Parallelism in genomic landscapes of differentiation, conserved genomic features and the role of linked selection

The great tit HapMap project: A continental-scale analysis of genomic variation in a songbird

A major aim of evolutionary biology is to understand why patterns of genomic diversity vary within taxa and space. Large-scale genomic studies of widespread species are useful for studying how environment and demography shape patterns of genomic divergence. Here, we describe one of the most geographically comprehensive surveys of genomic variation in a wild vertebrate to date; the great tit (Parus major) HapMap project. We screened ca 500,000 SNP markers across 647 individuals from 29 populations, spanning ~30 degrees of latitude and 40 degrees of longitude - almost the entire geographical range of the European subspecies. Genome-wide variation was consistent with a recent colonisation across Europe from a South-East European refugium, with bottlenecks and reduced genetic diversity in island populations. Differentiation across the genome was highly heterogeneous, with clear 'islands of differentiation', even among populations with very low levels of genome-wide differentiation. Low local recombination rates were a strong predictor of high local genomic differentiation (FST), especially in island and peripheral mainland populations, suggesting that the interplay between genetic drift and recombination causes highly heterogeneous differentiation landscapes. We also detected genomic outlier regions that were confined to one or more peripheral great tit populations, probably as a result of recent directional selection at the species' range edges. Haplotype-based measures of selection were related to recombination rate, albeit less strongly, and highlighted population-specific sweeps that likely resulted from positive selection. Our study highlights how comprehensive screens of genomic variation in wild organisms can provide unique insights into spatio-temporal evolutionary dynamics.

Widespread genomic signatures of reproductive isolation and sex-specific selection in the Eastern Yellow Robin, Eopsaltria australis

How new species evolve is one of the most fundamental questions in biology. Population divergence, which may lead to speciation, may be occurring in the Eastern Yellow Robin, a common passerine that lives along the eastern coast of Australia. This species is composed of 2 parapatric lineages that have highly divergent mitochondrial DNA; however, similar levels of divergence have not been observed in the nuclear genome. Here we re-examine the nuclear genomes of these mitolineages to test potential mechanisms underlying the discordance between nuclear and mitochondrial divergence. We find that nuclear admixture occurs in a narrow hybrid zone, although the majority of markers across the genome show evidence of reproductive isolation between populations of opposing mitolineages. There is an 8 MB section of a previously identified putative neo-sex chromosome that is highly diverged between allopatric but not parapatric populations, which may be the result of a chromosomal inversion. The neo-sex chromosomal nature of this region, as well as the geographic patterns in which it exhibits divergence, suggest it is unlikely to be contributing to reproductive isolation through mitonuclear incompatibilities as reported in earlier studies. In addition, there are sex differences in the number of markers that are differentiated between populations of opposite mitolineages, with greater differentiation occurring in females, which are heterozygous, than males. These results suggest that, despite the absence of previously observed assortative mating, mitolineages of Eastern Yellow Robin experience at least some postzygotic isolation from each other, in a pattern consistent with Haldane’s Rule.

Genome–Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome–environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat–based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change.

“I shall endeavor to find out how nature’s forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature” Alexander von Humboldt—Letter to Karl Freiesleben, June 1799.

Genetic differentiation of grain, fodder and pod vegetable type cowpeas (Vigna unguiculata L.) identified through single nucleotide polymorphisms from genotyping-by-sequencing

The species Vigna unguiculata L. (Walp), commonly known as cowpea, is a multi-purpose legume that has been selected into three subspecies that are divided into grain, fodder and pod (yardlong bean) types. However, genetic bases for distinctions are not well understood. The purpose of this study was to apply genotyping-by-sequencing (GBS) and current reference genome for V. unguiculata to distinguish three subspecies and identify signatures of divergence. The collection of 130 accessions included 128 cultivated from: 1) ssp. cylindrica, fodder type; 2) ssp. sesquipedalis, pod vegetable type; and 3) ssp. unguiculata, grain type. Two wilds genotypes from spp. dekindtiana and spp. pubescens, were used to anchor phylogeny. A total of 11,083 highly informative single nucleotide polymorphisms (SNPs) were discovered. Wild accessions showed distinct genetic fingerprints and were separated from cultivated subspecies. Principal component analysis showed closer relationship between ssp. unguiculata and ssp. cylindrica compared to ssp. sesquipedalis. Relative differentiation of cultivated subspecies (with Fixation Index, FST) indicated the existence of discrete signatures of selection. This work clarifies the population structure, phylogeny, and domestication of cultivated cowpeas. Furthermore, significant genetic differences between grain and pod vegetable types can provide valuable information for future breeding in three cowpea groups.

Predicting Thermal Adaptation by Looking Into Populations' Genomic Past

Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations' responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder's equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks.

Contingent Convergence: The Ability To Detect Convergent Genomic Evolution Is Dependent on Population Size and Migration

Outlier scans, in which the genome is scanned for signatures of selection, have become a prominent tool in studies of local adaptation, and more recently studies of genetic convergence in natural populations. However, such methods have the potential to be confounded by features of demographic history, such as population size and migration, which are considerably varied across natural populations. In this study, we use forward-simulations to investigate and illustrate how several measures of genetic differentiation commonly used in outlier scans (FST, DXY and Δπ) are influenced by demographic variation across multiple sampling generations. In a factorial design with 16 treatments, we manipulate the presence/absence of founding bottlenecks (N of founding individuals), prolonged bottlenecks (proportional size of diverging population) and migration rate between two populations with ancestral and diverged phenotypic optima. Our results illustrate known constraints of individual measures associated with reduced population size and a lack of migration; but notably we demonstrate how relationships between measures are similarly dependent on these features of demography. We find that false-positive signals of convergent evolution (the same simulated outliers detected in independent treatments) are attainable as a product of similar population size and migration treatments (particularly for DXY), and that outliers across different measures (for e.g., FST and DXY) can occur with little influence of selection. Taken together, we show how underappreciated, yet quantifiable measures of demographic history can influence commonly employed methods for detecting selection.

