- Research article
- Open Access
Rapid divergence and diversification of mammalian duplicate gene functions
© Assis and Bachtrog. 2015
- Received: 16 December 2014
- Accepted: 1 July 2015
- Published: 15 July 2015
Gene duplication provides raw material for the evolution of functional innovation. We recently developed a phylogenetic method that classifies evolutionary processes driving the retention of duplicate genes by quantifying divergence between their spatial gene expression profiles and that of their single-copy orthologous gene in a closely related sister species.
Here, we apply our classification method to pairs of duplicate genes in eight mammalian genomes, using data from 11 tissues to construct spatial gene expression profiles. We find that young mammalian duplicates are often functionally conserved, and that expression divergence rapidly increases over evolutionary time. Moreover, expression divergence results in increased tissue specificity, with an overrepresentation of expression in male kidney, underrepresentation of expression in female liver, and strong underrepresentation of expression in testis. Thus, duplicate genes acquire a diversity of new tissue-specific functions outside of the testis, possibly contributing to the origin of a multitude of complex phenotypes during mammalian evolution.
Our findings reveal that mammalian duplicate genes are initially functionally conserved, and then undergo rapid functional divergence over evolutionary time, acquiring diverse tissue-specific biological roles. These observations are in stark contrast to the much faster expression divergence and acquisition of broad housekeeping roles we previously observed in Drosophila duplicate genes. Due to the smaller effective population sizes of mammals relative to Drosophila, these analyses implicate natural selection in the functional evolution of duplicate genes.
- Gene duplication
- Duplicate genes
Gene duplication produces copies of existing genes, which can diverge from their ancestral states and contribute to the evolution of novel phenotypes. A large proportion of mammalian genes arose via gene duplication [1, 2], many of which are members of large gene families with diverse and important functions. For example, Hox, opsin, and olfactory receptor gene families were all produced by gene duplication [3, 4]. However, the evolutionary paths leading from redundant copies to distinct genes with essential functions remain unclear.
Different processes may drive the long-term retention of duplicate genes: Parent and child copies may each maintain the function of their single-copy ancestral gene (conservation ); one copy may maintain the ancestral function, while the other acquires a new function (neofunctionalization ); each copy may lose part of its function, such that together both copies carry out the ancestral function (subfunctionalization [6–8]); or both copies may acquire new functions (specialization, also called subneofunctionalization or neosubfunctionalization ). We recently developed a phylogenetic method that utilizes distances between gene expression profiles to classify these evolutionary processes (see  and Methods for details). Our method can be applied to pairs of duplicates and requires that, for each pair, we can distinguish between parent and child copies and identify their single-copy ortholog (referred to as “outgroup gene” here, and as “ancestral gene” in ) in a closely related sister species. Moreover, parent, child, and outgroup genes must all have spatial or temporal gene expression data from which expression profiles can be constructed.
To study the roles of conservation, neofunctionalization, subfunctionalization, and specialization in the retention of mammalian duplicate genes, we applied our method to pairs of duplicate genes in eight mammalian genomes: human (Homo sapiens), chimpanzee (Pan trogodytes), gorilla (Gorilla gorilla), orangutan (Pongo pygmaeus abelii), macaque (Macaca mulatta), mouse (Mus musculus), opossum (Monodelphis domestica), and platypus (Ornithorhynchus anatinus). Using synteny information from whole-genome alignments to determine orthologous genomic positions, and parsimony to infer gene acquisitions, we distinguished between parent and child copies and identified single-copy outgroup genes for each pair of duplicates (see Methods for details). Then, we applied our classification method to RNA-seq data from 11 mammalian tissues: female and male cerebrum, female and male cerebellum, female and male heart, female and male kidney, female and male liver, and testis .
We obtained 654 pairs of mammalian duplicate genes for which we could distinguish between parent and child copies and also identify at least one expressed single-copy outgroup gene in a closely related sister species. Application of our method to these pairs yielded 382 cases of conservation, 213 cases of neofunctionalization (105 neofunctionalized parent copies and 108 neofunctionalized child copies), 9 cases of subfunctionalization, and 50 cases of specialization (Additional file 1: Table S1; see Methods for details). Thus, most mammalian duplicate genes have conserved expression profiles. Moreover, expression divergence is often asymmetric between duplicates, and retention of duplicates by subfunctionalization is rare.
