Genetic mapping of QTL for the sizes of eight consecutive leaves below the tassel in maize (Zea mays L.)

Abstract

A set of RIL population was used to detect QTL associated with the sizes of eight consecutive leaves, across different environments, and ten QTL clusters were identified as main QTLs. One of the important parameters of the maize leaf architecture that affects light penetration into the canopy, leaf size, has long attracted breeders' attention for optimizing the plant type of maize and for maximizing the grain yield (GY). In this study, we used 253 RIL lines derived from a cross between B73 and SICAU1212 to investigate the leaf widths (LWs), leaf lengths (LLs), and leaf areas (LAs) of eight consecutive leaves of maize below the tassel and GY across different environments and to identify quantitative traits loci (QTLs) controlling the above-mentioned traits, using inclusive interval mapping for single-environment analysis plus a mixed-model-based composite interval mapping for joint analysis. A total of 171 and 159 putative QTLs were detected through these two mapping methods, respectively. Single-environment mapping revealed that 39 stable QTLs explained more than 10 % of the phenotypic variance, and 35 of the 39 QTLs were also detected by joint analysis. In addition, joint analysis showed that nine of the 159 QTLs exhibited significant QTL × environment interaction and 15 significant epistatic interactions were identified. Approximately 47.17 % of the QTLs for leaf architectural traits in joint analysis were concentrated in ten main chromosomal regions, namely, bins 1.07, 2.02, 3.06, 4.09, 5.01, 5.02, 5.03-5.04, 5.07, 6.07, and 8.05. This study should provide a basis for further fine-mapping of these main genetic regions and improvement of maize leaf architecture.

Distinct controls of leaf widening and elongation by light and evaporative demand in maize

“…). This contrasts to a study in wheat (Yang et al ) working with biparental population found that leaf width was less variable compared to leaf length. In our diversity panel, we found an even larger importance of leaf width on individual leaf area compared to that of leaf length (85% versus 15% of explained variance).…”

“…Within the few studies considering leaf width, most of them have shown that a larger part of variance of individual leaf area in biparental population was explained by leaf width compared to that by leaf length (Wei et al2016 ;Yang et al 2016a). This contrasts to a study in wheat (Yang et al 2016b) working with biparental population found that leaf width was less variable compared to leaf length. In our diversity panel, we found an even larger importance of leaf width on individual leaf area compared to that of leaf length (85% versus 15% of explained variance).…”

“…Firstly, final leaf width and length are largely uncorrelated in bi‐parental populations (Wei et al ; Yang et al ) resulting in few overlapping QTLs in maize (Tian et al ) and wheat (Yang et al . ). Secondly, leaf elongation and widening occur at different places in the leaf meristematic zone (Maurice et al ; Muller et al ).…”

“…The hypothesis of separate controls for leaf elongation and widening of monocotyledons leaves is supported by several observations. Firstly, final leaf width and length are largely uncorrelated in bi-parental populations (Wei et al 2016;Yang et al 2016a) resulting in few overlapping QTLs in maize (Tian et al 2011) and wheat (Yang et al 2016b). Secondly, leaf elongation and widening occur at different places in the leaf meristematic zone (Maurice et al 1997;Muller et al 2007).…”

Identification of additive and epistatic effects QTLs for seed oil content in soybean based on an integrating map of two RIL populations

“…Epistasis, or the interaction of a pair of loci may play an important role in the genetic of complex quantitative traits [18,52]. If epistasis is ignored, many individual loci could not be detected, which will weaken the detection power of QTL [53].…”