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

  •  Songtao Liu    
  •  Tinashe Zenda    
  •  Xuan Wang    
  •  Guo Liu    
  •  Hongyu Jin    
  •  Yatong Yang    
  •  Anyi Dong    
  •  Huijun Duan    


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 ( Further, we used a comparative genomics approach to identify the homologous regions of MQTL in rice (Oryza sativa Japonica) database ( 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.

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