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Association Mapping for Epistasis and Environmental Interaction of Yield Traits in 323 Cotton Cultivars under 9 Different Environments

机译:9种不同环境下323个棉花品种的上位性与产量性状的环境互作的关联图谱

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摘要

Improving yield is a major objective for cotton breeding schemes, and lint yield and its three component traits (boll number, boll weight and lint percentage) are complex traits controlled by multiple genes and various environments. Association mapping was performed to detect markers associated with these four traits using 651 simple sequence repeats (SSRs). A mixed linear model including epistasis and environmental interaction was used to screen the loci associated with these four yield traits by 323 accessions of Gossypium hirsutum L. evaluated in nine different environments. 251 significant loci were detected to be associated with lint yield and its three components, including 69 loci with individual effects and all involved in epistasis interactions. These significant loci explain ∼ 62.05% of the phenotypic variance (ranging from 49.06% ∼ 72.29% for these four traits). It was indicated by high contribution of environmental interaction to the phenotypic variance for lint yield and boll numbers, that genetic effects of SSR loci were susceptible to environment factors. Shared loci were also observed among these four traits, which may be used for simultaneous improvement in cotton breeding for yield traits. Furthermore, consistent and elite loci were screened with −Log10 (P-value) >8.0 based on predicted effects of loci detected in different environments. There was one locus and 6 pairs of epistasis for lint yield, 4 loci and 10 epistasis for boll number, 15 loci and 2 epistasis for boll weight, and 2 loci and 5 epistasis for lint percentage, respectively. These results provided insights into the genetic basis of lint yield and its components and may be useful for marker-assisted breeding to improve cotton production.
机译:提高产量是棉花育种计划的主要目标,皮棉产量及其三个组成特征(棉铃数,棉铃重和皮棉百分比)是受多个基因和不同环境控制的复杂性状。使用651个简单序列重复(SSR)进行关联映射以检测与这四个性状相关的标记。使用包括上位性和环境相互作用的混合线性模型,通过在9种不同环境中评估的323份陆地棉(Gossypium hirsutum L.)来筛选与这四个产量性状相关的基因座。检测到251个与棉绒产量及其三个组成部分相关的重要基因座,包括69个具有个体效应的基因座,所有基因座都参与上皮相互作用。这些显着位点解释了〜62.05%的表型变异(这四个特征的范围为49.06%〜72.29%)。环境相互作用对皮棉产量和铃数表型方差的巨大贡献表明,SSR基因座的遗传效应易受环境因素影响。在这四个性状中还观察到了共享的基因座,可用于同时改良棉花育种的性状。此外,基于在不同环境中检测到的基因座的预测效果,以-Log10(P值)> 8.0筛选了一致且优良的基因座。皮棉产量分别为1个位点和6对上皮,棉铃数分别为4个位点和10个上位点,棉铃重分别为15个位点和2个上位点,皮棉百分比分别为2个位点和5个上位点。这些结果提供了对皮棉产量及其组成的遗传基础的见解,对于标记辅助育种以提高棉花产量可能有用。

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