Genomic Scanning Method Research Articles

Uncovering ghost introgression through genomic analysis of a distinct eastern Asian hickory species.

Ghost introgression, or the transfer of genetic material from extinct or unsampled lineages to sampled species, has attracted much attention. However, conclusive evidence for ghost introgression, especially in plant species, remains scarce. Here, we newly assembled chromosome-level genomes for both Carya sinensis and Carya cathayensis, and additionally re-sequenced the whole genomes of 43 C. sinensis individuals as well as 11 individuals representing 11 diploid hickory species. These genomic datasets were used to investigate the reticulation and bifurcation patterns within the genus Carya (Juglandaceae), with a particular focus on the beaked hickory C. sinensis. By combining the D-statistic and BPP methods, we obtained compelling evidence that supports the occurrence of ghost introgression in C. sinensis from an extinct ancestral hickory lineage. This conclusion was reinforced through the phylogenetic network analysis and a genome scan method VolcanoFinder, the latter of which can detect signatures of adaptive introgression from unknown donors. Our results not only dispel certain misconceptions about the phylogenetic history of C. sinensis but also further refine our understanding of Carya's biogeography via divergence estimates. Moreover, the successful integration of the D-statistic and BPP methods demonstrates their efficacy in facilitating a more precise identification of introgression types.

Demographic history and distinct selection signatures of two domestication genes in mungbean.

Domestication is the long and complex process underlying the evolution of crops, in which artificial directional selection transformed wild progenitors into the desired form, affecting genomic variation and leaving traces of selection at targeted loci. However, whether genes controlling important domestication traits follow the same evolutionary pattern expected under the standard selective sweep model remains unclear. With whole-genome re-sequencing of mungbean (Vigna radiata), we investigated this issue by resolving its global demographic history and targeted dissection of the molecular footprints of genes underlying two key traits representing different stages of domestication. Mungbean originated in Asia, and the Southeast Asian wild population migrated to Australia about 50 thousand generations ago (kga). Later in Asia, the cultivated form diverged from the wild progenitor. We identified the gene associated with the pod shattering resistance trait, VrMYB26a, with lower expression across cultivars and reduced polymorphism in the promoter region, reflecting a hard selective sweep. On the other hand, the stem determinacy trait was associated with VrDet1. We found two ancient haplotypes of this gene have lower gene expression and exhibited intermediate frequencies in cultivars, consistent with selection favoring independent haplotypes in a soft selective sweep. In mungbean, contrasting signatures of selection were identified from the detailed dissection of two important domestication traits. The results suggest complex genetic architecture underlying the seemingly simple process of directional artificial selection and highlight the limitations of genome-scan methods relying on hard selective sweeps.

Whole Genome Resequencing Reveals Genetic Diversity and Selection Signatures of Ethiopian Indigenous Cattle Adapted to Local Environments

Cattle are among the most important domesticated bovid species in the world, of which Ethiopia possesses large populations adapted to different agro-ecologies and production systems. Though several molecular population genetic studies have been done on Ethiopian indigenous cattle, genomic diversity and selection signatures pertinent to adaptation to the different local environments have yet to be comprehensively characterized. Here, the whole genome sequences of 151 samples from 14 Ethiopian indigenous cattle populations were analyzed to assess genomic diversity and differentiation as well as signatures of positive selection (using Hp, iHS, FST, and XP-CLR) in comparison to Sudanese zebu, Asian zebu, Ankole, and African and European taurine cattle. High genomic differentiation was observed between Ethiopian and non-Ethiopian cattle populations, while low genomic differentiation and inbreeding were present between and within Ethiopian cattle populations. Sixteen genome regions overlapping with 40 candidate genes were commonly identified by at least three genome scan methods. High frequencies of missense SNPs in ITPR2, CHADL, GNAS, STING1, and KIT genes with high haplotype differentiations were observed in Ethiopian cattle compared to non-Ethiopian cattle. The candidate genes were significantly associated with several biological functions and molecular pathways responsible for nutrient metabolism, skeletal development, immune response, reproduction, water balance, coat color pigmentation, and circulatory homeostasis. Our results provide new insights into the adaptation of the Ethiopian indigenous cattle to the country’s diverse environments.

