proteintech, China, Cat#20543-1-AP, 1:400) for 1 h at room temperature. This was followed by incubation with Cy3-conjugated Affinipure Goat Anti-Rabbit IgG (H+L) (Proteintech, China, Cat#SA00009-2, 1:800) and Alexa Fluor® 647-conjugated goat anti-rabbit IgG (H+L) cross-adsorbed secondary antibody (Thermo Fisher, USA, Cat#A-21244, 1:800). Each incubation step was followed by three washes with PBS. Finally, slices were mounted with anti-fading fluorescent mounting medium (YEASEN, China, Cat#36307ES08) and examined under a confocal microscope (Leica, TCS SP8).

Confocal microscopy and image processing
Confocal microscopy was performed using a Leica TCS SP8 confocal laser scanning microscope equipped with a high-resolution 63× oil immersion objective. Image acquisition and processing were carried out using LAS AF Lite 2.6 software (Leica Microsystems, Wetzlar, Germany). To quantify colocalization in confocal fluorescence images, we employed the EzColocalization plug-in for ImageJ63. For each cell, the perimeter was manually outlined using the area selection tools, and colocalization measurements were performed for individual cells. For each cell, we calculated the mitochondrial and peroxisomal targeting efficiency of AGT, calculated as the percentage of total pixel intensity for AGT that colocalized with, respectively mitochondrial and peroxisomal fluorescence. Colocalization analysis was performed using Mander’s Colocalization Coefficients, applying an automatic threshold to ensure consistency64,65. To ensure reliable mitochondrial or peroxisomal targeting results, this was repeated for 20–25 cells per species and an average taken. A dashed line was drawn across regions of interest using the Straight Line tool in ImageJ, traversing cellular compartments with distinct fluorescence signals. Fluorescence intensity values along the dashed line were extracted using the Plot Profile function in ImageJ.

Molecular evolutionary analysis
We aligned 429 mammal AGXT orthologues in MUSCLE66, after removing pseudogenes and incomplete gene sequences. To characterize differences in selection pressure across the AGT gene, we built and analyzed separate datasets based on the full AGXT, MTS motif, Mature Region without PTS1 motif, and PTS1 motif. For each dataset, we generated Nei-Gojobori estimates of ω (dN/dS ratio) for each pairwise species comparison using the modified method implemented in MEGA735. An ω value <1 indicates purifying selection, ω=1 suggests neutral evolution, and ω >1 implies positive selection. Next, we also obtained independent ω estimates for each branch in the tree using the free-ratio model in PAML 4.967 based on the accepted species topology51–54.

To test for positive selection in lineages that feed on plant tissue, we also conducted branch-site models in PAML 4.967. We used Model A (model=2, NSsites=2, fix_omega=0) with herbivore lineages as the foreground and compared it to the corresponding null model in which the ω >1 class is constrained to ω₂=1 (fix_omega=1, omega=1). Positive selection on herbivore branches was inferred only when this one-sided likelihood ratio test was significant (p<0.05) and ω₂>1 in the alternative model; BEB posteriors for sites in classes 2a/2b were interpreted only under these conditions. All analyses were repeated for Laurasiatheria (239 species), Euarchontoglires (159 species), Afrotheria (10 species), and Metatheria (12 species). Xenarthra was not analyzed due to insufficient data.

To gain insights into the evolutionary history of herbivory in mammals, we also reconstructed ancestral protein sequences of the PTS1 region using the full dataset. Ancestral state inference was conducted using maximum likelihood under the JTT substitution model in PAML 4.9, based on a species tree derived from recent phylogenomic studies51–54. For downstream analyses, we used the inferred ancestral sequences with the highest posterior probabilities. Notably, over 95% of sites in the reconstructed sequences had high confidence (posterior probability >0.95).

Subcellular targeting and diet
We modelled subcellular targeting efficiency (peroxisomal and mitochondrial) of natural and mutant proteins, as quantified from our cell-based immunofluorescence assays, as a function of the proportion of plant tissue in the diet. We applied two approaches that account for statistical non-independence arising from phylogenetic inertia68. First, we ran phylogenetically-controlled Markov chain Monte Carlo generalized linear mixed models33 using the package MCMCglmm33 in Rstudio (v4.4.1). Phylogeny was fitted as a random effect, with the covariance matrix generated in the package ape69. The tree topology and branch lengths were generated using the TimeTree database (http://www.timetree.org/; last accessed April 15, 2025) with manual editing to add missing taxa51–54. The proportion of plant tissue in the diet was fitted as a fixed effect using data obtained from the PHYLACINE 1.2.1 database, as previously described. Our priors took the form of: prior <- list(G=list(G1=list(V=1, nu=0.002)), R=list(V=1, nu=0.002)). The prior distribution for the variance components was assumed to be an inverse-Gamma density, with a small degree of belief (i.e., nu=0.002). The Heidelberg was used to corroborate convergence of the MCMC runs. MCMCglmm was run with 130,000 iterations, after a burn-in of 30,000 iterations. Values from every 10 iterations were saved.

As a second test approach we used Phylogenetic Generalized Least Squares (PGLS) regressions, which test for phylogenetic autocorrelation in the residuals. PGLS allows for more direct modeling of the evolutionary relationships between species by incorporating a phylogenetic tree and estimating Pagel’s lambda (λ), which quantifies phylogenetic signal in the residuals. We ran PGLS in the R package Caper70, and the significance of each predictor was calculated using two-sided t-tests.

RNA-seq analysis for transcription start site usage
To determine variation in transcription start site usage, we analysed transcripts RNA-seq assemblies of liver tissue obtained for 172 mammal species from the NCBI (https://www.ncbi.nlm.nih.gov/, accessed December 16, 2024). Quality control of the assemblies and trimming of low-quality reads were performed using fastp (v0.23.2) and FastQC (v0.12.1, https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) with default settings to generate high-quality cleaned reads (Chen et al., 2018). Reads from each species were aligned to the respective reference genomes using HISAT2 (v2.2.1)71. Coverage of the AGT region was calculated using Samtools (v1.19)72. For species lacking a reference genome, de novo transcriptomes were assembled using Trinity (v2.9.1)73. These Trinity-assembled transcripts were then used to create databases with makeblastdb in BLAST+ v2.12.0, and the assemblies were compared to these databases using tBLASTn. Transcripts covering the upstream translation start site were considered to originate from the upstream transcription start site, while those covering the downstream translation start site were derived from both upstream and downstream transcription start sites. To quantify the usage of the upstream transcription start site, we calculated the ratio of coverage (ATG1/ATG2), where ATG1 refers to the coverage at the upstream translation start site and ATG2 refers to the coverage at the downstream translation start site. A higher ratio indicates a greater presence of longer AGT transcripts originating from the upstream transcription start site. We assessed ATG1/ATG2 usage as a function of diet using the same phylogenetic modelling approaches as described earlier.

