Identification and Fine-Mapping of a Major Maize Leaf Width QTL in a Re-sequenced Large Recombinant Inbred Lines Population

Abstract

Leaf width (LW) influences canopy architecture of population-cultured maize and can thus contribute to density breeding. In previous studies, almost all maize LW-related mutants have extreme effect on leaf development or accompanied unfavorable phenotypes. In addition, the identification of quantitative trait loci (QTLs) has been resolution-limited, with cloning and fine-mapping rarely performed. Here, we constructed a bin map for 670 recombinant inbred lines (RILs) using ∼1.2 billion 100-bp re-sequencing reads. QTL analysis of the LW trait directly narrowed the major effect QTL, qLW4, to a ∼270-kb interval. A fine-mapping population and near-isogenic lines (NILs) were quickly constructed using a key RIL harboring heterozygous genotypes across the qLW4 region. A recombinant-derived progeny testing strategy was subsequently used to further fine-map qLW4 to a 55-kb interval. Examination of NILs revealed that qLW4 has a completely dominant effect on LW, with no additional effect on leaf length. Candidate gene analysis suggested that this locus may be a novel LW controlling allele in maize. Our findings demonstrate the advantage of large-population high-density bin mapping, and suggest a strategy for efficiently fine-mapping or even cloning of QTLs. These results should also be helpful for further dissection of the genetic mechanism of LW variation, and benefit maize density breeding.

Identification of QTLs for grain yield and other traits in tropical maize under Striga infestation

“…In the present study, a linkage map was constructed corresponding to the 10 chromosomes of the maize genome using 1,386 markers, spanning 2076 cM in length. The length of the linkage map constructed in this study was shorter than those reported by Ramekar et al [ 26 ], Wang et al [ 28 ], and Ertiro et al [ 60 ] but longer than those reported by Samayoa et al [ 61 ], Zhao et al [ 62 ] and Badu-Apraku et al [ 39 ]. The differences between our findings and those of earlier researchers could be attributed to the number of markers used and the type and size of the mapping populations.…”

“…During the past few years, the recent advances in molecular marker technologies have facilitated the construction of high-density genetic linkage maps and detection of novel QTL associated with quantitative traits in segregating populations and the characterization of the map positions in the genome of crop plants [ 26 – 28 ]. In maize, studies on QTL identification for complex traits have focused mainly on abiotic stresses such as drought [ 29 – 31 ] and low soil nitrogen [ 32 , 33 ] and good progress has been made.…”

Genetic mapping of folate QTLs using a segregated population in maize

“…Those traits have a highly polygenic genetic architecture that is mainly controlled by many small effect QTLs (Mickelson et al ; Peiffer et al ; Raihan et al ; Xu et al ). Parental phenotypic and genetic distances are positively associated with the effects and numbers of QTLs yielded (Pan et al ), and major‐effect QTLs can be more easily mapped to a higher resolution (Wang et al ). In our case, the phenotypic variation contribution rates were 26.7% ( q5‐F‐THFa ) and 14.9% ( q5‐F‐THFb ), respectively, reflecting that both are major‐effect QTLs.…”

“…The LOD threshold for QTL defining was calculated by 1,000 times permutations ( P < 0.05) for each trait. The confidence intervals were estimated using the 1.5 LOD‐drop method (Wang et al ).…”

Genetic Dissection of Germinability under Low Temperature by Building a Resequencing Linkage Map in japonica Rice

“…Advances in genome-wide sequencing technology have provided an effective method to detect DNA sequencing differences among closely related rice materials and to ensure the presence of sufficient markers for a genetic mapping analysis. A genotype calling method for RILs that utilizes resequencing data was developed [19], which determined the construction of resequencing bin maps and accelerated genetics-based studies for many crops, including cereals [19][20][21][22][23][24][25][26][27]. Based on the above discussions, many important advances have been achieved in the study of rice cold stress, but we still need to use high-throughput sequencing technology to mine further cold-tolerance genes from japonica rice, especially cold tolerance genes at the germination stage for breeding practice.…”