Viruses interact with hundreds khổng lồ thousands of proteins in mammals, yet adaptation against viruses has only been studied in a few proteins specialized in antiviral defense. Whether adaptation to viruses typically involves only specialized antiviral proteins or affects a broad array of virus-interacting proteins is unknown. Here, we analyze adaptation in ~1300 virus-interacting proteins manually curated from a phối of 9900 proteins conserved in all sequenced mammalian genomes. We show that viruses (i) use the more evolutionarily constrained proteins within the cellular functions they interact with & that (ii) despite this high constraint, virus-interacting proteins account for a high proportion of all protein adaptation in humans & other mammals. Adaptation is elevated in virus-interacting proteins across all functional categories, including both immune & non-immune functions. We conservatively estimate that viruses have driven cthua trận lớn 30% of all adaptive sầu amino acid changes in the part of the human proteome conserved within mammals. Our results suggest that viruses are one of the most dominant drivers of evolutionary change across mammalian & human proteomes.

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eLife digest

When an environmental change occurs, species are able to adapt in response due khổng lồ mutations in their DNA. Although these mutations occur randomly, by chance some of them make the organism better suited to lớn their new environment. These are known as adaptive sầu mutations.

In the past ten years, evolutionary biologists have sầu discovered a large number of adaptive mutations in a wide variety of locations in the genome – the complete phối of DNA – of humans and other mammals. The fact that adaptive sầu mutations are so pervasive is puzzling. What kind of environmental pressure could possibly drive sầu so much adaptation in so many parts of the genome?

Viruses are igiảm giá suspects since they are always present, ever-changing and interact with many different locations of the genome. However, only a few mammalian genes had been studied to lớn see whether they adapt to the presence of viruses. By studying thousands of proteins whose genetic sequence is conserved in all mammalian species, Enard et al. now suggest that viruses explain a substantial part of the total adaptation observed in the genomes of humans and other mammals. For instance, as much as one third of the adaptive mutations that affect human proteins seem to have sầu occurred in response to viruses.

So far, Enard et al. have only studied old adaptations that occurred millions of years ago in humans & other mammals. Further studies will investigate how much of the recent adaptation in the human genome can also be explained by the arms race against viruses.


A number of proteins with a specialized role in antiviral defense have been shown to have exceptionally high rates of adaptation (Cagliani et al., 2011; Cagliani et al., 2012; Elde et al., 2009; Fumagalli et al., 2010; Kerns et al., 2008; Liu et al., 2005; Sawyer et al., 2004; Sawyer et al., 2005; Sawyer et al., 2007; Sironi et al., 2012; Vasseur et al., 2011). One example is protein kinase R (PKR), which recognizes viral double-stranded RNA upon infection, halts translation, và as a result blocks viral replication (Elde et al., 2009). PKR is one of the faschạy thử adaptively evolving proteins in mammals. Specific amino acid changes in PKR have been shown to be associated with an arms race against viral decoys for the control of translation (Elde et al., 2009).

However, PKR and other fast-evolving antiviral defense proteins may not be representative of the hundreds or even thousands of other proteins that interact physically with viruses (virus-interacting proteins or VIPs in the rest of this manuscript). Most VIPs are not specialized in antiviral defense và do not have sầu known roles in immunity. Many of these VIPs play instead key functions in basic cellular processes, some of which might be essential for viral replication.

In principle some VIPs without specific antiretroviral functions might nonetheless evolve to limit viral replication or alleviate deleterious effects of viruses despite the need to lớn balance this evolutionary response with the maintenance of the key cellular functions they play. There are reasons to believe that such an evolutionary response khổng lồ viruses might be limited, however. First, most VIPs evolve unusually slowly rather than unusually fast both in animals (Davis et al., 2015; Jäger et al., 2011) và in plants (Mukhtar et al., 2011; Weßling et al., 2014). Second, VIPs tover lớn interact with proteins that are functionally important hubs in the protein-protein interaction network of the host possibly limiting their ability to lớn adapt (Dyer et al., 2008; Halehalli và Nagarajaram, 2015). Finally, very few cases of adaptation to viruses are known outside of fast evolving, specialized antiviral proteins (Demogines et al., 2012; Meyerson et al., 2014; Meyerson & Sawyer, 2011; Meyerson et al., 2015; Ng et al., 2015; Ortiz et al., 2009; Schaller et al., 2011). Transferrin receptor or TFRC is the most notable exception, & serves as a striking example of a non-immune, housekeeping protein used by viruses (Demogines et al., 2013; Kaelber et al., 2012). TFRC is responsible for iron uptake in many different cell types và is used as a cell surface receptor by diverse viruses in rodents & carnivores. TFRC has repeatedly evaded binding by viruses through recurrent adaptive sầu amino acid changes. As such, TFRC is the only clear-cut example of a host protein not involved in antiviral response that is known lớn adapt in response to viruses.