ChIP-seq, ATAC-seq, and regulatory motif analysis
To investigate the regulatory basis of alternative AGT promoter usage, we analyzed publicly-available ChIP-sequencing (ChIP-seq) data from normal liver tissue across 13 mammalian species. These datasets were retrieved from the NCBI (https://www.ncbi.nlm.nih.gov/, accessed January 18, 2025). Data processing followed our RNA-seq pipeline, except that sequencing reads were aligned to each species’ reference genome using Bowtie2 (v2.5.4). Identification of enriched regions (peaks) was performed on two biological replicates per species using MACS2 (v2.2.9.1) with default settings and a p-value cutoff of 0.05 (one-sided Poisson test) for narrow peaks74.

We focused on two histone modifications associated with active promoter activity: H3K27ac and H3K4me336. Species were included if they had ChIP-seq data for two of these histone marks, a complete AGXT model, and a functional mitochondrial targeting signal (MTS). Visualisation of the identified peaks in relation to gene annotations and the underlying ChIP-seq signal, was conducted using the Integrated Genomics Viewer (IGV, v2.8.6)75.

To further assess regulatory architecture, we analyzed publicly available assay for transposase-accessible chromatin sequencing (ATAC-seq) data from normal liver tissue across seven mammalian species (NCBI; accessed 8 September 2025). Data were processed following the ChIP-seq pipeline, and chromatin accessibility patterns near AGXT promoters were visualized using IGV.

Finally, we predicted transcription factor binding motifs across the ~2 kb upstream region (including exon 1) in seven focal species with available RNA-seq, ChIP-seq, and ATAC-seq data. Scans were performed using JASPAR 202476 with a relative score threshold of 80%. Motif presence, orientation, and position relative to the AGXT translation start site (ATG) were compared among species.

Luciferase reporter assay
To evaluate the functional consequences of a specific upstream promoter region—identified via ChIP-seq analysis as exhibiting interspecies variation in activity—we employed a dual-luciferase reporter assay in HeGp2 cells (Procell, China, Cat#CL-0103). We selected 19 species that represented a range of subcellular localisation patterns, prioritising those with available ChIP-seq data.

For each species, a ~2 kb DNA fragment upstream of the primary translation start site, including exon 1, was cloned into the pGL3-Basic vector (Miao Ling Plasmid, China, Cat#P0193) to drive firefly luciferase expression. The AGT coding region was not included in the reporter; thus, any AGT triplets in the insert lie in the reporter 5′ UTR and cannot initiate luciferase translation. Reporter plasmids (250 ng) were co-transfected with the pRL-TK Renilla luciferase control plasmid (10 ng, Miao Ling Plasmid, China, Cat#P0372) using Lipofectamine 2000 in Opti-MEM medium, following the manufacturer’s protocol. After 36 h of incubation in medium supplemented with 31.6 mM sodium glyoxylate (Macklin, China, Cat#S923532), luciferase activity was measured using the Dual-Luciferase® Firefly & Renilla Assay Kit (UElandy, China, Cat#F6075M) on a GloMax® 20–20 Luminometer (Promega, USA).

Firefly luciferase activity was normalized to Renilla luciferase activity to calculate relative promoter activity77. Each assay was conducted in triplicate and averaged across replicates.

To test the contribution of the upstream start-site region, we introduced a single defined nucleotide substitution at the AGT ATG1 triplet within the promoter insert (overlap-extension PCR): ATG→GCG (coordinates +1..+3 relative to ATG1; A of ATG1 = +1). This triplet lies within a predicted motif overlapping the start-site region. Oligonucleotide sequences used for this experiment are provided in Supplementary Data 3. Wild-type and mutant constructs were transfected and assayed under identical conditions, with luciferase activity measured in triplicate for each construct.

To test whether the effect of the mutation on promoter activity varied with diet, we fitted a phylogenetic generalized least squares (PGLS) model. The response variable was the log-transformed difference in mean luciferase activity between the mutant and wild-type constructs. The predictor was the proportion of plant material in the species’ diet, treated as a continuous variable.

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

Data availability
All data supporting the findings of this study are available within the article and its supplementary files. The genomic and transcriptomic data used in our manuscript were obtained from National Center for Biotechnology Information (NCBI) database, and the corresponding accession codes have been provided in the Supplementary Data 1. Plasmids and primers used in this study are available from the corresponding authors upon reasonable request. Any additional requests for information can be directed to and will be fulfilled by the corresponding authors. Source data are provided with this paper.

