紫花苜蓿产量性状配合力的分子遗传机理与预测模型分析

The genetic mechanism analysis of alfalfa yield is the key for effective utilization of alfalfa germplasm characteristics and breeding of high yield new varieties. Based on National Natural Science Foundation of China, our previous research found that general MAS cannot capture major loci significantly associated with yield traits and the molecular mechanism of regulation remains to be revealed. To improve selection efficiency and shorten selection cycles, this project is designed to study the molecular genetic mechanism of yield traits and new MAS method for alfalfa breeding. The plant materials include breeding intermediate materials and cross populations in this experiment. Using phenotypic recurrent selection and genomic selection methods, this project focus on: (1) analysis of genetic parameters and genetic characteristics of alfalfa yield.(2) establish yield prediction model based on the whole genome SNP detection, test model fit and accuracy based on the residual variation evaluation and cross validation, and study the effects of marker data and genetic structure on model accuracy. (3) compare of phenotypic recurrent selection and genomic selection in genetic advances. (4) estimate the locus combining ability value based on combining ability model and genomic selection, and evaluate the effects of gene recombination and polymerization with marker assisted method. The objective of this project is to reveal the molecular genetic mechanism of alfalfa yield, and establish a new method to improve alfalfa yield and other complex quantitative traits.

解析紫花苜蓿产量性状的遗传机理是有效利用苜蓿种质特性、培育高产新品种的关键。课题组在前期青年基金研究中发现，常规标记方法无法捕获与产量显著关联的主效位点，其性状调控的分子机制仍有待揭示。本项目针对苜蓿产量遗传改良缓慢、评价周期长等难题，围绕产量性状的分子遗传机理与标记辅助选择新方法这一科学问题，采用表型轮回选择、基因组选择方法，以苜蓿育种中间材料、人工杂交群体为对象，重点研究：(1)产量性状的遗传特性及遗传参数分析；(2)在全基因组SNP检测的基础上构建产量预测模型，通过残差变异评估和交互验证检测模型的准确度，明确基因位点剂量、遗传结构等因素的影响；(3)表型轮回选择与基因组选择的遗传进展比较分析；(4)结合配合力模型进行基因位点配合力效应值估计，研究标记辅助基因重组、聚合的应用效果。预期研究结果为揭示苜蓿产量性状配合力的分子遗传机理提供新知识，探索建立苜蓿产量等复杂数量性状改良的新方法。

紫花苜蓿是最重要的豆科牧草之一，其商品草产量占我国商品草总量的90%以上。解析紫花苜蓿产量性状的遗传机理对于培育丰产和优质的苜蓿新品种具有重要的理论指导意义。前期研究表明，常规标记方法无法捕获与产量显著关联的主效位点，其性状调控的分子机制仍有待揭示。本项目针对苜蓿产量遗传改良缓慢、评价周期长等难题，以两组高产和早熟材料人工杂交 F1 代群体为实验材料，采用表型轮回选择、基因组选择方法，开展苜蓿产量性状的遗传特性、GS产量预测模型构建与评价、遗传进展比较分析等相关研究。综合分析多年多点田间表型数据表明，苜蓿杂交F1群体内部存在丰富的遗传变异，产量/单株变异系数为44%-55%；定位了产量相关性状（产量/单株、株高、分枝数）QTL位点43个，其中干重QTL位点9个，可解释遗传变异为2.73-21.63%；采用gBLUP、rrBLUP、BayesA等6种方法建立、评价、优化苜蓿产量全基因组选择预测模型，beiyesC模型和rrBLUP模型模型的准确度较高，两个群体模型的准确度最高分别为69.6%和60.5%；按照20%入选比例，基于表型轮回选择与GS选择两种方法筛选的81份高产单株，67份单株是相同的，占全部入选单株的82.7%。可见，根据GS产量预测模型和基因型数据进行优良单株的初步选择，正确率超过了80%。本项目成果已发表研究论文5篇，其中SCI收录3篇，中文核心期刊论文2篇。获得发明专利授权2项，培养研究生2名。本研究进一步揭示了紫花苜蓿产量性状配合力的遗传机理，为指导苜蓿产量等复杂数量性状的遗传改良提供了重要参考。