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W4313302397 abstract "Article Figures and data Abstract Editor's evaluation eLife digest Introduction Results Discussion Methods Data availability References Decision letter Author response Article and author information Metrics Abstract Body hair is a defining mammalian characteristic, but several mammals, such as whales, naked mole-rats, and humans, have notably less hair. To find the genetic basis of reduced hair quantity, we used our evolutionary-rates-based method, RERconverge, to identify coding and noncoding sequences that evolve at significantly different rates in so-called hairless mammals compared to hairy mammals. Using RERconverge, we performed a genome-wide scan over 62 mammal species using 19,149 genes and 343,598 conserved noncoding regions. In addition to detecting known and potential novel hair-related genes, we also discovered hundreds of putative hair-related regulatory elements. Computational investigation revealed that genes and their associated noncoding regions show different evolutionary patterns and influence different aspects of hair growth and development. Many genes under accelerated evolution are associated with the structure of the hair shaft itself, while evolutionary rate shifts in noncoding regions also included the dermal papilla and matrix regions of the hair follicle that contribute to hair growth and cycling. Genes that were top ranked for coding sequence acceleration included known hair and skin genes KRT2, KRT35, PKP1, and PTPRM that surprisingly showed no signals of evolutionary rate shifts in nearby noncoding regions. Conversely, accelerated noncoding regions are most strongly enriched near regulatory hair-related genes and microRNAs, such as mir205, ELF3, and FOXC1, that themselves do not show rate shifts in their protein-coding sequences. Such dichotomy highlights the interplay between the evolution of protein sequence and regulatory sequence to contribute to the emergence of a convergent phenotype. Editor's evaluation Several mammal species, including dolphins, have evolved to be relatively hairless. In this important work, Kowalczyk and colleagues scan the genomes of multiple species to identify genomic regions that appear to have evolved at a faster or slower evolutionary rate along hairless lineages. Using convincing analyses, they identify a number of protein-coding genes as well as noncoding regions that might explain how hairlessness evolved in mammals. This study is of interest to those investigating the development of the skin and its appendages as well as evolutionary biologists, especially those investigating instances of convergent evolution and those developing phylogenomic methods for genome comparisons. https://doi.org/10.7554/eLife.76911.sa0 Decision letter Reviews on Sciety eLife's review process eLife digest Whales, elephants, humans, and naked mole-rats all share a somewhat rare trait for mammals: their bodies are covered with little to no hair. The common ancestors of each of these species are considerably hairier which must mean that hairlessness evolved multiple times independently. When distantly related species evolve similar traits, it can be interpreted as a certain aspect of their evolution repeating itself. This process is called ‘convergent evolution’ and may provide insights about how different species were able to arrive at the same outcome. One possibility is that they have undergone similar genetic changes such as turning on or off key genes that play a role in the trait’s development. Kowalczyk et al. set out to identify what genetic changes may have contributed to the convergent evolution of hairlessness in unrelated species of mammals. By looking at the genomes of 62 mammalian species, they hoped to link specific genomic elements to the origins of the hairless trait. The genetic sequences under investigation included nearly 20,000 genes that encode information about how to make proteins, as well as 350,000 regulatory sequences composed of non-coding DNA, which specify when and how genes are activated. This marks the first time genetic mechanisms behind various hair traits have been studied in such a diverse group of mammals. Using a computational approach, Kowalczyk et al. identified parts of the genome that have evolved similarly in mammalian species that have lost their hair. They found that genes and regulatory sequences, that had been previously associated with hair growth, accumulated mutations at significantly different rates in hairless versus hairy mammals. This indicates that these regions associated hair growth are also related to evolution of hairlessness. This includes several genes that encode keratin proteins, the main material that makes up hair. The team also reported an increased rate of evolution in genes and regulatory sequences that were not previously known to be involved in hair growth or hairlessness in mammals. Together these results suggest that a specific set of genetic changes