Evolution in a changing environment: the genetic architecture of adaptation outside centers of domestication of Phaseolus vulgaris and P. coccineus

该项目旨在了解普通豆（Phaseolus vulgaris; Pv）及其杂交亲缘姊妹种菜豆（Phaseolus coccineus; Pc）在美洲起源中心和向欧洲扩散后的适应遗传结构，作为未来主要环境和社会经济变化的模型，如温度升高、降雨量变化和新的消费者偏好。我们将通过研究它们在欧洲的引进和扩张来确定适应新环境的遗传基础和表型后果，这是一个历史上明确定义的近期和快速适应事件。我们将使用多学科方法（基因组学，群体/数量遗传学，生物化学，植物生理学）对一组嵌套的样本。来自三个主要基因库的大量收集（21,500份，Pv_ALL和Pc_ALL）将通过基因分型测序（GBS）进行表征，以确定种群结构并获得基因型亚群，用于表型（场和生长室）和更深层次的基因组，转录组学，代谢组学特征。在500个Pv地理参考系（Pv_core1）的子集中，我们将获得~ 4x全基因组测序（WGS），该测序将通过比较来自两个大陆的亚群（地理和遗传定义）用于群体基因组学。这将确定选择对适应欧洲环境和全基因组关联研究（GWAS）的影响，后者将基于在四种不同环境中的田间试验，以关注物候适应。这两个物种（Pv_core2, Pc_core1）也将在受控条件下研究植物对光周期和温度的响应（生长，物候，转录组学，代谢组学）。差异表达分析、共表达模式分析和GWAS将用于鉴定与适应性相关的基因和代谢物，而从RNAseq数据获得的基因型信息将与GBS和WGS数据一起用于测试选择的特征。我们将比较异体Pc和自交配Pv的两个基因库之间的结果，其中物种和基因库之间的共享特征（中性测试，表达分析）将提供一个强大的交叉验证工具。整合的数据集将用于提供候选基因，以使用散装分离分析（BSA）进行验证。BEAN_ADAPT的主要成果之一是所有20,000份材料（HapBean）的单倍型Pv的发展，以及相关信息和种子库存，这将为植物科学家提供一个独特的工具。对于Pc，我们也将拥有一套定义良好的信息，这将构成其基因组资源开发和应用的基础。

This project seeks to understand the genetic architecture of adaptation of the common bean (Phaseolus vulgaris; Pv) and its cross compatible sister species, the runner bean (Phaseolus coccineus; Pc), in their centers of origin in the Americas and following their dispersal to Europe, as a model for future major environmental and socio economic changes, such as increases in temperature, variability in rainfall, and new consumer preferences. We will identify the genetic basis and phenotypic consequences of adaptation to new environments through the study of their introduction and expansion in Europe, as a historically well defined event of recent and rapid adaptation. We will use a multidisciplinary approach (genomics, population/ quantitative genetics, biochemistry, plant physiology) on a nested set of samples. A large collection (21,500 accessions, Pv_ALL and Pc_ALL) from three major genebanks, will be characterised by genotyping-by-sequencing (GBS), to define the population structure and to obtain subsets of genotypes for phenotyping (field and growth chamber) and deeper genomic, transcriptomic, metabolomic characterisation. In a subset of 500 geo-referenced lines of Pv (Pv_core1), we will obtain ~4× whole genome sequencing (WGS), which will be used for population genomics by comparing subpopulations from the two continents (defined geographically and genetically). This will identify the effect of selection for adaptation to European environments and for genome-wide association studies (GWAS), which will be based on field trials in four contrasting environments, to focus on phenological adaptation. Both species (Pv_core2, Pc_core1) will also be studied under controlled conditions for plant responses (growth, phenology, transcriptomics, metabolomics) to contrasting conditions of photoperiod and temperature. Differential expression analysis, analysis of the coexpression patterns, and GWAS will be used to identify genes and metabolites putatively associated with adaptation, while genotypic information obtained from RNAseq data will be used, with GBS and WGS data, to test for signatures of selection. We will compare the results between the allogamous Pc and the two gene pools of autogamous Pv, where shared signatures between species and gene pools (neutrality tests, expression analysis) will provide a powerful cross validation tool. The integrated datasets will be used to provide candidate genes to be validated using bulk segregant analysis (BSA). Among the main outcomes of BEAN_ADAPT are the development in Pv of haplotypes of all 20,000 accessions (HapBean), along with associated information and seed stocks, which will represent a unique tool for plant scientists. For Pc, we will also have a well-defined set of information that will constitute the foundation for the development and application of its genomic resources.