Evolutionary and ecological genomics of non-model plants

Dissecting evolutionary dynamics of ecologically important traits is a long-term challenge for biologists.Attempts to understand natural variation and molecular mechanisms have motivated a move from laboratory model systems to non-model systems in diverse natural environments.Next generation sequencing methods,along with an expansion of genomic resources and tools,have fostered new links between diverse disciplines,including molecular biology,evolution,ecology,and genomics.Great progress has been made in a few non-model wild plants,such as Arabidopsis relatives,monkey flowers,and wild sunflowers.Until recently,the lack of comprehensive genomic information has limited evolutionary and ecological studies to larger QTL (quantitative trait locus) regions rather than single gene resolution,and has hindered recognition of general patterns of natural variation and local adaptation.Further efforts in accumulating genomic data and developing bioinformatic and biostatistical tools are now poised to move this field forward.Integrative national and international collaborations and research communities are needed to facilitate development in the field of evolutionary and ecological genomics.     

Cranial evolution in sakis (Pithecia, Platyrrhini). II: Evolutionary processes and morphological integration

Patterns of interspecific differentiation in saki monkeys (Pithecia) are quantitatively described and possible evolutionary processes producing them are examined. The comparison of species correlation matrices to expected patterns of morphological integration reveal significant and similar patterns of development-based cranial integration among species. Aspects of the facial region are more heavily influenced by general size variation than features of the neural region. The comparison of pooled within- and between-groups V/CV matrices suggests that genetic drift might be a sufficient explanation for saki cranial evolution. Differential natural selection gradients are also reconstructed because selection may also have caused population differentiation through evolutionary time. These gradients illustrate the inherent multivariate nature of selection, being a consequence of the interaction between existing morphological integration (correlation) among traits and the action of natural selection. Yet, our attempt to interpret selection gradients in terms of their functional significance did not result in any clear association between selection and function. Perhaps this is also an indication that morphological evolution in sakis was mostly neutral.     

Evolutionary and ecological genomics of non‐model plants

Abstract Dissecting evolutionary dynamics of ecologically important traits is a long‐term challenge for biologists. Attempts to understand natural variation and molecular mechanisms have motivated a move from laboratory model systems to non‐model systems in diverse natural environments. Next generation sequencing methods, along with an expansion of genomic resources and tools, have fostered new links between diverse disciplines, including molecular biology, evolution, ecology, and genomics. Great progress has been made in a few non‐model wild plants, such as Arabidopsis relatives, monkey flowers, and wild sunflowers. Until recently, the lack of comprehensive genomic information has limited evolutionary and ecological studies to larger QTL (quantitative trait locus) regions rather than single gene resolution, and has hindered recognition of general patterns of natural variation and local adaptation. Further efforts in accumulating genomic data and developing bioinformatic and biostatistical tools are now poised to move this field forward. Integrative national and international collaborations and research communities are needed to facilitate development in the field of evolutionary and ecological genomics.     

Coalescence 2.0: a multiple branching of recent theoretical developments and their applications

Population genetics theory has laid the foundations for genomic analyses including the recent burst in genome scans for selection and statistical inference of past demographic events in many prokaryote, animal and plant species. Identifying SNPs under natural selection and underpinning species adaptation relies on disentangling the respective contribution of random processes (mutation, drift, migration) from that of selection on nucleotide variability. Most theory and statistical tests have been developed using the Kingman coalescent theory based on the Wright‐Fisher population model. However, these theoretical models rely on biological and life history assumptions which may be violated in many prokaryote, fungal, animal or plant species. Recent theoretical developments of the so‐called multiple merger coalescent models are reviewed here (Λ‐coalescent, beta‐coalescent, Bolthausen‐Sznitman, Ξ‐coalescent). We explain how these new models take into account various pervasive ecological and biological characteristics, life history traits or life cycles which were not accounted in previous theories such as (i) the skew in offspring production typical of marine species, (ii) fast adapting microparasites (virus, bacteria and fungi) exhibiting large variation in population sizes during epidemics, (iii) the peculiar life cycles of fungi and bacteria alternating sexual and asexual cycles and (iv) the high rates of extinction‐recolonization in spatially structured populations. We finally discuss the relevance of multiple merger models for the detection of SNPs under selection in these species, for population genomics of very large sample size and advocate to potentially examine the conclusion of previous population genetics studies.     

