水稻生物学产量及其构成性状的QTL定位(英文)

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QTL的加性效应、加性×加性上位性效应及它们与环境的互作效应是数量性状的重要遗传分量。利用IR64/Azucena的125个DH品系为群体,分析了水稻生物学产量及其两个构成性状干草产量和谷粒产量的遗传组成。用基于混合模型的复合区间作图(MCIM)方法进行QTL定位。检测到12个位点有加性主效应,27个位点涉及双位点互作,18个位点存在环境互作。结果表明水稻生物学产量和它的两个构成性状普遍存在上位性效应和QE互作效应。此外,还探讨了性状间相关的遗传基础。发现4个QTLs和一对上位性QTLs可能与生物学产量与干草产量之间的正相关有关。3个QTL可能与干草产量与谷粒产量之间的负相关有关。这些结果可能部分地解释了这3个性状相关的遗传原因。通过对水稻生物学产量及其两个构成性状所定位QTL的分析,加深了对数量性状QTL的认识。首先,QTL的上位性效应和QE互作效应是普遍存在的;其次,QTL的多效性或紧密连锁可能是遗传相关的原因,当QTL对两个性状作用的方向相同时可导致正向遗传相关,反之则为负向遗传相关,当有些QTL表现为同向作用而另一些QTL表现为反向作用时,则可削弱性状间的遗传相关性;第三,复合性状的QTL效应可分解为其组成性状的QTL效应,如果QTL对各组成性状的效应方向相反而相互抵消,可使复合性状的QTL效应不易被检测;第四,加性效应的QTL常参预构成上位性效应,而具有上位性效应的QTL并非都有加性主效应,表明忽略上位性的QTL定位方法会降低检测QTL的功效;最后,鉴别不同类型的QTL效应有利于指导育种实践,选择主效QTL适用于多环境,QE互作QTL适用于特定环境,对上位性QTL应强调选择基因组合而并非单个基因。 The additive effects of QTLs, additive × additive epistatic effects and their interaction with the environment are important genetic components of quantitative traits. Using 125 DH lines from IR64 / Azucena as a population, the genetic composition of rice biological yield and its two traits, hay yield and grain yield, were analyzed. QTL mapping was performed using a hybrid model based composite interval mapping (MCIM) method. Twelve loci were found to have additive main effects, 27 loci involved double locus interactions and 18 loci interacted. The results showed that there were ubiquitous epistasis effects and QE interactions in rice biological yield and its two constituent traits. In addition, the genetic basis associated with traits was also explored. Four QTLs and a pair of epistatic QTLs were found to be related to the positive correlation between biological yield and hay production. Three QTLs may be related to the negative correlation between hay yield and grain yield. These results may partly explain the genetic causes associated with the three traits. Through the analysis of the QTL mapping of rice biological yield and its two constituent traits, the understanding of QTL for quantitative traits has been deepened. First, the epistatic effects of QTL and QE interactions are ubiquitous. Second, the pleiotropy or tight linkage of QTLs may be the cause of genetic correlation. When QTLs act in the same direction on both traits, they can lead to forward genetic While the other is negatively inherited. When some of the QTLs show the same direction and some of the QTLs reverse, it can weaken the genetic correlation between the traits. Third, the QTL effect of the composite traits can be decomposed into The QTL effect of its trait can not make the QTL effect of composite trait easily detectable if the effect of QTL on each trait is opposite and counteract each other. Fourthly, the QTL of additive trait often participates in the epistatic effect, QTLs for sexual effects did not all have additive main effects, indicating that omission of epistasis QTL mapping method will reduce the efficacy of QTL detection; Finally, to identify different types of QTL effects are conducive to guide breeding practice, selection of major QTLs for multi-environment, QE Interaction QTLs apply to a particular environment, and epistatic QTLs should emphasize selection of genes rather than single genes.
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