have occurred several times in different mammalian lineages to drive the evolution of hairlessness in unrelated species. Kowalczyk et al. describe the parts of the genome that may be involved in controlling hair growth. Once their findings are validated, they could be used to develop treatments for hair loss in humans. Additionally, their computational approach could be applied to other examples of convergent evolution where genomic data is available, allowing scientists to better understand how the same traits evolve in different species. Introduction Hair is a defining mammalian characteristic with a variety of functions, from sensory perception to heat retention to skin protection (Pough et al., 1989). Although the mammalian ancestor is believed to have had hair, and in fact the development of hair is a key evolutionary innovation along the mammalian lineage (Eckhart et al., 2008), numerous mammals subsequently lost much of their hair. Many marine mammals, including whales, dolphins, porpoises, manatees, dugongs, and walruses, have sparse hair coverage likely related to hydrodynamic adaptations to allow those species to thrive in a marine environment (Chen et al., 2013; Nery et al., 2014). Large terrestrial mammals such as elephants, rhinoceroses, and hippopotamuses also have little hair, likely to enable heat dissipation diminished by the species’ large sizes (Fuller et al., 2016). Notably, humans are also relatively hairless, a phenotypic characteristic that, while stark, has long been of mysterious origin (Kushlan, 1980). Just as hair coverage varies across mammal species, coverage for an individual organism can change over time in response to environmental factors. For example, Arctic mammals such as foxes and hares famously demonstrate dramatic coat changes in different seasons (Johnson, 1981). Hair follicles are established during embryonic development as a result of interactions between epithelial and mesenchymal cells in the skin, and such interactions also drive follicle movement in adults (Zhou et al., 2018). Hair follicles consist of a complex set of structures under the skin that support the hair shaft itself, which protrudes above the skin. The hair shaft contains an outer layer called the cuticle, an inner cortex later, and sometimes a central medulla core (Plowman et al., 2018). Structures under the skin support the growth and formation of the hair follicle. Of particular interest are the dermal papilla and matrix region, both located at the base of the hair follicle. The dermal papilla is a key controller of regulation of hair growth and follicle morphogenesis (Veraitch et al., 2017). In fact, transplantation of dermal papilla cells has been repeatedly demonstrated to result in hair growth in previously hairless tissue (Jahoda et al., 1984; Jahoda et al., 1993; Reynolds and Jahoda, 1992). Just above the dermal papilla, the matrix generates stem cells to the growing hair shaft and the root sheath (Plowman et al., 2018). The two regions work together to regulate and carry out hair growth – the dermal papilla is the master controller that instructs the hair-growing engine of the matrix region. During hair growth, a hair follicle goes through three stages of growth called anagen, catagen, and telogen phases. During the anagen phase, the hair shaft is generated and grows out through the skin, while catagen phase ends hair growth and telogen phase causes the follicle to become dormant (Alonso and Fuchs, 2006). Changes to several hair-related genes are known to result in hairlessness in specific species. The Hr gene in mice, so named because of its role in the hair phenotype, results in hairless mice when knocked out (Benavides et al., 2009). In Mexican dogs, the FOXI3 gene has been found to be associated not only with hairlessness, but also associated with dental abnormalities (Drögemüller et al., 2008). In the American Hairless Terrier, mutation in a different gene, SGK3, is responsible for relative hairlessness (Parker et al., 2017). Fibroblast growth factor genes such as FGF5 and FGF7 are also heavily implicated in hair growth because their absence causes drastic changes to coat length and appearance in mice (Ahmad et al., 1998). Such genes are associated with keratinocyte growth in which keratins and keratin-associated proteins play a key role. Unsurprisingly, specific structural proteins that comprise hair shafts and their associated genes, known as KRTAP genes or hair-specific keratins, are also heavily implicated in hair-related functions (Plowman et al., 2018). They also appear to be unique to mammals, although some KRTAP-like genes have been found in reptiles (Eckhart et al., 2008). Although genetic changes associated with induced hairlessness in specific domesticated species are useful, it is unclear whether such changes reflect evolutionary changes that result in spontaneous hairlessness and how much such changes are convergent across all or many naturally hairless species. By taking advantage of natural