To determine the types of tissue-specific functions that arise under neofunctionalization, we compared proportions of single-copy, outgroup, functionally conserved (from conserved and neofunctionalized classes), and neofunctionalized genes with highest expression levels in each tissue (Fig. 2b; Additional file 1: Table S2). We observed significant differences in male kidney, female liver, and testis tissues. Relative to single-copy genes, there was an underrepresentation of outgroup genes and an overrepresentation of neofunctionalizad genes with highest expression in male kidney. Additionally, relative to outgroup genes, there were overrepresentations of conserved and neofunctionalized genes with highest expression in male kidney. These patterns suggest that ancestral genes are deficient in male kidney expression, which generally increases in both gene copies after duplication. Also, relative to both single-copy and outgroup genes, there were underrepresentations of conserved and neofunctionalized genes with highest expression in female liver tissue. This is suggestive of a general decrease in female liver tissue expression in both gene copies after duplication. Finally, relative to both single-copy and outgroup genes, there was an overrepresentation of conserved and a severe underrepresentation (only one gene) of neofunctionalized genes with highest expression in testis. This indicates that after duplication, testis expression increases in conserved copies and decreases in neofunctionalized copies. Thus, unlike the trends observed in male kidney and female liver, both copies alter their testis expression in opposite ways, such that tissue-specific neofunctionalized copies are highly underrepresented in testis.
Studies of duplicate genes have shown that expression divergence between copies occurs rapidly [12–21] and is often asymmetric [13, 16, 19, 20]. Moreover, differences between expression levels of single-copy and duplicate genes and their relationships to neofunctionalization and subfunctionalization have also been studied previously [22, 23]. However, our analysis is the first to utilize gene expression data and phylogenetic relationships among species to classify the evolutionary processes driving the retention of mammalian duplicates on a genome-wide scale.
In a previous study, we applied our classification method to duplicate genes in Drosophila melanogaster and D. pseudoobscura . However, in our Drosophila dataset, K s ranged from 0.11 (between D. melanogaster and D. simulans ) to 1.79 (between D. melanogaster and D. pseudoobscura ). In our mammalian dataset, K s ranges from 0.01 (between human and chimpanzee ) to 1.41 (between human and platypus ). Thus, the smallest K s in our mammalian dataset is an order of magnitude smaller than in our Drosophila dataset, enabling us to capture much younger duplicates in our current analysis. Moreover, our current dataset contains gene expression profiles from nine vertebrate species at varying evolutionary distances, compared to only three species in Drosophila. This provided us with greater temporal resolution in mammals than in Drosophila, and allowed us to more closely examine the functional diversification of mammalian duplicates over evolutionary time.
Contrary to our observation in mammalian duplicates, we found that most Drosophila duplicates were neofunctionalized, and examination of evolutionary processes over shorter divergence times suggested that novel functions arise within a few million years of evolution . This difference may be due to the larger effective population size (N e) of Drosophila than of mammals [28–30], which contributes to more efficient adaptive protein and regulatory sequence evolution in Drosophila [31–33], and could similarly result in more rapid acquisition of adaptive functions by Drosophila duplicate genes. Even so, expression divergence of duplicate genes occurs much faster than that of single-copy genes in mammals. Thus, though natural selection may not be as efficient as in Drosophila, it still appears to play an important role in the functional divergence of duplicate genes in mammals.
While small N e is also thought to result in a higher prevalence of subfunctionalization , this process does not appear to play a major role in the retention of duplicate genes in either lineage. One possible reason for this observation is that subfunctionalization may be more common in duplicate genes produced by whole genome duplication events [18, 35], which our study does not examine. Another possibility is that the stringency of our subfunctionalization classification resulted in an underestimation of such cases. Because our cutoff for expression divergence was conservative (see Methods), this would have most likely resulted in subfunctionalized genes being grouped with conserved genes. However, decreasing the cutoff increases the number of specialized, rather than subfunctionalized, genes (Additional file 1: Table S3). One potential solution to this problem is to apply our method to a dataset consisting of more tissues, which may help better differentiate functions of genes, resulting in the classification of fewer conserved duplicates.
