Analysis of the genetic architecture of maize kernel size traits by combined linkage and association mapping

Abstract

SummaryKernel size‐related traits are the most direct traits correlating with grain yield. The genetic basis of three kernel traits of maize, kernel length (KL), kernel width (KW) and kernel thickness (KT), was investigated in an association panel and a biparental population. A total of 21 single nucleotide polymorphisms (SNPs) were detected to be most significantly (P < 2.25 × 10−6) associated with these three traits in the association panel under four environments. Furthermore, 50 quantitative trait loci (QTL) controlling these traits were detected in seven environments in the intermated B73 × Mo17 (IBM) Syn10 doubled haploid (DH) population, of which eight were repetitively identified in at least three environments. Combining the two mapping populations revealed that 56 SNPs (P < 1 × 10−3) fell within 18 of the QTL confidence intervals. According to the top significant SNPs, stable‐effect SNPs and the co‐localized SNPs by association analysis and linkage mapping, a total of 73 candidate genes were identified, regulating seed development. Additionally, seven miRNAs were found to situate within the linkage disequilibrium (LD) regions of the co‐localized SNPs, of which zma‐miR164e was demonstrated to cleave the mRNAs of Arabidopsis CUC1,CUC2 and NAC6 in vitro. Overexpression of zma‐miR164e resulted in the down‐regulation of these genes above and the failure of seed formation in Arabidopsis pods, with the increased branch number. These findings provide insights into the mechanism of seed development and the improvement of molecular marker‐assisted selection (MAS) for high‐yield breeding in maize.

Large‐scale GWAS in sorghum reveals common genetic control of grain size among cereals

“…A significant overlap between the QTL identified in this study and grain size SNPs identified in rice (Huang et al , ) was observed, with 60% of the rice grain size SNPs identified within a 1‐cM window of the sorghum QTL identified in this study ( P ‐value < 0.05, chi‐square test), and with 80% of the rice grain size SNPs identified within 5 cM (Table S13). A similar trend was found when comparing with kernel size SNPs identified in maize (Liu et al , ), with 26% and 70% of maize kernel size SNPs identified within 1‐cM and 5‐cM window of sorghum QTL identified in this study (Table S13).…”

“…Sorghum shares close ancestry with maize and rice, with orthologous genes from these species commonly sharing the same function (Bolot et al , ; Paterson et al , ; Zhang et al , ). A significant association was found between the locations of the QTL in this study and GWAS signals for grain size in rice (Huang et al , ) and maize (Liu et al , ), and orthologous of cloned grain size genes from rice and maize. Both findings strongly support a common genetic architecture underlying this trait across these cereals.…”

Large-scale GWAS in sorghum reveals common genetic control of grain size among cereals

“…A significant overlap between the QTL identified in this study and grain size SNPs identified 338 in rice (Huang et al, 2012) was observed, with 60% of the rice grain size SNPs identified 339 within a 1cM window of the sorghum QTL identified in this study (p-value<0.05, χ 2 test), 340 and with 85% of the rice grain size SNPs identified within 5 cM (Table S13). A similar trend 341 was found when comparing with kernel size SNPs identified in maize (Liu et al, 2019), with 342 30% and 70% of maize kernel size SNPs identified within 1 cM and 5 cM window of 343 sorghum QTL identified in this study (Table S13).…”

“…Sorghum shares close ancestry with maize and rice, with orthologous genes from these 495 species commonly sharing the same function (Bolot et al, 2009;Paterson et al, 1995). A 496 significant association was found between the locations of the QTL in this study and GWAS 497 signals for grain size in rice (Huang et al, 2012) and maize (Liu et al, 2019), and 498 orthologous of cloned grain size genes from rice and maize. Both findings strongly support a 499 common genetic architecture underlying this trait across these cereals.…”

Genome‐wide association studies and QTL mapping uncover the genetic architecture of ear tip‐barrenness in maize

“…Genome‐wide association study (GWAS) is a powerful tool to dissect the genetic architecture of complex traits (Korte and Farlow ), overcome the limitations of QTL and narrow down the candidate regions (Han et al ). To date, GWAS was widely used to analyze a number of agronomic traits in maize, such as seedling root‐related traits (Pace et al ), stalk strength (Peiffer et al ), leaf architecture (Tian et al ), stalk cell wall components (Li et al ), plant and ear height (Li et al ), stalk lodging‐related traits (Zhang et al ), embryonic callus regenerative capacity (Ma et al ) and maize kernel size (Liu et al ). However, GWAS has not been applied to detect the associations with the length of ETB because of the hysteretic study on maize ETB.…”