biological replicates of independent evolution of hairlessness in mammals, we can learn about global genetic mechanisms underlying the hairless phenotype. Mammalian hairlessness is a convergent trait since it independently evolved multiple times across the mammalian phylogeny. We can therefore characterize the nature of its convergence at the molecular level to provide insights into the mechanisms underlying the trait. For example, if a gene is evolving quickly in hairless species and slowly in non-hairless species, that implies that the gene may be associated with hairlessness. We focus on the relative evolutionary rate of genomic sequence, which is a measure of how fast the sequence is evolving relative to its expected rate. Unlike seeking sequence convergence to a specific amino acid or nucleotide, using an evolutionary-rates-based method detects convergent shifts in evolutionary rates across an entire region of interest (such as a gene or putative regulatory element). Evolutionary rate shifts reflect the amount of evolutionary pressure acting on genomic elements, and multiple studies investigating diverse phenotypes have found that phenotypic convergence is indeed associated with convergent changes in evolutionary rates (Chikina et al., 2016; Hiller et al., 2012; Hu et al., 2019; Kapheim et al., 2015; Kowalczyk et al., 2020; Partha et al., 2017; Partha et al., 2019; Prudent et al., 2016; Wertheim et al., 2015). We used RERconverge, an established computational pipeline, to link convergently evolving genes and noncoding regions to convergent evolution of mammalian hairlessness. Previous work using RERconverge (Kowalczyk et al., 2019) to detect convergent evolutionary rate shifts in genes and noncoding elements associated with convergently evolving traits has identified the putative genetic basis of the marine phenotype in mammals (Chikina et al., 2016), the fossorial phenotype in subterranean mammals (Partha et al., 2017; Partha et al., 2019), and extreme longevity in mammals (Kowalczyk et al., 2020). Those studies revealed trends that are not species-specific, but instead represent relevant genetic changes that occurred phylogeny-wide. Here, we further explored the genetic basis of hairlessness across the mammalian phylogeny by finding genes and noncoding regions under relaxation of evolutionary constraint (i.e., evolving faster) in hairless species. Such genetic elements likely have reduced selective constraint in species with less hair and thus accumulate substitutions at a more rapid rate. To find genetic elements under accelerated evolution in hairless species, we performed a genome-wide scan across 62 mammal species using RERconverge on 19,149 orthologous genes and 343,598 conserved noncoding elements. In addition to recapturing known hair-related elements, we also identified novel putative hair-related genetic elements previously overlooked by targeted studies. Importantly, newly uncovered genes and noncoding regions were not only related to keratins, but they also represented a suite of genetic functionality underlying hair growth. Such findings represent strong candidates for future experimental testing related to the hair phenotype. Results Phenotype assignment The hairless phenotype in mammals arose at least nine independent times along the mammalian phylogeny (Figure 1A, Figure 1—source data 1). Genomic regions that experienced evolutionary rate shifts in tandem with mammalian loss of hair were considered potentially associated with phenotype loss. Ten extant and one ancestral hairless species were identified based on species hair density (Figure 1A). Broadly, species with skin visible through hair were classified as hairless, namely, rhinoceros, elephant, naked mole-rat, human, pig, armadillo, walrus, manatee, dolphin, and orca. The cetacean (dolphin-orca) ancestor was also included because it was likely a hairless marine mammal. Figure 1 with 11 supplements see all Download asset Open asset Hairless species show an enrichment of hair-related genes and noncoding elements whose evolutionary rates are significantly associated with phenotype evolution. (A) Phylogenetic tree showing a subset of the 62 mammal species used for analyses. Note that all 62 species were included in analyses and only a subset are shown here for visualization purposes. Foreground branches representing the hairless phenotype are depicted in orange alongside photographs of the species. (B) Q-Q plots for uniformity of permulation p-values for association tests per genetic element for coding and noncoding elements. Shown are both positive associations that indicate accelerated evolution in hairless species and negative associations that indicate decelerated evolution in hairless species. The deviation from the red line (the identity) indicates an enrichment of low permulation p-values – there are more significant permulation p-values than we would observe under the uniform null expectation. This indicates significant evolutionary rate shifts for many