Another difference between our findings in Drosophila and mammals was that neofunctionalization primarily occurred in child copies in Drosophila , whereas it occurred with equal frequency in child and parent copies in mammals. This may also be attributed to differences in efficiencies of natural selection between Drosophila and mammals. Under neutrality, most duplicate genes should be lost within the first few million years of evolution . In Drosophila, many neofunctionalized child genes likely arose with or quickly acquired new beneficial functions that were retained by natural selection . In mammals, for which natural selection is less efficient, such genes may be lost more often. However, new genes with conserved functions may be more easily maintained. In particular, recent studies of mammalian duplicate genes have shown that transcription of one duplicate is often suppressed by methylation, and that methylation decreases over evolutionary time [37, 38]. Thus, child copies with conserved functions may initially be silenced in mammals. Then, once fixed via a neutral or nearly neutral process, they can be demethylated, enabling them to acquire new functions. Under this scenario, neofunctionalization is likely equally probable in either duplicate, resulting in the relatively similar frequencies of neofunctionalized parent and child copies that we observed.
In both Drosophila and mammals, neofunctionalized genes have tissue-specific functions. However, neofunctionalized Drosophila genes are primarily testis-specific , whereas neofunctionalized mammalian genes are mostly excluded from testis and expressed in a diversity of other tissues. Moreover, in Drosophila, comparison of young and old duplicates supported the “out of the testis” hypothesis of new gene emergence, in which new genes arise with testis-specific functions and evolve broader functions over time . According to this hypothesis, testis may facilitate the initial transcription of young genes, while sheltering them from pseudogenization as they acquire new functions , making testis an ideal tissue for young genes. In mammals, neofunctionalization happens more slowly, and most neofunctionalized genes are relatively old. Because young mammalian duplicates are often conserved, we can perhaps better understand the initial forces retaining duplicates by examining expression profiles of conserved duplicates. Among conserved duplicates, there is an overrepresentation of highest testis-expressed genes. Thus, this finding may support a special case of the “out of the testis” hypothesis in mammals, in which young genes often acquire higher, but not necessarily specific, expression in testis. Then, as they age, they acquire diverse tissue-specific functions outside of the testis, possibly facilitating the evolution of a multitude of complex phenotypes across species.
While gene duplication has long been hypothesized to play an important role in the evolution of novel phenotypes, the processes driving the retention of mammalian duplicate genes remained unclear. In this study, we utilized our previously developed classification method to identify the roles of different evolutionary processes in the retention of mammalian duplicate genes. We found that most mammalian duplicate genes are functionally conserved, and that they diverge rapidly over evolutionary time, acquiring a diversity of tissue-specific functions. In contrast, our previous study in Drosophila revealed that duplicate genes are primarily retained via neofunctionalization, and that they diverge even faster than in mammals, acquiring broad housekeeping functions. Thus, our current study highlights key differences in the retention of duplicate genes between mammals and Drosophila and, moreover, supports the hypothesis that positive selection drives the functional evolution of duplicate genes in both lineages.
Identification of duplicate and single-copy genes
We downloaded protein sequences and annotation files for eight mammals (Homo sapiens, Pan trogodytes, Gorilla gorilla, Pongo pygmaeus abelii, Macaca mulatta, Mus musculus, Monodelphis domestica, and Ornithorhynchus anatinus) and three outgroups (Gallus gallus, Anolis carolinensis, and Takifugu rubripes) from the Ensembl database (release 74) at http://www.ensembl.org. We obtained lists of duplicate genes in each mammalian genome from the Ensembl database (release 74) at http://www.ensembl.org, from the Duplicated Genes Database (DGD) at http://www.dgd.genouest.org, and from protein BLAST searches , which we performed as previously described . Any annotated genes not on these lists were considered to be single-copy genes, and gene families with more than two copies were excluded from our analysis.
Phylogenetic dating and identification of outgroup genes
We downloaded whole-genome alignments from Ensembl (http://www.ensembl.org) and UCSC Genome Bioinformatics (http://www.genome.ucsc.edu) databases and extracted syntenic regions in all genomes for each duplicate gene. We used parsimony to phylogenetically date the origin of each pair of duplicates. In particular, we inferred a duplication event that occurred after the divergence of two sister species if one sister contains two gene copies, while the other sister and all outgroups (including non-mammals) contain a single-copy gene. Duplicates that are present in all species or that could not be resolved via parsimony (e.g., tandem duplicates) were removed from our analysis. For each pair, the gene copy aligned to outgroup genes in the whole-genome alignment was designated as the parent, and the copy that did not align to any regions of the outgroup genomes was considered the child. Because annotation of exons may be unreliable in many of the species used, we did not distinguish between DNA- and RNA-mediated duplication mechanisms. Orthologs for single-copy genes were also obtained via synteny and aligned with MACSE . PAML  was used to estimate K a and K s between orthologous pairs of single-copy genes.
