Understanding the genetic basis of local adaption is crucial in the context of global climate change. Mangroves, as salt-tolerant trees and shrubs in the intertidal zone of tropical and subtropical coastlines, are particularly vulnerable to climate change. Kandelia obovata, the most cold-tolerant mangrove species, has undergone ecological speciation from its cold-intolerant counterpart, Kandelia candel, with geographic separation by the South China Sea. In this study, we conducted whole-genome re-sequencing of K. obovata populations along China\'s southeast coast, to elucidate the genetic basis responsible for mangrove local adaptation to climate. Our analysis revealed a strong population structure among the three K. obovata populations, with complex demographic histories involving population expansion, bottleneck, and gene flow. Genome-wide scans unveiled pronounced patterns of selective sweeps in highly differentiated regions among pairwise populations, with stronger signatures observed in the northern populations compared to the southern population. Additionally, significant genotype-environment associations for temperature-related variables were identified, while no associations were detected for precipitation. A set of 39 high-confidence candidate genes underlying local adaptation of K. obovata were identified, which are distinct from genes under selection detected by comparison between K. obovata and its cold-intolerant relative K. candel. These results significantly contribute to our understanding of the genetic underpinnings of local adaptation in K. obovata and provide valuable insights into the evolutionary processes shaping the genetic diversity of mangrove populations in response to climate change.

Sheep are important livestock animals that have evolved under various ecological pressures. Xinjiang is a region with diverse and harsh environments that have shaped many local sheep breeds with unique characteristics and environmental adaptability. However, these breeds are losing ecological flexibility due to the promotion of intensive farming practices. Here we sequenced 14 local sheep breeds from Xinjiang and analyzed their genetic structure and gene flow with other sheep breeds from neighboring regions. The Tibetan Plateau was the geographic origin of Xinjiang native sheep evolution. We performed genome-environment association analysis and identified Bio9: Mean Temperature of Driest Quarter and Bio15: Precipitation Seasonality as the key environmental factors affecting Xinjiang local sheep and the key genes involved in their survival and adaptation. We classified Xinjiang native sheep breeds into six groups based on their differential genes by pairwise selective sweep analysis and Community Network Analysis. We analyzed transcriptome expression data of 832 sheep tissues and detected tissue-specific enrichment of six group-specific genes in different biological systems. Our results revealed the genetic basis of year-round estrus, drought tolerance, hypoxia resistance, and cold tolerance traits of Xinjiang sheep breeds. Moreover, we proposed conservation strategies for Xinjiang local sheep breeds and provided theoretical guidance for breeding new sheep breeds under global extreme environments.

According to models of ecological speciation, adaptation to adjacent, contrasting habitat types can lead to population divergence given strong enough environment-driven selection to counteract the homogenizing effect of gene flow. We tested this hypothesis in the common chaffinch (Fringilla coelebs) on the small island of La Palma, Canary Islands, where it occupies two markedly different habitats. Isotopic (δ13 C, δ15 N) analysis of feathers indicated that birds in the two habitats differed in ecosystem and/or diet, and analysis of phenotypic traits revealed significant differences in morphology and plumage colouration that are consistent with ecomorphological and ecogeographical predictions respectively. A genome-wide survey of single-nucleotide polymorphism revealed marked neutral structure that was consistent with geography and isolation by distance, suggesting low dispersal. In contrast, loci putatively under selection identified through genome-wide association and genotype-environment association analyses, revealed amarked adaptive divergence between birds in both habitats. Loci associated with phenotypic and environmental differences among habitats were distributed across the genome, as expected for polygenic traits involved in local adaptation. Our results suggest a strong role for habitat-driven local adaptation in population divergence in the chaffinches of La Palma, a process that appears to be facilitated by a strong reduction in effective dispersal distances despite the birds\' high dispersal capacity.

Understanding the role of the host genome in modulating microbiota variation is a need to shed light on the holobiont theory and overcome the current limits on the description of host-microbiota interactions at the genomic and molecular levels. However, the host genetic architecture structuring microbiota is only partly described in plants. In addition, most association genetic studies on microbiota are often carried out outside the native habitats where the host evolves and the identification of signatures of local adaptation on the candidate genes has been overlooked. To fill these gaps and dissect the genetic architecture driving adaptive plant-microbiota interactions, we adopted a genome-environment association (GEA) analysis on 141 whole-genome sequenced natural populations of Arabidopsis thaliana characterized in situ for their leaf and root bacterial communities in fall and spring, and a large range of nonmicrobial ecological factors (i.e., climate, soil, and plant communities). A much higher fraction of among-population microbiota variance was explained by the host genetics than by nonmicrobial ecological factors. Importantly, the relative importance of host genetics and nonmicrobial ecological factors in explaining the presence of particular operational taxonomic units (OTUs) differs between bacterial families and genera. In addition, the polygenic architecture of adaptation to bacterial communities was highly flexible between plant compartments and seasons. Relatedly, signatures of local adaptation were stronger on quantitative trait loci (QTLs) of the root microbiota in spring. Finally, plant immunity appears as a major source of adaptive genetic variation structuring bacterial assemblages in A. thaliana.