Single-cell enabled comparative genomics of a deep ocean SAR11 bathytype

Bacterioplankton of the SAR11 clade are the most abundant microorganisms in marine systems, usually representing 25% or more of the total bacterial cells in seawater worldwide. SAR11 is divided into subclades with distinct spatiotemporal distributions (ecotypes), some of which appear to be specific to deep water. Here we examine the genomic basis for deep ocean distribution of one SAR11 bathytype (depth-specific ecotype), subclade Ic. Four single-cell Ic genomes, with estimated completeness of 55%–86%, were isolated from 770 m at station ALOHA and compared with eight SAR11 surface genomes and metagenomic datasets. Subclade Ic genomes dominated metagenomic fragment recruitment below the euphotic zone. They had similar COG distributions, high local synteny and shared a large number (69%) of orthologous clusters with SAR11 surface genomes, yet were distinct at the 16S rRNA gene and amino-acid level, and formed a separate, monophyletic group in phylogenetic trees. Subclade Ic genomes were enriched in genes associated with membrane/cell wall/envelope biosynthesis and showed evidence of unique phage defenses. The majority of subclade Ic-specfic genes were hypothetical, and some were highly abundant in deep ocean metagenomic data, potentially masking mechanisms for niche differentiation. However, the evidence suggests these organisms have a similar metabolism to their surface counterparts, and that subclade Ic adaptations to the deep ocean do not involve large variations in gene content, but rather more subtle differences previously observed deep ocean genomic data, like preferential amino-acid substitutions, larger coding regions among SAR11 clade orthologs, larger intergenic regions and larger estimated average genome size.     

Adaptive divergence despite strong genetic drift: genomic analysis of the evolutionary mechanisms causing genetic differentiation in the island fox (Urocyon littoralis)

The evolutionary mechanisms generating the tremendous biodiversity of islands have long fascinated evolutionary biologists. Genetic drift and divergent selection are predicted to be strong on islands and both could drive population divergence and speciation. Alternatively, strong genetic drift may preclude adaptation. We conducted a genomic analysis to test the roles of genetic drift and divergent selection in causing genetic differentiation among populations of the island fox (Urocyon littoralis). This species consists of six subspecies, each of which occupies a different California Channel Island. Analysis of 5293 SNP loci generated using Restriction‐site Associated DNA (RAD) sequencing found support for genetic drift as the dominant evolutionary mechanism driving population divergence among island fox populations. In particular, populations had exceptionally low genetic variation, small N_e (range = 2.1–89.7; median = 19.4), and significant genetic signatures of bottlenecks. Moreover, islands with the lowest genetic variation (and, by inference, the strongest historical genetic drift) were most genetically differentiated from mainland grey foxes, and vice versa, indicating genetic drift drives genome‐wide divergence. Nonetheless, outlier tests identified 3.6–6.6% of loci as high F_ST outliers, suggesting that despite strong genetic drift, divergent selection contributes to population divergence. Patterns of similarity among populations based on high F_ST outliers mirrored patterns based on morphology, providing additional evidence that outliers reflect adaptive divergence. Extremely low genetic variation and small N_e in some island fox populations, particularly on San Nicolas Island, suggest that they may be vulnerable to fixation of deleterious alleles, decreased fitness and reduced adaptive potential.     

Variation within and among species in gene expression: raw material for evolution

Heritable variation in regulatory or coding regions is the raw material for evolutionary processes. The advent of microarrays has recently promoted examination of the extent of variation in gene expression within and among taxa and examination of the evolutionary processes affecting variation. This review examines these issues. We find: (i) microarray-based measures of gene expression are precise given appropriate experimental design; (ii) there is large inter-individual variation, which is composed of a minor nongenetic component and a large heritable component; (iii) variation among populations and species appears to be affected primarily by neutral drift and stabilizing selection, and to a lesser degree by directional selection; and (iv) neutral evolutionary divergence in gene expression becomes nonlinear with greater divergence times due to functional constraint. Evolutionary analyses of gene expression reviewed here provide unique insights into partitioning of regulatory variation in nature. However, common limitations of these studies include the tendency to assume a linear relationship between expression divergence and species divergence, and failure to test explicit hypotheses that involve the ecological context of evolutionary divergence.     

Book review of evolutionary genetics: Concepts,analysis, and practice

Recent technological advances have expanded and increased the resolution of studies in evolutionary biology, creating a need for a modern textbook that highlights the latest developments in the field. Evolutionary Genetics: Concepts, Analysis, and Practice, by Glenn‐Peter Sætre and Mark Ravinet (2019), as well as the book's accompanying online tutorials, provide a clear, up‐to‐date, and enjoyable introduction to evolutionary biology and genetics that explains fundamental evolutionary concepts, illustrates recent exciting findings, and offers hands‐on experience in analysing and interpreting genomic data. The book's accessible nature and emphasis on developing practical skills make it a valuable resource for undergraduate courses on evolutionary biology.     

Evolutionary significance of the variation in acoustic communication of a cryptic nocturnal primate radiation (Microcebus spp.)

