A clever solution to a vexing problem

F_ST (as well as related measures such as G_ST) has long been used both as a measure of the relative amount of genetic variation between populations and as an indicator of the amount of gene flow among populations. Unfortunately, F_ST and its clones are also sensitive to mutation, particularly when the mutation rate per locus is greater than the migration rate among populations. Relatively high mutation rates cause estimates of F_ST and G_ST to be much lower than researchers sometimes expect, when migration rates are low in the studied species. Several recent suggestions for dealing with this problem have been unsatisfactory for one reason or another, and no general solution exists (if we are not to abandon these otherwise useful measures of differentiation). In an important article in this issue, Jinliang Wang (2015) shows that it is possible to identify whether the genetic markers in a given study are likely to give estimates of F_ST that are strongly affected by mutation. The proposed test is simple and elegant, and with it, molecular ecologists can determine whether the F_ST from their makers can be depended on for further inference about their species’ genome and the demographic forces which shaped its patterns.     

Large‐scale adaptive divergence in Boechera fecunda,an endangered wild relative of Arabidopsis

Many biological species are threatened with extinction because of a number of factors such as climate change and habitat loss, and their preservation depends on an accurate understanding of the extent of their genetic variability within and among populations. In this study, we assessed the genetic divergence of five quantitative traits in 10 populations of an endangered cruciferous species, Boechera fecunda, found in only several populations in each of two geographic regions (WEST and EAST) in southwestern Montana. We analyzed variation in quantitative traits, neutral molecular markers, and environmental factors and provided evidence that despite the restricted geographical distribution of this species, it exhibits a high level of genetic variation and regional adaptation. Conservation efforts therefore should be directed to the preservation of populations in each of these two regions without attempting transplantation between regions. Heritabilities and genetic coefficients of variation estimated from nested ANOVAs were generally high for leaf and rosette traits, although lower (and not significantly different from 0) for water‐use efficiency. Measures of quantitative genetic differentiation, Q_ST, were calculated for each trait from each pair of populations. For three of the five traits, these values were significantly higher between regions compared with those within regions (after adjustment for neutral genetic variation, F_ST). This suggested that natural selection has played an important role in producing regional divergence in this species. Our analysis also revealed that the B. fecunda populations appear to be locally adapted due, at least in part, to differences in environmental conditions in the EAST and WEST regions.     

Reanalysis suggests that genomic islands of speciation are due to reduced diversity,not reduced gene flow

The metaphor of ‘genomic islands of speciation’ was first used to describe heterogeneous differentiation among loci between the genomes of closely related species. The biological model proposed to explain these differences was that the regions showing high levels of differentiation were resistant to gene flow between species, while the remainder of the genome was being homogenized by gene flow and consequently showed lower levels of differentiation. However, the conditions under which such differentiation can occur at multiple unlinked loci are restrictive; additionally, essentially, all previous analyses have been carried out using relative measures of divergence, which can be misleading when regions with different levels of recombination are compared. Here, we test the model of differential gene flow by asking whether absolute divergence is also higher in the previously identified ‘islands’. Using five species pairs for which full sequence data are available, we find that absolute measures of divergence are not higher in genomic islands. Instead, in all cases examined, we find reduced diversity in these regions, a consequence of which is that relative measures of divergence are abnormally high. These data therefore do not support a model of differential gene flow among loci, although islands of relative divergence may represent loci involved in local adaptation. Simulations using the program IMa2 further suggest that inferences of any gene flow may be incorrect in many comparisons. We instead present an alternative explanation for heterogeneous patterns of differentiation, one in which postspeciation selection generates patterns consistent with multiple aspects of the data.     

