Dataset Information

Genomic Signature of Shifts in Selection in a Subalpine Ant and Its Physiological Adaptations.

ABSTRACT: Understanding how organisms adapt to extreme environments is fundamental and can provide insightful case studies for both evolutionary biology and climate-change biology. Here, we take advantage of the vast diversity of lifestyles in ants to identify genomic signatures of adaptation to extreme habitats such as high altitude. We hypothesized two parallel patterns would occur in a genome adapting to an extreme habitat: 1) strong positive selection on genes related to adaptation and 2) a relaxation of previous purifying selection. We tested this hypothesis by sequencing the high-elevation specialist Tetramorium alpestre and four other phylogenetically related species. In support of our hypothesis, we recorded a strong shift of selective forces in T. alpestre, in particular a stronger magnitude of diversifying and relaxed selection when compared with all other ants. We further disentangled candidate molecular adaptations in both gene expression and protein-coding sequence that were identified by our genome-wide analyses. In particular, we demonstrate that T. alpestre has 1) a higher level of expression for stv and other heat-shock proteins in chill-shock tests and 2) enzymatic enhancement of Hex-T1, a rate-limiting regulatory enzyme that controls the entry of glucose into the glycolytic pathway. Together, our analyses highlight the adaptive molecular changes that support colonization of high-altitude environments.

SUBMITTER: Cicconardi F

PROVIDER: S-EPMC7403626 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Genomic Signature of Shifts in Selection in a Subalpine Ant and Its Physiological Adaptations.

Cicconardi Francesco F Krapf Patrick P D'Annessa Ilda I Gamisch Alexander A Wagner Herbert C HC Nguyen Andrew D AD Economo Evan P EP Mikheyev Alexander S AS Guénard Benoit B Grabherr Reingard R Andesner Philipp P Wolfgang Arthofer A Di Marino Daniele D Steiner Florian M FM Schlick-Steiner Birgit C BC

Molecular biology and evolution 20200801 8

Understanding how organisms adapt to extreme environments is fundamental and can provide insightful case studies for both evolutionary biology and climate-change biology. Here, we take advantage of the vast diversity of lifestyles in ants to identify genomic signatures of adaptation to extreme habitats such as high altitude. We hypothesized two parallel patterns would occur in a genome adapting to an extreme habitat: 1) strong positive selection on genes related to adaptation and 2) a relaxation ...[more]

PMID: 32181804

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Project description:The majority of empirical population genetic studies have tried to understand the evolutionary processes that have shaped genetic variation in a single sample taken from a present-day population. However, genomic data collected over tens of generations in both natural and laboratory populations are increasingly used to find selected loci underpinning adaptation over these short timescales. Although these studies have been quite successful in detecting selection on large-effect loci, the fitness differences between individuals are often polygenic, such that selection leads to allele frequency changes that are difficult to distinguish from genetic drift. However, one promising signal comes from polygenic selection's effect on neutral sites that become stochastically associated with the genetic backgrounds that lead to fitness differences between individuals. Previous theoretical work has established that the random associations between a neutral allele and heritable fitness backgrounds act to reduce the effective population size experienced by this neutral allele. These associations perturb neutral allele frequency trajectories, creating autocovariance in the allele frequency changes across generations. Here, we show how temporal genomic data allow us to measure the temporal autocovariance in allele frequency changes and characterize the genome-wide impact of polygenic selection. We develop expressions for these temporal autocovariances, showing that their magnitude is determined by the level of additive genetic variation, recombination, and linkage disequilibria in a region. Furthermore, by using analytic expressions for the temporal variances and autocovariances in allele frequency, we demonstrate that one can estimate the additive genetic variation for fitness and the drift-effective population size from temporal genomic data. We also show how the proportion of total variation in allele frequency change due to linked selection can be estimated from temporal data. Overall, we demonstrate that temporal genomic data offer opportunities to identify the role of linked selection on genome-wide diversity over short timescales, and can help bridge population genetic and quantitative genetic studies of adaptation.

Project description:BackgroundThe breeding of layers emphasizes the continual selection of egg-related traits, such as egg production, egg quality and eggshell, which enhance their productivity and meet the demand of market. As the breeding process continued, the genomic homozygosity of layers gradually increased, resulting in the emergence of runs of homozygosity (ROH). Therefore, ROH analysis can be used in conjunction with other methods to detect selection signatures and identify candidate genes associated with various important traits in layer breeding.ResultsIn this study, we generated whole-genome sequencing data from 686 hens in a Rhode Island Red population that had undergone fifteen consecutive generations of intensive artificial selection. We performed a genome-wide ROH analysis and utilized multiple methods to detect signatures of selection. A total of 141,720 ROH segments were discovered in whole population, and most of them (97.35%) were less than 3 Mb in length. Twenty-three ROH islands were identified, and they overlapped with some regions bearing selection signatures, which were detected by the De-correlated composite of multiple signals methods (DCMS). Sixty genes were discovered and functional annotation analysis revealed the possible roles of them in growth, development, immunity and signaling in layers. Additionally, two-tailed analyses including DCMS and ROH for 44 phenotypes of layers were conducted to find out the genomic differences between subgroups of top and bottom 10% phenotype of individuals. Combining the results of GWAS, we observed that regions significantly associated with traits also exhibited selection signatures between the high and low subgroups. We identified a region significantly associated with egg weight near the 25 Mb region of GGA 1, which exhibited selection signatures and has higher genomic homozygosity in the low egg weight subpopulation. This suggests that the region may be play a role in the decline in egg weight.ConclusionsIn summary, through the combined analysis of ROH, selection signatures, and GWAS, we identified several genomic regions that associated with the production traits of layers, providing reference for the study of layer genome.

Dataset Information

Genomic Signature of Shifts in Selection in a Subalpine Ant and Its Physiological Adaptations.

Publications

Genomic Signature of Shifts in Selection in a Subalpine Ant and Its Physiological Adaptations.

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