Bayesian Detection of Convergent Rate Changes of Conserved Noncoding Elements on Phylogenetic Trees

Modeling Substitution Rate Evolution across Lineages and Relaxing the Molecular Clock

Relaxing the molecular clock using models of how substitution rates change across lineages has become essential for addressing evolutionary problems. The diversity of rate evolution models and their implementations are substantial, and studies have demonstrated their impact on divergence time estimates can be as significant as that of calibration information. In this review, we trace the development of rate evolution models from the proposal of the molecular clock concept to the development of sophisticated Bayesian and non-Bayesian methods that handle rate variation in phylogenies. We discuss the various approaches to modeling rate evolution, provide a comprehensive list of available software, and examine the challenges and advancements of the prevalent Bayesian framework, contrasting them to faster non-Bayesian methods. Lastly, we offer insights into potential advancements in the field in the era of big data.

A phylogenetic method linking nucleotide substitution rates to rates of continuous trait evolution

Genomes contain conserved non-coding sequences that perform important biological functions, such as gene regulation. We present a phylogenetic method, PhyloAcc-C, that associates nucleotide substitution rates with changes in a continuous trait of interest. The method takes as input a multiple sequence alignment of conserved elements, continuous trait data observed in extant species, and a background phylogeny and substitution process. Gibbs sampling is used to assign rate categories (background, conserved, accelerated) to lineages and explore whether the assigned rate categories are associated with increases or decreases in the rate of trait evolution. We test our method using simulations and then illustrate its application using mammalian body size and lifespan data previously analyzed with respect to protein coding genes. Like other studies, we find processes such as tumor suppression, telomere maintenance, and p53 regulation to be related to changes in longevity and body size. In addition, we also find that skeletal genes, and developmental processes, such as sprouting angiogenesis, are relevant.

Unifying approaches from statistical genetics and phylogenetics for mapping phenotypes in structured populations

In both statistical genetics and phylogenetics, a major goal is to identify correlations between genetic loci or other aspects of the phenotype or environment and a focal trait. In these two fields, there are sophisticated but disparate statistical traditions aimed at these tasks. The disconnect between their respective approaches is becoming untenable as questions in medicine, conservation biology, and evolutionary biology increasingly rely on integrating data from within and among species, and once-clear conceptual divisions are becoming increasingly blurred. To help bridge this divide, we derive a general model describing the covariance between the genetic contributions to the quantitative phenotypes of different individuals. Taking this approach shows that standard models in both statistical genetics (e.g., Genome-Wide Association Studies; GWAS) and phylogenetic comparative biology (e.g., phylogenetic regression) can be interpreted as special cases of this more general quantitative-genetic model. The fact that these models share the same core architecture means that we can build a unified understanding of the strengths and limitations of different methods for controlling for genetic structure when testing for associations. We develop intuition for why and when spurious correlations may occur using analytical theory and conduct population-genetic and phylogenetic simulations of quantitative traits. The structural similarity of problems in statistical genetics and phylogenetics enables us to take methodological advances from one field and apply them in the other. We demonstrate this by showing how a standard GWAS technique-including both the genetic relatedness matrix (GRM) as well as its leading eigenvectors, corresponding to the principal components of the genotype matrix, in a regression model-can mitigate spurious correlations in phylogenetic analyses. As a case study of this, we re-examine an analysis testing for co-evolution of expression levels between genes across a fungal phylogeny, and show that including covariance matrix eigenvectors as covariates decreases the false positive rate while simultaneously increasing the true positive rate. More generally, this work provides a foundation for more integrative approaches for understanding the genetic architecture of phenotypes and how evolutionary processes shape it.