Identification of evolutionary processes maintaining duplicate genes
We quantile-normalized RNA-seq data from mammalian and chicken tissues , and restricted our analysis to pairs for which both copies, and one or more single-copy outgroup genes, are expressed (FPKM ≥ 1) in at least one tissue. The expression profile of the single-copy outgroup gene in the most closely related species with available expression data (see Additional file 1: Table S1) was used as a proxy for the expression of the single-copy ancestral gene prior to duplication. We converted all absolute tissue expression levels to their relative expression levels (proportions of total expression), which were used as gene expression profiles for comparison.
Next, we classified the processes retaining pairs of mammalian duplicate genes by applying our previously developed phylogenetic method  to expression profiles of parent, child, and outgroup genes. To summarize, we first calculated Euclidian distances between expression profiles of parent and outgroup copies (E P,O ), between expression profiles of child and outgroup copies (E C,O ), and between the combined parent–child expression profile and that of the outgroup copy (E P+C,O ). We next established baseline divergence levels for genes by calculating Euclidian distances between expression profiles of single-copy genes present in both sister species (E S1,S2), and used these distances to set cutoffs for expression divergence in each pair of species (see Choice of cutoff for expression divergence). Last, we classified each pair of duplicates as conserved, neofunctionalized, subfunctionalized, or specialized by applying previously described rules . In particular, we expect E P,O ≤ E S1,S2 and E C,O ≤ E S1,S2 when duplicates are functionally conserved, E P,O > E S1,S2 and E C,O ≤ E S1,S2 when the parent copy is neofunctionalized, E P,O ≤ E S1,S2 and E C,O > E S1,S2 when the child copy is neofunctionalized, E P,O > E S1,S2, E C,O > E S1,S2, and E P+C,O ≤ E S1,S2 when duplicates are subfunctionalized, and E P,O > E S1,S2, E C,O > E S1,S2, and E P+C,O > E S1,S2 when duplicates are specialized.
Choice of cutoff for expression divergence
We explored several cutoff values for defining expression divergence (Additional file 1: Table S3). Modifying the cutoff changed numbers of pairs in different classes in predictable ways. In particular, more stringent cutoff values resulted in more pairs classified as conserved, while less stringent values resulted in fewer pairs classified as conserved. However, the main finding was unaffected by the cutoff value. For all cutoffs tested, most duplicates were classified as conserved, and the relative numbers of pairs in parent and child neofunctionalization classes were similar. Of the cutoffs examined, we chose to use the semi-interquartile range from the median because it is robust to outliers, as we did in a previous study of Drosophila duplicate genes. In Drosophila duplicate genes, the distribution of E S1,S2 was right-skewed. In the current study, there are 36 distributions to consider—one for each pair of species compared. While most are approximately normally distributed, we wanted to be able to use the same type of cutoff for all comparisons, and so we did not want to use a cutoff that would be sensitive to differences among shapes of distributions. Moreover, we wanted to ensure that our identification of genes with divergent expression profiles was conservative, which appears to be the case when we use the semi-interquartile range from the median as our cutoff.
A final point about cutoff values is that they are expected to increase as a function of evolutionary distance between the species being compared. However, this is not always the case in the present study (Additional file 1: Table S4) and, in fact, cutoff values do not change much in general. One possibility is that this effect is caused by the use of relative, rather than absolute, expression values in calculating distances. While relative values reduce the effects of experimental differences among data for different species , they may also reduce true differences among expression profiles to some degree. Thus, the classification approach may be more conservative as a result of this transformation.
Fits of least-squares linear regression lines were tested with F-statistics, and all were significant (p < 0.05). Two-sided t-tests were used to assess significance of slopes shown in Figs. 1b and Additional file 2: Figure S1. Two-sided Mann–Whitney U tests were used to compare distributions of tissue specificities of outgroup, parent, and child genes to those of single-copy genes shown in Fig. 2a. Fisher’s Exact tests were used to compare numbers of genes with highest relative expression levels in each tissue among all pairs of groups shown in Fig. 2b (absolute counts provided in Additional file 1: Table S2). Bonferroni corrections were applied to tests involving multiple comparisons. All statistical analyses were performed in the R software environment .
Availability of supporting data
The data sets supporting the results of this article are included within the article and its additional files.
This work was supported by NIH fellowship F32 GM100673-02 awarded to R.A and NIH grants R01GM076007 and R01GM093182 awarded to D.B.