Here we analyze patterns of evolutionary constraint và adaptation in a high quality set of ~1300 VIPs that we manually curated from virology literature. These 1300 VIPs come from a phối of ~10000 proteins conserved across 24 well-sequenced mammalian genomes (Materials & methods). As expected, the vast majority of these VIPs (~80%) have sầu no known antiviral or any other more broadly defined immune activity. We confirm that VIPs vì tkết thúc lớn evolve slowly & demonstrate that this is because VIPs experience much stronger evolutionary constraint than other proteins within the same functional categories. However, despite this greater evolutionary constraint, VIPs display higher rates of adaptation compared to other proteins. This excess of adaptation is visible in VIPs across biological functions, on multiple time scales, in multiple taxa, và across multiple studied viruses. Finally, we showcase the power of our global scan for adaptation in VIPs by studying the case of aminopeptidase N, a well-known multifunctional enzyme (Mina-Osorio, 2008) used by coronaviruses as a receptor (Delmas et al., 1992; Yeager et al., 1992). Using our approach we reach an amino-acid màn chơi understanding of parallel adaptive evolution in aminopeptidase N in response to lớn coronaviruses in a wide range of mammals.

We curated a phối of 1256 VIPs from the low-throughput virology literature (Materials and methods và Supplementary file 1A). VIPs were defined as proteins that interact physically with viral proteins, viral RNA, and/or viral DNA (Supplementary file 1A). We excluded interactions identified by high-throughput experiments because we were concerned about a high rate of false positives (Mellacheruvu et al., 2013). The 1256 VIPs were annotated from an initial set of 9861 proteins with clear orthologs in all 24 analyzed mammalian high unique genomes (Figure 1, Supplementary file 1B & Materials & methods) (Enard et al., 2016).

Tree of 24 mammals used in the analysis.
Most of the VIPs (95%) correspond to lớn an interaction between a human protein and a virut infecting humans (Supplementary tệp tin 1A). Human Immunodeficiency Virus type 1 (HIV-1) is the best-represented vi khuẩn with 240 VIPs, with nine other viruses (HPV, HCV, EBV, HBV, HSV, Influenza Virus, ADV, HTLV và KSHV) having at least 50 VIPs (Supplementary tệp tin 1A).

This dataset represents the largest, most up-to-date phối of VIPs backed by individual low-throughput publications. Nonetheless, given that many VIPs were discovered only recently, with half of all publications reporting VIPs published in the past 7 years (Figure 2), it is likely that many additional VIPs remain to lớn be discovered.

Number of VIPs discovered per year until năm trước.
The identified 1256 VIPs are involved in diverse cellular & supracellular processes with 162 overlapping GO cellular và supracellular processes having more than 50 VIPs (Gene Ontology (GO) classes (October 2013 version) (Ashburner et al., 2000; The Gene Ontology Consortium, 2015); Supplementary file 1C). These cellular processes include transcription (354 VIPs), post-translational protein modification (224 VIPs), signal transduction (396 VIPs), apoptosis (185 VIPs), & transport (264 VIPs). The supracellular processes notably include defense response (103 VIPs) & developmental processes (327 VIPs). Only 57 VIPs or 5% of VIPs have sầu known antiviral activity (Supplementary file 1D). These 57 antiviral VIPs are part of a larger group of 241 VIPs (20% of VIPs) with known immune functions, defined here as any activity that modulates the immune response or involved in the development of the immune response (Materials and methods và Supplementary file 1D). Most - more than 80% - of the VIPs have no known immune activity.

We analyze both purifying selection and positive selection in VIPs versus non-VIPs at two distinct evolutionary time scales: (i) in the great apes in general & in the human branch specifically and (ii) across the entire mammalian phylogeny. We use the ratio of nonsynonymous to synonymous polymorphisms (abbreviated as pN/pS) within humans and great apes as a measure of purifying selection. We use McDonald-Kreitman (MK) và the branch-site tests of positive selection using the BS-REL (Kosakovsky Pond et al., 2011) và BUSTED (Murrell et al., 2015) tests from the HYPHY package (Pond et al., 2005) lớn assess the prevalence of positive sầu selection in VIPs compared lớn non-VIPs in the human lineage và in mammals in general (Material and methods).

