Future-proofing our food: exploiting landrace diversity for more efficient and resilient wheat

为了确保全球粮食安全，作物育种者必须开发出更高产、更能抵御气候变化潜在影响的品种。面包小麦（Triticum aestivum）是人类最重要的谷物来源，但绿色革命的集约化育种在拯救数十亿人生命的同时，也导致了遗传多样性的巨大瓶颈。这意味着耐热性和耐旱性等性状可能在未来几十年内成为重要的育种目标，可能需要从其他来源重新引入育种池。由传统的、适应当地的品种组成的全球地方品种库可能是寻找能够耐受高温和干旱胁迫的小麦品系的好地方，如果这些性状背后的遗传变异也可以被分离出来，那么基因渗入到优良品种中将更有效。哈珀/班克罗夫特实验室最近开发的基于地方品种小麦种质的关联转录组学平台为将性状变异与基因序列（SNP）和表达（GEM）标记相关联提供了极好的资源。在这个项目中，学生将表型的地方品种对热和干旱的反应，然后使用关联转录组学来确定与它们相关的遗传标记。这些标记将被验证用于标记辅助选择，并将用于提出候选基因，揭示这些性状的机制。该项目提供了一个机会，首次将一种新的统计遗传学方法应用于面包小麦的重要育种目标，并适合有兴趣从事结合温室，实验室和生物信息学活动的项目的学生。

To ensure global food security, crop breeders must develop varieties which are more productive as well as more resilient to the potential impacts of climate change. Bread wheat (Triticum aestivum) is the most important grain source for humans, but the intensive breeding of the green revolution, whilst saving billions of lives, led to a huge bottleneck in genetic diversity. This means that traits such as heat and drought tolerance, which could become vital breeding targets in the next few decades, may need to be introduced back into the breeding pool from additional sources. Global landrace collections, made up of traditional, locally-adapted varieties, may be a good place to look for wheat lines that can tolerate heat and drought stress, and if the genetic variants underlying these traits can also be isolated, then introgression back into elite cultivars will be more efficient. The recent development of an Associative Transcriptomics platform based on landrace wheat accessions by the Harper/Bancroft labs, provides an excellent resource for associating trait variation with gene sequence (SNP) and expression (GEM) markers. During this project, the student will phenotype the landraces for their response to heat and drought, before using Associative Transcriptomics to identify genetic markers associated with them. These markers will be validated for use in marker-assisted selection, and will be used to propose candidate genes and reveal the mechanisms underlying these traits. This project offers the opportunity to apply a new statistical genetics approach to important breeding targets in bread wheat for the first time, and would suit a student who is interested in pursuing a project which combines glasshouse, laboratory and bioinformatics activities.