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菜豆（Phaseolus vulgaris; Pv）及其交叉兼容的姊妹种菜豆（Phaseolus coccineus; Pc）在美洲的起源中心以及在其传播到欧洲之后的适应性遗传结构，作为未来主要环境和社会经济变化的模型，例如温度升高，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，确定适应新环境的遗传基础和表型后果，作为最近和快速适应的历史上明确定义的事件。我们将使用多学科的方法（基因组学，人口/数量遗传学，生物化学，植物生理学）对一套嵌套的样品。将通过测序基因分型（GBS）对来自三个主要基因库的大量样本（21，500份登记资料，Pv_ALL和Pc_ALL）进行表征，以确定群体结构并获得用于表型分析（田间和生长室）的基因型子集以及更深入的基因组学、转录组学和代谢组学表征。在500个Pv地理参考系的子集（Pv_core1）中，我们将获得约4×全基因组测序（WGS），通过比较来自两大洲的亚群（地理和遗传定义），将其用于群体基因组学。这将确定选择适应欧洲环境和全基因组关联研究（GWAS）的影响，GWAS将基于四个对比环境中的田间试验，重点是物候适应。这两个物种（Pv_core2，Pc_core1）也将在受控条件下研究植物响应（生长，物候，转录组学，代谢组学）的光周期和温度的对比条件。差异表达分析、共表达模式分析和GWAS将用于鉴定与适应相关的基因和代谢产物，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。我们将比较异花受精的Pc和两个基因池的自花受精的Pv，物种和基因池之间的共享签名（中性测试，表达分析）将提供一个强大的交叉验证工具之间的结果。整合的数据集将用于提供候选基因，以使用批量分离分析（BSA）进行验证。BEAN_ADAPT的主要成果之一是在Pv中开发了所有20，000个种质（HapBean）的单倍型，沿着相关信息和种子库，这将代表植物科学家的独特工具。对于Pc，我们还将拥有一组定义明确的信息，这些信息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.