Code availability
R scripts that were used to analyze datasets and make figures are available in the GitHub repository https://github.com/Hcheni0131/Analysis-in-R.git. and archived on Zenodo78.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Here, Huang and colleagues considered the functional evolution of the detoxifying gene AGT in mammals. The manuscript explores an interesting facet of herbivory by interrogating a large number of publicly available datasets and by conducting in vitro experiments. Overall, I am happy to recommend this study for publication. However, I have some questions for the authors.\n1. The term carnivorous needs to be clarified. Some species (e.g., most microbats and some afrotherian species) sometimes eat invertebrates in addition to insects but it is not meat. For example, afrotherians in Fig. 3 are termed ‘Meat’(eaters). Instead of using the term 'Meat' (i.e., diet of vertebrates), why not use the term 'carnivorous diet' to include invertebrate carnivory?\n2. You state that you classified species based on whether their diet is >50% meat or not into carnivores and herbivores. If you, instead of the 50% cut-off, consider an obligate hypercarnivore cut-off (i.e., a diet of at least 70% meat), what does your data look like? Also, it may be helpful to colour hypercarnivores in a different colour in figures or indicate it in other ways (for example, a dotted line at 0.7 on the Fig. 2b,c x-axis).\n3. Table S8 includes 354 SRA records from 172 species (with some having more than one record). It may be useful to show the S.D. and/or S.E.M. in a column to better indicate if there are any outliers.\n4.I do not understand why one of the most striking herbivorous groups among afrotherian mammals, extant hyraxes/elephants/sirenians (Paenungulata), is not discussed. These are a key group of herbivores in most people's minds. I can see in Table S1 that they have a \"functional\" MTS and a PST1 NKL motif. It seems like you did not test any paenungulate AGT in your immunofluorescence assays. Also, in Table S8, you show the expression of AGT in mammals: I gather there were no suitable liver RNA-seq data for any paenungulate. In any case, what is your hypothesis on the importance of AGT functional evolution in afrotherians?\nIt may also be informative to include herbivorous afrotherians in the molecular adaptation analysis (gene selection), perhaps as a supplementary figure, to show that the data hold beyond the 37 mammals studied (which includes the insectivorous Aardvark, Orycteropus afer, an afrotherian).\n5. Consider moving some of the Discussion into the Results to explain the logic of your data better—for example, the putative promoter activity pattern analysis. I found it a bit hard to follow until the Discussion explained it clearly.\n6. Other\n• BLAST, not blast\n• 'n' as in 'n=number' in italics\n• Please provide your code (including for the PGLS analysis) in a repository such as GitHub", "reviewer_2": "The article by Huang et al., provides a detailed molecular analysis of the evolutionary shifts in the intracellular distribution of the liver-specific enzyme alanine:glyoxylate aminotransferase (AGT) as a consequence of diet. AGT plays a crucial role in the detoxification of glyoxylate to glycine preventing the build up of potentially harmful calcium oxalate crystals in the kidney. Over evolutionary time, the adaptation of AGT to changes in diet has been proposed to occur through alterations in its subcellular distribution, through the gain or loss of the N-terminal mitochondrial targeting sequence (MTS). In the present study, Huang et al., propose that increased efficiency of the C-terminal peroxisomal targeting sequence (PTS) plays an important role in driving the evolution of peroxisomal AGT localisation in herbivores.\nThis study provides a wealth of new data on the molecular adaptation of AGT to changes in dietary selection pressure through the analysis of many new species across multiple families using in silico tools, in vitro validation assays and bioinformatic analysis of epigenetic sequencing datasets. These analyses provide a richer and broader understanding of AGT subcellular distribution linked to diet than previous studies. However, the manuscript in its present form requires some changes before it may be suitable for publication.\nComments\nLine 70: “As with many proteins, AGT’s subcellular localization….” This phrase suggests that multiple proteins possess both an MTS and a PTS sequence, such that they can be dually targeted to both organelles. This should be clarified to indicate how often this is found in mammalian cells. Or otherwise remove the first four words.\nSupplementary Figures S2, S3, & S4: The resolution of the confocal images is low and it is very hard to clearly see the AGT expression, especially when it is localised to the peroxisomes. Please increase image quality and brightness/contrast levels. I suggest that you consider showing the single channel AGT images in greyscale (rather than magenta) to increase the chances of seeing the punctate distribution of AGT in peroxisomes. The main Fig 2 panels are better quality, and it is easier to see the AGT expression.\nFigure 2f-m: These data need to be more thoroughly describes in the results text. There is no mention in the text of P. cinereus in the context of these experiments (from line 157), and as such the results are not explained to the reader in sufficient detail.\nLine 166: Change text “mitochondrial targeting” to “peroxisomal targeting”.\nFigure 2b: Spelling mistake on the Y-axis, it is missing the first letter t in “targeting”.\nSupplementary Figure 5. I think the heading on the diagram should say “Mitochondrial targeting efficiency”, instead of “Peroxisomal targeting efficiency”.\nLine 265: The statement that the epigenetic mark H3K4me1 is a marker for inactive promoters is confusing. Typically, H3K4me1 is used as a specific marker for active or primed enhancers. It is not really a marker for “inactive promoters”. As such, the inclusion of H3K4me1 in the analysis (Figure 3d) is not informative when looking at the AGXT (note correct gene name) promoter, nor is it warranted in this section and should be removed.\nLine 270: You mention HNF1A/C/EBP binding but provide no context or information on what this is or why it might be informative. The manuscript would be enhanced if you showed ChIP-seq data for this transcription factor binding at the AGXT promoter (if such datasets for different species exist). However, I appreciate that these data are unlikely to be available, so an alternative approach would be to show the presence/absence of the HNF1 motif(s) in this region across species.\nFigure 2d: The layout of ChIP-seq data for the histone promoter marks is very hard to follow. It might be more informative to select only a few representative species with herbivorous vs carnivorous diets and show a more detailed view of the AGXT gene locus (focussing on the promoter region) but also including an overlay of the RNA-seq profile data. This might provide a qualitative view of the promoter usage using the gene transcription RNAseq data and the relative enrichment of the histone marks showing which promoters are active. Are there any liver ATAC-seq datasets available for AGXT in different species? These data would complement the histone marks in showing which promoters were active.\nLine 273: It is unclear what nucleotides are being mutated in the AGXT gene and what particular transcription factor binding site is being targeted. I am rather confused by the terminology since you describe targeting a methionine residue in the first codon of a predicted TF binding site. Since TFs bind the genomic DNA directly, the presence of a methionine residue is irrelevant in this context. More details of the mutagenesis are needed here and in the methods section.\nSupplementary Figure S6 (line 55): The correct name of the cells is HepG2.\nLine 444: Supplementary Table S1 (not S2).\nLine 614: The correct name of the cells is HepG2."