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Comprehensive Meta-Analysis of Maize QTLs Associated With Grain Yield, Flowering Date and Plant Height Under Drought Conditions

机译:干旱条件下与玉米产量,开花日期和株高相关的玉米QTL的综合Meta分析

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Drought remains the primary abiotic constraint to maize (Zea mays L.) productivity globally. Maize drought response involves several regulatory quantitative traits and complex gene networks. Therefore, precise location of drought-related quantitative trait loci (QTL) is imperative for drought tolerance breeding. Despite numerous studies identifying several drought-related maize QTLs, some QTL from particular genetic backgrounds showed smaller effects or could not be identified at all in different backgrounds, affected by marker sets, experimental design, mapping populations and statistical methods. Herein, therefore; using 457 published maize QTLs conferring for 18 traits, we have performed meta-analysis of data from various experiments to obtain meta-QTL (MQTL), integrate these fruitful QTL and to mine candidate genes related to drought. Resultantly, 24 MQTL with confidence interval (CI) < 5 cm were identified to be hot regions. Additionally, 47 drought related gene loci were observed and several candidate genes of the hot MQTL were reorganized by bioinformatics techniques. Thirteen gene (sod4, taf1, rps1, nthr3, oc13, bas, apx1, asn4, pck2, nac1, gst2, ao1 and kch4) loci of hot MQTL regions were homologous to their corresponding gene sequences from the PlantGDB database (http://www.plantgdb.org/search/). Further, we used a comparative genomics approach to identify the homologous regions of MQTL in rice (Oryza sativa Japonica) database (http://www.gramene.org) and observed that drought-related rice gene ATG6 was homologous to maize candidate genes GRMZM2G027857_T01 and GRMZM2G027857_T02. Conclusively, our identified MQTLs with narrowed CI could be useful for marker-assisted selection and the candidate genes harnessed for maize drought tolerance breeding.
机译:干旱仍然是全球玉米(Zea mays L.)生产力的主要非生物限制因素。玉米干旱反应涉及几个调控的数量性状和复杂的基因网络。因此,与干旱有关的数量性状基因座(QTL)的精确定位对于耐旱育种至关重要。尽管进行了许多研究,确定了几个与干旱相关的玉米QTL,但某些特定遗传背景的QTL受标记集,实验设计,作图种群和统计方法的影响,显示出较小的影响或根本无法在不同的背景下被鉴定。因此,在此;我们使用457个公开发表的具有18个性状的玉米QTL,对来自各种实验的数据进行了荟萃分析,以获得Meta-QTL(MQTL),整合了这些卓有成效的QTL,并挖掘了与干旱相关的候选基因。结果,置信区间(CI)<5 cm的24个MQTL被确定为热点区域。此外,观察到47个干旱相关基因位点,并通过生物信息技术重组了热MQTL的几个候选基因。热MQTL区域的13个基因位点(sod4,taf1,rps1,nthr3,oc13,bas,apx1,asn4,pck2,nac1,gst2,ao1和kch4)位点与来自PlantGDB数据库的相应基因序列同源(http:// www.plantgdb.org/search/)。此外,我们使用比较基因组学方法在水稻(Oryza sativa Japonica)数据库(http://www.gramene.org)中鉴定MQTL的同源区域,并观察到干旱相关的水稻基因ATG6与玉米候选基因GRMZM2G027857_T01同源和GRMZM2G027857_T02。结论是,我们鉴定出的具有狭窄CI的MQTL可用于标记辅助选择和可用于玉米抗旱育种的候选基因。

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