We confirm that VIPs tover to evolve sầu slowly (Jäger et al., 2011; Davis et al., 2015). On average, the VIPs have ~15% lower mammal-wide dN/dS ratio compared to non-VIPs (0.124 versus 0.145, 95% CI <0.136,0.148>; Materials & methods). The difference in dN/dS is highly significant (permutation test P=0 after 109 iterations; Supplementary file 1B). In order to disentangle whether this slower evolution of VIPs is due khổng lồ stronger purifying selection or lớn a lower rate of adaptation, we first assess the strength of purifying selection in the VIPs using the pN/pS ratio.

Genome-wide polymorphism data required lớn measure pN/pS are available in humans (Abecasis et al., 2012) (1000 Genomes Project) (Supplementary file 1E), and other great apes: chimpanzee, gorilla, và orangutans (Prado-Martinez et al., 2013) (Great Apes Genome Project) (Supplementary file 1F). The 1000 Genomes Project and the Great Apes Genome Project are complementary for this analysis. On the one h&, the 1000 Genomes Project provides high unique variants with frequencies estimated from a large number of individuals. On the other hand while the Great Ape Genome project includes fewer individuals & provides coarser frequency data, it provides substantially higher pN và pS counts than the 1000 Genomes data because non-human great apes tkết thúc to be more polymorphic overall (Prado-Martinez et al., 2013).

In the human African populations from the 1000 Genomes project (Materials và methods), the average pN/pS is 21% lower in VIPs compared khổng lồ non-VIPs (0.759 versus 0.966, 95% CI <0.92,1.01>, simple permutation test P=0 after 109 iterations). VIPs also show an excess of low frequency (≤10%) deleterious non-synonymous variants compared to non-VIPs (Figure 3—figure supplement 1; simple permutation chạy thử P=0 after 109 iterations). In great apes, the average pN/pS ratio is 25% lower in VIPs compared lớn non-VIPs (0.526 versus 0.697, 95% CI <0.66,0.72>, simple permutation demo P=0 after 109 iterations; Figure 3A). Finally, stronger purifying selection acting on VIPs is widespread và is not limited to VIPs interacting with any one particular vi khuẩn (Figure 3B).

Patterns of purifying selection in VIPs.
(A) Distribution of pN/pS in VIPs (blue) & non-VIPs (pink). The blue curve is the density curve of pN/(pS+1) for 1256 VIPs. We use pN/(pS+1) instead of pN/pS lớn trương mục for those coding sequences where pS=0. pN và pS are measured using great ape genomes from the Great Ape Genome Project (Materials và methods). The pink area represents the superimposition of the density curves for each of 5000 sets of randomly sampled non-VIPs. (B) Average pN/pS in VIPs (xanh dot) versus average pN/pS in non-VIPs (red dot và red 95% confidence interval) within ten viruses with more than 50 VIPs The number between parentheses is the number of VIPs for each vi khuẩn. KSHV: Kaposi’s Sarcoma Herpesvi khuẩn. HIV-1: Human Immunodeficiency Virus type 1. HBV: Hepatitis B Virus. ADV: Adenovirut. HPV: Human Papillomavirus. HSV: Herpes Simplex Virus. EBV: Epstein-Barr Virus. Influenza: Influenza Virus. HTLV: Human T-lymphotropic Virus. HCV: Hepatitis C virut. (C) Same as B), but for the trăng tròn most high level GO processes with the highest number of VIPs. The full GO process name for “protein modification” as written in the figure is “post-translational protein modification”.

VIPs và non-VIPs have sầu slightly different coding sequence GC content (0.516 versus 0.523 on average, P=6x10-4), coding sequence lengths (668 versus 606 amino acids on average, P=0) & recombination rates (Kong et al., 2010) (1.145 cM/Mb versus 1.175 cM/Mb on average, P=0.21). To ensure that the difference in pN/pS between VIPs và non-VIPs is robust to lớn these differences, we compare VIPs with non-VIPs with similar values for each potential confounding factor using permutations with a target average (Materials and methods). The difference in pN/pS in great apes between VIPs và non-VIPs persists when comparing VIPs & non-VIPs with similar GC content (0.526 versus 0.655, P=0 after 109 iterations), similar coding sequence length (0.526 versus 0.654, P=0), or similar recombination (0.526 versus 0.702, P=0). The difference in pN/pS between VIPs & non-VIPs is therefore a genuine difference in the strength of purifying selection & not due khổng lồ confounding factors biasing the pN/pS ratio.