genes and noncoding elements in hairless mammals. (C) Hair-related Mouse Genome Informatics (MGI) category genes are under significantly accelerated evolution in hairless species. Shown are the AUC (Area Under the Receiver Operating Characteristic curve) values minus 0.5 (maximum enrichment statistic = 0.5, minimum enrichment statistic = –0.5; statistic = 0 indicates no enrichment) for each hair- or skin-related pathway with a permulation p-value≤0.01. In parentheses are the statistic-based ranks of those pathways among all pathways under accelerated evolution in hairless mammals with permulation p-values≤0.01. (D) Skin- and hair-expressed genes are under significant evolutionary rate acceleration in hairless species. All genesets except hair follicle are from the GTEx tissue expression database. Hair follicle genes are the top 69 most highly expressed genes from Zhang et al., 2017 hair follicle RNA sequencing that are not ubiquitously expressed across GTEx tissue types. Figure 1—source data 1 Phenotypes. Species phenotype information (weight, marine status, and hairless status), names, and genome codes. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data1-v2.csv Download elife-76911-fig1-data1-v2.csv Figure 1—source data 2 Gene results. Full gene results, including gene name, UCID, RERconverge results, Bayes factor results, and enrichment statistics, for nearby noncoding regions. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data2-v2.xlsx Download elife-76911-fig1-data2-v2.xlsx Figure 1—source data 3 Conserved noncoding element results. Conserved noncoding element RERconverge results. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data3-v2.csv Download elife-76911-fig1-data3-v2.csv Figure 1—source data 4 Positive selection results. Results from branch-site models to test for positive selection on KRTs, KRTAPs, and genes under accelerated evolution in hairless species. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data4-v2.csv Download elife-76911-fig1-data4-v2.csv Figure 1—source data 5 Pathway enrichment results. Pathway enrichment results from coding and noncoding regions. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data5-v2.xlsx Download elife-76911-fig1-data5-v2.xlsx Figure 1—source data 6 Pathway enrichment results with no KRT or KRTAP genes. Pathway enrichment results from coding regions after removing all KRT and KRTAP proteins. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data6-v2.xlsx Download elife-76911-fig1-data6-v2.xlsx Figure 1—source data 7 hg19 coordinates for conserved noncoding elements. Human genome (hg19) coordinates for all conserved noncoding elements. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data7-v2.txt Download elife-76911-fig1-data7-v2.txt Figure 1—source data 8 mm10 coordinates for conserved noncoding elements. Mouse genome (mm10) coordinates for all conserved noncoding elements. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data8-v2.txt Download elife-76911-fig1-data8-v2.txt Figure 1—source data 9 Shared genes in Mouse Genome Informatics (MGI) and tissue expression pathway annotations. Number of genes annotated and number of annotated genes shared for MGI and tissue expression enrichment results in Figure 1C and D. https://cdn.elifesciences.org/articles/76911/elife-76911-fig1-data9-v2.xlsx Download elife-76911-fig1-data9-v2.xlsx An ancestral point of phenotypic ambiguity existed at the ancestor of manatee and elephant. Considerable uncertainty exists as to whether the ancestral species had hair and independent trait losses occurred on the manatee and elephant lineages or, alternatively, whether the ancestral species lost hair prior to manatee–elephant divergence and regained hair along mammoth lineages post-divergence (Roca et al., 2009). Since foreground assignment of the manatee–elephant ancestor had little impact on skin-specific signal, we retained the parsimonious assignment of the ancestral species as haired with inferred independent losses in the manatee and post-mammoth elephant lineages (Figure 1—figure supplement 1B). Similarly, assigning foreground branches based on the state of being hairless or the transition from haired to hairless – that is, assigning the entire cetacean clade as foreground versus only assigning the cetacean ancestor as foreground – had little impact on skin-specific signal (Figure 1—figure supplement 1A). In the case of cetaceans, we retained all three branches (orca, dolphin, and the orca-dolphin ancestor) as foreground to maximize statistical power. Phenotypic confounders Hairless species share other convergent characteristics that could confound associations between the hairless phenotype and evolutionary rate shifts. In particular, several hairless species are large and many are marine mammals. Therefore, any signal related to hairless species could be driven instead by confounders. Problems with these two confounders were handled in two different ways. To handle large body size as a confounder, body size was