Genome Scan of Rice Landrace Populations Collected Across Time Revealed Climate Changes’ Selective Footprints in the Genes Network Regulating Flowering Time

Analyses of the genetic bases of plant adaptation to climate changes, using genome-scan approaches, are often conducted on natural populations, under hypothesis of out-crossing reproductive regime. We report here on a study based on diachronic sampling (1980 and 2011) of the autogamous crop species, Oryza sativa and Oryza glaberrima, in the tropical forest and the Sudanian savannah of West Africa. First, using historical meteorological data we confirmed changes in temperatures (+ 1 °C on average) and rainfall regime (less predictable and reduced amount) in the target areas. Second, phenotyping the populations for phenology, we observed significantly earlier heading time in the 2010 samples. Third, implementing two genome-scan methods (one of which specially developed for selfing species) on genotyping by sequencing genotypic data of the two populations, we detected 31 independent selection footprints. Gene ontology analysis detected significant enrichment of these selection footprints in genes involved in reproductive processes. Some of them bore known heading time QTLs and genes, including OsGI, Hd1 and OsphyB. This rapid adaptive evolution, originated from subtle changes in the standing variation in genetic network regulating heading time, did not translate into predominance of multilocus genotypes, as it is often the case in selfing plants, and into notable selective sweeps. The high adaptive potential observed results from the multiline genetic structure of the rice landraces, and the rather large and imbricated genetic diversity of the rice meta-population at the farm, the village and the region levels, that hosted the adaptive variants in multiple genetic backgrounds before the advent of the environmental selective pressure. Our results illustrate the evolution of in situ diversity through processes of human and natural selection, and provide a model for rice breeding and cultivars deployment strategies aiming resilience to climate changes. It also calls for further development of population genetic models for adaptation of plant populations to environmental changes. To our best knowledge, this is the first study dealing with climate-changes’ selective footprint in crops.

Pattern of Adaptive Divergence in Zingiber kawagoii Hayata (Zingiberaceae) along a Narrow Latitudinal Range.

Ecological and evolutionary processes linking adaptation to environment are related to species’ range shifts. In this study, we employed amplified-fragment-length-polymorphism-based genome scan methods to identify candidate loci among Zingiber kawagoii populations inhabiting varying environments distributed at low to middle elevations (143–1488 m) in a narrow latitudinal range (between 21.90 and 25.30° N). Here, we show evidence of selection driving the divergence of Z. kawagoii. Twenty-six FST outliers were detected, which were significantly correlated with various environmental variables. The allele frequencies of nine FST outliers were either positively or negatively correlated with the population mean FST. Using several independent approaches, we found environmental variables act in a combinatorial fashion, best explaining outlier genetic variation. Nonetheless, we found that adaptive divergence was affected mostly by annual temperature range, and it is significantly positively correlated with latitude and significantly negatively correlated with the population mean FST. This study addresses a latitudinal pattern of changes in annual temperature range (which ranged from 13.8 °C in the Lanyu population to 18.5 °C in the Wulai population) and emphasizes the pattern of latitudinal population divergence closely linked to the allele frequencies of adaptive loci, acting in a narrow latitudinal range. Our results also indicate environmentally dependent local adaptation for both leading- and trailing-edge populations.

Time-Series Sequences for Evolutionary Inferences.

