NSF Postdoctoral Fellowship in Biology FY 2015

这一行动为NSF国家植物基因组计划2015财年生物学博士后研究奖学金提供了资金。该奖学金支持在东道主实验室为该研究员制定的研究和培训计划，该研究员还提出了扩大生物学参与度的计划。为Michael S.Campbell设立的这一奖学金的研究和培训计划的标题是“稻米与男人：推进基因组辅助作物改良的基于图表的工具和资源”。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Doreen Ware博士和Paul Kerse博士。自1万多年前农业开始以来，人类就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现在为挖掘作物的新特征和改进育种方法提供了前所未有的资源。这些DNA序列现在可以用来通过一种名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的共识或“参考”DNA序列来代表整个物种的基因组。遗憾的是，这些参考序列并不能捕捉到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，人类基因组学社区已经开始试验一个有希望的解决这个问题的方案，称为变异图，其中图结构被用来表示在参考基因组方法中丢失的序列变异。在这个项目中，将开发水稻作为模式作物的变异图，将有助于识别新的性状变异，并最终适用于任何作物物种。结果将为植物育种者提供基本信息，从而显著影响作物改良工作的速度和绩效，有助于确保安全和持续的粮食供应。该项目将开发方法，并探索变异图方法的用途，以创建水稻泛基因组参考和结构注释资源，从三个不同水稻品系的基因组开始，然后扩展到3,000个。生物信息学和基于统计学的基因组表示和注释方法将提供植物育种者可用变异材料的种群水平视图，并将提供每个个体加入的基因组的清晰图景。研究工作是针对水稻基因组的，但开发的工具和技术与所有农业动植物都相关。将建立将这一资源复制到其他农业植物的基础设施，并通过iPlants Collaborative.org提供。这些稻米资源将通过Gramene网站(gram ene.org)向公众开放。

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).