}, "author_response": "Responses to Reviewers’s Comments:\nReviewer #1 (Remarks to the Author):\nHere, Huang and colleagues considered the functional evolution of the detoxifying gene AGT\nin mammals. The manuscript explores an interesting facet of herbivory by interrogating a\nlarge number of publicly available datasets and by conducting in vitro experiments. Overall, I\nam happy to recommend this study for publication. However, I have some questions for the\nauthors.\nComment 1.1\nThe term carnivorous needs to be clarified. Some species (e.g., most microbats and some\nafrotherian species) sometimes eat invertebrates in addition to insects but it is not meat. For\nexample, afrotherians in Fig. 3 are termed ‘Meat’(eaters). Instead of using the term 'Meat' (i.e.,\ndiet of vertebrates), why not use the term 'carnivorous diet' to include invertebrate carnivory?\nResponse to 1.1\nWe agree with this comment. We have revised all instances of \"Meat\" in figures, figure\nlegends and text to \"Animal tissue\" or \"Animal-based diet\" as appropriate, and clarified that\nthis includes invertebrate-eating species (Methods now reads “For each species, we\ncalculated the proportion of animal tissue (vertebrate prey and/or invertebrate prey”).\nSimilarly, we revised the term “Plant tissue” to the term “Plant tissue” in all figures.\nComment 1.2\nYou state that you classified species based on whether their diet is >50% meat or not into\ncarnivores and herbivores. If you, instead of the 50% cut-off, consider an obligate\nhypercarnivore cut-off (i.e., a diet of at least 70% meat), what does your data look like? Also,\nit may be helpful to colour hypercarnivores in a different colour in figures or indicate it in\nother ways (for example, a dotted line at 0.7 on the Fig. 2b,c x-axis).\nResponse to 1.2\nThanks for this suggestion. In our original manuscript, the classification of species as\ncarnivores based on whether their diets comprised >50% animal tissue was for display\npurposes only (i.e. used in the figures). In all our actual analyses, carnivory was modelled as a\ncontinuous variable (proportion of animal matter in diet) using information from the\npublished PHYLACINE 1.2.1 database. Because the phylogenetic models were significant\n(diet explained variation in AGT targeting), we have not repeated these with categorical diets.\nHowever, after reflecting on Reviewer 1’s comments, in our revised figures we have now\nused a heat map to represent herbivory/carnivory diet as a continuum, which is more accurate\nand corresponds better to the analyses.\nWe also agree with the reviewer that showing hypercarnivores is informative, and in our\nrevision we now include cut-offs for carnivores, herbivores, hypercarnivores, and strict\nherbivores. In doing so we have replaced the original cut-offs of ≥50% and ≤50% dietary\nanimal tissue for carnivores and herbivores, and now instead use ≥70% and ≤30% following\nAtwood et al. (2020). We now also describe species with intermediate diets as omnivores,\nspecies with diets of ≥90% animal tissue as hypercarnivores, and ≤5% as strict herbivores\n(see Table S1). We have now added these cut-offs on Fig. 2b and c, as suggested, and we\nhave also checked that statements in the Results and Discussion are consistent with these\ncut-offs.\nComment 1.3\nTable S8 includes 354 SRA records from 172 species (with some having more than one\nrecord). It may be useful to show the S.D. and/or S.E.M. in a column to better indicate if there\nare any outliers.\nResponse to 1.3\nWe have now added the standard error in a new column in Table S9. Additionally, we now\nshow the standard error bars in Fig 3a, with a new sentence added in the figure legend:\nStandard error bars are shown for species with multiple biological replicates.\nComment 1.4\nI do not understand why one of the most striking herbivorous groups among afrotherian\nmammals, extant hyraxes/elephants/sirenians (Paenungulata), is not discussed. These are a\nkey group of herbivores in most people's minds. I can see in Table S1 that they have a\n\"functional\" MTS and a PST1 NKL motif. It seems like you did not test any paenungulate\nAGT in your immunofluorescence assays. Also, in Table S8, you show the expression of\nAGT in mammals: I gather there were no suitable liver RNA-seq data for any paenungulate.\nIn any case, what is your hypothesis on the importance of AGT functional evolution in\nafrotherians?\nIt may also be informative to include herbivorous afrotherians in the molecular adaptation\nanalysis (gene selection), perhaps as a supplementary figure, to show that the data hold\nbeyond the 37 mammals studied (which includes the insectivorous Aardvark, Orycteropus\nafer, an afrotherian).\nResponse to 1.4\nThanks for these comments. As mentioned in the Methods, we only performed\nimmunofluorescence assays on species for which immunoelectron microscopy data were\nalready published1, thus allowing us to compare and validate observed patterns of localization\nfor wildtype AGT. Unfortunately, no such published data were available for any members of\nthe Paenungulata, and the only two species of afrotherian in our paper were either\ninsectivorous (aardvark) or omnivorous (tenrec). We also confirm that no liver RNA-seq data\nwere available for any herbivorous afrotherians.\nWe agree with Reviewer 1 that the taxa included in our tests of molecular adaptation should\nbe expanded from the 37 focal mammals to all taxa for which the complete gene sequence of\nAGT is available. In our revision we now perform separate analyses of molecular evolution\nfor AGXT gene sequences for each superorder in Eutheria\n(Laurasiatheria/Euarchontoglires/Xenarthra/Afrotheria) as well as Metatheria and\nMonotremata. For all mammals, as well as for each clade, we also now include explicit tests\nfor positive selection in branches of herbivores versus non-herbivores.\nOur improved Methods section reads as follows:\n‘We aligned 429 mammal AGXT orthologues in MUSCLE (Edgar 2004), after removing\npseudogenes and incomplete gene sequences. To characterise differences in selection\npressure across the AGT gene, we built and analyzed separate datasets based on the full\nAGXT gene, MTS motif, Mature Region without PTS1 motif, and PTS1 motif. For each\ndataset, we generated Nei-Gojobori estimates of ω (d/d ratio) for each pairwise species\nN S\ncomparison using the modified method implemented in MEGA72. An ω value < 1 indicates\npurifying selection, ω = 1 suggests neutral evolution, and ω > 1 implies positive selection.\nNext, we also obtained independent ω estimates for each branch in the tree using the\nfree-ratio model in PAML 4.93 based on the accepted species topology4-7 (Alvarez-Carretero\net al. 2022; Deakin & O'Neill 2020; Foley et al. 2023; Hao et al. 2024).\nTo test for positive selection in lineages that feed on plant tissue, we also conducted\nbranch-site models in PAML 4.93. We used Model A (model = 2, NSsites = 2, fix_omega = 0)\nwith herbivore lineages as the foreground and compared it to the corresponding null model in\nwhich the ω>1 class is constrained to ω₂ = 1 (fix_omega = 1, omega = 1). Positive selection\non herbivore branches was inferred only when this likelihood ratio test was significant (p <\n0.05) and ω₂>1 in the alternative model; BEB posteriors for sites in classes 2a/2b were\ninterpreted only under these conditions. All analyses were repeated for Laurasiatheria (239\nspecies), Euarchontoglires (159 species), Afrotheria (10 species), and Metatheria (12 species).\nXenarthra was not analyzed due to insufficient data.\nTo gain insights into the evolutionary history of herbivory in mammals, we also reconstructed\nancestral protein sequences of the PTS1 region using the full dataset. Ancestral state\ninference was conducted using maximum likelihood under the JTT substitution model in\nPAML 4.9, based on a species tree. For downstream analyses, we used the inferred ancestral\nsequences with the highest posterior probabilities. Notably, >95% of sites in the\nreconstructed sequences had high confidence (posterior probability > 0.95).’