VIPs have sầu been shown before to be broadly expressed genes và lớn serve sầu as hubs in the human protein-protein interactions network (Dyer et al., 2008, Halehalli & Nagarajaram, 2015). These differences in gen expression and the number of protein-protein interactions may explain the stronger purifying selection experienced by VIPs. We confirm that VIPs are indeed expressed in more tissues than non-VIPs both at the RNA level (GTEx Consortium, 2015) (GTEx V4 RNA-seq expression RPKM≥10 in 25.5 tissues on average in VIPs versus 11.9 tissues in non-VIPs, simple permutation chạy thử P=0) và at the protein cấp độ (Kim et al., 2014) (Human Proteome Map spectral count≥5 in 15.1 tissues on average for VIPs versus 6.1 for non-VIPs, simple permutation chạy thử P=0). VIPs also have many more protein-protein interaction partners than non-VIPs based on a dataset of human protein-protein interactions curated by (Luiđam mê et al., 2015) from the Biogrid database (Stark et al., 2011) (18.4 on average versus 3.2, simple permutation demo P=0).

The magnitude of the difference in pN/pS between VIPs & non-VIPs expressed in a similar number of tissues at the RNA cấp độ (GTEx) (0.526 versus 0.647, P=0) or in a similar number of tissues at the protein cấp độ (Human protein Map) (0.526 versus 0.662, P=0) remains largely unchanged. In contrast, the difference in pN/pS is strongly affected when comparing VIPs và non-VIPs with a similar number of protein-protein interactions. Indeed, non-VIPs with the same number of interacting partners as VIPs have a pN/pS ratio of 0.605 versus 0.697 for all non-VIPs, and the difference in the pN/pS rattiện ích ios between VIPs and non-VIPs is reduced from 25% to lớn 13%. These results show that VIPs vị experience stronger purifying selection than non-VIPs, và that the difference in purifying selection is driven at least partly by the fact that VIPs tover to lớn be hubs with many interacting partners in the human protein-protein interactions network.

The higher cấp độ of purifying selection in VIPs might be due khổng lồ the fact that VIPs participate in the more constrained host functions, or, alternatively, because within each specific host function, viruses tend khổng lồ interact with the more constrained proteins. In order to kiểm tra these two non-mutually exclusive scenargame ios we generated 104 control sets of non-VIPs chosen to be in the same 162 Gene Ontology processes as VIPs (GO processes with more than 50 VIPs; Supplementary tệp tin 1C & Materials và methods). In great apes, GO-matched non-VIPs still have a much higher pN/pS ratio compared to VIPs, suggesting that VIPs tkết thúc to lớn be more conserved than non-VIPs from the same GO category. On average, pN/pS in the GO-matched non-VIPs is 0.647 (95% CI <0.621,0.674>). This is only slightly lower than the average ratio in non-VIPs in general (pN/pS=0.697, P=2x10-3), but much higher than the average ratio in VIPs (0.526, permutation kiểm tra P=0 after 104 iterations). Moreover, the stronger purifying selection acting on VIPs is apparent within most functions. Figure 3C shows stronger purifying selection in the đôi mươi high cấp độ GO categories with the most VIPs. In all the trăng tròn GO categories pN/pS is lower in VIPs than in non-VIPs, and the difference is significant for 17 of these categories (Supplementary tệp tin 1C). This shows that within a wide range of host functions, viruses tkết thúc to interact with the most conserved proteins.

Interestingly, even immune VIPs (Supplementary tệp tin 1D) have a significantly reduced pN/pS ratio compared khổng lồ immune non-VIPs (Figure 3C), which suggests that immune proteins in direct physical liên hệ with viruses are more constrained. The reduction in pN/pS in non-immune VIPs is very similar to the reduction observed in the entire set of VIPs (Figure 3C). The table at Supplementary tệp tin 1C further shows stronger purifying selection in 124 of the 162 GO categories (77%) with more than 50 VIPs.

