NSF Postdoctoral Fellowship in Biology FY 2015

该行动资助了2015财年NSF国家植物基因组计划生物学博士后研究奖学金。该研究金支持研究员在东道实验室的研究和培训计划，研究员还提出了扩大生物学参与的计划。该奖学金的研究和培训计划标题为Michael S。坎贝尔是“水稻和人类：基于图形的工具和资源，用于推进基因组辅助作物改良“该奖学金的主办机构是冷泉港实验室和EMBL-EBI，赞助科学家是多琳·韦尔博士和保罗·克西博士。自从1万年前农业开始以来，人类一直在驯化作物以提高产量和生产力。过去十年的基因组测序为挖掘作物新性状和推进育种方法提供了前所未有的资源。这些DNA序列现在可以通过一种称为基因组辅助作物改良的过程来指导未来的植物育种。基因组辅助作物改良的核心是使用单一共有或“参考”DNA序列来代表整个物种的基因组。不幸的是，这些参考序列不能捕获每个群体的序列变异特征。因此，如果不能充分利用基因变异的多样性，育种就会受到阻碍。 最近，人类基因组学界已经开始试验一种有前途的解决方案，称为“变异图”，其中图结构用于表示参考基因组方法丢失的序列变异。在这个项目中，变异图将被开发用于水稻作为模式作物，将有助于识别新的性状变异，并最终适用于任何作物物种。这些结果将为植物育种者提供重要信息，从而对作物改良工作的速度和绩效产生重大影响，有助于确保安全和持续的粮食供应。该项目将开发变体图方法的方法并探索其实用性，以创建水稻的泛基因组参考和结构注释资源，从三种不同水稻品系的基因组开始，然后扩展到3，000个。基于生物信息学和统计学的基因组表示和注释方法将为植物育种者提供变异材料的群体水平视图，并将提供每个个体登录的基因组的清晰图像。研究工作针对水稻基因组，但开发的工具和技术与所有农业植物和动物有关。将通过iPlant Collaborative（iplantcollaborative.org）建立并提供为其他农业植物复制这一资源的基础设施。稻米资源将通过Gramene网站（gramene.org）公开提供。

This action funds an NSF National Plant Genome Initiative Postdoctoral Research Fellowship in Biology for FY 2015. The fellowship supports a research and training plan in a host laboratory for the Fellow who also presents a plan to broaden participation in biology. The title of the research and training plan for this fellowship to Michael S. Campbell is "Of Rice and Men: Graph-Based Tools and Resources for Advancing Genome Assisted Crop Improvement " The host institutions for the fellowship are Cold Spring Harbor Laboratories and EMBL-EBI and the sponsoring scientists are Dr. Doreen Ware and Dr. Paul Kersey.Humans have been domesticating crop plants to increase yield and productivity ever since agriculture began over 10,000 years ago. Genome sequencing in the last decade now provides unprecedented resources for mining crops for new traits and for advancing breeding methods. These DNA sequences can now be used to guide the future of plant breeding through a process called genome assisted crop improvement. Central to genome assisted crop improvement is the use of a single consensus, or 'reference' DNA sequence to represent the genome of an entire species. Unfortunately, these reference sequences do not capture sequence variation characteristic of every population. Breeding is therefore hampered without full access to the diversity of gene variants. Recently, the human genomics community has begun to experiment with a promising solution to this problem called a 'Variant Graph', wherein a graph structure is used to represent sequence variation that is lost with the reference-genome approach. In this project, Variant Graphs will be developed for rice as a model crop plant, will help to identify new trait variants and will ultimately be applicable to any crop species. The outcomes will provide essential information to plant breeders and therefore significantly impact the speed and performance of crop improvement efforts, helping to ensure a secure and constant food supply. This project will develop methods for, and explore the utility of, a Variant Graph approach to create a pan-genome reference and structural annotation resource for rice, starting with the genomes of three diverse rice strains and then expanding to 3,000. The bioinformatics and statistically based approach to genome representation and annotation will give a population level view of the variant material available to plant breeders and will provide a clear picture of the genome of each individual accession. The research efforts are directed towards rice genomes, but the tools and techniques developed are relevant to all agricultural plants and animals. The infrastructure to replicate this resource for other agricultural plants will be established and made available through the iPlant Collaborative (iplantcollaborative.org). The rice resources will be publicly available through the Gramene website (gramene.org).