Convergent genomic signatures associated with vertebrate viviparity

BACKGROUND

Viviparity-live birth-is a complex and innovative mode of reproduction that has evolved repeatedly across the vertebrate Tree of Life. Viviparous species exhibit remarkable levels of reproductive diversity, both in the amount of care provided by the parent during gestation, and the ways in which that care is delivered. The genetic basis of viviparity has garnered increasing interest over recent years; however, such studies are often undertaken on small evolutionary timelines, and thus are not able to address changes occurring on a broader scale. Using whole genome data, we investigated the molecular basis of this innovation across the diversity of vertebrates to answer a long held question in evolutionary biology: is the evolution of convergent traits driven by convergent genomic changes?

RESULTS

We reveal convergent changes in protein family sizes, protein-coding regions, introns, and untranslated regions (UTRs) in a number of distantly related viviparous lineages. Specifically, we identify 15 protein families showing evidence of contraction or expansion associated with viviparity. We additionally identify elevated substitution rates in both coding and noncoding sequences in several viviparous lineages. However, we did not find any convergent changes-be it at the nucleotide or protein level-common to all viviparous lineages.

CONCLUSIONS

Our results highlight the value of macroevolutionary comparative genomics in determining the genomic basis of complex evolutionary transitions. While we identify a number of convergent genomic changes that may be associated with the evolution of viviparity in vertebrates, there does not appear to be a convergent molecular signature shared by all viviparous vertebrates. Ultimately, our findings indicate that a complex trait such as viviparity likely evolves with changes occurring in multiple different pathways.

Evolutionary dynamics of genome size and content during the adaptive radiation of Heliconiini butterflies

Heliconius butterflies, a speciose genus of Müllerian mimics, represent a classic example of an adaptive radiation that includes a range of derived dietary, life history, physiological and neural traits. However, key lineages within the genus, and across the broader Heliconiini tribe, lack genomic resources, limiting our understanding of how adaptive and neutral processes shaped genome evolution during their radiation. Here, we generate highly contiguous genome assemblies for nine Heliconiini, 29 additional reference-assembled genomes, and improve 10 existing assemblies. Altogether, we provide a dataset of annotated genomes for a total of 63 species, including 58 species within the Heliconiini tribe. We use this extensive dataset to generate a robust and dated heliconiine phylogeny, describe major patterns of introgression, explore the evolution of genome architecture, and the genomic basis of key innovations in this enigmatic group, including an assessment of the evolution of putative regulatory regions at the Heliconius stem. Our work illustrates how the increased resolution provided by such dense genomic sampling improves our power to generate and test gene-phenotype hypotheses, and precisely characterize how genomes evolve.

PhyloAcc-GT: A Bayesian Method for Inferring Patterns of Substitution Rate Shifts on Targeted Lineages Accounting for Gene Tree Discordance

An important goal of evolutionary genomics is to identify genomic regions whose substitution rates differ among lineages. For example, genomic regions experiencing accelerated molecular evolution in some lineages may provide insight into links between genotype and phenotype. Several comparative genomics methods have been developed to identify genomic accelerations between species, including a Bayesian method called PhyloAcc, which models shifts in substitution rate in multiple target lineages on a phylogeny. However, few methods consider the possibility of discordance between the trees of individual loci and the species tree due to incomplete lineage sorting, which might cause false positives. Here, we present PhyloAcc-GT, which extends PhyloAcc by modeling gene tree heterogeneity. Given a species tree, we adopt the multispecies coalescent model as the prior distribution of gene trees, use Markov chain Monte Carlo (MCMC) for inference, and design novel MCMC moves to sample gene trees efficiently. Through extensive simulations, we show that PhyloAcc-GT outperforms PhyloAcc and other methods in identifying target lineage-specific accelerations and detecting complex patterns of rate shifts, and is robust to specification of population size parameters. PhyloAcc-GT is usually more conservative than PhyloAcc in calling convergent rate shifts because it identifies more accelerations on ancestral than on terminal branches. We apply PhyloAcc-GT to two examples of convergent evolution: flightlessness in ratites and marine mammal adaptations, and show that PhyloAcc-GT is a robust tool to identify shifts in substitution rate associated with specific target lineages while accounting for incomplete lineage sorting.