We estimate the proportion of adaptive sầu non-synonymous substitutions (noted α) in VIPs & non-VIPs in the human lineage by using the classic McDonald-Kreitman chạy thử (MK test) (McDonald và Kreitman, 1991) (Materials and methods). We use the 1000 Genomes Project polymorphism data from African populations (Materials và methods và Supplementary tệp tin 1E) & divergence between humans & chimpanzees. We first attempt khổng lồ limit the effect of deleterious variants by excluding all variants with a derived allele frequency lower than 10% (Materials và methods) (Keightley and Eyre-Walker, 2007, Charlesworth & Eyre-Walker, 2008a, Eyre-Walker và Keightley, 2009, Messer and Petrov, 2013). We find that α is strongly elevated in VIPs compared to lớn non-VIPs (α=0.19 in VIPs versus −0.02 in non-VIPs, permutation test P=2.x10−5).

cảnh báo that the classic MK chạy thử is known to lớn underestimate the true α in the presence of slightly deleterious polymorphisms (Charlesworth và Eyre-Walker, 2008b). Given that VIPs tkết thúc lớn have more non-synonymous deleterious low frequency variants than non-VIPs (Figure 3—figure supplement 1) this downward bias should be stronger in the VIPs, making this comparison conservative sầu and indicating that VIPs likely have sầu a substantial excess of adaptation compared to non-VIPs.

The difference in α is robust khổng lồ recombination (α =−0.025 in non-VIPs with similar recombination to VIPs versus −0.02 without control). It is also robust to lớn coding sequence GC nội dung (α=−0.019 with versus −0.02 without control), coding sequence length (α=−0.023 with versus −0.02 without control). The difference is also robust to variation in levels of expression at the RNA level measured as the number of tissues with GTEx V4 RNA-seq expression RPKM≥10 (α=0.001 with versus 0.02 without control) & as the average expression across all GTEx V4 tissues (α=−0.018 with versus 0.02 without control), as well as at the protein cấp độ measured as the number of Human Proteome Map tissues with spectral count>=5 (α=−0.024 with versus 0.02 without control) or the average expression across all the Human Proteome Map tissues (α=−0.035 with versus 0.02 without control). The difference in α is also not affected by the number of protein-protein interactions (α=0.025 with versus −0.02 without control). The difference in α is not affected either by purifying selection, as shown by the fact that using great apes pN/pS or human pN/pS as a control has no effect (α=0.001 with versus 0.02 without control in both cases). Finally, we match VIPs & non-VIPs with similar GO categories (Materials and methods, paragraph titled "Gene Ontology-matching control samples"). The higher rate of adaptation in VIPs is not explained by higher rates of adaptation in the host GO processes where VIPs are well represented (α=0.003 with versus −0.02 without control). For all the controls, the difference in α between VIPs and non-VIPs remains highly significant (permutation chạy thử P-3 in all cases). Together these results show that the excess of adaptation in VIPs is robust khổng lồ many different host factors.

We further investigate the excess of adaptation for the specific VIPs of ten human viruses và in the trăng tròn high màn chơi GO categories with the most VIPs (Figure 4A & B). Although the small number of proteins interacting with individual viruses precludes precise estimates of α (see the large confidence intervals on Figure 4A), the VIPs show nominally higher values of α for eight out of 10 viruses, with HIV-1 and Hepatitis B Virus (HBV) displaying statistically significant increases in adaptation. Likewise, VIPs in most GO categories show higher rates of adaptation (14 out of 20) with 9 of 14 showing statistically significant increases (Figure 4B).

Patterns of human adaptation in VIPs.
(A) Classic MK kiểm tra (Materials & methods) for VIPs (blue dot) và non-VIPs (red dot & 95% confidence interval) for the ten viruses with 50 or more VIPs. (B) Same as A) but for the 20 top high cấp độ GO processes with the most VIPs below the dotted blaông xã line. Above sầu the dotted blaông xã line: the classic MK demo for all VIPs, for non-immune VIPs và for immune VIPs (Supplementary tệp tin 1D). (C) Asymptotic MK demo (Materials and methods) for the proportion of adaptive amino acid substitutions (α) in VIPs (xanh dots và curve) and non-VIPs (red dots and curve). Pink area: superposition of fitted logarithmic curves (Materials and methods) for 5000 random sets of 1256 non-VIPs (as many as VIPs) where the estimated α falls within α‘s 95% confidence interval.

