整合多组学数据的复杂性状关联分析与分子设计新方法研究

Most crop yield and quality related traits are complex traits, controlled cooperatively by gene interaction network and environment. Genetic dissection and molecular design of complex traits is a research hot and challenge in crop genetics and improvement. Currently, association mapping based on saturated SNP of genome has been an important method to dissect genetic mechanism of complex traits; however, current methods based on testing of individual SNP exhibit very lower power and couldn’t effectively analyze interaction between SNPs and their interaction effect with environment, and the distinguished loci may not be the functional genes which could be selected in breeding. This research will develop system quantitative genetics method based on integrated analysis of genetic data on genome sequence, gene annotation, trait phenotype, transcriptome, metablism or proteomics, for effectively identifying and analyzing pleiotropy and non-pleiotropy functional genes which genetic effects are tested as basic unit, estimating epistatic effects and gene-environment interaction effects; while, genotype design method will be developed for improvement of single or multiple traits. Accordingly, software will be developed. An experiment of a super-rice permanent F2 population will be conducted for testing of the method and the software; while, genotype design of functional genes will be proposed for improving targeted traits and promoting super-rice breeding. The expected results of this research are very valuable for dissection of genetic architecture and molecular design of crop complex traits in science and breeding.

作物产量品质相关性状大多为复杂性状，受多基因互作网络与环境的协同调控，其遗传规律剖析与分子设计是作物遗传育种研究的热点，也面临巨大挑战。目前，基于高密度SNP的关联分析已成为复杂性状遗传剖析的重要方法，但已有方法以SNP为检测单位，分析功效低，无法有效剖析全基因组多位点间及其与环境间互作，鉴别的显著位点也不一定是可供选择的功能基因。课题将发展整合基因组结构与注释、性状表型、转录组、代谢或蛋白质组等多组学信息的系统数量遗传学方法，以基因为检测单位，全基因组有效鉴别和分析多效性和非多效性功能基因，估算上位性及基因与环境互作的各项效应分量；发展单性状/多性状基因型设计方法，研制配套分析软件。用超级稻永久F2群体为材料，验证和完善分析方法和软件，提出目标性状改良的功能基因组配方案，推动超级稻育种。课题研究成果对作物复杂性状的遗传结构剖析与分子设计具有重要科学意义和实践应用价值。

作物产量、品质、抗逆性等复杂性状受微效多基因调控，存在基因间互作、基因与环境间互作。此外，产量等复杂性状与其构成因素间又存在内在遗传组分的相关性，使多目标性状的同步改良难上加难。因此，传统的基于表型和大效应基因定位及相应的育种选择方法亟待革新。课题组针对这一挑战，开展了利用基因组结构与注释信息、整合多组学的高通量数据，发展一套具有较高功效的复杂性状遗传结构及调控网络剖析的关联分析新方法，高效地鉴别中低效应的功能基因位点，明确基因的多效性，主要开展了以下几方面内容的研究：1）在混合线性模型理论框架下，发展了包含环境、基因上位性、基因与环境互作效应的多性状关联分析模型和分析算法，实现多个遗传相关性状的联合关联分析，为性状遗传相关的分子剖析提供方法；2）以水稻、油菜及棉花为实例，整合基因组、转录组等多组学数据，开展了重要农艺性状的联合关联分析，鉴别显著关联的遗传位点，并采用生物信息学方法，筛选具有育种潜在应用价值的功能基因，展开多个性状同步改良的基因型分子设计与育种展望评价；3）发展了稳健的线性回归方法，有效降低了组学中异常数据对参数估计的影响；4）课题研究已有6篇研究论文在SCI期刊正式刊出，申请了1个软件著作权并得到转化应用，资助培养了8名硕博研究生及1名博士后。课题发展的方法与软件促进了动植物复杂性状遗传结构有效剖析及功能基因挖掘和育种利用，已经在全国推广应用，举办了两届全国数量遗传分析与QTX定位研讨班，起到了良好社会效果。