Finding needles in a genomic haystack: targeted capture identifies clear signatures of selection in a nonmodel plant species

Teasing apart neutral and adaptive genomic processes and identifying loci that are targets of selection can be difficult, particularly for nonmodel species that lack a reference genome. However, identifying such loci and the factors driving selection have the potential to greatly assist conservation and restoration practices, especially for the management of species in the face of contemporary and future climate change. Here, we focus on assessing adaptive genomic variation within a nonmodel plant species, the narrow‐leaf hopbush (Dodonaea viscosa ssp. angustissima), commonly used for restoration in Australia. We used a hybrid‐capture target enrichment approach to selectively sequence 970 genes across 17 populations along a latitudinal gradient from 30°S to 36°S. We analysed 8462 single‐nucleotide polymorphisms (SNPs) for F_ST outliers as well as associations with environmental variables. Using three different methods, we found 55 SNPs with significant correlations to temperature and water availability, and 38 SNPs to elevation. Genes containing SNPs identified as under environmental selection were diverse, including aquaporin and abscisic acid genes, as well as genes with ontologies relating to responses to environmental stressors such as water deprivation and salt stress. Redundancy analysis demonstrated that only a small proportion of the total genetic variance was explained by environmental variables. We demonstrate that selection has led to clines in allele frequencies in a number of functional genes, including those linked to leaf shape and stomatal variation, which have been previously observed to vary along the sampled environmental cline. Using our approach, gene regions subject to environmental selection can be readily identified for nonmodel organisms.     

A trait‐based approach to predict population genetic structure in bees

Understanding population genetic structure is key to developing predictions about species susceptibility to environmental change, such as habitat fragmentation and climate change. It has been theorized that life‐history traits may constrain some species in their dispersal and lead to greater signatures of population genetic structure. In this study, we use a quantitative comparative approach to assess if patterns of population genetic structure in bees are driven by three key species‐level life‐history traits: body size, sociality, and diet breadth. Specifically, we reviewed the current literature on bee population genetic structure, as measured by the differentiation indices Nei's G_ST, Hedrick's G′_ST, and Jost's D. We then used phylogenetic generalised linear models to estimate the correlation between the evolution of these traits and patterns of genetic differentiation. Our analyses revealed a negative and significant effect of body size on genetic structure, regardless of differentiation index utilized. For Hedrick's G′_ST and Jost's D, we also found a significant impact of sociality, where social species exhibited lower levels of differentiation than solitary species. We did not find an effect of diet specialization on population genetic structure. Overall, our results suggest that physical dispersal or other functions related to body size are among the most critical for mediating population structure for bees. We further highlight the importance of standardizing population genetic measures to more easily compare studies and to identify the most susceptible species to landscape and climatic changes.     

Nonrandom dispersal drives phenotypic divergence within a bird population

Gene flow through dispersal has traditionally been thought to function as a force opposing evolutionary differentiation. However, directional gene flow may actually reinforce divergence of populations in close proximity. This study documents the phenotypic differentiation over more than two decades in body size (tarsus length) at a very short spatial scale (1.1 km) within a population of pied flycatchers Ficedula hypoleuca inhabiting deciduous and coniferous habitats. Unlike females, males breeding in the deciduous forest were consistently larger than those from the managed coniferous forest. This assortment by size is likely explained by preset habitat preferences leading to dominance of the largest males and exclusion of the smallest ones toward the nonpreferred coniferous forest coupled with directional dispersal. Movements of males between forests were nonrandom with respect to body size and flow rate, which might function to maintain the phenotypic variation in this heritable trait at such a small spatial scale. However, a deeply rooted preference for the deciduous habitat might not be in line with its quality due to the increased levels of breeding density of hole‐nesting competitors therein. These results illustrate how eco‐evolutionary scenarios can develop under directional gene flow over surprisingly small spatial scales. Our findings come on top of recent studies concerning new ways in which dispersal and gene flow can influence microevolution.     

ABC inference of multi‐population divergence with admixture from unphased population genomic data

Rapidly developing sequencing technologies and declining costs have made it possible to collect genome‐scale data from population‐level samples in nonmodel systems. Inferential tools for historical demography given these data sets are, at present, underdeveloped. In particular, approximate Bayesian computation (ABC) has yet to be widely embraced by researchers generating these data. Here, we demonstrate the promise of ABC for analysis of the large data sets that are now attainable from nonmodel taxa through current genomic sequencing technologies. We develop and test an ABC framework for model selection and parameter estimation, given histories of three‐population divergence with admixture. We then explore different sampling regimes to illustrate how sampling more loci, longer loci or more individuals affects the quality of model selection and parameter estimation in this ABC framework. Our results show that inferences improved substantially with increases in the number and/or length of sequenced loci, while less benefit was gained by sampling large numbers of individuals. Optimal sampling strategies given our inferential models included at least 2000 loci, each approximately 2 kb in length, sampled from five diploid individuals per population, although specific strategies are model and question dependent. We tested our ABC approach through simulation‐based cross‐validations and illustrate its application using previously analysed data from the oak gall wasp, Biorhiza pallida.     