The genomic landscape, causes, and consequences of extensive phylogenomic discordance in Old World mice and rats

A species tree is a central concept in evolutionary biology whereby a single branching phylogeny reflects relationships among species. However, the phylogenies of different genomic regions often differ from the species tree. Although tree discordance is often widespread in phylogenomic studies, we still lack a clear understanding of how variation in phylogenetic patterns is shaped by genome biology or the extent to which discordance may compromise comparative studies. We characterized patterns of phylogenomic discordance across the murine rodents (Old World mice and rats) - a large and ecologically diverse group that gave rise to the mouse and rat model systems. Combining new linked-read genome assemblies for seven murine species with eleven published rodent genomes, we first used ultra-conserved elements (UCEs) to infer a robust species tree. We then used whole genomes to examine finer-scale patterns of discordance and found that phylogenies built from proximate chromosomal regions had similar phylogenies. However, there was no relationship between tree similarity and local recombination rates in house mice, suggesting that genetic linkage influences phylogenetic patterns over deeper timescales. This signal may be independent of contemporary recombination landscapes. We also detected a strong influence of linked selection whereby purifying selection at UCEs led to less discordance, while genes experiencing positive selection showed more discordant and variable phylogenetic signals. Finally, we show that assuming a single species tree can result in high error rates when testing for positive selection under different models. Collectively, our results highlight the complex relationship between phylogenetic inference and genome biology and underscore how failure to account for this complexity can mislead comparative genomic studies.

Repeated evolution of similar phenotypes: Integrating comparative methods with developmental pathways

Repeated phenotypes, often referred to as 'homoplasies' in cladistic analyses, may evolve through changes in developmental processes. Genetic bases of recurrent evolution gained attention and have been studied in the past years using approaches that combine modern analytical phylogenetic tools with the stunning assemblage of new information on developmental mechanisms. In this review, we evaluated the topic under an integrated perspective, revisiting the classical definitions of convergence and parallelism and detailing comparative methods used to evaluate evolution of repeated phenotypes, which include phylogenetic inference, estimates of evolutionary rates and reconstruction of ancestral states. We provide examples to illustrate how a given methodological approach can be used to identify evolutionary patterns and evaluate developmental mechanisms associated with the intermittent expression of a given trait along the phylogeny. Finally, we address why repeated trait loss challenges strict definitions of convergence and parallelism, discussing how changes in developmental pathways might explain the high frequency of repeated trait loss in specific lineages.

Molecular mechanisms of adaptive evolution in wild animals and plants

Wild animals and plants have developed a variety of adaptive traits driven by adaptive evolution, an important strategy for species survival and persistence. Uncovering the molecular mechanisms of adaptive evolution is the key to understanding species diversification, phenotypic convergence, and inter-species interaction. As the genome sequences of more and more non-model organisms are becoming available, the focus of studies on molecular mechanisms of adaptive evolution has shifted from the candidate gene method to genetic mapping based on genome-wide scanning. In this study, we reviewed the latest research advances in wild animals and plants, focusing on adaptive traits, convergent evolution, and coevolution. Firstly, we focused on the adaptive evolution of morphological, behavioral, and physiological traits. Secondly, we reviewed the phenotypic convergences of life history traits and responding to environmental pressures, and the underlying molecular convergence mechanisms. Thirdly, we summarized the advances of coevolution, including the four main types: mutualism, parasitism, predation and competition. Overall, these latest advances greatly increase our understanding of the underlying molecular mechanisms for diverse adaptive traits and species interaction, demonstrating that the development of evolutionary biology has been greatly accelerated by multi-omics technologies. Finally, we highlighted the emerging trends and future prospects around the above three aspects of adaptive evolution.