- Li WH, Gu Z, Wang H, Nekrutenko A. Evolutionary analyses of the human genome. Nature. 2001;409:847–9.PubMedView ArticleGoogle Scholar
- Ryvkin P, Jun J, Hemphill E, Nelson C. Duplication mechanisms and disruptions in flanking regions influence the fate of mammalian gene duplicates. J Comput Biol. 2009;16:1253–66.PubMedView ArticleGoogle Scholar
- Holland PW, Garcia-Fernández J, Williams NA, Sidow A. Gene duplications and the origins of vertebrate development. Dev Suppl. 1994;125–133.Google Scholar
- Taylor JS, Raes J. Duplication and divergence: the evolution of new genes and old ideas. Annu Rev Genet. 2004;38:615–43.PubMedView ArticleGoogle Scholar
- Ohno S. Evolution by gene duplication. Berlin: Springer-Verlag; 1970.View ArticleGoogle Scholar
- Hughes AL. The evolution of functionally novel proteins after gene duplication. Proc Royal Soc B. 1994;256:119–24.View ArticleGoogle Scholar
- Force A, Lynch M, Pickett FB, Amores A, Yan Y, Postlethwait J. Preservation of duplicate genes by complementary, degenerative mutations. Genetics. 1999;151:1531–45.PubMed CentralPubMedGoogle Scholar
- Stoltzfus A. On the possibility of constructive neutral evolution. J Mol Evol. 1999;49:169–81.PubMedView ArticleGoogle Scholar
- He X, Zhang J. Rapid subfunctionalization accompanied by prolonged and substantial neofunctionalization in duplicate gene evolution. Genetics. 2005;169:1157–64.PubMed CentralPubMedView ArticleGoogle Scholar
- Assis R, Bachtrog D. Neofunctionalization of young duplicate genes in Drosophila. Proc Natl Acad Sci U S A. 2013;110:17409–14.PubMed CentralPubMedView ArticleGoogle Scholar
- Brawand D, Soumillon M, Necsulea A, Julien P, Csardi G, Harrigan P, et al. The evolution of gene expression levels in mammalian organs. Nature. 2011;478:343–8.PubMedView ArticleGoogle Scholar
- Gu Z, Nicolae D, Lu HH, Li WH. Rapid divergence in expression between duplicate genes inferred from microarray data. Trends Genet. 2002;18:609–13.PubMedView ArticleGoogle Scholar
- Wagner A. Asymmetric functional divergence of duplicate genes in yeast. Mol Biol Evol. 2002;19:1760–8.PubMedView ArticleGoogle Scholar
- Makova KD, Li WH. Divergence in the spatial pattern of gene expression between human duplicate genes. Genome Res. 2003;13:1638–45.PubMed CentralPubMedView ArticleGoogle Scholar
- Gu Z, Rifkin SA, White KP, Li WH. Duplicate genes increase gene expression diversity within and between species. Nat Genet. 2004;36:577–9.PubMedView ArticleGoogle Scholar
- Gu X, Zhang Z, Huang W. Rapid evolution of expression and regulatory divergences after yeast gene duplication. Proc Natl Acad Sci U S A. 2005;102:707–12.PubMed CentralPubMedView ArticleGoogle Scholar
- Li WH, Yang J, Gu X. Expression divergence between duplicate genes. Trends Genet. 2005;21:602–7.PubMedView ArticleGoogle Scholar
- Casneuf T, Bodt SD, Raes J, Maere S, Van de Peer Y. Nonrandom divergence of gene expression following gene and genome duplications in the flowering plant Arabidopsis thaliana. Genome Biol. 2006;7:R13.PubMed CentralPubMedView ArticleGoogle Scholar
- Chung WY, Albert R, Albert I, Nekrutenko A, Makova KD. Rapid and asymmetric divergence of duplicate genes in the human gene coexpression network. BMC Bioinformatics. 2006;7:46.PubMed CentralPubMedView ArticleGoogle Scholar
- Ganko EW, Meyers BC, Vision TJ. Divergence in expression between duplicated genes in Arabidopsis. Mol Biol Evol. 2007;24:2298–309.PubMedView ArticleGoogle Scholar
- Farrè D, Albà MM. Heterogeneous patterns of gene-expression diversification in mammalian gene duplicates. Mol Biol Evol. 2010;27(2):325–35.PubMedView ArticleGoogle Scholar
- Huminiecki L, Wolfe KH. Divergence of spatial gene expression profiles following species-specific gene duplications in human and mouse. Genome Res. 2004;14:1870–9.PubMed CentralPubMedView ArticleGoogle Scholar