BACKGROUND: Taro has a long history of being consumed and remains orphan and on the hand Nigeria farmers. The role of farmer-driven artificial selection is not negligible to fit landraces to a particular ecological condition. Limited study has been conducted on genome-wide association and no study has been conducted on genome-environment association for clinal adaptation for taro. Therefore, the objective of this study was to detect loci that are associated with environmental variables and phenotype traits and forward input to breeders. The study used 92 geographical referred taro landraces collected from Southeast (SE) Nigeria.
RESULTS: The result indicates that SE Nigerian taro has untapped phenotype and genetic variability with low admixture. Redundancy analysis indicated that collinear explained SNP variation more than single climatic variable. Overall, the results indicated that no single method exclusively was able to capture population confounding effects better than the others for all six traits. Nevertheless, based on overall model performance, Blink seemed to provide slight advantage over other models and was selected for all subsequent assessment of genome-environment association (GEA) and genome-wide association study (GWAS) models. Genome scan and GEA identified local adapted loci and co-located genes. A total of nine SNP markers associated with environmental variables. Some of the SNP markers (such as S_101024366) co-located with genes which previously reported for climatic adaptation such as astringency, diaminopimelate decarboxylase and MYB transcription factor. Genome-wide association also identified 45, 40 and 34 significant SNP markers associated with studied traits in combined, year 1 and year 2 data sets, respectively. Out of these, five SNP markers (S1_18891752 S3_100795476, S1_100584471 S1_100896936 and S2_10058799) were consistent in two different data sets.
CONCLUSIONS: The findings from this study improve our understanding of the genetic control of adaptive and phenotypic traits in Nigerian taro. However, the study suggests further study on identification of local adaptive loci and GWAS through collection of more landraces throughout the country, and across different agro-ecologies.

Range expansion requires peripheral populations to shift adaptive optima to breach range boundaries. Opportunities for range expansion can be assessed by investigating the associations of core-periphery environmental and genetic differences. This study investigates differences in the core-periphery adaptation of Ammopiptanthus mongolicus, a broad-leaved evergreen shrub species in a relatively homogeneous temperate Asian desert environment, to explore the environmental factors that limit the expansion of desert plants. Temperate deserts are characterized by severe drought, a large diurnal temperature range, and seasonality. Long-standing adaptation to the harsh desert environment may confine the genetic diversity of A. mongolicus, despite its distribution over a wide range of longitude, latitude, and altitude. Since range edges defined by climate niches may have different genetic responses to environmental extremes, we compared genome-wide polymorphisms between nine environmental core populations and ten fragmented peripheral populations to determine the \"adaptive peripheral\" populations. At least four adaptive peripheral populations had similar genetic-environmental association patterns. High elevations, summer drought, and winter cold were the three main determinants of converging these four adaptive peripheral populations. Elevation mainly caused similar local climates among different geographic regions. Altitudinal adaptation resulting from integrated environmental-genetic responses was a breakthrough in breaching niche boundaries. These peripheral populations are also located in relatively humid and warmer environments. Relaxation of the drought and cold constraints facilitated the genetic divergence of these peripheral populations from the core population\'s adaptive legacy. We conclude that pleiotropic selection synchronized adaptative divergence to cold and drought vs. warm and humid environments between the core and peripheral populations. Such parallel adaptation of peripheral populations relies on selection under a background of abundant new variants derived from the core population\'s standing genetic variation, i.e., integration of genetic surfing and local adaptation.

Both models and case studies suggest that chromosomal inversions can facilitate adaptation and speciation in the presence of gene flow by suppressing recombination between locally adapted alleles. Until recently, however, it has been laborious and time-consuming to identify and genotype inversions in natural populations. Here we apply RAD sequencing data and newly developed population genomic approaches to identify putative inversions that differentiate a sand dune ecotype of the prairie sunflower (Helianthus petiolaris) from populations found on the adjacent sand sheet. We detected seven large genomic regions that exhibit a different population structure than the rest of the genome and that vary in frequency between dune and nondune populations. These regions also show high linkage disequilibrium and high heterozygosity between, but not within, arrangements, consistent with the behaviour of large inversions, an inference subsequently validated in part by comparative genetic mapping. Genome-environment association analyses show that key environmental variables, including vegetation cover and soil nitrogen, are significantly associated with inversions. The inversions colocate with previously described \"islands of differentiation,\" and appear to play an important role in adaptive divergence and incipient speciation within H. petiolaris.

Genetic time-series data from historical samples greatly facilitate inference of past population dynamics and species evolution. Yet, although climate and landscape change are often touted as post-hoc explanations of biological change, our understanding of past climate and landscape change influences on evolutionary processes is severely hindered by the limited application of methods that directly relate environmental change to species dynamics through time. Increased integration of spatiotemporal environmental and genetic data will revolutionize the interpretation of environmental influences on past population processes and the quantification of recent anthropogenic impacts on species, and vastly improve prediction of species responses under future climate change scenarios, yielding widespread revelations across evolutionary biology, landscape ecology and conservation genetics. This review encourages greater use of spatiotemporal landscape genetic analyses that explicitly link landscape, climate and genetic data through time by providing an overview of analytical approaches for integrating historical genetic and environmental data in five key research areas: population genetic structure, demography, phylogeography, metapopulation connectivity and adaptation. We also include a tabular summary of key methodological information, suggest approaches for mitigating the particular difficulties in applying these techniques to ancient DNA and palaeoclimate data, and highlight areas for future methodological development.

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity.

Two recent articles were written in response to our paper \"Breaking RAD: An evaluation of the utility of restriction site associated DNA sequencing scans of adaptation.\" While we agree with some of the comments made by the authors of these two response papers, we still believe caution should be employed in RADseq studies that aim to detect loci that contribute to adaptation. In this rebuttal, we evaluate the key points made in these papers, attempt to identify a middle ground and make suggestions for responsibly conducting future studies to understand the genomewide mechanisms of adaptation.