The GRN concept as a guide for evolutionary developmental biology

Organismal phenotypes result largely from inherited developmental programs, usually executed during embryonic and juvenile life stages. These programs are not blank slates onto which natural selection can draw arbitrary forms. Rather, the mechanisms of development play an integral role in shaping phenotypic diversity and help determine the evolutionary trajectories of species. Modern evolutionary biology must, therefore, account for these mechanisms in both theory and in practice. The gene regulatory network (GRN) concept represents a potent tool for achieving this goal whose utility has grown in tandem with advances in "omic" technologies and experimental techniques. However, while the GRN concept is widely utilized, it is often less clear what practical implications it has for conducting research in evolutionary developmental biology. In this Perspective, we attempt to provide clarity by discussing how experiments and projects can be designed in light of the GRN concept. We first map familiar biological notions onto the more abstract components of GRN models. We then review how diverse functional genomic approaches can be directed toward the goal of constructing such models and discuss current methods for functionally testing evolutionary hypotheses that arise from them. Finally, we show how the major steps of GRN model construction and experimental validation suggest generalizable workflows that can serve as a scaffold for project design. Taken together, the practical implications that we draw from the GRN concept provide a set of guideposts for studies aiming at unraveling the molecular basis of phenotypic diversity.

Genome Evolution and the Future of Phylogenomics of Non-Avian Reptiles

Non-avian reptiles comprise a large proportion of amniote vertebrate diversity, with squamate reptiles-lizards and snakes-recently overtaking birds as the most species-rich tetrapod radiation. Despite displaying an extraordinary diversity of phenotypic and genomic traits, genomic resources in non-avian reptiles have accumulated more slowly than they have in mammals and birds, the remaining amniotes. Here we review the remarkable natural history of non-avian reptiles, with a focus on the physical traits, genomic characteristics, and sequence compositional patterns that comprise key axes of variation across amniotes. We argue that the high evolutionary diversity of non-avian reptiles can fuel a new generation of whole-genome phylogenomic analyses. A survey of phylogenetic investigations in non-avian reptiles shows that sequence capture-based approaches are the most commonly used, with studies of markers known as ultraconserved elements (UCEs) especially well represented. However, many other types of markers exist and are increasingly being mined from genome assemblies in silico, including some with greater information potential than UCEs for certain investigations. We discuss the importance of high-quality genomic resources and methods for bioinformatically extracting a range of marker sets from genome assemblies. Finally, we encourage herpetologists working in genomics, genetics, evolutionary biology, and other fields to work collectively towards building genomic resources for non-avian reptiles, especially squamates, that rival those already in place for mammals and birds. Overall, the development of this cross-amniote phylogenomic tree of life will contribute to illuminate interesting dimensions of biodiversity across non-avian reptiles and broader amniotes.

Evolutionary genetics of flipper forelimb and hindlimb loss from limb development-related genes in cetaceans

Background

Cetacean hindlimbs were lost and their forelimb changed into flippers characterized by webbed digits and hyperphalangy, thus allowing them to adapt to a completely aquatic environment. However, the underlying molecular mechanism behind cetacean limb development remains poorly understood.

Results

In the present study, we explored the evolution of 16 limb-related genes and their cis-regulatory elements in cetaceans and compared them with that of other mammals. TBX5, a forelimb specific expression gene, was identified to have been under accelerated evolution in the ancestral branches of cetaceans. In addition, 32 cetacean-specific changes were examined in the SHH signaling network (SHH, PTCH1, TBX5, BMPs and SMO), within which mutations could yield webbed digits or an additional phalange. These findings thus suggest that the SHH signaling network regulates cetacean flipper formation. By contrast, the regulatory activity of the SHH gene enhancer—ZRS in cetaceans—was significantly lower than in mice, which is consistent with the cessation of SHH gene expression in the hindlimb bud during cetacean embryonic development. It was suggested that the decreased SHH activity regulated by enhancer ZRS might be one of the reasons for hindlimb degeneration in cetaceans. Interestingly, a parallel / convergent site (D42G) and a rapidly evolving CNE were identified in marine mammals in FGF10 and GREM1, respectively, and shown to be essential to restrict limb bud size; this is molecular evidence explaining the convergence of flipper-forelimb and shortening or degeneration of hindlimbs in marine mammals.

