ERA-CAPS: BARley yield associated Network

农业面临着用更少的土地、更少的资源、不断变化的气候和日益增长的社会环境质量要求来养活日益增长的人口的“巨大挑战”。因此，单位面积产量更高、资源更少、具有弹性和适应性的作物将是应对这一重大挑战的关键组成部分。向健全农业系统迈出的重要第一步是深入了解产量的遗传控制。在大麦中，产量由许多因素决定，通过标准育种方法提高产量的能力已经放缓。这个ERA-CAPS项目的主要目标是识别控制小粒温带谷类作物大麦产量相关性状的基因，并开始了解它们是如何对这种复杂的表型做出贡献的。该项目的三个合作伙伴将分别关注种子、穗(花序)和分蘖(结籽茎)的特征。该项目将从汇集三个合作伙伴的遗传资源和专门知识中受益。通过与更广泛的大麦遗传和育种社区共享资源、工具和信息，以及培训下一代分子育种者和科学家，将确保长期的社区整合。在大麦中，产量由许多因素决定，通过标准育种方法提高产量的能力已经放缓。大麦籽粒产量受种子(大小和数量)、穗(花序)和分蘖(营养枝)三个因素的影响。这个由ERA-CAPS资助的项目的总体目标是识别控制大麦产量的形态和发育因素的基因，并开始了解它们如何对这种复杂的表型做出贡献。这项研究利用了之前捕获的外显子序列种质小组，该小组将对与产量相关的性状进行表型鉴定。这些数据将为增加对关键性状的GxE交互作用的了解提供机会。该团队将对每个基因型的六个与特征相关的组织进行转录组测序，并分析基因表达如何与特征发展相关。为了能够准确量化转录阅读深度，将使用来自cv的六个组织的深度配对末端Illumina RNA-seq和PacBio ISO-seq数据开发参考转录数据集。莫雷克斯。这将被用来量化RNA-SEQ数据的转录丰度，这些数据来自于从整个种群中采样的相同的六个组织中收集的RNA-SEQ数据。来自RNA-seq的SNP等位基因将补充外显子组捕获的SNPs，SNP数据集和转录本读取深度变异将用于与产量相关性状的关联分析。基因共表达网络将使用来自MOREX的参考转录本数据集和来自种质小组采样的六个组织的RNA-SEQ数据来构建。这两个数据集将被整合，以确定候选基因或产量相关性状的关键调控因素。候选基因的功能特征将通过从三个合作实验室中的每一个合作实验室提供的耕作群体中识别有害等位基因来启动。该项目将提供具有广泛影响的全球社区资源，包括：参考转录数据集，来自地方品种收集的额外SNPs，以及用于探索关键调控基因及其与产量相关试验关系的基因共表达网络。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Agriculture faces the 'Grand Challenge' of feeding a growing population with less land, fewer resources, a changing climate, and increasing environmental quality demands from society. Thus, crops that produce more per unit area with fewer resources and are both resilient and adaptable will be key components in addressing this Grand Challenge. An important first step towards robust agricultural systems is to develop a deep understanding of the genetic control of yield. In barley, yield is determined by many components and the ability to increase yield through standard breeding approaches has slowed. The primary goal of this ERA-CAPS project is to identify genes that control yield-related traits in the small grain temperate cereal crop barley, and to begin to understand how they contribute to this complex phenotype. The three partners in this project will separately focus on seed, spike (inflorescence) and tiller (seed bearing stem) traits. The project will benefit from bringing together a collection of genetic resources and expertise from the three partners. Long-term community integration will be assured by sharing the resources, tools and information with the broader barley genetics and breeding community and by training the next generation of molecular breeders and scientists.In barley, yield is determined by many components and the ability to increase yield through standard breeding approaches has slowed. Barley grain yield is impacted by three components including: seed (size and number), spike (inflorescence) and tillers (vegetative branches). The overall goal of this ERA-CAPS funded project is to identify genes that control morphological and developmental components of yield in barley, and to begin to understand how they contribute to this complex phenotype. The research leverages a previously exome captured sequenced germplasm panel, which will be phenotyped for yield-related traits. These data will provide the opportunity to gain an increased understanding of GxE interactions for key traits. The team will conduct transcriptome sequencing of six trait-related tissues per genotype and analyze how gene expression relates to trait development. To enable accurate quantification of transcript read depth, a reference transcript dataset will be developed by using deep paired-end Illumina RNA-seq and PacBio ISO-seq data from six tissues from cv. Morex. This will be used to quantify transcript abundance from RNA-seq data collected from the same six tissues sampled across the population. RNA-seq derived SNP alleles will supplement the exome capture SNPs and both SNP datasets and transcript read depth variation will be used for association analysis with yield-related traits. Gene co-expression networks will be constructed using reference transcript dataset from Morex and RNA-seq data from the six tissues sampled from the germplasm panel. Both datasets will be integrated to identify candidate genes or key regulators of yield related traits. Functional characterization of candidate genes will be initiated by identifying deleterious alleles from TILLING populations available in each of the three partner labs. The project will provide global community resources of broad impact including: a reference transcript dataset, additional SNPs derived from the landrace collection, and gene co-expression networks for exploring key regulatory genes and their relationship to yield-related traits.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.