Acoustic phenotypic variation is of major importance for speciation and the evolution of species diversity. Whereas selective and stochastic forces shaping the acoustic divergence of signaling systems are well studied in insects, frogs, and birds, knowledge on the processes driving acoustic phenotypic evolution in mammals is limited. We quantified the acoustic variation of a call type exchanged during agonistic encounters across eight distinct species of the smallest‐bodied nocturnal primate radiation, the Malagasy mouse lemurs. The species live in two different habitats (dry forest vs. humid forest), differ in geographic distance to each other, and belong to four distinct phylogenetic clades within the genus. Genetically defined species were discriminated reliably on the phenotypic level based on their acoustic distinctiveness in a discriminant function analysis. Acoustic variation was explained by genetic distance, whereas differences in morphology, forest type, or geographic distance had no effect. The strong impact of genetics was supported by a correlation between acoustic and genetic distance and the high agreement in branching pattern between the acoustic and molecular phylogenetic trees. In sum, stochastic factors such as genetic drift best explained acoustic diversification in a social communication call of mouse lemurs.     

Structural and functional analysis of rice genome

Rice is an excellent system for plant genomics as it represents a modest size genome of 430 Mb. It feeds more than half the population of the world. Draft sequences of the rice genome, derived by whole-genome shotgun approach at relatively low coverage (4-6 X), were published and the International Rice Genome Sequencing Project (IRGSP) declared high quality (> 10 X), genetically anchored, phase 2 level sequence in 2002. In addition, phase 3 level finished sequence of chromosomes 1, 4 and 10 (out of 12 chromosomes of rice) has already been reported by scientists from IRGSP consortium. Various estimates of genes in rice place the number at >50,000. Already, over 28,000 full-length cDNAs have been sequenced, most of which map to genetically anchored genome sequence. Such information is very useful in revealing novel features of macroand micro-level synteny of rice genome with other cereals. Microarray analysis is unraveling the identity of rice genes expressing in temporal and spatial manner and should help target candidate genes useful for improving traits of agronomic importance. Simultaneously, functional analysis of rice genome has been initiated by marker-based characterization of useful genes and employing functional knock-outs created by mutation or gene tagging. Integration of this enormous information is expected to catalyze tremendous activity on basic and applied aspects of rice genomics.     

Variation in aggressiveness components of Zymoseptoria tritici populations in Iran

Zymoseptoria tritici, the causal agent of Septoria tritici blotch, has emerged and evolved as a pathogen on wheat in the Fertile Crescent. Iran is located in this region, and study on the ancient pathogen populations in the country can improve our understanding on adaptive potential of aggressiveness, the role of local adaptation in shaping population structure and the involvement of selection and genetic drift in favouring aggressiveness adaptation to environments. To this aim, three aggressiveness components including days until first lesion (DUFL), days until first pycnidia (DUFP) and percentage of leaf area covered by pycnidia, in five populations of the pathogen collected from different provinces of Iran were compared in greenhouse conditions. All populations except for Golestan showed high within‐population diversity for the examined traits. No difference in aggressiveness components was found between fungal collections from Khuzestan and Fars; however, significant variation was evident among the populations originated from other provinces. Comparisons of estimated Q_ST values to F_ST indicated that genetic differentiation in pycnidial coverage has been the result of selection imposed by different variables; however, the divergence found for DUFL and DUFP has been achieved by genetic drift. The possible mechanisms involved in aggressiveness diversity of the pathogen populations and the impact of these findings on breeding programs for quantitative resistance are discussed.     

driftsel: an R package for detecting signals of natural selection in quantitative traits

Approaches and tools to differentiate between natural selection and genetic drift as causes of population differentiation are of frequent demand in evolutionary biology. Based on the approach of Ovaskainen et al. (2011), we have developed an R package (driftsel ) that can be used to differentiate between stabilizing selection, diversifying selection and random genetic drift as causes of population differentiation in quantitative traits when neutral marker and quantitative genetic data are available. Apart from illustrating the use of this method and the interpretation of results using simulated data, we apply the package on data from three‐spined sticklebacks (Gasterosteus aculeatus) to highlight its virtues. driftsel can also be used to perform usual quantitative genetic analyses in common‐garden study designs.     