Conclusions

We did evolutionary analyses of 16 limb-related genes and their cis-regulatory elements in cetaceans and compared them with those of other mammals to provide novel insights into the molecular basis of flipper forelimb and hindlimb loss in cetaceans.

Enhancer Function and Evolutionary Roles of Human Accelerated Regions

Human accelerated regions (HARs) are the fastest-evolving sequences in the human genome. When HARs were discovered in 2006, their function was mysterious due to scant annotation of the noncoding genome. Diverse technologies, from transgenic animals to machine learning, have consistently shown that HARs function as gene regulatory enhancers with significant enrichment in neurodevelopment. It is now possible to quantitatively measure the enhancer activity of thousands of HARs in parallel and model how each nucleotide contributes to gene expression. These strategies have revealed that many human HAR sequences function differently than their chimpanzee orthologs, though individual nucleotide changes in the same HAR may have opposite effects, consistent with compensatory substitutions. To fully evaluate the role of HARs in human evolution, it will be necessary to experimentally and computationally dissect them across more cell types and developmental stages.

Chromosome-level genome assembly of the Muscovy duck provides insight into fatty liver susceptibility

The Muscovy duck (Cairina moschata) is an economically important poultry species, which is susceptible to fatty liver. Thus, the Muscovy duck may serve as an excellent candidate animal model of non-alcoholic fatty liver disease. However, the mechanisms underlying fatty liver development in this species are poorly understood. In this study, we report a chromosome-level genome assembly of the Muscovy duck, with a contig N50 of 11.8 Mb and scaffold N50 of 83.16 Mb. The susceptibility of Muscovy duck to fatty liver was mainly attributed to weak lipid catabolism capabilities (fatty acid β-oxidation and lipolysis). Furthermore, conserved noncoding elements (CNEs) showing accelerated evolution contributed to fatty liver formation by down-regulating the expression of genes involved in hepatic lipid catabolism. We propose that the susceptibility of Muscovy duck to fatty liver is an evolutionary by-product. In conclusion, this study revealed the potential mechanisms underlying the susceptibility of Muscovy duck to fatty liver.

Genomic signatures of the evolution of a diurnal lifestyle in Strigiformes

Understanding the targets of selection associated with changes in behavioral traits represents an important challenge of current evolutionary research. Owls (Strigiformes) are a diverse group of birds, most of which are considered nocturnal raptors. However, a few owl species independently adopted a diurnal lifestyle in their recent evolutionary history. We searched for signals of accelerated rates of evolution associated with a diurnal lifestyle using a genome-wide comparative approach. We estimated substitution rates in coding and noncoding conserved regions of the genome of seven owl species, including three diurnal species. Substitution rates of the noncoding elements were more accelerated than those of protein-coding genes. We identified new, owl-specific conserved noncoding elements as candidates of parallel evolution during the emergence of diurnality in owls. Our results shed light on the molecular basis of adaptation to a new niche and highlight the importance of regulatory elements for evolutionary changes in behavior. These elements were often involved in the neuronal development of the brain.

Venom gene sequence diversity and expression jointly shape diet adaptation in pitvipers

Understanding the joint roles of protein sequence variation and differential expression during adaptive evolution is a fundamental, yet largely unrealized goal of evolutionary biology. Here, we use phylogenetic path analysis to analyze a comprehensive venom-gland transcriptome dataset spanning three genera of pitvipers to identify the functional genetic basis of a key adaptation (venom complexity) linked to diet breadth (DB). The analysis of gene-family-specific patterns reveals that, for genes encoding two of the most important venom proteins (snake venom metalloproteases and snake venom serine proteases), there are direct, positive relationships between sequence diversity (SD), expression diversity (ED), and increased DB. Further analysis of gene-family diversification for these proteins showed no constraint on how individual lineages achieved toxin gene SD in terms of the patterns of paralog diversification. In contrast, another major venom protein family (PLA₂s) showed no relationship between venom molecular diversity and DB. Additional analyses suggest that other molecular mechanisms—such as higher absolute levels of expression—are responsible for diet adaptation involving these venom proteins. Broadly, our findings argue that functional diversity generated through sequence and expression variations jointly determine adaptation in the key components of pitviper venoms, which mediate complex molecular interactions between the snakes and their prey.