QST–FST comparisons with unbalanced half‐sib designs

Q_ST, a measure of quantitative genetic differentiation among populations, is an index that can suggest local adaptation if Q_ST for a trait is sufficiently larger than the mean F_ST of neutral genetic markers. A previous method by Whitlock and Guillaume derived a simulation resampling approach to statistically test for a difference between Q_ST and F_ST, but that method is limited to balanced data sets with offspring related as half‐sibs through shared fathers. We extend this approach (i) to allow for a model more suitable for some plant populations or breeding designs in which offspring are related through mothers (assuming independent fathers for each offspring; half‐sibs by dam); and (ii) by explicitly allowing for unbalanced data sets. The resulting approach is made available through the R package QstFstComp.     

Local adaptation through genetic differentiation in highly fragmented Tilia cordata populations

We assessed the level of geographic differentiation of Tilia cordata in Denmark based on tests of 91 trees selected from 12 isolated populations. We used quantitative analysis of spring phenology and population genetic analysis based on SSR markers to infer the likely historical genetic processes within and among populations. High genetic variation within and among populations was observed in spring phenology, which correlated with spring temperatures at the origin of the tested T. cordata trees. The population genetic analysis revealed significant differentiation among the populations, but with no clear sign of isolation by distance. We infer the findings as indications of ongoing fine scale selection in favor of local growth conditions made possible by limited gene flow among the small and fragmented populations. This hypothesis fits well with reports of limited fruiting in the investigated Danish T. cordata populations, while the species is known for its ability to propagate vegetatively by root suckers. Our results suggest that both divergent selection and genetic drift may have played important roles in forming the genetic patterns of T. cordata at its northern distribution limit. However, we also speculate that epigenetic mechanism arising from the original population environment could have created similar patterns in regulating the spring phenology.     

Population genomic evidence for adaptive differentiation in the Baltic Sea herring

Detecting and estimating the degree of genetic differentiation among populations of highly mobile marine fish having pelagic larval stages is challenging because their effective population sizes can be large, and thus, little genetic drift and differentiation is expected in neutral genomic sites. However, genomic sites subject to directional selection stemming from variation in local environmental conditions can still show substantial genetic differentiation, yet these signatures can be hard to detect with low‐throughput approaches. Using a pooled RAD‐seq approach, we investigated genomewide patterns of genetic variability and differentiation within and among 20 populations of Atlantic herring in the Baltic Sea (and adjacent Atlantic sites), where previous low‐throughput studies and/or studies based on few populations have found limited evidence for genetic differentiation. Stringent quality control was applied in the filtering of 1 791 254 SNPs, resulting in a final data set of 68 182 polymorphic loci. Clear differentiation was identified between Atlantic and Baltic populations in many genomic sites, while differentiation within the Baltic Sea area was weaker and geographically less structured. However, outlier analyses – whether including all populations or only those within the Baltic Sea – uncovered hundreds of directionally selected loci in which variability was associated with either salinity, temperature or both. Hence, our results support the view that although the degree of genetic differentiation among Baltic Sea herring populations is low, there are many genomic regions showing elevated divergence, apparently as a response to temperature‐ and salinity‐related natural selection. As such, the results add to the increasing evidence of local adaptation in highly mobile marine organisms, and those in the young Baltic Sea in particular.     

