谷子磷效率相关性状的全基因组关联分析和基因组预测

The deficiency of available phosphorus (P) in soil is one of the major factors limiting the improvement of crop yield and quality in China. The characteristic of leanness-resistant in foxtail millet means that foxtail millet contains valuable genetic resources of P-efficiency. Nowadays, the exploitation of excellent genes has already studied in foreign countries, but in our country, we have not identified the phosphorus efficiency characteristics in 916 core accessions of foxtail millet. In order to fully protect and exploit the abundant germplasm resources and gene resources of foxtail millet in China, this project will prepare to identify the phenotype of 405 accessions of foxtail millet, including phosphorus content and acid phosphatase activity of fully expanded fifth leaf, phosphorus content and dry weight of root and above-ground part, plant height under low phosphorus and normal phosphorus conditions. Combined genome-wide association analysis and QTL-seq analysis, excellent haplotypes and candidate genes will be explored to study the genetic basis of P efficient, which would lay a foundation for revealing the molecular mechanism of high phosphorus efficiency in foxtail millet. Selective breeding is an important method to breed new varieties. At present, relatively few works of genomic prediction are done on mineral elements in crops. In this project, Bayes and rrBLUP models will be used to estimate genome-wide SNP effects. Meanwhile, the potential application in P-efficiency individual selection of foxtail millet will be discussed using the cross-validation and independent population without trait values of P-efficiency. This will lay a theoretical foundation for the rapid selection of P-efficiency varieties in the future.

土壤中有效磷缺乏是限制我国作物产量和品质提高的重要因素之一，而谷子耐贫瘠特性意味着其蕴藏了重要的磷高效基因资源。国外已开展谷子控制磷高效的基因挖掘研究，而我国还未对916份谷子核心种质的磷效率特性进行鉴定。为了充分保护和发掘我国丰富的谷子种质资源和重要基因资源，本项目拟以405份谷子为材料，以低磷和正常磷条件下第五完全展开叶的磷含量和酸性磷酸酶活性、根系和地上部的磷含量与干重、株高为表型，采用全基因组关联分析与QTL-seq分析相结合策略，发掘优良单倍型和候选基因，解析谷子磷效率遗传基础，为揭示谷子磷高效分子机理奠定基础。选择育种是培育优良新品种的重要手段，目前对作物矿质元素效率的基因组预测研究相对较少。本项目拟利用Bayes、rrBLUP模型估计基因组SNP效应值，采用交叉验证和未知表型的独立群体验证，探讨基因组选择在谷子磷高效个体选择的应用潜力，为今后快速选择磷高效型品种奠定应用基础。

磷是植物生长和发育所必需的大量营养元素之一。由于大部分土壤中都存在磷素严重缺乏的问题，植物在漫长的进化过程中发展出了一系列的应答反应，来应对环境中的低磷胁迫。谷子作为耐贫瘠作物，低磷条件下根系的根毛数显著增加，叶片酸性磷酸酶活性显著提高，耐低磷种质比磷敏感型种质根体积增加更加明显，这些变化有利于提高谷子耐低磷特性。本项目利用含有328份种质的关联群体，首先对低磷和对照条件下的谷子苗期生长性状和生理性状进行全基因组关联分析。结果在低磷和相对值条件下共找到201个显著关联位点。进一步通过QTL定位策略验证全基因组关联分析得到的显著位点，共检测到15个QTL位点，对表型的表型贡献率范围为5.54-13.64%。然后开展功能富集注释和基因表达差异分析，共发现9个候选基因和响应低磷胁迫关键候选基因（SiACPs，SiPAPs和SiHATs等）。并通过重测序的方法挖掘了目标关键基因SiACP1的耐低磷性状优良单体型。最后通过RRBLUP预测模型及交叉验证方法对谷子不同磷水平下的生理性状和生长性状进行预测。结果显示，7个性状表型是可以被预测的，不同性状间的预测准确性存在明显的差异，尤其是在正常和低磷条件的同一个性状。对低磷条件下的PH、RL和生理性状Acp-L和Acp-R预测准确性显著提高了14.3%和22.7%。该项目研究结果不仅有助于进一步评估和选育谷子和其它禾谷类作物的耐低磷种质，也为其它营养代谢和非生物胁迫（重金属、干旱、盐碱等）的耐性品种选育提供了理论支持。