CAREER: Integrating Whole-Genome Association Mapping and Landscape Genomics to Understand Climatic Adaptation in Populus

内休眠是温带和北方地区多年生木本植物的一个标志，它使地上的分生组织能够在冬季的冰冻和脱水压力下存活下来。本项目采用种群基因组学方法，剖析杨树内生休眠转变和抗寒性的基因组基础。最近开发的一项降低基因组复杂性的技术将用于在全基因组范围内实现这一目标，与相关杨树物种研究小组的合作将促进适应的比较分析。序列捕获技术将用于检索黑棉杨（Populus trichocarpa）中所有表达基因的外显子和上游调控序列，并将捕获的靶点在跨越大部分物种范围的大型黑棉种群中进行测序。基因型-表型关联将寻求与三个表型性状，即初芽时间，出芽时间和抗寒性。还将寻求与代表与这些特征有关的主要选择约束的气候变量之间的联系。将在一个单独的杨树无性系队列中验证正相关性，并利用合作者提供的数据，确定tremuloides（颤杨）和deltoides（东部棉杨）的适应性位点重叠程度。将开发一个基于网络的生物信息学资源来传播序列数据、SNP数据和SNP关联。这项工作将提供迄今为止最全面的基因组基础，以适应当地的气候在一个树种。除了回答进化生态学中关于适应基因组结构的长期存在的问题外，这项工作还将为实际育种应用提供一个链接，可以利用自然发生的生态相关遗传变异来改善气候变化中的树木。目前，森林树木种群对当地环境适应良好，但气候变化正在极大地改变适应性景观，预计将导致树木种群对其季节性温度制度的广泛不适应。调整管理策略以适应这些变化，关键取决于对适应性性状的基因组结构的理解。通过整合分子生物学、生物信息学和群体基因组学，该项目将大大推进这一目标，同时提供不同层次（本科生、研究生和博士后）的跨学科教育和培训。与该项目有关的研究人员将与弗吉尼亚林业教育项目（LEAF）合作，为学生和土地所有者开展实地调查讲习班。田间试验将用于举办这些户外LEAF学习讲习班，通过这些讲习班，土地所有者、从业者和当地学生将探索气候适应与种子来源之间的关系，以及气候变化对森林生产力的潜在影响。此外，将开发与实地经验讲习班互补的公开的网络模块。序列数据将存储在GenBank， dbSNP存储在NCBI，基因型-表型数据存储在data Dryad （www.datadryad.org）。

Endodormancy is a hallmark of woody perennial plants of the temperate and boreal regions that enables above ground meristems to survive the freezing and dehydration stresses of winter. This project takes a population genomics approach to dissect the genomic basis for endodormancy transitions and cold hardiness in Populus. A recently developed technology for genome complexity reduction will be used to pursue this goal on a genome-wide scale, and collaboration with groups working in related poplar species will facilitate comparative analysis of adaptation. Sequence capture technology will be employed to retrieve exons and upstream regulatory sequences for all expressed genes in Populus trichocarpa (black cottonwood), and captured targets will be sequenced in a large black cottonwood mapping population that spans most of the species range. Genotype-phenotype associations will be sought with three phenotypic traits, namely, timing of budset, timing of budflush, and cold hardiness. Associations will also be sought with climate variables that represent the principle selective constraint related to these traits. Positive associations will be validated in a separate cohort of poplar clones, and using data provided by collaborators, the extent of overlap in adaptive loci in both Populus tremuloides (trembling aspen) and Populus deltoides (eastern cottonwood) will be determined. A web-based bioinformatic resource will be developed to disseminate sequence data, SNP data, and SNP associations. This work will provide by far the most comprehensive picture to date of the genomic basis for local adaptation to climate in a tree species. In addition to answering long standing questions in evolutionary ecology about the genomic architecture of adaptation, this work will provide a link to practical breeding applications that can exploit naturally occurring ecologically-relevant genetic variation for tree improvement in a changing climate. Forest tree populations are well adapted to their local environments at present, but climate change is substantially altering adaptive landscapes, and is expected to lead to widespread maladaptation of tree populations to their seasonal temperature regimes. Adapting management strategies to account for these changes depends crucially on an understanding of the genomic architecture of adaptive traits. By integrating molecular biology, bioinformatics, and population genomics, this project will substantially advance this goal, while providing interdisciplinary education and training at various levels (undergraduate, graduate and postdoctoral). Research personnel associated with this project will develop investigative field workshops for students and landowners in collaboration with Virginia's Link to Education about Forestry (LEAF) program. Field trials will be used to host these outdoor LEAF learning workshops, through which landowners, practitioners, and local students will explore the relationship between climatic adaptation and seed sources, as well as the potential impacts of climate change on forest productivity. In addition, publicaly available web-based modules complimentary to the field experiences workshop will be developed. Sequence data will be deposited at GenBank, dbSNP at NCBI, and genotype-phenotype data at Data Dryad (www.datadryad.org).