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首页> 外文OA文献 >Genome wide screening and comparative genome analysis for Meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice
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Genome wide screening and comparative genome analysis for Meta-QTLs, ortho-MQTLs and candidate genes controlling yield and yield-related traits in rice

机译：基因组宽筛选和对比较基因组分析，QTLS，Ortho-MQTLS和候选基因控制水稻产量和产量相关性状

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Abstract Background Improving yield and yield-related traits is the crucial goal in breeding programmes of cereals. Meta-QTL (MQTL) analysis discovers the most stable QTLs regardless of populations genetic background and field trial conditions and effectively narrows down the confidence interval (CI) for identification of candidate genes (CG) and markers development. Results A comprehensive MQTL analysis was implemented on 1052 QTLs reported for yield (YLD), grain weight (GW), heading date (HD), plant height (PH) and tiller number (TN) in 122 rice populations evaluated under normal condition from 1996 to 2019. Consequently, these QTLs were confined into 114 MQTLs and the average CI was reduced up to 3.5 folds in compare to the mean CI of the original QTLs with an average of 4.85 cM CI in the resulted MQTLs. Among them, 27 MQTLs with at least five initial QTLs from independent studies were considered as the most stable QTLs over different field trials and genetic backgrounds. Furthermore, several known and novel CGs were detected in the high confident MQTLs intervals. The genomic distribution of MQTLs indicated the highest density at subtelomeric chromosomal regions. Using the advantage of synteny and comparative genomics analysis, 11 and 15 ortho-MQTLs were identified at co-linear regions between rice with barley and maize, respectively. In addition, comparing resulted MQTLs with GWAS studies led to identification of eighteen common significant chromosomal regions controlling the evaluated traits. Conclusion This comprehensive analysis defines a genome wide landscape on the most stable loci associated with reliable genetic markers and CGs for yield and yield-related traits in rice. Our findings showed that some of these information are transferable to other cereals that lead to improvement of their breeding programs.
机译：摘要背景提高产量和产量相关的特征是谷物繁殖计划中的重要目标。 Meta-QTL（MQTL）分析发现最稳定的QTL，无论人群遗传背景和现场试验条件如何，有效地缩小置信区间（CI），以鉴定候选基因（CG）和标记发育。结果在1996年的正常情况下评估的122种稻米群中的1052 QTL，综合MQTL分析综合分析，据报道，粒度（GW），谷物重量（GW），植物高度（pH）和分蘖数（TN）。因此，因此，这些QTL被限制在114个MQTL中，并且平均CI减少到3.5倍，以比较原始QTL的平均CI，平均为4.85cm CI在所产生的MQTLS中。其中，从独立研究中至少有五个初始QTL的27个MQTL被认为是不同现场试验和遗传背景上最稳定的QTL。此外，以高自信的MQTLS间隔检测若干已知的和新型CGS。 MQTL的基因组分布表明了亚细胞微调染色体区域的最高密度。使用同步和对比基因组学分析的优点，分别在米饭和玉米之间的共线区域鉴定了11和15个Ortho-MQTS。此外，比较导致的MQTL与GWAS研究导致鉴定控制评估性状的十八常见的重要染色体区域。结论该综合分析定义了与水稻中可靠遗传标记和CGS相关的最稳定的基因座上的基因组景观。我们的调查结果表明，一些信息可转移到导致其繁殖计划的其他谷物。

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