Finally và importantly, the 80% of VIPs with no known antiviral or broader immune function (Supplementary file 1D) have a strongly increased rate of adaptation according to lớn the classic MK thử nghiệm (α=0.26 in VIPs versus 0.02 in non-VIPs, permutation kiểm tra P=3x10−7; Figure 2B). Intriguingly, unlike for non-immune VIPs or all VIPs considered together (top of Figure 4B), immune VIPs, including antiviral VIPs (Supplementary file 1D), vị not show any increase of adaptation compared lớn immune non-VIPs. The laông chồng of a signal is unlikely to lớn be due to reduced statistical power of the comparison in a smaller mix of immune proteins, given that 1000 random samples of non-immune VIPs with the same kích cỡ as the immune VIPs sample (241) always exhibited a significantly (p The asymptotic MK demo

Excess of adaptation across mammals in VIPs The excess of adaptation is measured as the extra percentage of adaptation in VIPs compared to lớn non-VIPs.

GO-analysis of adaptation in mammals

Distribution of adaptation in VIPs across mammalian clades

We have shown that rates of adaptation are globally elevated in VIPs in humans & mammals in general, suggesting the existence of tens of thousands of isolated events of adaptations to a diverse range of viruses. Here, we test if our global approach has enough power khổng lồ isolate new specific cases of adaptation khổng lồ viruses by looking for instances where viruses are the plausible cause of adaptation in a VIP. with no known antiviral activity. This is particularly relevant because, to lớn our knowledge, the transferrin receptor (TFRC) is one of the only well understood case of a non-antiviral protein adapting in response to lớn viruses (Demogines et al., 2013).

To identify a non-antiviral VIP for in-depth investigation we first excluded all VIPs with a well-known antiviral activity (Supplementary file 6; here as in the rest of the manuscript antiviral means a protein activity that restricts viral infection) and then selected all remaining VIPs with strong overall evidence of adaptation (Supplementary tệp tin 1I) and at least 10 branches with signals of adaptation. We also selected proteins with i) at least one available tertiary structure, ii) amino acid cấp độ resolution of the interaction with one or more viruses, & iii) host tropism.

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The most positively selected non-antiviral VIPhường that fulfills all these requirements is aminopeptidase N, abbreviated ANPEP, APN or CD13 (Mina-Osorio, 2008). The analysis of a phylogenetic tree including 84 mammals (Supplementary file 1J) confirms pervasive adaptation of ANPEP across mammals, with 76 out of 165 branches in the tree showing signals of adaptation (Figure 7A). lưu ý that adaptation of ANPEP. has previously been detected in the context of oxidative stress in Cetaceans (Yim et al., 2014). ANPEPhường. is a cell-surface enzyme well known for its surprisingly wide range & diversity of functions (Mina-Osorio, 2008). In particular, it is used by group I coronaviruses as a receptor, including the Human Coronavi khuẩn 229E (HCoV-229E) (Yeager et al., 1992), Transmissible Gastroenteritis Virus (TGEV) (Delmas et al., 1992), Feline Coronavirus (FCoV) (Tresnan và Holmes, 1998), Canine Coronavirut (CCoV) (Tusell et al., 2007), Porcine Respiratory Coronavirut (PRCV) (Delmas et al., 1993) & Porcine Epidemic Diarrhea Virus (PEDV) (Oh et al., 2003). Reguera et al. (Reguera et al., 2012) solved the structure of porcine ANPEPhường bound together with TGEV và PRCV. The authors identified in the extracellular domain of ANPEPhường 22 amino acids that form a surface of tương tác with TGEV và PRCV (Figure 7B) (Pettersen et al., 2004). The most important component of this contact surface for host tropism is a N-glycosylation site at position 736 in porcine ANPEP. (orthologous position 739 in human ANPEP) that forms hydrogen bonds with TGEV & PRCV (Tusell et al., 2007; Reguera et al., 2012). Deleting this site abolishes the ability of TGEV và PRCV to bind porcine ANPEPhường. (Reguera et al., 2012). Adding the glycosylation site in human ANPEP.. that natively lacks it transforms it inkhổng lồ a receptor for TGEV và PRCV (Reguera et al., 2012).

Materials and Mmethods

Multiple alignments of mammalian orthologs

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Annotation of antiviral & immune mammalian orthologs

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Quantifying adaptation in human with the classic và the asymptotic McDonald-Kreitman tests

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We estimate & compare the proportion of adaptive amino acid changes, noted α, in VIPs & non-VIPs using either the classic McDonald-Kreitman kiểm tra (MK test) (McDonald & Kreitman, 1991) or an asymptotic MK demo (Messer and Petrov, 2013). The MK thử nghiệm measures α as follows:


Quantifying adaptation in the mammalian phylogeny

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