\nThe results of our tests for positive selection are presented in Figure S7 and Table S8, and we\nhave added the following sentences to the Results:\n‘Tests of molecular adaptation\nTo investigate whether positive selection has acted on the AGXT gene—particularly within\nthe MTS and PTS1 regions that govern subcellular localization—we analyzed separate\ndatasets corresponding to the MTS, PTS1, and the mature region excluding PTS1 across all\nmammals as well within major superorders. For each dataset, we estimated rates of\nsynonymous and nonsynonymous substitutions (d and d , respectively) and the d /d ratio ω\nS N N S\nfor all branches on the tree under the free ratio model.\nAcross all mammals we recorded ω values >1 in 642 out of 854 branches for PTS1 (Fig. S7),\ncompared to 221 branches for the MTS region, and 56 branches for the mature region\nwithout PTS1. Pairwise ω estimates using the modified Nei-Gojobori method2 further\nsupported these results: 62.38% of pairwise comparisons in the PTS1 region showed d > d ,\nN S\ncompared to 12.90% in the MTS region, and none in the mature region without PTS1 (Fig.\nS7). These findings suggest that the PTS1 region of AGXT gene is subject to more positive\nselection than both the MTS and the rest of the mature protein sequence. These trends were\nalso seen when analyzing separate superorders with the PTS1 region showing the strongest\nselection pressure compared to the MTS and the rest of the mature protein sequence in all\ngroups except Monotremata (Fig. S7).\nBranch-site tests with herbivore lineages as the foreground revealed (Fig. S8) no evidence\nfor positive selection when applied across mammals as a whole (ω₂ = 1.0; LRT p = 0.92,\nmodel A in Table S8), nor within Afrotheria or Metatheria (ω₂ ≈ 1.0–1.3; LRT p ≥ 0.38,\nmodel G/I in Table S8). In contrast, analyses restricted to Laurasiatheria and\nEuarchontoglires detected a strongly supported class of codons with ω>1 on herbivore\nbranches (ω₂ ≈ 33 and 32 respectively; LRT p = 0.001 in both cases, model C/E in Table S8).\nThe inferred proportion of such sites was extremely small (p₂a + p₂b ≈ 0, model C/E in Table\nS8), indicating that adaptive changes are highly localised. BEB analysis identified a handful\nof candidate codons in these two clades, including 215I and 286T in Laurasiatheria (PP ≥\n0.95, model C in Table S8), and 20V and 286T in Euarchontoglires (PP > 0.8, model E in\nTable S8), whereas no codons had supported ω >1 in Afrotheria or Metatheria.’\nComment 1.5\nConsider moving some of the Discussion into the Results to explain the logic of your data\nbetter—for example, the putative promoter activity pattern analysis. I found it a bit hard to\nfollow until the Discussion explained it clearly.\nResponse to 1.5\nApologies if some of the logic was hard to follow. Reviewer 2 also asked for more clarity\nregarding the results of the promoter activity analyses and requested that we make a number\nof changes (including that we remove some material). Please see our response to Reviewer 2\n(Response 2.9) for more detail, and we hope the new wording is simpler and easier to follow.\nComment 1.6\n• BLAST, not blast\nNow changed to all caps through the manuscript (e.g. TBLASTN, TBLAST etc)\n• 'n' as in 'n=number' in italics\nChanged throughout the manuscript.\n• Please provide your code (including for the PGLS analysis) in a repository such as GitHub\nCodes now made available on GitHub (https://github.com/Hcheni0131/Analysis-in-R.git).\nAccordingly, we have now added a section to the manuscript:\nCODE AVAILABILITY\nR scripts that were used to analyze datasets and make figures are available in the GitHub\nrepository https://github.com/Hcheni0131/Analysis-in-R.git.\nReviewer #2 (Remarks to the Author):\nThe article by Huang et al., provides a detailed molecular analysis of the evolutionary shifts in\nthe intracellular distribution of the liver-specific enzyme alanine:glyoxylate aminotransferase\n(AGT) as a consequence of diet. AGT plays a crucial role in the detoxification of glyoxylate\nto glycine, preventing the build up of potentially harmful calcium oxalate crystals in the\nkidney. Over evolutionary time, the adaptation of AGT to changes in diet has been proposed\nto occur through alterations in its subcellular distribution, through the gain or loss of the\nN-terminal mitochondrial targeting sequence (MTS). In the present study, Huang et al.,\npropose that increased efficiency of the C-terminal peroxisomal targeting sequence (PTS)\nplays an important role in driving the evolution of peroxisomal AGT localisation in\nherbivores.\nThis study provides a wealth of new data on the molecular adaptation of AGT to changes in\ndietary selection pressure through the analysis of many new species across multiple families\nusing in silico tools, in vitro validation assays and bioinformatic analysis of epigenetic\nsequencing datasets. These analyses provide a richer and broader understanding of AGT\nsubcellular distribution linked to diet than previous studies. However, the manuscript in its\npresent form requires some changes before it may be suitable for publication.\nComment 2.1\nLine 70: “As with many proteins, AGT’s subcellular localization….” This phrase suggests\nthat multiple proteins possess both an MTS and a PTS sequence, such that they can be dually\ntargeted to both organelles. This should be clarified to indicate how often this is found in\nmammalian cells. Or otherwise remove the first four words.\nResponse to 2.1\nWe accept that this opening clause implies that dual targeting is common in proteins, whereas\nit seems to be rare. We have therefore removed these four words, as recommended.\nComment 2.2\nSupplementary Figures S2, S3, & S4: The resolution of the confocal images is low and it is\nvery hard to clearly see the AGT expression, especially when it is localised to the\nperoxisomes. Please increase image quality and brightness/contrast levels. I suggest that you\nconsider showing the single channel AGT images in greyscale (rather than magenta) to\nincrease the chances of seeing the punctate distribution of AGT in peroxisomes. The main Fig\n2 panels are better quality, and it is easier to see the AGT expression.\nResponse to 2.2\nAs suggested, we have increased image quality and brightness levels in the confocal images\nin Figs. S3, S4 and S5. We feel that this has made the patterns of AGT expression much\nclearer, and so we have retained magenta for the single channel AGT images.\nComment 2.3\nFigure 2f-m: These data need to be more thoroughly described in the results text. There is no\nmention in the text of P. cinereus in the context of these experiments (from line 157), and as\nsuch the results are not explained to the reader in sufficient detail.\nResponse to 2.3\nWe have now clarified in the legend of Fig 2 that P. cinereus and R. ferrumequinum are\nincluded as examples of species that show strongly contrasting impacts of PTS1 removal:\n‘Panels f-g and l-m are confocal images showing contrasting patterns of AGT peroxisomal\nlocalization in the koala (P. cinereus) and greater horseshoe bat (R. ferrumequinum),\nrespectively. For each species, localization is shown for AGT with and without the PTS1 (left\nand right, respectively), revealing a strong effect of PTS1 removal in the former species and\nnegligible effect in the latter’.\nSimilarly, we have also described these findings in the Results, as follows: ‘In contrast,\ncarnivorous mammals maintained low peroxisomal targeting efficiencies, with the greater\nhorseshoe bats showing almost no change (3.71%) in efficiency (Fig. 2a, Fig. S4, and Table\nS6). Closer examination of these strongly contrasting species showed that, following removal\nof PTS1, the peak intensity of AGT in koalas no longer overlapped with that of peroxisomes\n(Fig.2 g/j), whereas AGT in the greater horseshoe bat retained a wildtype condition of\nmitochondrial localization (Fig.2 k/m)’.\nComment 2.4\nLine 166: Change text “mitochondrial targeting” to “peroxisomal targeting”.\nResponse to 2.4\nNow corrected.