Geographic distribution patterns of melanistic Arabian Wolves,Canis lupus arabs (Pocock), in Saudi Arabia (Mammalia: Carnivora)

Melanism is a common colour polymorphism in carnivores, and may have adaptive relevance in certain ecological scenarios. This coat colour variation is present in Arabian Wolves Canis lupus arabs, a widely distributed species in the Arabian Peninsula, especially in western Highlands of Saudi Arabia. Data collection involved field surveys conducted between 2010 and 2017 including active searches for black wolf carcasses, records of live animals encountered during field surveys, and by using >100 camera traps. Niche models were generated for non-melanistic and melanistic wolves based on environmental predictors aiming to discover geographic patterns of distinct phenotypes distribution in this area. In this study, melanistic wolves were recorded at 12 locations from western highlands ranges. Niche model predicts suitability for melanistic and non-melanistic wolves mainly in western highlands and found that melanistic wolves were encountered in regions where moisture is high, predicting a close relationship between humidity and the presence of black animals.     

Genome-scale analysis of demographic history and adaptive selection

One of the main topics in population genetics is identification of adaptive selection among populations. For this purpose, population history should be correctly inferred to evaluate the effect of random drift and exclude it in selection identification. With the rapid progress in genomics in the past decade, vast genomescale variations are available for population genetic analysis, which however requires more sophisticated models to infer species’ demographic history and robust methods to detect local adaptation. Here we aim to review what have been achieved in the fields of demographic modeling and selection detection. We summarize their rationales, implementations, and some classical applications. We also propose that some widely-used methods can be improved in both theoretical and practical aspects in near future.     

Sexual selection and the evolutionary dynamics of the major histocompatibility complex

The genes of the major histocompatibility complex (MHC) are a key component of the adaptive immune system and among the most variable loci in the vertebrate genome. Pathogen-mediated natural selection and MHC-based disassortative mating are both thought to structure MHC polymorphism, but their effects have proven difficult to discriminate in natural systems. Using the first model of MHC dynamics incorporating both survival and reproduction, we demonstrate that natural and sexual selection produce distinctive signatures of MHC allelic diversity with critical implications for understanding host–pathogen dynamics. While natural selection produces the Red Queen dynamics characteristic of host–parasite interactions, disassortative mating stabilizes allele frequencies, damping major fluctuations in dominant alleles and protecting functional variants against drift. This subtle difference generates a complex interaction between MHC allelic diversity and population size. In small populations, the stabilizing effects of sexual selection moderate the effects of drift, whereas pathogen-mediated selection accelerates the loss of functionally important genetic diversity. Natural selection enhances MHC allelic variation in larger populations, with the highest levels of diversity generated by the combined action of pathogen-mediated selection and disassortative mating. MHC-based sexual selection may help to explain how functionally important genetic variation can be maintained in populations of conservation concern.     

The evolutionary consequences of habitat fragmentation: Body morphology and coloration differentiation among brook trout populations of varying size

A reduction in population size due to habitat fragmentation can alter the relative roles of different evolutionary mechanisms in phenotypic trait differentiation. While deterministic (selection) and stochastic (genetic drift) mechanisms are expected to affect trait evolution, genetic drift may be more important than selection in small populations. We examined relationships between mature adult traits and ecological (abiotic and biotic) variables among 14 populations of brook trout. These naturally fragmented populations have shared ancestry but currently exhibit considerable variability in habitat characteristics and population size (49 < N_c < 10,032; 3 < N_b < 567). Body size, shape, and coloration differed among populations, with a tendency for more variation among small populations in both trait means and CV when compared to large populations. Phenotypic differences were more frequently and directly linked to habitat variation or operational sex ratio than to population size, suggesting that selection may overcome genetic drift at small population size. Phenotype–environment associations were also stronger in females than males, suggesting that natural selection due to abiotic conditions may act more strongly on females than males. Our results suggest that natural and sexual‐selective pressures on phenotypic traits change during the process of habitat fragmentation, and that these changes are largely contingent upon existing habitat conditions within isolated fragments. Our study provides an improved understanding of the ecological and evolutionary consequences of habitat fragmentation and lends insight into the ability of some small populations to respond to selection and environmental change.     

Complexity, pleiotropy, and the fitness effect of mutations

One of the assumptions underlying many theoretical predictions in evolutionary biology concerns the distribution of the fitness effect of mutations. Approximations to this distribution have been derived using various theoretical approaches, of which Fisher's geometrical model is among the most popular ones. Two key concepts in this model are complexity and pleiotropy. Recent studies have proposed different methods for estimating how complexity varies across species, but their results have been contradictory. Here, we show that contradictory results are to be expected when the assumption of universal pleiotropy is violated. We develop a model in which the two key parameters are the total number of traits and the mean number of traits affected by a single mutation. We derive approximations for the distribution of the fitness effect of mutations when populations are either well-adapted or away from the optimum. We also consider drift load in a well-adapted population and show that it is independent of the distribution of the fitness effect of mutations. We show that mutation accumulation experiments can only measure the effect of the mean number of traits affected by mutations, whereas drift load only provides information about the total number of traits. We discuss the plausibility of the model.