Transcription factors evolve faster than their structural gene targets in the flavonoid pigment pathway

Dissecting the relationship between gene function and substitution rates is key to understanding genome-wide patterns of molecular evolution. Biochemical pathways provide powerful systems for investigating this relationship because the functional role of each gene is often well characterized. Here, we investigate the evolution of the flavonoid pigment pathway in the colorful Petunieae clade of the tomato family (Solanaceae). This pathway is broadly conserved in plants, both in terms of its structural elements and its MYB, basic helix–loop–helix, and WD40 transcriptional regulators, and its function has been extensively studied, particularly in model species of petunia. We built a phylotranscriptomic data set for 69 species of Petunieae to infer patterns of molecular evolution across pathway genes and across lineages. We found that transcription factors exhibit faster rates of molecular evolution (dN/dS) than their targets, with the highly specialized MYB genes evolving fastest. Using the largest comparative data set to date, we recovered little support for the hypothesis that upstream enzymes evolve slower than those occupying more downstream positions, although expression levels do predict molecular evolutionary rates. Although shifts in floral pigmentation were only weakly related to changes affecting coding regions, we found a strong relationship with the presence/absence patterns of MYB transcripts. Intensely pigmented species express all three main MYB anthocyanin activators in petals, whereas pale or white species express few or none. Our findings reinforce the notion that pathway regulators have a dynamic history, involving higher rates of molecular evolution than structural components, along with frequent changes in expression during color transitions.

Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness

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.

Positive selection in noncoding genomic regions of vocal learning birds is associated with genes implicated in vocal learning and speech functions in humans

Vocal learning, the ability to imitate sounds from conspecifics and the environment, is a key component of human spoken language and learned song in three independently evolved avian groups—oscine songbirds, parrots, and hummingbirds. Humans and each of these three bird clades exhibit specialized behavioral, neuroanatomical, and brain gene expression convergence related to vocal learning, speech, and song. To understand the evolutionary basis of vocal learning gene specializations and convergence, we searched for and identified accelerated genomic regions (ARs), a marker of positive selection, specific to vocal learning birds. We found avian vocal learner-specific ARs, and they were enriched in noncoding regions near genes with known speech functions or brain gene expression specializations in humans and vocal learning birds, including FOXP2, NEUROD6, ZEB2, and MEF2C, and near genes with major neurodevelopmental functions, including NR2F1, NRP2, and BCL11B. We also found enrichment near the SFARI class S genes associated with syndromic vocal communication forms of autism spectrum disorders. These findings reveal strong candidate noncoding regions near genes for the evolutionary adaptations that distinguish vocal learning species from their close vocal nonlearning relatives and provide further evidence of molecular convergence between birdsong and human spoken language.

Life in Deserts: The Genetic Basis of Mammalian Desert Adaptation

Deserts are among the harshest environments on Earth. The multiple ages of different deserts and their global distribution provide a unique opportunity to study repeated adaptation at different timescales. Here, we summarize recent genomic research on the genetic mechanisms underlying desert adaptations in mammals. Several studies on different desert mammals show large overlap in functional classes of genes and pathways, consistent with the complexity and variety of phenotypes associated with desert adaptation to water and food scarcity and extreme temperatures. However, studies of desert adaptation are also challenged by a lack of accurate genotype-phenotype-environment maps. We encourage development of systems that facilitate functional analyses, but also acknowledge the need for more studies on a wider variety of desert mammals.

