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QTL Analysis of Floral Traits of Rice (Oryza Sadva L.) under Well-Watered and Drought Stress Conditions

机译:干旱和干旱条件下水稻(Oryza Sadva L.)花性状的QTL分析

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Three floral traits, spikelet number per particle (SNP), percentage of single exserted stigma (PSES) and dual exserted stigma (PDES) of a RI population with 185 lines under water stress and non-stress conditions for two years were investigated in a drought tolerance screening facility. ANOVA results showed high significance between years, lines, and water stress treatments, together with interactions among them in pairs. High phenotypic con-elation was found between PSES and PDES (r = 0.5424***). Based on a linkage map of 203 SSR markers, when under well-watered condition, six QTLs (qSNP-3b, qSNP-4 qSNP-11 qSNP-2, qSNP-5 and qSNT-9) were detected for SNP. Half of them had significant Q x E interactions. Three QTLs (qPSES-1, qPSES-2, qPSES-5) were found to influence PSES, including one locus (qPSES-2) having Q x E interaction. And three QTLs (qPDES-2, qPDES-5 and qPDES-6) were also detected to influence PDES. qPDES-5 was found to have Q x E interaction. The contribution rate of a single QTL varied from 0.80% to 8.83% for additive effect, and 1.86% to 15.25% for Q x E interactions. Under drought stress, six QTLs (qSNP-3a, qSNP-4, qSNP-7a, qSNP-7b, qSNP-8 and qSNP-9) were associated with SNP, including qSNP-3a and qSNP-4 with Q x E interaction. Three QTLs (qPSES-1, qPSES-10 and qPSES-12 were located on nice chromosome 1, 10 and 12 for PSES. Four QTLs (qPDES-1a, qPDES-1b, qPDES-4 and qPDES-9 were detected for PDES, including qPDES-9 with Q x E interaction. The additive effect of single QTL can only explain 1.16% to 5.84% of total variance while Q x E interaction of four loci can explain 4.25% to 11.54% of total variance for each locus. There were one to nine pairs of epistatic QTLs influencing SNP and stigma exsertion. The contribution rates of additive and epistatic effects seemed to be in a low magnitude for most cases (0.76%similar to 9.92%) while a few QTLs or QTL pairs explained more than 10% of total variance. Some main effect QTL and epistasis were commonly detected among PSES and PDES, explaining the high positive correlation between them. Few QTLs were detected under both water stress and non-stress conditions, indicating that drought had severe impact on the genetic behaviors of both spikelet number and stigma exsertion.
机译:在干旱和非胁迫条件下,研究了185个品系的RI群体在干旱两年下的三个花性状,每粒小穗数(SNP),单显性柱头(PSES)和双显性柱头(PDES)的百分比公差筛选工具。方差分析结果显示了年,线和水分胁迫处理之间的高度意义,以及它们之间成对的相互作用。在PSES和PDES之间发现高表型相关(r = 0.5424 ***)。根据203个SSR标记的连锁图,在浇水条件良好时,检测到6个QTL(qSNP-3b,qSNP-4,qSNP-11,qSNP-2,qSNP-5和qSNT-9)。他们中有一半具有显着的Q x E相互作用。发现三个QTL(qPSES-1,qPSES-2,qPSES-5)影响PSES,包括一个具有Q x E相互作用的基因座(qPSES-2)。并且还检测到三个QTL(qPDES-2,qPDES-5和qPDES-6)影响PDES。发现qPDES-5具有Q x E相互作用。单个QTL的加性效应贡献率为0.80%至8.83%,Q x E相互作用的贡献率为1.86%至15.25%。在干旱胁迫下,六个QTL(qSNP-3a,qSNP-4,qSNP-7a,qSNP-7b,qSNP-8和qSNP-9)与SNP相关,包括具有Q x E相互作用的qSNP-3a和qSNP-4。三个QTL(qPSES-1,qPSES-10和qPSES-12位于PSES的1号,10号和12号染色体上。四个QTL(qPDES-1a,qPDES-1b,qPDES-4和qPDES-9被检出PDES,包括具有Q x E相互作用的qPDES-9,单个QTL的加和效应只能解释总变异的1.16%至5.84%,而四个基因座的Q x E相互作用可以解释每个基因座的总变异的4.25%至11.54%。是影响SNP和柱头外露的一到九对上位QTL,在大多数情况下,加性和上位效应的贡献率似乎较低(0.76%,与9.92%相似),而少数QTL或QTL对解释的影响要大得多。总体方差的10%,在PSES和PDES中通常检测到一些主要影响QTL和上位性,这说明它们之间具有很高的正相关性,在水分胁迫和非胁迫条件下都检测到很少的QTL,表明干旱对干旱和干旱有严重影响。小穗数和柱头的遗传行为离子。

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