The application of genomics to evolutionary biology has provided unprecedented power and resolution to investigate processes like mutation (Nachman and Crowell 2000; Rozhok and Degregori 2019), genetic drift (Whitney and Garland 2010; Funk et al. 2016), gene flow (Gallego-García et al. 2019; LaCava et al. 2021), and natural selection (Brauer et al. 2016; Martins et al. 2018). Evolutionary genomics has historically used contemporary or single-timepoint samples to study microevolutionary processes that most often depend on idealized model assumptions (e.g., Wright–Fisher model) (Butlin 2008; Hoban et al. 2016). For example, genome scanning methods aim to detect natural selection by assuming that the impact of selection can be discerned from the effects of neutral evolutionary processes on genetic differentiation (Hoban et al. 2016). However, different demographic scenarios can also produce signatures of selection, leading to false positives (Lotterhos and Whitlock 2015; Haasl and Payseur 2016). Similarly, when using measures of genetic differentiation to estimate gene flow, most models assume that population size is large enough that genetic drift is negligible—that is, not driving neutral divergence between populations (Whitlock and McCauley 1999; Ma et al. 2015).

Detection of sexually antagonistic transmission distortions in trio datasets.

Sexual dimorphisms are widespread in animals and plants, for morphological as well as physiological traits. Understanding the genetic basis of sexual dimorphism and its evolution is crucial for understanding biological differences between the sexes. Genetic variants with sex‐antagonistic effects on fitness are expected to segregate in populations at the early phases of sexual dimorphism emergence. Detecting such variants is notoriously difficult, and the few genome‐scan methods employed so far have limited power and little specificity. Here, we propose a new framework to detect a signature of sexually antagonistic (SA) selection. We rely on trio datasets where sex‐biased transmission distortions can be directly tracked from parents to offspring, and identify signals of SA transmission distortions in genomic regions. We report the genomic location of six candidate regions detected in human populations as potentially under sexually antagonist selection. We find an enrichment of genes associated with embryonic development within these regions. Last, we highlight two candidate regions for SA selection in humans.

Genome-wide signatures in flax pinpoint to adaptive evolution along its ecological gradient

Flax is one of the eight founder crops of agriculture. It is believed to have been domesticated as a long-day plant that has since spread to survive in a wide range of eco-geographic regions extending from the warm Indian subcontinent to the low latitude east African highlands and to the cool and high-latitude Eurasia. Understanding the genetic basis underlying its adaptation and selection events throughout its dispersion is essential to develop cultivars adapted to local environmental conditions.Here we detected genetic signatures of local adaptation and selection events of flax based on 385 accessions from all major flax growing regions of the world using genome scan methods and three genomic datasets: (1) a genome-wide dataset of more than 275K single nucleotide polymorphisms (SNPs), (2) a filtered dataset of 23K SNPs with minor allele frequency >10% and, (3) a 34K exon-derived SNP dataset.Principal component (PC) and fixation index (FS⁢T)-based genome scans yielded consistent outlier SNP loci on chromosomes 1, 8, 9 and 12. Additional loci on chromosomes 3, 7, 8, 10, 11, 13 and 14 were detected using both the PC and FS⁢T methods in two of the three datasets. A genome-environment association (GEA) analysis using the 23K dataset and the first PC of cropping season temperature, day-length and latitude identified significant SNPs on chromosomes 3, 7, 9 and 13.Most of the loci detected by the three methods harbored relevant genes for local adaptation, including some that play roles in day-length, light and other biotic and abiotic stresses responses. Such genetic signatures may help to select pre-breeding materials potentially adapted to specific growing niches prior to field performance trials. Given the current low genotyping cost and freely available environmental data, the genome scans along with GEA can readily provide opportunity to sort out materials suitable to various environmental conditions from large set of germplasm in gene banks and/or in situ, thereby assisting the breeding and genetic conservation efforts.

Genomic Signatures of a Major Adaptive Event in the Pathogenic Fungus Melampsora larici-populina.

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

Identifying loci under selection via explicit demographic models.

