Genomic signatures of climate adaptation in bank voles

Evidence for divergent selection and adaptive variation across the landscape can provide insight into a species’ ability to adapt to different environments. However, despite recent advances in genomics, it remains difficult to detect footprints of climate mediated selection in natural populations. Here we analysed ddRAD sequencing data (21,892 SNPs) in conjunction with geographic climate variation to search for signatures of adaptive differentiation in twelve populations of the bank vole (Clethrionomys glareolus) distributed across Europe. To identify the loci subject to selection associated with climate variation, we applied multiple genotype-environment association (GEA) methods, two univariate and one multivariate, and controlled for the effect of population structure. In total, we identified 213 candidate loci for adaptation, 74 of which were located within genes. In particular, we identified signatures of selection in candidate genes with functions related to lipid metabolism ..., We investigate genomic adaptations in a small mammal distributed throughout Europe (3,200 km) using a multivariate and multimethod approach. We sampled 12 populations and 276 individuals using a ddRAD sequencing approach. We found strong spatial structuring of populations, and identified candidate genes for climate adaptation using genotype-environmental association methods., , This README file was generated on 2024-02-18 by Remco Folkertsma. # Data from: Genomic signatures of climate adaptation in bank voles [https://doi.org/10.5061/dryad.1c59zw42p](https://doi.org/10.5061/dryad.1c59zw42p) We utilized a ddRAD sequencing approach to sequence the genome of 276 bank voles (*Clethrionomys glareolus*) from 12 populations from across Europe. This dataset includes the input files containing genomic data and environmental data, as well as R-scripts and sample meta-data. Genomic and environmental data was used to perform genotype-environmental analysis using LFMM, Bayenv2 and redundancy analysis in R (RDA-script included). ## GENERAL INFORMATION 1\. Title of Dataset: Genomic signatures of climate adaptation in bank voles 2\. Author Information ``` A. Principal Investigator Contact Information Name: Remco Folkertsma Institution: Potsdam University Email: [e-mail] ``` 3\. Date of data collection (single date, range, approximate date): 201...,全景观范围内的歧化选择与适应性变异证据，可揭示物种适应不同环境的能力。然而，尽管基因组学领域近年来取得诸多进展，在自然种群中检测气候介导选择的印迹仍颇具挑战。本研究结合地理气候变异数据，对双酶切限制性位点相关DNA测序（double-digest restriction site-associated DNA sequencing, ddRAD）获得的21892个单核苷酸多态性（Single Nucleotide Polymorphism, SNP）位点数据进行分析，以探究分布于欧洲的12个棕背䶄（bank vole, *Clethrionomys glareolus*）种群的适应性分化信号。为筛选与气候变异相关的受选择位点，本研究采用多种基因型-环境关联分析（Genotype-Environment Association, GEA）方法（2种单变量方法与1种多变量方法），并对种群结构的影响进行控制。本研究共筛选得到213个适应性候选位点，其中74个位于基因区域内。特别地，我们在与脂质代谢功能相关的候选基因中检测到选择信号……本研究采用多变量、多方法策略，对分布于欧洲全域（跨度3200公里）的小型哺乳动物的基因组适应性展开研究。我们通过ddRAD测序技术，对12个种群的276只个体进行测序。研究发现种群存在显著的空间遗传结构，并通过基因型-环境关联分析方法筛选得到气候适应性候选基因。 本说明文件由Remco Folkertsma于2024年2月18日生成。 # 数据集来源：棕背䶄的气候适应性基因组信号 https://doi.org/10.5061/dryad.1c59zw42p 本研究采用ddRAD测序技术，对来自欧洲12个种群的276只棕背䶄（*Clethrionomys glareolus*）的基因组进行测序。本数据集包含基因组数据与环境数据的输入文件、R语言脚本以及样本元数据。研究人员利用基因组与环境数据，通过LFMM、Bayenv2以及R语言中的冗余分析（Redundancy Analysis, RDA，配套RDA脚本已提供）开展基因型-环境关联分析。 ## 基本信息 1. 数据集标题：棕背䶄的气候适应性基因组信号 2. 作者信息 A. 项目负责人联系方式 姓名：Remco Folkertsma 所属机构：波茨坦大学 邮箱：[e-mail] 3. 数据收集日期（单一日期、日期范围或近似日期）：201……