How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature

Phylogenetic comparative methods are often used to test functional relationships between traits. However, million-year macroevolutionary observational datasets cannot definitively prove causal links between traits-correlation does not equal causation and experimental manipulation over such timescales is impossible. Although this caveat is widely understood, it is less appreciated that different phylogenetic approaches imply different causal assumptions about the functional relationships of traits. To make meaningful inferences, it is critical that our statistical methods make biologically reasonable assumptions. Here we illustrate the importance of causal reasoning in comparative biology by examining a recent study by Avaria-Llautureo et al (2019). that tested for the evolutionary coupling of metabolic rate and body temperature across endotherms and found that these traits were unlinked through evolutionary time and that body temperatures were, on average, higher in the early Cenozoic than they are today. We argue that the causal assumptions embedded into their models made it impossible for them to test the relevant functional and evolutionary hypotheses. We reanalyze their data using more biologically appropriate models and find support for the exact opposite conclusions, corroborating previous evidence from physiology and paleontology. We highlight the vital need for causal thinking, even when experiments are impossible.

Phylogenetic Permulations: A Statistically Rigorous Approach to Measure Confidence in Associations in a Phylogenetic Context

Many evolutionary comparative methods seek to identify associations between phenotypic traits or between traits and genotypes, often with the goal of inferring potential functional relationships between them. Comparative genomics methods aimed at this goal measure the association between evolutionary changes at the genetic level with traits evolving convergently across phylogenetic lineages. However, these methods have complex statistical behaviors that are influenced by nontrivial and oftentimes unknown confounding factors. Consequently, using standard statistical analyses in interpreting the outputs of these methods leads to potentially inaccurate conclusions. Here, we introduce phylogenetic permulations, a novel statistical strategy that combines phylogenetic simulations and permutations to calculate accurate, unbiased P values from phylogenetic methods. Permulations construct the null expectation for P values from a given phylogenetic method by empirically generating null phenotypes. Subsequently, empirical P values that capture the true statistical confidence given the correlation structure in the data are directly calculated based on the empirical null expectation. We examine the performance of permulation methods by analyzing both binary and continuous phenotypes, including marine, subterranean, and long-lived large-bodied mammal phenotypes. Our results reveal that permulations improve the statistical power of phylogenetic analyses and correctly calibrate statements of confidence in rejecting complex null distributions while maintaining or improving the enrichment of known functions related to the phenotype. We also find that permulations refine pathway enrichment analyses by correcting for nonindependence in gene ranks. Our results demonstrate that permulations are a powerful tool for improving statistical confidence in the conclusions of phylogenetic analysis when the parametric null is unknown.

RERconverge: an R package for associating evolutionary rates with convergent traits

MOTIVATION

When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits.

RESULTS

Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results.

AVAILABILITY AND IMPLEMENTATION

RERconverge source code, documentation and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila and yeast are available at https://bit.ly/2J2QBnj.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Prospects for sociogenomics in avian cooperative breeding and parental care

For the last 40 years, the study of cooperative breeding (CB) in birds has proceeded primarily in the context of discovering the ecological, geographical, and behavioral drivers of helping. The advent of molecular tools in the early 1990s assisted in clarifying the relatedness of helpers to those helped, in some cases, confirming predictions of kin selection theory. Methods for genome-wide analysis of sequence variation, gene expression, and epigenetics promise to add new dimensions to our understanding of avian CB, primarily in the area of molecular and developmental correlates of delayed breeding and dispersal, as well as the ontogeny of achieving parental status in nature. Here, we outline key ways in which modern -omics approaches, in particular genome sequencing, transcriptomics, and epigenetic profiling such as ATAC-seq, can be used to add a new level of analysis of avian CB. Building on recent and ongoing studies of avian social behavior and sociogenomics, we review how high-throughput sequencing of a focal species or clade can provide a robust foundation for downstream, context-dependent destructive and non-destructive sampling of specific tissues or physiological states in the field for analysis of gene expression and epigenetics. -Omics approaches have the potential to inform not only studies of the diversification of CB over evolutionary time, but real-time analyses of behavioral interactions in the field or lab. Sociogenomics of birds represents a new branch in the network of methods used to study CB, and can help clarify ways in which the different levels of analysis of CB ultimately interact in novel and unexpected ways.