Adaptive genetic variation is a function of both selective and neutral forces. To accurately identify adaptive loci, it is thus critical to account for demographic history. Theory suggests that signatures of selection can be inferred using the coalescent, following the premise that genealogies of selected loci deviate from neutral expectations. Here, we build on this theory to develop an analytical framework to identify loci under selection via explicit demographic models (LSD). Under this framework, signatures of selection are inferred through deviations in demographic parameters, rather than through summary statistics directly, and demographic history is accounted for explicitly. Leveraging the property of demographic models to incorporate directionality, we show that LSD can provide information on the environment in which selection acts on a population. This can prove useful in elucidating the selective processes underlying local adaptation, by characterizing genetic trade‐offs and extending the concepts of antagonistic pleiotropy and conditional neutrality from ecological theory to practical application in genomic data. We implement LSD via approximate Bayesian computation and demonstrate, via simulations, that LSD (a) has high power to identify selected loci across a large range of demographic‐selection regimes, (b) outperforms commonly applied genome‐scan methods under complex demographies and (c) accurately infers the directionality of selection for identified candidates. Using the same simulations, we further characterize the behaviour of isolation‐with‐migration models conducive to the study of local adaptation under regimes of selection. Finally, we demonstrate an application of LSD by detecting loci and characterizing genetic trade‐offs underlying flower colour in Antirrhinum majus.

Looking for the needle in a downsized haystack: Whole-exome sequencing unravels genomic signals of climatic adaptation in Douglas-fir (Pseudotsuga menziesii).

Conifers often occur along steep gradients of diverse climates throughout their natural ranges, which is expected to result in spatially varying selection to local climate conditions. However, signals of climatic adaptation can often be confounded, because unraveled clines covary with signals caused by neutral evolutionary processes such as gene flow and genetic drift. Consequently, our understanding of how selection and gene flow have shaped phenotypic and genotypic differentiation in trees is still limited.A 40‐year‐old common garden experiment comprising 16 Douglas‐fir (Pseudotsuga menziesii) provenances from a north‐to‐south gradient of approx. 1,000 km was analyzed, and genomic information was obtained from exome capture, which resulted in an initial genomic dataset of >90,000 single nucleotide polymorphisms. We used a restrictive and conservative filtering approach, which permitted us to include only SNPs and individuals in environmental association analysis (EAA) that were free of potentially confounding effects (LD, relatedness among trees, heterozygosity deficiency, and deviations from Hardy–Weinberg proportions). We used four conceptually different genome scan methods based on FST outlier detection and gene–environment association in order to disentangle truly adaptive SNPs from neutral SNPs.We found that a relatively small proportion of the exome showed a truly adaptive signal (0.01%–0.17%) when population substructuring and multiple testing was accounted for. Nevertheless, the unraveled SNP candidates showed significant relationships with climate at provenance origins, which strongly suggests that they have featured adaptation in Douglas‐fir along a climatic gradient. Two SNPs were independently found by three of the employed algorithms, and one of them is in close proximity to an annotated gene involved in circadian clock control and photoperiodism as was similarly found in Populus balsamifera. Synthesis. We conclude that despite neutral evolutionary processes, phenotypic and genomic signals of adaptation to climate are responsible for differentiation, which in particular explain disparity between the well‐known coastal and interior varieties of Douglas‐fir.

Association of putatively adaptive genetic variation with climatic variables differs between a parasite and its host.

Parasitism is a pervasive phenomenon in nature with the relationship between species driving evolution in both parasite and host. Due to their host‐dependent lifestyle, parasites may adapt to the abiotic environment in ways that differ from their hosts or from free‐living relatives; yet rarely has this been assessed. Here, we test two competing hypotheses related to whether putatively adaptive genetic variation in a specialist mistletoe associates with the same, or different, climatic variables as its host species. We sampled 11 populations of the specialist mistletoe Amyema gibberula var. tatei (n = 154) and 10 populations of its associated host Hakea recurva subsp. recurva (n = 160). Reduced‐representation sequencing was used to obtain genome‐wide markers and putatively adaptive variation detected using genome scan methods. Climate associations were identified using generalized dissimilarity modelling, and these were mapped geographically to visualize the spatial patterns of genetic composition. Our results supported the hypothesis of parasites and host species responding differently to climatic variables. Temperature was relatively more important in predicting allelic turnover in the specialist mistletoe while precipitation was more important for the host. This suggests that parasitic plants and host species may respond differently to selective pressures, potentially as a result of differing nutrient acquisition strategies. Specifically, mistletoes acquire water from hosts (rather than the abiotic environment), which may provide a buffer to precipitation as a selective pressure. This work deepens and complements the physiological and other ecological studies of adaptation and provides a window into the evolutionary processes that underlie previously observed phenomena. Applying these methods to a comparative study in a host–parasite system has also highlighted factors that affect the study of selection pressure on nonmodel organisms, such as differing adaptation rates and lack of reference genomes.