regressed from relative evolutionary rates on an element-by-element basis. In other words, the residuals from the linear relationship between body size and relative evolutionary rates were retained to eliminate the effect of body size on relative evolutionary rate trend. In doing so, any effects related to the relationship between body size and hairlessness were mitigated. Marine status, on the other hand, is a trait of potential interest because marine mammals experienced unique hair and skin changes during the transition from a terrestrial to a marine environment. However, it is also of interest how much signal is driven by the marine phenotype versus the hairless phenotype. Therefore, Bayes factors were used to quantify the amount of support for the marine phenotype versus the hairless phenotype. A larger Bayes factor indicated more contribution from one model versus another. A ratio of 5 or greater for the hairless phenotype versus the marine phenotype indicated strongly more support for signal driven by hairlessness. Many hair-related pathways evolving faster in hairless species according to RERconverge also indicated that signal was indeed driven by the hairless phenotype as opposed to its heavy confounder, the marine phenotype, according to Bayes factor analyses (Figure 2). Figure 2 Download asset Open asset Bayes factors reveal the proportion of signal driven by the marine phenotype versus the hairless phenotype. Depicted are precision-recall curves demonstrating how Bayes factors of the contrasting hairless and marine phenotypes rank genes related to skin, hair, and olfaction. Also plotted is a ranking based on the ratio of hairlessness and marine Bayes factors (hVSm = hairlessness Bayes factor/marine Bayes factor). The ratio of the Bayes factors quantifies the amount of support for the hairless phenotype beyond the support for the marine phenotype per gene. In other words, a high Bayes factor ratio indicates a signal of evolutionary convergence associated with hairlessness that is not only driven by signals of convergence in hairless marine mammals. The hairless phenotype had much greater power to enrich for genes expressed in skin (GTEx data) compared to the marine phenotype, indicating that accelerated evolution is driven more strongly by hairlessness. Both the marine and hairless phenotypes enriched for genes in hair follicle expression genes, indicating that both contribute to accelerated evolution of those genes. Olfactory genes, on the other hand, are expected to show acceleration only related to the marine phenotype. As expected, the marine phenotype is much more strongly enriched for olfactory genes than the hairless phenotype. Species-specific analyses In addition to conducting convergent evolution analyses to identify genetic elements evolving at different rates across all hairless species, we also conducted complementary analyses to detect elements evolving at different rates in individual hairless species to demonstrate the importance of convergent evolution in our analyses. Indeed, the strength of enrichment for hair follicle-related genes among top hits steadily increases as more hairless species share rate shifts in those genes, an indicator of the power of the convergent signal (Figure 3). Further, analyses on single species alone only show enrichment for hair follicle-related genes among top hits in 2 hairless species out of 10 – armadillo and pig (Figure 3—figure supplement 1). Together, these results demonstrate the importance of testing for convergent evolutionary rate shifts across all hairless mammals to best detect hair-related elements. Figure 3 with 1 supplement see all Download asset Open asset Convergent analyses show stronger enrichment for hair-related genes than single-species analyses. Each hairless species was individually tested for a significant rate shift compared to non-hairless species using a Wilcoxon signed-rank test. Then a Fisher’s exact test was used to test for an enrichment of hair follicle genes (as shown in Figure 1D) with a minimum number of hairless species, ranging from 1 species to all 10 species, with significant rate shifts. Note that the odds ratio for an enrichment with a minimum of one species is not well defined because most genes genome-wide have at least one hairless species with a significant rate shift (18,582 genes out of 18,822 that could be tested), including all hair follicle genes, and their enrichment was not significant (p=0.64). Overall, enrichment strength increases moving from left to right on the plot as the geneset of interest becomes restricted to genes with a larger number of species with rate shifts, although p-values are less extreme because there are simply fewer genes in those categories with higher numbers of species. This demonstrates the convergent signal that allows for detection of hair-related genetic elements based on shared rate shifts. Figure 3—source data 1 Species-specific analysis results. Species-specific analysis results shown in Figure 