Noncoding regions underpin avian bill shape diversification at macroevolutionary scales

Recent progress has been made in identifying genomic regions implicated in trait evolution on a microevolutionary scale in many species, but whether these are relevant over macroevolutionary time remains unclear. Here, we directly address this fundamental question using bird beak shape, a key evolutionary innovation linked to patterns of resource use, divergence, and speciation, as a model trait. We integrate class-wide geometric-morphometric analyses with evolutionary sequence analyses of 10,322 protein-coding genes as well as 229,001 genomic regions spanning 72 species. We identify 1434 protein-coding genes and 39,806 noncoding regions for which molecular rates were significantly related to rates of bill shape evolution. We show that homologs of the identified protein-coding genes as well as genes in close proximity to the identified noncoding regions are involved in craniofacial embryo development in mammals. They are associated with embryonic stem cell pathways, including BMP and Wnt signaling, both of which have repeatedly been implicated in the morphological development of avian beaks. This suggests that identifying genotype-phenotype association on a genome-wide scale over macroevolutionary time is feasible. Although the coding and noncoding gene sets are associated with similar pathways, the actual genes are highly distinct, with significantly reduced overlap between them and bill-related phenotype associations specific to noncoding loci. Evidence for signatures of recent diversifying selection on our identified noncoding loci in Darwin finch populations further suggests that regulatory rather than coding changes are major drivers of morphological diversification over macroevolutionary times.

Integrating natural history collections and comparative genomics to study the genetic architecture of convergent evolution

Evolutionary convergence has been long considered primary evidence of adaptation driven by natural selection and provides opportunities to explore evolutionary repeatability and predictability. In recent years, there has been increased interest in exploring the genetic mechanisms underlying convergent evolution, in part, owing to the advent of genomic techniques. However, the current 'genomics gold rush' in studies of convergence has overshadowed the reality that most trait classifications are quite broadly defined, resulting in incomplete or potentially biased interpretations of results. Genomic studies of convergence would be greatly improved by integrating deep 'vertical', natural history knowledge with 'horizontal' knowledge focusing on the breadth of taxonomic diversity. Natural history collections have and continue to be best positioned for increasing our comprehensive understanding of phenotypic diversity, with modern practices of digitization and databasing of morphological traits providing exciting improvements in our ability to evaluate the degree of morphological convergence. Combining more detailed phenotypic data with the well-established field of genomics will enable scientists to make progress on an important goal in biology: to understand the degree to which genetic or molecular convergence is associated with phenotypic convergence. Although the fields of comparative biology or comparative genomics alone can separately reveal important insights into convergent evolution, here we suggest that the synergistic and complementary roles of natural history collection-derived phenomic data and comparative genomics methods can be particularly powerful in together elucidating the genomic basis of convergent evolution among higher taxa. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.

Convergent regulatory evolution and loss of flight in paleognathous birds

A core question in evolutionary biology is whether convergent phenotypic evolution is driven by convergent molecular changes in proteins or regulatory regions. We combined phylogenomic, developmental, and epigenomic analysis of 11 new genomes of paleognathous birds, including an extinct moa, to show that convergent evolution of regulatory regions, more so than protein-coding genes, is prevalent among developmental pathways associated with independent losses of flight. A Bayesian analysis of 284,001 conserved noncoding elements, 60,665 of which are corroborated as enhancers by open chromatin states during development, identified 2355 independent accelerations along lineages of flightless paleognaths, with functional consequences for driving gene expression in the developing forelimb. Our results suggest that the genomic landscape associated with morphological convergence in ratites has a substantial shared regulatory component.