Testing the Effect of Mountain Ranges as a Physical Barrier to Current Gene Flow and Environmentally Dependent Adaptive Divergence in Cunninghamia konishii (Cupressaceae).

Populations can be genetically isolated by differences in their ecology or environment that hampered efficient migration, or they may be isolated solely by geographic distance. Moreover, mountain ranges across a species’ distribution area might have acted as barriers to gene flow. Genetic variation was quantified using amplified fragment length polymorphism (AFLP) and 13 selective amplification primer combinations used generated a total of 482 fragments. Here, we tested the barrier effects of mountains on gene flow and environmentally dependent local adaptation of Cunninghamia konishii occur in Taiwan. A pattern of genetic isolation by distance was not found and variation partitioning revealed that environment explained a relatively larger proportion of genetic variation than geography. The effect of mountains as barriers to genetic exchange, despite low population differentiation indicating a high rate of gene flow, was found within the distribution range of C. konishii. Twelve AFLP loci were identified as potential selective outliers using genome-scan methods (BAYESCAN and DFDIST) and strongly associated with environmental variables using regression approaches (LFMM, Samβada, and rstanarm) demonstrating adaptive divergence underlying local adaptation. Annual mean temperature, annual precipitation, and slope could be the most important environmental factors causally associated with adaptive genetic variation in C. konishii. The study revealed the existence of physical barriers to current gene flow and environmentally dependent adaptive divergence, and a significant proportion of the rate of gene flow may represent a reflection of demographic history.

Haplotype Loci Under Selection in Canadian Durum Wheat Germplasm Over 60 Years of Breeding: Association With Grain Yield, Quality Traits, Protein Loss, and Plant Height.

Durum wheat was introduced in the southern prairies of western Canada in the late nineteenth century. Breeding efforts have mainly focused on improving quality traits to meet the pasta industry demands. For this study, 192 durum wheat lines were genotyped using the Illumina 90K Infinium iSelect assay, and resulted in a total of 14,324 polymorphic SNPs. Genetic diversity changed over time, declining during the first 20 years of breeding in Canada, then increased in the late 1980s and early 1990s. We scanned the genome for signatures of selection, using the total variance Fst-based outlier detection method (Lositan), the hierarchical island model (Arlequin) and the Bayesian genome scan method (BayeScan). A total of 407 outliers were identified and clustered into 84 LD-based haplotype loci, spanning all 14 chromosomes of the durum wheat genome. The association analysis detected 54 haplotype loci, of which 39% contained markers with a complete reversal of allelic state. This tendency to fixation of favorable alleles corroborates the success of the Canadian durum wheat breeding programs over time. Twenty-one haplotype loci were associated with multiple traits. In particular, hap_4B_1 explained 20.6, 17.9 and 16.6% of the phenotypic variance of pigment loss, pasta b∗ and dough extensibility, respectively. The locus hap_2B_9 explained 15.9 and 17.8% of the variation of protein content and protein loss, respectively. All these pleiotropic haplotype loci offer breeders the unique opportunity for further improving multiple traits, facilitating marker-assisted selection in durum wheat, and could help in identifying genes as functional annotations of the wheat genome become available.