Does the Genomic Landscape of Species Divergence in Phaseolus Beans Coerce Parallel Signatures of Adaptation and Domestication?

Exploring the genomic architecture of species and populations divergence aids understanding how lineages evolve and adapt, and ultimately can show the repeatability of evolutionary processes. Yet, the genomic signatures associated with divergence are still relatively unexplored, leading to a knowledge gap on whether species divergence ultimately differs in its genetic architecture from divergence at other spatial scales (i.e., populations, ecotypes). Our goal in this research was to determine whether genomic islands of speciation are more prone to harbor within-species differentiation due to genomic features, suppressed recombination, smaller effective population size or increased drift, across repeated hierarchically nested levels of divergence. We used two species of Phaseolus beans with strong genepool and population sub-structure produced by multiple independent domestications each especially in Andean and Mesoamerican / Middle American geographies. We genotyped 22,531 GBS-derived SNP markers in 209 individuals of wild and cultivated Phaseolus vulgaris and Phaseolus lunatus. We identified six regions for species-associated divergence. Out of these divergence peaks, 21% were recovered in the four within-species between-genepool comparisons and in the five within-genepool wild-cultivated comparisons (some of the latter did retrieve genuine signatures of the well described multiple domestication syndromes). However, genomic regions with overall high relative differentiation (measured by FST) coincided with regions of low SNP density and regions of elevated delta divergence between-genepools (ΔDiv), independent of the scale of divergence. The divergence in chromosome Pv10 further coincided with a between-species pericentric inversion. These convergences suggest that shared variants are being recurrently fixed at replicated regions of the genome, and in a similar manner across different hierarchically nested levels of divergence, likely as result of genomic features that make certain regions more prone to accumulate islands of speciation and within-species divergence. In summary, neighboring signatures of speciation, adaptation and domestication in Phaseolus beans are influenced by ubiquitous genomic constrains, which may continue to fortuitously shape genomic differentiation at various others scales of divergence.

A comparison of genomic islands of differentiation across three young avian species pairs

Detailed evaluations of genomic variation between sister species often reveal distinct chromosomal regions of high relative differentiation (i.e., "islands of differentiation" in F_ST ), but there is much debate regarding the causes of this pattern. We briefly review the prominent models of genomic islands of differentiation and compare patterns of genomic differentiation in three closely related pairs of New World warblers with the goal of evaluating support for the four models. Each pair (MacGillivray's/mourning warblers; Townsend's/black-throated green warblers; and Audubon's/myrtle warblers) consists of forms that were likely separated in western and eastern North American refugia during cycles of Pleistocene glaciations and have now come into contact in western Canada, where each forms a narrow hybrid zone. We show strong differences between pairs in their patterns of genomic heterogeneity in F_ST , suggesting differing selective forces and/or differing genomic responses to similar selective forces among the three pairs. Across most of the genome, levels of within-group nucleotide diversity (π_Within ) are almost as large as levels of between-group nucleotide distance (π_Between ) within each pair, suggesting recent common ancestry and/or gene flow. In two pairs, a pattern of the F_ST peaks having low π_Between suggests that selective sweeps spread between geographically differentiated groups, followed by local differentiation. This "sweep-before-differentiation" model is consistent with signatures of gene flow within the yellow-rumped warbler species complex. These findings add to our growing understanding of speciation as a complex process that can involve phases of adaptive introgression among partially differentiated populations.

Heterogeneous Patterns of Genetic Diversity and Differentiation in European and Siberian Chiffchaff (Phylloscopus collybita abietinus/P. tristis)

Identification of candidate genes for trait variation in diverging lineages and characterization of mechanistic underpinnings of genome differentiation are key steps toward understanding the processes underlying the formation of new species. Hybrid zones provide a valuable resource for such investigations, since they allow us to study how genomes evolve as species exchange genetic material and to associate particular genetic regions with phenotypic traits of interest. Here, we use whole-genome resequencing of both allopatric and hybridizing populations of the European (Phylloscopus collybita abietinus) and the Siberian chiffchaff (P. tristis)—two recently diverged species which differ in morphology, plumage, song, habitat, and migration—to quantify the regional variation in genome-wide genetic diversity and differentiation, and to identify candidate regions for trait variation. We find that the levels of diversity, differentiation, and divergence are highly heterogeneous, with significantly reduced global differentiation, and more pronounced differentiation peaks in sympatry than in allopatry. This pattern is consistent with regional differences in effective population size and recurrent background selection or selective sweeps reducing the genetic diversity in specific regions prior to lineage divergence, but the data also suggest that postdivergence selection has resulted in increased differentiation and fixed differences in specific regions. We find that hybridization and backcrossing is common in sympatry, and that phenotype is a poor predictor of the genomic composition of sympatric birds. The combination of a differentiation scan approach with identification of fixed differences pinpoint a handful of candidate regions that might be important for trait variation between the two species.