Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population

Abstract

Background Maize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize. Results Here, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN. Conclusions This study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.

The Genetic Structures and Molecular Mechanisms Underlying Ear Traits in Maize (Zea mays L.)

“…The authors also found that only a few QTLs overlap with previously reported loci, and they proposed that this may be due to different parents being used for the construction of the mapping population, and epistasis might modulate the effect of a QTL depending on the genetic background [21]. KRN is one of the most important ear trait components and an important selection target during maize domestication and breeding [13,14,30,31]. Many efforts have been made to dissect the genetic basis of KRN and more than three hundred QTLs have been identified [13,[30][31][32][33][34], and at least four of the KRN QTLs have been cloned [35][36][37][38].…”

“…KRN is one of the most important ear trait components and an important selection target during maize domestication and breeding [13,14,30,31]. Many efforts have been made to dissect the genetic basis of KRN and more than three hundred QTLs have been identified [13,[30][31][32][33][34], and at least four of the KRN QTLs have been cloned [35][36][37][38]. A significant amount of information on the genetic basis for the most important ear traits has accumulated, which provides a solid basis for combining the different individual studies to summarize the genetic regulation of ear traits.…”

“…A significant amount of information on the genetic basis for the most important ear traits has accumulated, which provides a solid basis for combining the different individual studies to summarize the genetic regulation of ear traits. Based on this consideration, we initially collected QTLs from published QTL mapping articles [16,21,[30][31][32][33][34]. A consensus map for ear trait QTLs was constructed with the positional information of all the original QTLs, which was normalized to the same version of B73 reference genome (RefGen_v5.0) when the primer sequences of the molecular markers were available.…”

Genome-Wide Association Studies on the Kernel Row Number in a Multi-Parent Maize Population

“…A GWAS study revealed 31 associated SNPs representing 17 genomic loci with effects in at least one of the five individual environments. In another study, Fei et al [ 24 ] utilized a nested association mapping (NAM) population consisting of 1617 RILs and identified five QTLs related to KRN via joint linkage mapping (JLM). These QTLs were further validated through linkage mapping (SLM) and GWAS.…”