Signs of adaptation to trace metal contamination in a common urban bird

Metals and metalloids at elevated concentrations can be toxic to both humans and wildlife. In particular, lead exposure can act as a stressor to wildlife and cause negative effects on fitness. Any ability to adapt to stress caused by the negative effects of trace metal exposure would be beneficial for species living in contaminated environments. However, mechanisms for responding adaptively to metal contamination are not fully understood in free-living organisms. The Australian populations of the house sparrow (Passer domesticus) provides an excellent opportunity to study potential adaptation to environmental lead contamination because they have a commensal relationship with humans and are distributed broadly across Australian settlements including many long-term mining and smelting communities. To examine the potential for an evolutionary response to long-term lead exposure, we collected genomic SNP data using the house sparrow 200 K SNP array, from 11 localities across the Australian distribution including two mining sites (Broken Hill and Mount Isa, which are two genetically independent populations) that have well-established elevated levels of lead contamination as well as trace metals and metalloids. We contrast these known contaminated locations to other lesser-contaminated environments. Using an ecological association genome scan method to identify genomic differentiation associated with estimates of lead contamination we identified 60 outlier loci across three tests. A total of 39 genes were found to be physically linked (within 20 kbps) of all outliers in the house sparrow reference genome. The linked candidate genes included 12 genes relevant to lead exposure, such as two metal transporters that can transport metals including lead and zinc across cell membranes. These candidate genes provide targets for follow up experiments comparing resilience to lead exposure between populations exposed to varied levels of lead contamination.

The Contribution of Neutral and Environmentally Dependent Processes in Driving Population and Lineage Divergence in Taiwania (Taiwania cryptomerioides).

The question of what determines divergence both between and within species has been the central topic in evolutionary biology. Neutral drift and environmentally dependent divergence are predicted to play roles in driving population and lineage divergence. However, neutral drift may preclude adaptation if the rate of gene flow between populations is high. Here, we sampled populations of three Taiwania (Taiwania cryptomerioides) lineages occurring in Taiwan, the mainland of China (Yunnan-Myanmar border), and northern Vietnam, and tested the relative strength of neutral drift and divergent selection in shaping divergence of those populations and lineages. We quantified genetic and epigenetic variation, respectively, using amplified fragment length polymorphism (AFLP) and methylation-sensitive amplification polymorphism (MSAP). Analysis of 1413 AFLP and 462 MSAP loci using frequency-based genome scan methods and generalized linear models (GLMs) found no potential selective outliers when only Taiwanese populations were examined, suggesting that neutral drift was the predominant evolutionary process driving differentiation between those populations. However, environmentally associated divergence was found when lineages were compared. Thirty-two potential selective outliers were identified based on genome scans and their associations with environmental variables were tested with GLMs, generalized linear mixed effect models (GLMMs), and model selection with a model averaging approach. Ten loci (six AFLP and four MSAP) were found to be strongly associated with environmental variables, particularly monthly temperature variation and normalized difference vegetation index (NDVI) using model selection and a model averaging approach. Because only a small portion of genetic and epigenetic loci were found to be potential selective outliers, neutral evolutionary process might also have played crucial roles in driving lineage divergence, particularly between geographically and genetically isolated island and mainland Asia lineages. Nevertheless, the vast amount of neutral drift causing genetic and epigenetic variations might have the potential for adaptation to future climate changes. These could be important for the survival of Taiwania in different geographic areas.

Genome Scans Reveal Homogenization and Local Adaptations in Populations of the Soybean Cyst Nematode.