On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system

Dispersal and natural selection are key evolutionary processes shaping the distribution of phenotypic and genetic diversity. For species inhabiting complex spatial environments however, it is unclear how the balance between gene flow and selection may be influenced by landscape heterogeneity and environmental variation. Here, we evaluated the effects of dendritic landscape structure and the selective forces of hydroclimatic variation on population genomic parameters for the Murray River rainbowfish, Melanotaenia fluviatilis across the Murray–Darling Basin, Australia. We genotyped 249 rainbowfish at 17,503 high‐quality SNP loci and integrated these with models of network connectivity and high‐resolution environmental data within a riverscape genomics framework. We tested competing models of gene flow before using multivariate genotype–environment association (GEA) analysis to test for signals of adaptive divergence associated with hydroclimatic variation. Patterns of neutral genetic variation were consistent with expectations based on the stream hierarchy model and M. fluviatilis’ moderate dispersal ability. Models incorporating dendritic network structure suggested that landscape heterogeneity is a more important factor determining connectivity and gene flow than waterway distance. Extending these results, we also introduce a novel approach to controlling for the unique effects of dendritic network structure in GEA analyses of populations of aquatic species. We identified 146 candidate loci potentially underlying a polygenic adaptive response to seasonal fluctuations in stream flow and variation in the relative timing of temperature and precipitation extremes. Our findings underscore an emerging predominant role for seasonal variation in hydroclimatic conditions driving local adaptation and are relevant for informing proactive conservation management.     

Global patterns of population genetic differentiation in seed plants

Evaluating the factors that drive patterns of population differentiation in plants is critical for understanding several biological processes such as local adaptation and incipient speciation. Previous studies have given conflicting results regarding the significance of pollination mode, seed dispersal mode, mating system, growth form and latitudinal region in shaping patterns of genetic structure, as estimated by F_ST values, and no study to date has tested their relative importance together across a broad scale. Here, we assembled a 337‐species data set for seed plants from publications with data on F_ST from nuclear markers and species traits, including variables pertaining to the sampling scheme of each study. We used species traits, while accounting for sampling variables, to perform phylogenetic multiple regressions. Results demonstrated that F_ST values were higher for tropical, mixed‐mating, non‐woody species pollinated by small insects, indicating greater population differentiation, and lower for temperate, outcrossing trees pollinated by wind. Among the factors we tested, latitudinal region explained the largest portion of variance, followed by pollination mode, mating system and growth form, while seed dispersal mode did not significantly relate to F_ST. Our analyses provide the most robust and comprehensive evaluation to date of the main ecological factors predicted to drive population differentiation in seed plants, with important implications for understanding the basis of their genetic divergence. Our study supports previous findings showing greater population differentiation in tropical regions and is the first that we are aware of to robustly demonstrate greater population differentiation in species pollinated by small insects.     

Taking advantage from phenotype variability in a local animal genetic resource: identification of genomic regions associated with the hairless phenotype in Casertana pigs

Casertana is an endangered autochthonous pig breed (raised in south‐central Italy) that is considered to be the descendant of the influential Neapolitan pig population that was used to improve British breeds in the 19th century. Casertana pigs are characterized by a typical, almost complete, hairless phenotype, even though a few Casertana pigs are normal haired. In this work, using Illumina PorcineSNP60 BeadChip data, we carried out a genome‐wide association study and an F_ST analysis with this breed by comparing animals showing the classical hairless phenotype (n = 81) versus pigs classified as haired (n = 15). Combining the results obtained with the two approaches, we identified two significant regions: one on porcine chromosome (SSC) 7 and one on SSC15. The SSC7 region contains the forkhead box N3 (FOXN3) gene, the most plausible candidate gene of this region, considering that mutations in another gene of the same family (forkhead box N1; Foxn1 or FOXN1) are responsible for the nude locus in rodents and alopecia in humans. Another potential candidate gene, rho guanine nucleotide exchange factor 10 (ARHGEF10), is located in the SSC15 region. FOXN3 and ARHGEF10 have been detected as differentially expressed in androgenetic and senescent alopecia respectively. This study on an autochthonous pig breed contributes to shed some light on novel genes potentially involved in hair development and growth and demonstrates that local animal breeds can be valuable genetic resources for disclosing genetic factors affecting unique traits, taking advantage of phenotype variability segregating in small populations.     

