Literature DB >> 30043259

Linkage mapping combined with association analysis reveals QTL and candidate genes for three husk traits in maize.

Zhenhai Cui1,2, Aiai Xia2, Ao Zhang1, Jinhong Luo2, Xiaohong Yang2, Lijun Zhang1, Yanye Ruan3, Yan He4.   

Abstract

Key message Combined linkage and association mapping analyses facilitate the emphasis on the candidate genes putatively involved in maize husk growth. The maize (Zea mays L.) husk consists of multiple leafy layers and plays important roles in protecting the ear from pathogen infection and in preventing grain dehydration. Although husk morphology varies widely among different maize inbred lines, the genetic basis of such variation is poorly understood. In this study, we used three maize recombinant inbred line (RIL) populations to dissect the genetic basis of three husk traits: i.e., husk length (HL), husk width (HW), and the number of husk layers (HN). Three husk traits in all three RIL populations showed wide phenotypic variation and high heritability. The HL showed stronger correlations with ear traits than did HW and HN. A total of 21 quantitative trait loci (QTL) were identified for the three traits in three RIL populations, and some of them were commonly observed for the same trait in different populations. The proportions of total phenotypic variation explained by QTL in three RIL populations were 31.8, 35.3, and 44.5% for HL, HW, and HN, respectively. The highest proportions of phenotypic variation explained by a single QTL were 14.7% for HL in the By815/K22 RIL population (BYK), 13.5% for HW in the By815/DE3 RIL population (BYD), and 19.4% for HN in the BYD population. A combined analysis of linkage mapping with a previous genome-wide association study revealed five candidate genes related to husk morphology situated within three QTL loci. These five genes were related to metabolism, gene expression regulation, and signal transduction.

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Year:  2018        PMID: 30043259     DOI: 10.1007/s00122-018-3142-2

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  77 in total

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