\nComment 2.5\nFigure 2b: Spelling mistake on the Y-axis, it is missing the first letter t in “targeting”.\nResponse to 2.5\nNow corrected.\nComment 2.6\nSupplementary Figure 5. I think the heading on the diagram should say “Mitochondrial\ntargeting efficiency”, instead of “Peroxisomal targeting efficiency”.\nResponse to 2.6\nYes, thanks for spotting that. Now corrected.\nComment 2.7\nLine 265: The statement that the epigenetic mark H3K4me1 is a marker for inactive\npromoters is confusing. Typically, H3K4me1 is used as a specific marker for active or primed\nenhancers. It is not really a marker for “inactive promoters”. As such, the inclusion of\nH3K4me1 in the analysis (Figure 3d) is not informative when looking at the AGXT (note\ncorrect gene name) promoter, nor is it warranted in this section and should be removed.\nResponse to 2.7\nAs suggested, we have now removed the epigenetic mark H3K4me1, and we corrected the\ngene name from AGT to AGXT throughout the manuscript.\nComment 2.8\nLine 270: You mention HNF1A/C/EBP binding but provide no context or information on\nwhat this is or why it might be informative. The manuscript would be enhanced if you showed\nChIP-seq data for this transcription factor binding at the AGXT promoter (if such datasets for\ndifferent species exist). However, I appreciate that these data are unlikely to be available, so\nan alternative approach would be to show the presence/absence of the HNF1 motif(s) in this\nregion across species.\nResponse to 2.8\nWe agree that further context was needed to clarify why HNF1A and C/EBP were mentioned\nin relation to AGXT promoter regulation. Both are well-known liver-specific transcription\nfactors implicated in the regulation of metabolic genes, including AGXT in humans.\nUnfortunately, ChIP-seq data for these transcription factors are only available for mouse liver\ntissue, and therefore could not be extended across our comparative dataset.\nAs an alternative, in our revised paper, we have used the JASPAR 2024 database8 to predict\ntranscription factor binding motifs across the AGXT promoter region in seven species species\nwith RNA-seq, ChIP-seq, and ATAC-seq data. While most transcription factor binding motifs\n(including HNF1A and C/EBP) were conserved across these species, we observed notable\ndifferences in the location of ZNF454 and VAX2 motifs in the dog and both rodents\ncompared to the ungulate clade. Specifically, ZNF454 is predicted to bind directly on top of\nthe AGXT translation start site (ATG) in ungulates, while VAX2 shows the opposite pattern,\nbinding upstream of ATG. Given that Carnivora and Euungulata are sister clades in\nLaurasiatheria, this pattern is consistent with evolutionary shifts on the branch leading to\nungulates. While these observations suggest that diet-specific differences in transcription\nfactor binding may influence AGXT expression, further experimental validation (e.g.,\nChIP-seq or functional assays) would be needed to confirm their roles in liver regulation.\nThese new results are displayed in Fig. S11 and are shown below.\nComment 2.9\nFigure 2d: The layout of ChIP-seq data for the histone promoter marks is very hard to follow.\nIt might be more informative to select only a few representative species with herbivorous vs\ncarnivorous diets and show a more detailed view of the AGXT gene locus (focussing on the\npromoter region) but also including an overlay of the RNA-seq profile data. This might\nprovide a qualitative view of the promoter usage using the gene transcription RNAseq data\nand the relative enrichment of the histone marks showing which promoters are active. Are\nthere any liver ATAC-seq datasets available for AGXT in different species? These data would\ncomplement the histone marks in showing which promoters were active.\nResponse to 2.9\nThanks for these helpful suggestions. As recommended, we have now modified Figure 2d to\nfocus on the seven species for which we were able to obtain ATAC-seq datasets from liver\ntissue. We also now display readouts for RNA-seq, ChIP-seq (H3K27ac and H3K4me3) and\nthe ATAC-seq. The ChIP-seq data for the larger species dataset has been moved to Fig. S9.\nTo address the comments 2.7, 2.8 and 2.9, we have made changes to the parts of the Methods,\nResults and Discussion, as follows.\nMethods (Lines 701-731)\nChIP-seq, ATAC-seq, and Regulatory Motif Analysis\nTo investigate the regulatory basis of alternative AGXT promoter usage, we analyzed\npublicly-available ChIP-sequencing (ChIP-seq) data from normal liver tissue across 18\nmammalian species. These datasets were retrieved from the National Center for\nBiotechnology Information (NCBI; https://www.ncbi.nlm.nih.gov/, accessed January 18,\n2025). Data processing followed our RNA-seq pipeline, except that sequencing reads were\naligned to each species’ reference genome using Bowtie2 (v2.5.4). Identification of enriched\nregions (peaks) was performed on two biological replicates per species using MACS2\n(v2.2.9.1) with default settings and a p-value cutoff of 0.05 for narrow peaks (Zhang et al.\n2008).\nWe focused on two histone modifications associated with active promoter activity: H3K27ac\nand H3K4me39,10. Species were included if they had ChIP-seq data for at least one of these\nhistone marks, a complete AGXT gene model, and a functional mitochondrial targeting signal\n(MTS). Visualisation of peak regions in relation to gene annotations and ChIP-seq signal was\nconducted using the Integrated Genomics Viewer (IGV, v2.8.6)11.\nTo further assess regulatory architecture, we analyzed publicly available assay for\ntransposase-accessible chromatin sequencing (ATAC-seq) data from normal liver tissue\nacross seven mammalian species (NCBI; accessed 8 September 2025). Data were processed\nfollowing the ChIP-seq pipeline, and chromatin accessibility patterns near AGXT promoters\nwere visualized using IGV.\nFinally, we predicted transcription factor binding motifs across the ~2 kb upstream region\n(including exon 1) in seven focal species with available RNA-seq, ChIP-seq, and ATAC-seq\ndata. Scans were performed using JASPAR 20248 with a relative score threshold of 80%.\nMotif presence, orientation, and position relative to the AGXT translation start site (ATG)\nwere compared among species.\nResults (Lines 307-361)\nVariation in promoter activity across species\nWe hypothesised that herbivory is associated with reduced usage of the upstream AGXT\npromoter (ATG1) and compensatory activation of a downstream start region, which should\nmanifest as weaker upstream promoter marks/accessibility and lower upstream promoter\nactivity. To probe the regulatory basis of the start-site shift, we examined liver ChIP-seq\nprofiles for active promoter marks (H3K4me3, H3K27ac) across 13 species (Fig. 3d, Fig. S9\nand Table S10). In multiple herbivores, enrichment was weaker upstream of ATG1 and\ncomparatively stronger near the downstream start region, whereas dog (Carnivora) showed\nextended upstream signal—patterns consistent with reduced upstream promoter activity in\nherbivores and greater upstream activity in some non-herbivores. Consistent with these\nprofiles, RNA-seq coverage over the AGXT start-site region was higher in the dog than in the\nherbivores within this subset (Fig. 3d).\nWe then assessed chromatin accessibility using liver ATAC-seq (subset of species in Fig. 3d,\nTable 11). Herbivores generally showed lower accessibility upstream of ATG1 with more\nopen chromatin nearer the downstream start region, mirroring the ChIP-seq profiles, while\nthe dog showed accessible chromatin extending upstream of ATG1. Taken together,\nconcordant shifts in active promoter marks, chromatin accessibility, and subset RNA-seq\ncoverage support a diet-associated reduction in upstream promoter activity in herbivores,\nproviding a mechanistic link to the ATG1/ATG2 usage patterns described above.