Detecting selection signatures in three Iranian sheep breeds

The objective of genome mapping is to achieve valuable insight into the connection between gene variants (genotype) and observed traits (phenotype). Part of that objective is to understand the selective forces that have operated on a population. Finding links between genotype–phenotype changes makes it possible to identify selective sweeps by patterns of genetic variation and linkage disequilibrium. Based on Illumina 50KSNP chip data, two approaches, XP‐EHH (cross‐population extend haplotype homozygosity) and F_ST (fixation index), were carried out in this research to identify selective sweeps in the genome of three Iranian local sheep breeds: Baluchi (n = 86), Lori‐Bakhtiari (n = 45) and Zel (n = 45). Using both methods, 93 candidate genomic regions were identified as harboring putative selective sweeps. Bioinformatics analysis of the genomic regions showed that signatures of selection related to multiple candidate genes, such as HOXB9, HOXB13, ACAN, NPR2, TRIL, AOX1, CSF2, GHR, TNS2, SPAG8, HINT2, ALS2, AAAS, RARG, SYCP2, CAV1, PPP1R3D, PLA2G7, TTLL7 and C20orf10, that play a role in skeletal system and tail, sugar and energy metabolisms, growth, reproduction, immune and nervous system traits. Our findings indicated diverse genomic selection during the domestication of Iranian sheep breeds.     

Functional genomic analysis of corals from natural CO2‐seeps reveals core molecular responses involved in acclimatization to ocean acidification

Little is known about the potential for acclimatization or adaptation of corals to ocean acidification and even less about the molecular mechanisms underpinning these processes. Here, we examine global gene expression patterns in corals and their intracellular algal symbionts from two replicate population pairs in Papua New Guinea that have undergone long‐term acclimatization to natural variation in pCO₂. In the coral host, only 61 genes were differentially expressed in response to pCO₂ environment, but the pattern of change was highly consistent between replicate populations, likely reflecting the core expression homeostasis response to ocean acidification. Functional annotations highlight lipid metabolism and a change in the stress response capacity of corals as key parts of this process. Specifically, constitutive downregulation of molecular chaperones was observed, which may impact response to combined climate change‐related stressors. Elevated CO₂ has been hypothesized to benefit photosynthetic organisms but expression changes of in hospite Symbiodinium in response to acidification were greater and less consistent among reef populations. This population‐specific response suggests hosts may need to adapt not only to an acidified environment, but also to changes in their Symbiodinium populations that may not be consistent among environments, adding another challenging dimension to the physiological process of coping with climate change.     

The role of immigration and local adaptation on fine‐scale genotypic and phenotypic population divergence in a less mobile passerine

Dispersal and local patterns of adaptation play a major role on the ecological and evolutionary trajectory of natural populations. In this study, we employ a combination of genetic (25 microsatellite markers) and field‐based information (seven study years) to analyse the impact of immigration and local patterns of adaptation in two nearby (< 7 km) blue tit (Cyanistes caeruleus) populations. We used genetic assignment analyses to identify immigrant individuals and found that dispersal rate is female‐biased (72%). Data on lifetime reproductive success indicated that immigrant females produced fewer local recruits than their philopatric counterparts whereas immigrant males recruited more offspring than those that remained in their natal location. In spite of the considerably higher immigration rates of females, our results indicate that, in absolute terms, their demographic and genetic impact in the receiving populations is lower than that in immigrant males. Immigrants often brought novel alleles into the studied populations and a high proportion of them were transmitted to their recruits, indicating that the genetic impact of immigrants is not ephemeral. Although only a few kilometres apart, the two study populations were genetically differentiated and showed strong divergence in different phenotypic and life‐history traits. An almost absent inter‐population dispersal, together with the fact that both populations receive immigrants from different source populations, is probably the main cause of the observed pattern of genetic differentiation. However, phenotypic differentiation (P_ST) for all the studied traits greatly exceeded neutral genetic differentiation (F_ST), indicating that divergent natural selection is the prevailing factor determining the evolutionary trajectory of these populations. Our study highlights the importance of integrating individual‐ and population‐based approaches to obtain a comprehensive view about the role of dispersal and natural selection on structuring the genotypic and phenotypic characteristics of natural populations.