2 and its supplement. Included are Wilcoxon signed-rank test results per species per gene, hair enrichment per species, hair enrichment per minimum species cutoff, and total number of genes with significant shifts per species. https://cdn.elifesciences.org/articles/76911/elife-76911-fig3-data1-v2.xlsx Download elife-76911-fig3-data1-v2.xlsx Also of important note is that every individual hairless species has thousands of genes with significant rate shifts in that species (Figure 3—source data 1). It is impossible to tell which of those rate shifts is associated with hairlessness specifically because the species have many unique phenotypes other than hairlessness that could be responsible for rate shifts in their respective genes. Convergent analyses allow for more concrete identification of hair-related elements by weeding out rate shifts that are not shared across species with the convergent hairless phenotype. Known hair-related genetic elements evolve faster in hairless species We used RERconverge to identify genes and noncoding elements evolving at significantly faster or slower rates in hairless species compared to haired species (see ‘Methods’). Briefly, the evolutionary rates of genetic elements were compared in hairless versus haired species using a rank-based hypothesis test, and we generated p-values empirically with a newly developed method, termed permulations, that uses phylogenetically constrained phenotype permutations (Saputra et al., 2020). The permulation method compares the correlation statistics from the true phenotype to correlation statistics that arise from randomized phenotypes that preserve the relative species relationships. Thus, small p-values indicate a specific association with the hairless phenotype. We find that quantile–quantile (Q-Q) plots of permulation p-values from hypothesis tests for all genetic elements indicate a large deviation from the expected uniform distribution and thus an enrichment of significant permulation p-values (Figure 1B, Figure 1—source data 2 and 3). Interestingly, noncoding regions appeared to show even stronger deviation from uniformity than coding regions, perhaps because regulatory changes more strongly underlie the convergent evolution of hairlessness. For both coding and noncoding regions, we show enrichment of significant p-values for both positive and negative evolutionary rate shifts, and the direction of the rate shifts is critical to interpretation. Positive rate shifts imply rate acceleration, which we interpret as a relaxation of evolutionary constraint. While positive rate shifts could theoretically be driven by positive selection, we demonstrate that this is not the case for our top-accelerated genes. Branch-site models to test for positive selection were performed using Phylogenetic Analysis by Maximum Likelihood (PAML) (Yang, 2007) on top-accelerated genes. Tests showed little evidence for foreground-specific positive selection; out of 199 genes tested, 27 genes demonstrated hairless acceleration, but all such genes also showed evidence for tree-wide positive selection, suggesting that positive selection was not specific to hairless species although perhaps stronger (Figure 1—source data 4). In fact, over half of our top genes from show evidence of pseudogenization, and therefore defunctionalized, in one or more hairless species (Table 1; Meyer et al., 2018). Thus, regions with positive rate shifts evolve faster in hairless species due to relaxation of evolutionary constraint, perhaps because of reduced functionality driving or in conjunction with the hairlessness phenotype. Negative rate shifts indicate increased evolutionary constraint in hairless species, which implies increased functional importance of a genomic region. While negative shifts are more difficult to interpret in the context of trait loss, they may represent compensatory phenotypic evolution in response to trait loss. Table 1 Genes whose evolutionary rates are significantly associated with the hairless phenotype with significant parametric p-values, significant permulation p-values, positive statistic, and hairless versus marine Bayes factors (BF) greater than five. BF marine and BF hairless are BF for those phenotypes individually, while BF hairless/BF marine is the ratio of the two. The ratio of the BF quantifies the amount of support for the hairless phenotype beyond the support for the marine phenotype per gene. In other words, a high BF ratio indicates a signal of evolutionary convergence associated with hairlessness that is not only driven by signals of convergence in hair" @default.
W4313302397 created "2023-01-06" @default.
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W4313302397 date "2022-03-21" @default.
W4313302397 modified "2023-09-26" @default.
W4313302397 title "Editor's evaluation: Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness" @default.
W4313302397 doi "https://doi.org/10.7554/elife.76911.sa0" @default.
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