Programmed DNA elimination of germline development genes in songbirds, bioRxiv, 2018-10-16
Genomes can vary within individual organisms. Programmed DNA elimination leads to dramatic changes in genome organisation during the germline-soma differentiation of ciliates, lampreys, nematodes, and various other eukaryotes. A particularly remarkable example of tissue-specific genome differentiation is the germline-restricted chromosome (GRC) in the zebra finch which is consistently absent from somatic cells. Although the zebra finch is an important animal model system, molecular evidence from its large GRC (>150 megabases) is limited to a short intergenic region and a single mRNA. Here, we combined cytogenetic, genomic, transcriptomic, and proteomic evidence to resolve the evolutionary origin and functional significance of the GRC. First, by generating tissue-specific de-novo linked-read genome assemblies and re-sequencing two additional germline and soma samples, we found that the GRC contains at least 115 genes which are paralogous to single-copy genes on 18 autosomes and the Z chromosome. We detected an amplification of 38 GRC-linked genes into high copy numbers (up to 308 copies) but, surprisingly, no enrichment of transposable elements on the GRC. Second, transcriptome and proteome data provided evidence for functional expression of GRC genes at the RNA and protein levels in testes and ovaries. Interestingly, the GRC is enriched for genes with highly expressed orthologs in chicken gonads and gene ontologies involved in female gonad development. Third, we detected evolutionary strata of GRC-linked genes. Genes such as bicc1 and trim71 have resided on the GRC for tens of millions of years, whereas dozens have become GRC-linked very recently. The GRC is thus likely widespread in songbirds (half of all bird species) and its rapid evolution may have contributed to their diversification. Together, our results demonstrate a highly dynamic evolutionary history of the songbird GRC leading to dramatic germline-soma genome differences as a novel mechanism to minimize genetic conflict between germline and soma.
biorxiv evolutionary-biology 200-500-users 2018A Multi-State Birth-Death model for Bayesian inference of lineage-specific birth and death rates, bioRxiv, 2018-10-11
AbstractHeterogeneous populations can lead to important differences in birth and death rates across a phylogeny Taking this heterogeneity into account is thus critical to obtain accurate estimates of the underlying population dynamics. We present a new multi-state birth-death model (MSBD) that can estimate lineage-specific birth and death rates. For species phylogenies, this corresponds to estimating lineage-dependent speciation and extinction rates. Contrary to existing models, we do not require a prior hypothesis on a trait driving the rate differences and we allow the same rates to be present in different parts of the phylogeny. Using simulated datasets, we show that the MSBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a re-analysis of two empirical datasets and compare the results obtained by MSBD and by the existing software BAMM. The MSBD model is implemented as a package in the Bayesian inference software BEAST2, which allows joint inference of the phylogeny and the model parameters.Significance statementPhylogenetic trees can inform about the underlying speciation and extinction processes within a species clade. Many different factors, for instance environmental changes or morphological changes, can lead to differences in macroevolutionary dynamics within a clade. We present here a new multi-state birth-death (MSBD) model that can detect these differences and estimate both the position of changes in the tree and the associated macroevolutionary parameters. The MSBD model does not require a prior hypothesis on which trait is driving the changes in dynamics and is thus applicable to a wide range of datasets. It is implemented as an extension to the existing framework BEAST2.
biorxiv evolutionary-biology 0-100-users 2018Bayesian Estimation of Species Divergence Times Using Correlated Quantitative Characters, bioRxiv, 2018-10-11
Discrete morphological data have been widely used to study species evolution, but the use of quantitative (or continuous) morphological characters is less common. Here, we implement a Bayesian method to estimate species divergence times using quantitative characters. Quantitative character evolution is modelled using Brownian diffusion with character correlation and character variation within populations. Through simulations, we demonstrate that ignoring the population variation (or population noise) and the correlation among characters leads to biased estimates of divergence times and rate, especially if the correlation and population noise are high. We apply our new method to the analysis of quantitative characters (cranium landmarks) and molecular data from carnivoran mammals. Our results show that time estimates are affected by whether the correlations and population noise are accounted for or ignored in the analysis. The estimates are also affected by the type of data analysed, with analyses of morphological characters only, molecular data only, or a combination of both; showing noticeable differences among the time estimates. Rate variation of morphological characters among the carnivoran species appears to be very high, with Bayesian model selection indicating that the independent-rates model fits the morphological data better than the autocorrelated-rates model. We suggest that using morphological continuous characters, together with molecular data, can bring a new perspective to the study of species evolution. Our new model is implemented in the MCMCtree computer program for Bayesian inference of divergence times.