\nTo test whether upstream promoter sequence contributes to these differences, we used\nalanine-scanning mutagenesis, specifically targeting a conserved methionine residue at the\nfirst codon of a predicted transcription factor binding site. The effect of this mutation on AGT\npromoter activity was then quantified using dual-luciferase reporter assays across 19\nmammalian species. The selection of these species was informed by prior\nimmunofluorescence colocalization data, the availability of complete AGT gene sequences,\nand the presence of a functional mitochondrial targeting sequence (MTS). Across mammals,\nthere was no overall association between diet and the magnitude of difference in luciferase\nactivity between mutant and corresponding wildtype binding sites (p = 0.16, Fig. S10, Table\nS5 and S12). Within bats, however, we recorded lower impacts of mutagenesis on promoter\nactivity in the insectivorous species Rhinolophus ferrumequinum and Myotis myotis, and in\nthe blood-feeding Desmodus rotundus, than in plant-feeding bats (Fig. S10). Striking\nexceptions were also seen, notably in the donkey (Equus asinus) in which the mutant\nconstruct displayed a strong increase in promoter activity.\nFinally, we asked whether transcription factor (TF) binding architecture differs among\nlineages. Using motif prediction in the upstream region for the species with matched\nRNA-seq/ChIP-seq/ATAC-seq, canonical liver TF motifs (e.g., HNF1A, C/EBP) were\nconserved in position. By contrast, we observed positional shifts for ZNF454 and VAX2: in\nungulates, the predicted ZNF454 motif overlaps the ATG1 codon, whereas in dog and in both\nrodents it lies downstream; VAX2 shows the opposite pattern (upstream in dog and rodents,\ndownstream in ungulates) (Fig. S11). Given that Carnivora and Euungulata are sister clades\nwithin Laurasiatheria, these shifts are consistent with lineage-specific regulatory remodeling\non the branch leading to ungulates. Functional validation (e.g., TF ChIP or targeted reporter\nmutagenesis of the predicted sites) will be required to establish causality for liver regulation\nof AGXT.\nDiscussion (Lines 453-469)\nRegulatory differences in transcription start site usage were further supported by histone\nmodification patterns and chromatin accessibility. Across the species subset with epigenomic\ndata, active promoter marks (H3K27ac and H3K4me3) extended further upstream of the\nupstream start region (ATG1) in non-herbivores such as dog, whereas in herbivores\nenrichment was comparatively concentrated nearer the downstream start region. This pattern\nis consistent with the presence of an extended upstream promoter region in some\nnon-herbivores, potentially reflecting divergent regulatory architecture associated with\ndietary specialization. Although functional validation via luciferase assays revealed no clear\nassociation between promoter activity and diet across mammals, we observed that editing this\nthe conserved sequence around the upstream start site significantly reduced AGT promoter\nactivity in some species, including in three divergent bats that appear to have evolved similar\npatterns of promoter regulation. Together, these observations indicate that shifts in\ntranscriptional architecture can complement changes in targeting signals, with clade-specific\nsolutions.\nComment 2.10\nLine 273: It is unclear what nucleotides are being mutated in the AGXT gene and what\nparticular transcription factor binding site is being targeted. I am rather confused by the\nterminology since you describe targeting a methionine residue in the first codon of a predicted\nTF binding site. Since TFs bind the genomic DNA directly, the presence of a methionine\nresidue is irrelevant in this context. More details of the mutagenesis are needed here and in\nthe methods section.\nResponse to 2.10\nWe agree our wording was confusing. In the luciferase reporter we mutated nucleotides, not\nan amino acid. Specifically, we introduced a single codon substitution at the AGXT upstream\nstart codon (ATG1) within a predicted motif that overlaps the ATG: ATG→GCG (Met→Ala\nat the codon level). The AGXT coding sequence was not present in the reporter; the insert\ncomprised ~2 kb upstream plus exon 1 only, cloned upstream of the firefly luciferase ORF, so\nthis triplet resides in the 5′ UTR of the reporter transcript and cannot serve as a start codon for\nluciferase. We have revised the Methods to specify the exact nucleotide change, positioning\nrelative to ATG1, the motif name, and primer design; we have removed protein-level\nlanguage. We also clarify our rationale for including exon 1 (to capture promoter/TSS context\nobserved in ChIP/ATAC/RNA-seq).\nThe revised wording in the Methods reads:\n‘To test the contribution of the upstream start-site region, we introduced a single defined\nnucleotide substitution at the AGXT ATG1 triplet within the promoter insert\n(overlap-extension PCR): ATG→GCG (coordinates +1..+3 relative to ATG1; A of ATG1 =\n+1). This triplet lies within a predicted motif overlapping the start-site region. Wild-type and\nmutant constructs were transfected and assayed under identical conditions, with luciferase\nactivity measured in triplicate for each construct.’\nThe revised wording in the results reads:\n‘To test whether upstream promoter sequence contributes to these differences, we edited the\nupstream start codon (ATG1) within the promoter fragment cloned upstream of luciferase\n(single base-triplet substitution ATG→GCG at ATG1; +1..+3 relative to ATG1). The effect of\nthis substitution on promoter activity was then quantified using dual-luciferase reporter\nassays across 19 mammalian species—selected for their immunofluorescence colocalization\ndata, available complete AGXT gene sequences, and functional mitochondrial targeting\nsequence (MTS). Across mammals, there was no overall association between diet and the\nmagnitude of difference in luciferase activity between ATG1-edited and corresponding\nwild-type constructs (p = 0.16, Fig. S10, Table S5 and S12). Within bats, however, we\nrecorded lower impacts of the ATG1 substitution on promoter activity in the insectivorous\nspecies Rhinolophus ferrumequinum and Myotis myotis, and in the blood-feeding Desmodus\nrotundus, than in plant-feeding bats (Fig. S10). Striking exceptions were also seen, notably in\nthe donkey (Equus asinus) in which the mutant construct displayed a strong increase in\npromoter activity.’\nComment 2.11\nSupplementary Figure S6 (line 55): The correct name of the cells is HepG2.\nResponse to 2.11\nNow corrected.\nComment 2.12\nLine 444: Supplementary Table S1 (not S2).\nResponse to 2.12\nNow corrected.\nComment 2.13\nLine 614: The correct name of the cells is HepG2.\nResponse to 2.13\nNow corrected.\nLiterature cited in response letter:\n1. Birdsey GM, Lewin J, Holbrook JD, Simpson VR, Cunningham AA, Danpure CJ. A\ncomparative analysis of the evolutionary relationship between diet and enzyme\ntargeting in bats, marsupials and other mammals. Proc. Biol. Sci. 272, 833-840\n(2005).\n2. Zhang JZ, Rosenberg HF, Nei M. Positive Darwinian selection after gene duplication\nin primate ribonuclease genes. Proc. Natl Acad. Sci. USA95, 3708-3713 (1998).\n3. Yang ZH. PAML 4: Phylogenetic analysis by maximum likelihood. Mol. Biol. Evol.\n24, 1586-1591 (2007).\n4. Alvarez-Carretero S, et al. A species-level timeline of mammal evolution integrating\nphylogenomic data. Nature602, 263-267 (2022).\n5. Deakin JE, O'Neill RJ. Evolution of Marsupial genomes. In: Annual Review of\nAnimal Biosciences, Vol 8, 2020 (eds Lewin HA, Roberts RM) (2020).\n6. Foley NM, et al. A genomic timescale for placental mammal evolution. Science 380,\neabl8189 (2023).\n7. Hao XY, Lu Q, Zhao HB. A molecular phylogeny for all 21 families within\nChiroptera (bats). Integr. Zool.19, 989-998 (2024).\n8. Rauluseviciute I, et al. JASPAR 2024: 20th anniversary of the open-access database\nof transcription factor binding profiles. Nucleic Acids Res.52, D174-D182 (2023).\n9. Shlyueva D, Stampfel G, Stark A. Transcriptional enhancers: from properties to\ngenome-wide predictions. Nat. Rev. Genet.15, 272-286 (2014).\n10. Li MS, et al. Core transcription regulatory circuitry orchestrates corneal epithelial\nhomeostasis. Nat. Commun.12, 240 (2021).