- Huerta-Cepas J, Dopazo J, Huynen MA, Gabaldón T. Evidence for short-time divergence and long-time conservation of tissue-specific expression after gene duplication. Briefings in Bioinformatics. 2011; doi:10.1093/bib/bbr022
- Lazzaro B. Elevated polymorphism and divergence in the class c scavenger receptors of Drosophila melanogaster and D. simulans. Genetics. 2005;169:2023–34.PubMed CentralPubMedView ArticleGoogle Scholar
- Richards S, Liu Y, Bettencourt BR, Hradecky P, Letovsky S, Nielsen R, et al. Comparative genome sequencing of Drosophila pseudoobscura: chromosomal, gene, and cis-element evolution. Genome Res. 2005;15:1–18.PubMed CentralPubMedView ArticleGoogle Scholar
- Chen FC, Li WH. Genomic divergences between humans and other hominoids and the effective population size of the common ancestor of humans and chimpanzees. Am J Hum Genet. 2001;68:444–56.PubMed CentralPubMedView ArticleGoogle Scholar
- Warren WC, Hillier LW, Marshall Graves JA, Birney E, Ponting CP, Grützner F, et al. Genome analysis of the platypus reveals unique signatures of evolution. Nature. 2008;453:175–83.PubMed CentralPubMedView ArticleGoogle Scholar
- Beckenbach AT, Wei YW, Liu H. Relationships in the Drosophila obscura species group inferred from mitochondrial cytochrome oxidase II sequences. Mol Biol Evol. 1993;10:619–34.PubMedGoogle Scholar
- Lynch M, Conery S. The origins of genome complexity. Science. 2003;302:1401–4.PubMedView ArticleGoogle Scholar
- Jensen JD, Bachtrog D. Characterizing the influence of effective population size on the rate of adaptation, Gillespie’s Darwin domain. Genome Biol Evol. 2011;3:687–701.PubMed CentralPubMedView ArticleGoogle Scholar
- Britten RJ. Rates of DNA sequence evolution differ between taxonomic groups. Science. 1986;231:1393–8.PubMedView ArticleGoogle Scholar
- Moriyama EN. Higher rates of nucleotide substitution in Drosophila than in mammals. Jpn J Genetics. 1987;62:139–47.View ArticleGoogle Scholar
- Carroll SB. Evolution at two levels, on genes and form. PLoS Biol. 2005;3:e245.PubMed CentralPubMedView ArticleGoogle Scholar
- Lynch M, O’hely M, Walsch B, Force A. The probability of preservation of a newly arisen gene duplicate. Genetics. 2001;159:1789–804.PubMed CentralPubMedGoogle Scholar
- Fares MA, Keane OM, Toft C, Carretero-Paulet L, Jones GW. The roles of whole-genome and small-scale duplications in the functional specialization of Saccharomyces cerevisiae genes. PLoS Genet. 2013;9:e1003176.PubMed CentralPubMedView ArticleGoogle Scholar
- Lynch M, Conery JS. The evolutionary fate and consequence of duplicate genes. Science. 2000;290:1151–5.PubMedView ArticleGoogle Scholar
- Chang AY, Liao BY. DNA methylation rebalances gene dosage after mammalian gene duplications. Mol Biol Evol. 2012;29:133–44.PubMedView ArticleGoogle Scholar
- Keller TE, Yi SV. DNA methylation and evolution of duplicate genes. Proc Natl Acad Sci U S A. 2014;111:5932–7.PubMed CentralPubMedView ArticleGoogle Scholar
- Kaessmann H. Origins, evolution, and phenotypic impact of new genes. Genome Res. 2010;20:1313–26.PubMed CentralPubMedView ArticleGoogle Scholar
- Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.PubMedView ArticleGoogle Scholar
- Ranwez V, Harispe S, Delsuc F, Douzery EJP. MACSE, Multiple Alignment of Coding SEquences accounting for frameshifts and stop codons. PLoS One. 2011;6:e22594.PubMed CentralPubMedView ArticleGoogle Scholar
- Yang Z. PAML 4, Phylogenetic Analysis by Maximum Likelihood. Mol Biol Evol. 2007;24:1586–91.PubMedView ArticleGoogle Scholar
- Pereira V, Waxman D, Eyre-Walker A. A problem with the correlation coefficient as a measure of gene expression divergence. Genetics. 2009;183:1597–600.PubMed CentralPubMedView ArticleGoogle Scholar
- R Development Core Team. R, A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2009.Google Scholar
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