biorxiv evolutionary-biology 0-100-users 2018Exploiting selection at linked sites to infer the rate and strength of adaptation, bioRxiv, 2018-09-26
Genomic data encodes past evolutionary events and has the potential to reveal the strength, rate, and biological drivers of adaptation. However, robust estimation of adaptation rate (alpha) and adaptation strength remains a challenging problem because evolutionary processes such as demography, linkage, and non-neutral polymorphism can confound inference. Here, we exploit the influence of background selection to reduce the fixation rate of weakly-beneficial alleles to jointly infer the strength and rate of adaptation. We develop a novel MK-based method (ABC-MK) to infer adaptation rate and strength, and estimate alpha=0.135 in human protein-coding sequences, 72% of which is contributed by weakly adaptive variants. We show that in this adaptation regime alpha is reduced approx. 25% by linkage genome-wide. Moreover, we show that virus-interacting proteins (VIPs) undergo adaptation that is both stronger and nearly twice as frequent as the genome average (alpha=0.224, 56% due to strongly-beneficial alleles). Our results suggest that while most adaptation in human proteins is weakly-beneficial, adaptation to viruses is often strongly-beneficial. Our method provides a robust framework for estimating adaptation rate and strength across species.
biorxiv evolutionary-biology 0-100-users 2018Stronger and higher proportion of beneficial amino acid changing mutations in humans compared to mice and flies, bioRxiv, 2018-09-26
ABSTRACTQuantifying and comparing the amount of adaptive evolution among different species is key to understanding evolutionary processes. Previous studies have shown differences in adaptive evolution across species, however their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and estimate that 30–34% of nonsynonymous substitutions between humans and outgroup species have been fixed by positive selection. This estimate is much higher than previous estimates, which did not account for the population size of the outgroup species. Next, we directly estimate the proportion and selection coefficients of newly arising strongly beneficial nonsynonymous mutations in humans, mice, and D. melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same proportion and the same selection coefficients of beneficial mutations across species, and estimate that humans have a higher proportion of beneficial mutations compared to Drosophila and mice. We demonstrate that this result cannot be attributed to biased gene conversion. In summary, we find the proportion of beneficial mutations is higher in humans than in D. melanogaster or mice, suggesting that organismal complexity, which increases the number of steps required in adaptive walks, may be a key predictor of the amount of adaptive evolution within a species.
biorxiv evolutionary-biology 0-100-users 2018How to make a rodent giant Genomic basis and tradeoffs of gigantism in the capybara, the world’s largest rodent, bioRxiv, 2018-09-23
AbstractGigantism is the result of one lineage within a clade evolving extremely large body size relative to its small-bodied ancestors, a phenomenon observed numerous times in animals. Theory predicts that the evolution of giants should be constrained by two tradeoffs. First, because body size is negatively correlated with population size, purifying selection is expected to be less efficient in species of large body size, leading to a genome-wide elevation of the ratio of non-synonymous to synonymous substitution rates (dNdS) or mutation load. Second, gigantism is achieved through higher number of cells and higher rates of cell proliferation, thus increasing the likelihood of cancer. However, the incidence of cancer in gigantic animals is lower than the theoretical expectation, a phenomenon referred to as Peto’s Paradox. To explore the genetic basis of gigantism in rodents and uncover genomic signatures of gigantism-related tradeoffs, we sequenced the genome of the capybara, the world’s largest living rodent. We found that dNdS is elevated genome wide in the capybara, relative to other rodents, implying a higher mutation load. Conversely, a genome-wide scan for adaptive protein evolution in the capybara highlighted several genes involved in growth regulation by the insulininsulin-like growth factor signaling (IIS) pathway. Capybara-specific gene-family expansions included a putative novel anticancer adaptation that involves T cell-mediated tumor suppression, offering a potential resolution to Peto’s Paradox in this lineage. Gene interaction network analyses also revealed that size regulators function simultaneously as growth factors and oncogenes, creating an evolutionary conflict. Based on our findings, we hypothesize that gigantism in the capybara likely involved three evolutionary steps 1) Increase in body size by cell proliferation through the ISS pathway, 2) coupled evolution of growth-regulatory and cancer-suppression mechanisms, possibly driven by intragenomic conflict, and 3) establishment of the T cell-mediated tumor suppression pathway as an anticancer adaptation. Interestingly, increased mutation load appears to be an inevitable outcome of an increase in body size.Author SummaryThe existence of gigantic animals presents an evolutionary puzzle. Larger animals have more cells and undergo exponentially more cell divisions, thus, they should have enormous rates of cancer. Moreover, large animals also have smaller populations making them vulnerable to extinction. So, how do gigantic animals such as elephants and blue whales protect themselves from cancer, and what are the consequences of evolving a large size on the ‘genetic health’ of a species? To address these questions we sequenced the genome of the capybara, the world’s largest rodent, and performed comparative genomic analyses to identify the genes and pathways involved in growth regulation and cancer suppression. We found that the insulin-signaling pathway was involved in the evolution of gigantism in the capybara. We also found a putative novel anticancer mechanism mediated by the detection of tumors by T-cells, offering a potential solution to how capybaras mitigated the tradeoff imposed by cancer. Furthermore, we show that capybara genome harbors a higher proportion of slightly deleterious mutations relative to all other rodent genomes. Overall, this study provides insights at the genomic level into the evolution of a complex and extreme phenotype, and offers a detailed picture of how the evolution of a giant body size in the capybara has shaped its genome.
biorxiv evolutionary-biology 100-200-users 2018