\n11. Robinson JT, et al. Integrative genomics viewer. Nat. Biotechnol.29, 24-26 (2011)."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have addressed my comments and have significantly improved the manuscript text and layout.\nI still have some comments/suggestions that may further improve their manuscript.\n• Lines 79-80: \"Moreover, in some species with intact MTS—such as the domestic horse (Equus ferus) and olive baboon (Papio anubis)—AGT predominantly targets peroxisomes\"\n... consider clarifying here: e.g. *herbivorous* domestic horse ... *omnivorous* olive baboon\n• Table S1: typo \"Speceis Name\" ... Also consider adding the common name of each species here and aligning each cell to the left to make the spreadsheet easier to read\n• SI Table legends (I think S2, S3, S6, S7): I do not like the term \"in 37 experimental mammals.\" This wording suggests you performed in vivo experiments on these, including giant pandas (Ailuropoda melanoleuca) and brown bears (Ursus arctos) – clearly not the case.\n• I think the naming of BLAST is still not correct. Should be tBLASTn (e.g., see line 105), instead of TBLASTN, etc\n• I think it is confusing to say \"AGXT gene(s)\". The gene is AGXT and the protein is AGT, right? Perhaps \"AGTX gene\" is ingrained in the literature, but I would ensure that the Table/Figure legends and MS text are in line with the correct nomenclature.\n• line 118: perhaps specify: \"three hypercarnivores (e.g. Iberian mole, Talpa occidentalis)\" => \"three hypercarnivores (species with a diet comprising >70% animal tissue; e.g. the Iberian mole, Talpa occidentalis)\"\n• lines 207-208: \"with the most marked decreases seen in herbivorous mammals, ranging from 8.96% in olive baboons to 73.16% in\" ... but the olive baboon is omnivorous, right? Your data suggest a 50/50 between plant/animal tissue in its diet (Table S1). Perhaps say this (and reverse the order since you focus on herbivory): \"... ranging from 73.16% in the obligate herbivorous koalas to 8.96% in omnivorous olive baboons\"?\n• On the lack of selection signal in Afroheria and Metatheria, perhaps you could comment on when herbivory is said to have occurred in each group of interest in the Discussion? Afrotheria I assume ~60-70 Mya; Metatheria, not sure, but surely <70 Mya and around the same time as herbivorous ancestor of sea cows/elephants/hyraxes. So, these herbivores have been around a lot longer than most other mammal groups where herbivory evolved (ruminants and, of course, primates).\n• lines 447-448: \"we also found that AGT in herbivores tends to be transcribed from downstream transcription start sites,\" ... Sure? Should it not be AGTX being transcribed here since AGT is its protein form?\n• Very minor comment: figure legends and style in the text seem to not fit NC style (e.g., in text \"Fig. 2c g/j\"; in legend \"c)\"", "reviewer_2": "The authors have addressed my comments and I am happy to recommend acceptance of the manuscript for publication."}, "author_response": "Responses to Reviewers’ Comments:\nReviewer #1 (Remarks to the Author):\nThe authors have addressed my comments and have significantly improved the manuscript text\nand layout.\nI still have some comments/suggestions that may further improve their manuscript.\nComment 1.1\nLines 79-80: \"Moreover, in some species with intact MTS—such as the domestic horse (Equus\nferus) and olive baboon (Papio anubis)—AGT predominantly targets peroxisomes\"\n... consider clarifying here: e.g. *herbivorous* domestic horse ... *omnivorous* olive baboon\nResponse to 1.1\nWe have revised the sentence as suggested.\nComment 1.2\nTable S1: typo \"Speceis Name\" ... Also consider adding the common name of each species here\nand aligning each cell to the left to make the spreadsheet easier to read\nResponse to 1.2\nThank you for your careful suggestion. We have corrected the wrong spelling, and have added\ncommon names for each species and aligned each cell to the left in all supplementary tables.\nComment 1.3\nSI Table legends (I think S2, S3, S6, S7): I do not like the term \"in 37 experimental mammals.\"\nThis wording suggests you performed in vivo experiments on these, including giant pandas\n(Ailuropoda melanoleuca) and brown bears (Ursus arctos) – clearly not the case.\nResponse to 1.3\nWe agree with this comment that the term “experimental mammals” is misleading. We have\nchanged it to “37 mammals included in this study” in Table S2/S3/S6/S7 (Now all in Source\nData file).\nComment 1.4\nI think the naming of BLAST is still not correct. Should be tBLASTn (e.g., see line 105), instead\nof TBLASTN, etc.\nResponse to 1.4\nWe have changed “TBLASTN” to “tBLASTn” throughout the manuscript.\nComment 1.5\nI think it is confusing to say \"AGXT gene(s)\". The gene is AGXT and the protein is AGT, right?\nPerhaps \"AGTX gene\" is ingrained in the literature, but I would ensure that the Table/Figure\nlegends and MS text are in line with the correct nomenclature.\nResponse to 1.5\nWe have strictly checked and used AGXT for the gene and AGT for the protein throughout all\nTable/Figure legends and MS text.\nComment 1.6\nline 118: perhaps specify: \"three hypercarnivores (e.g. Iberian mole, Talpa occidentalis)\" => \"three\nhypercarnivores (species with a diet comprising >70% animal tissue; e.g. the Iberian mole, Talpa\noccidentalis)\"\nResponse to 1.6\nWe have revised the sentence as suggested.\nComment 1.7\nlines 207-208: \"with the most marked decreases seen in herbivorous mammals, ranging from 8.96%\nin olive baboons to 73.16% in\" ... but the olive baboon is omnivorous, right? Your data suggest a\n50/50 between plant/animal tissue in its diet (Table S1). Perhaps say this (and reverse the order\nsince you focus on herbivory): \"... ranging from 73.16% in the obligate herbivorous koalas to 8.96%\nin omnivorous olive baboons\"?\nResponse to 1.7\nWe agree that the olive baboon should be classified as omnivorous rather than herbivirous.\nWe have revised it as suggested.\nComment 1.8\nOn the lack of selection signal in Afroheria and Metatheria, perhaps you could comment on when\nherbivory is said to have occurred in each group of interest in the Discussion? Afrotheria I assume\n~60-70 Mya; Metatheria, not sure, but surely <70 Mya and around the same time as herbivorous\nancestor of sea cows/elephants/hyraxes. So, these herbivores have been around a lot longer than\nmost other mammal groups where herbivory evolved (ruminants and, of course, primates).\nResponse to 1.8\nThank you for this suggestion. We agreed that the evolutionary timescale is a crucial factor in\nexplaining the lack of significant selection signals in Afrotheria and Metatheria. In that case, we\nadded a paragraph at the end of “AGT evolution with PTS1 and MTS during mammal dietary\ndiversification” of Discussion (Line 391-396):\n“However, AGT in Afrotheria and Metatheria was observed to lack significant selection\nsignals in our nested models (Table S2), possibly because these herbivorous lineages\noriginated much earlier, around 60-70 million years ago41, 42. Over such a long period, the\ninitial selection signals from their dietary transitions may have been masked, whereas\nstronger selection signals remain detectable in herbivores of Laurasiatheria and\nEuarchontoglires, reflecting their later dietary shifts.”\nComment 1.9\nlines 447-448: \"we also found that AGT in herbivores tends to be transcribed from downstream\ntranscription start sites,\" ... Sure? Should it not be AGTX being transcribed here since AGT is its\nprotein form?\nResponse to 1.9\nWe have corrected it as suggested. See line 423 on page 11 and line 469 on page 12.\nComment 1.10\nVery minor comment: figure legends and style in the text seem to not fit NC style (e.g., in text\n\"Fig. 2c g/j\"; in legend \"c)\"\nResponse to 1.10\nWe have revised these as suggested.\nReviewer #2 (Remarks to the Author):\nThe authors have addressed my comments and I am happy to recommend acceptance of the\nmanuscript for publication.\nResponse to Reviewer2\nThank you. We are pleased that we have addressed your comments."}]

Decision letter