Identification of epistasis loci underlying rice flowering time by controlling population stratification and polygenic effect
Identification of epistasis loci underlying rice flowering time by controlling population stratification and polygenic effect
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通过控制群体分层和多基因效应识别水稻开花时间的上位位点
DOI：
10.1093/dnares/dsy043
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发表时间：
2019-04-01
期刊：
影响因子：
4.1
通讯作者：
Chen, Ming
中科院分区：
文献类型：
--
作者：
Ahsan, Md. Asif;Monir, Md. Mamun;Chen, Ming
开花时间是一个重要的农艺性状，由多个基因，基因 - 基因相互作用和环境因素归因。种群分层和多基因效应可能会混淆这种复杂性状的因果基因座的遗传作用。我们提出了一种两步方法，用于通过计算种群结构和多基因效应来检测水稻开花时间的上毒相互作用。模拟研究表明，就种群分层和多基因效应而言，本研究中使用的方法的性能优于经典和PC线性方法。整个基因组上毒分析确定了589个开花时间的假定遗传相互作用。这些相互作用中的18个位于已知蛋白质蛋白相互作用区域的10千倍酶内。接近25个基因的37个SNP涉及大米或/和拟南芥（直向）开花途径。生物信息学分析表明，在各种基因组特征中，已确定相互作用的66.55％成对基因（在589个相互作用中有392个）具有相似性。此外，大量检测到的上皮基因在不同的花卉组织中具有很高的表达。我们的发现通过控制人口分层和多基因效应，强调了上毒分析的重要性，并为水稻开花的遗传结构提供了新的见解，这可以帮助育种计划。
Flowering time is an important agronomic trait, attributed by multiple genes, gene-gene interactions and environmental factors. Population stratification and polygenic effects might confound genetic effects of the causal loci underlying this complex trait. We proposed a two-step approach for detecting epistasis interactions underlying rice flowering time by accounting population structure and polygenic effects. Simulation studies showed that the approach used in this study performs better than classical and PC-linear approaches in terms of powers and false discovery rates in the case of population stratification and polygenic effects. Whole genome epistasis analyses identified 589 putative genetic interactions for flowering time. Eighteen of these interactions are located within 10 kilobases of regions of known protein-protein interactions. Thirty-seven SNPs near to twenty-five genes involve in rice or/and Arabidopsis (orthologue) flowering pathway. Bioinformatics analysis showed that 66.55% pairwise genes of the identified interactions (392 out of the 589 interactions) have similarity in various genomic features. Moreover, significant numbers of detected epistatic genes have high expression in different floral tissues. Our findings highlight the importance of epistasis analysis by controlling population stratification and polygenic effect and provided novel insights into the genetic architecture of rice flowering which could assist breeding programmes.