Determining the adaptive potential of alien invasive species in a new environment is a key concern for risk assessment. As climate change is affecting local climatic conditions, widespread modifications in species distribution are expected. Therefore, the genetic mechanisms underlying local adaptations must be understood in order to predict future species distribution. The soybean cyst nematode (SCN), Heterodera glycines Ichinohe, is a major pathogen of soybean that was accidentally introduced in most soybean-producing countries. In this study, we explored patterns of genetic exchange between North American populations of SCN and the effect of isolation by geographical distance. Genotyping-by-sequencing was used to sequence and compare 64 SCN populations from the United States and Canada. At large scale, only a weak correlation was found between genetic distance (Wright's fixation index, FST) and geographic distance, but local effects were strong in recently infested states. Our results also showed a high level of genetic differentiation within some populations, allowing them to adapt to new environments and become established in new soybean-producing areas. Bayesian genome scan methods identified 15 loci under selection for climatic or geographic co-variables. Among these loci, two non-synonymous mutations were detected in SMAD-4 (mothers against decapentaplegic homolog 4) and DOP-3 (dopamine receptor 3). High-impact variants linked to these loci by genetic hitchhiking were also highlighted as putatively involved in local adaptation of SCN populations to new environments. Overall, it appears that strong selective pressure by resistant cultivars is causing a large scale homogenization with virulent populations.

Combining six genome scan methods to detect candidate genes to salinity in the Mediterranean striped red mullet (Mullus surmuletus)

BackgroundAdaptive genomics may help predicting how a species will respond to future environmental changes. Genomic signatures of local adaptation in marine organisms are often driven by environmental selective agents impacting the physiology of organisms. With one of the highest salinity level, the Mediterranean Sea provides an excellent model to investigate adaptive genomic divergence underlying salinity adaptation. In the present study, we combined six genome scan methods to detect potential genomic signal of selection in the striped red mullet (Mullus surmuletus) populations distributed across a wide salinity gradient. We then blasted these outlier sequences on published fish genomic resources in order to identify relevant potential candidate genes for salinity adaptation in this species.ResultsAltogether, the six genome scan methods found 173 outliers out of 1153 SNPs. Using a blast approach, we discovered four candidate SNPs belonging to three genes potentially implicated in adaptation of M. surmuletus to salinity. The allele frequency at one of these SNPs significantly increases with salinity independently from the effect of longitude. The gene associated to this SNP, SOCS2, encodes for an inhibitor of cytokine and has previously been shown to be expressed under osmotic pressure in other marine organisms. Additionally, our results showed that genome scan methods not correcting for spatial structure can still be an efficient strategy to detect potential footprints of selection, when the spatial and environmental variation are confounded, and then, correcting for spatial structure in a second step represents a conservative method.ConclusionThe present outcomes bring evidences of potential genomic footprint of selection, which suggest an adaptive response of M. surmuletus to salinity conditions in the Mediterranean Sea. Additional genomic data such as sequencing of a full-genome and transcriptome analyses of gene expression would provide new insights regarding the possibility that some striped red mullet populations are locally adapted to their saline environment.

Navigating the Interface Between Landscape Genetics and Landscape Genomics.

As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used.

Postglacial range expansion and the role of ecological factors in driving adaptive evolution of Musa basjoo var. formosana

Genetic variation evolves during postglacial range expansion of a species and is important for adapting to varied environmental conditions. It is crucial for the future survival of a species. We investigate the nuclear DNA sequence variation to provide evidence of postglacial range expansion of Musa basjoo var. formosana, a wild banana species, and test for adaptive evolution of amplified fragment length polymorphic (AFLP) loci underlying local adaptation in association with environmental variables. Postglacial range expansion was suggested by phylogeographical analyses based on sequence variation of the second intron of copper zinc superoxide dismutase 2 gene. Two glacial refugia were inferred by the average FST parameter (mean FST of a population against the remaining populations). Using variation partitioning by redundancy analysis, we found a significant amount of explained AFLP variation attributed to environmental and spatially-structured environmental effects. By combining genome scan methods and multiple univariate logistic regression, four AFLP loci were found to be strongly associated with environmental variables, including temperature, precipitation, soil moisture, wet days, and surface coverage activity representing vegetation greenness. These environmental variables may have played various roles as ecological drivers for adaptive evolution of M. basjoo var. formosana during range expansion after the last glacial maximum.