Veisi Sheida, Sabouri Atefeh, Abedi Amin
Department of Agronomy and Plant Breeding, Faculty of Agricultural Sciences, University of Guilan, P.O. Box: 41635-1314, Rasht, Iran.
Department of Plant Biotechnology, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran.
Physiol Mol Biol Plants. 2022 Aug;28(8):1587-1605. doi: 10.1007/s12298-022-01232-1. Epub 2022 Sep 21.
Seed germination is one of the critical stages of plant life, and many quantitative trait loci (QTLs) control this complex trait. Meta-analysis of QTLs is a powerful computational technique for estimating the most stable QTLs regardless of the population's genetic background. Besides, this analysis effectively narrows down the confidence interval (CI) to identify candidate genes (CGs) and marker development. In the current study, a comprehensive genome-wide meta-analysis was performed on QTLs associated with germination in rice. This analysis was conducted based on the data reported over the last two decades. In this case, various analyses were performed, including seed germination rate, plumule length, radicle length, germination percentage, coleoptile length, coleorhiza length, radicle fresh weight, germination potential, and germination index. A total of 67 QTLs were projected onto a reference map for these traits and then integrated into 32 meta-QTLs (MQTLs) to provide a genetic framework for seed germination. The average CI of MQTLs was considerably reduced from 15.125 to 8.73 cM compared to the initial QTLs. This situation identified 728 well-known functionally characterized genes and novel putative CGs for investigated traits. The fold change calculation demonstrated that 155 CGs had significant changes in expression analysis. In this case, 112 and 43 CGs were up-regulated and down-regulated during germination, respectively. This study provides an overview and compares genetic loci controlling traits related to seed germination in rice. The findings can bridge the gap between QTLs and CGs for seed germination.
The online version contains supplementary material available at 10.1007/s12298-022-01232-1.
种子萌发是植物生命的关键阶段之一，许多数量性状基因座（QTL）控制着这一复杂性状。QTL的元分析是一种强大的计算技术，可用于估计最稳定的QTL，而不考虑群体的遗传背景。此外，该分析有效地缩小了置信区间（CI），以识别候选基因（CG）和进行标记开发。在本研究中，对水稻中与萌发相关的QTL进行了全面的全基因组元分析。该分析基于过去二十年报道的数据进行。在这种情况下，进行了各种分析，包括种子萌发率、胚芽长度、胚根长度、发芽率、胚芽鞘长度、胚根鞘长度、胚根鲜重、发芽势和发芽指数。总共67个QTL被投影到这些性状的参考图谱上，然后整合到32个元QTL（MQTL）中，为种子萌发提供遗传框架。与初始QTL相比，MQTL的平均CI从15.125显著降低到8.73 cM。这种情况确定了728个功能特征明确的已知基因和用于所研究性状的新推定CG。倍数变化计算表明，155个CG在表达分析中有显著变化。在这种情况下，分别有112个和43个CG在萌发过程中上调和下调。本研究提供了一个概述，并比较了控制水稻种子萌发相关性状的遗传位点。这些发现可以弥合种子萌发QTL和CG之间的差距。
在线版本包含可在10.1007/s12298-022-01232-1获取的补充材料。
