Dissect Genetic Architecture Of Maize Kernel Row Number & Clone And Functional Analysis Of The Major QTL KRN4

Kernel row number(KRN) is an important yield component in maize and directly affects grain yield. As a selection target during the domestication and improvement of maize, KRN is controlled by quantitative trait locus(QTL).The formation of maize KRN is a key stage of maize inflorescence development, and KRN is affected by the genes involved in the inflorescence development. In this study, we combined linkage and association mapping by three linkage population and an association panel with 513 diverse inbreed lines to uncover the genetic architecture of maize KRN, and to evaluate the phenotypic predictability using these detected loci and the influence of population structure in genomic prediction. We focused on a major effect KRN QTL KRN4 detected by GWAS and linkage mapping, and fine mapped the QTL to investigate the causal polymorphisms of KRN4. We also employed expression analysis, association analysis, molecular evolutionary analysis to interpret the regulation model and evolutionary pattern of KRN4. The major achievement of this study is as following:1. A genome-wide association study(GWAS) revealed 31 associated single nucleotide polymorphisms(SNPs) representing 17 genomic loci with an effect in at least one of five individual environments and the best linear unbiased prediction(BLUP)over all environments. Linkage mapping in three F2:3 populations identified 33 KRN QTLs representing 21 QTLs common to several population / environments. The majority of these common QTLs that displayed a large effect were additive or partially dominant. We found 70% KRN-associated genomic loci were mapped in KRN QTLs identified in this study, KRN-associated SNP hotspots detected in NAM population and /or previous identified KRN QTL hotspots.2. KRN of inbred lines and hybrids could be predicted by the additive effect of the SNPs,which was estimated using inbred lines as a training set. The prediction accuracy using the top KRN-associated tag SNPs was obviously higher than that of the randomly selected SNPs, and approximately 300 top KRN-associated tag SNPs were sufficient for predicting the KRN of the inbred lines and hybrids.3. We fine-mapped a major KRN QTL, KRN4, which can enhance grain productivity by increasing KRN per ear without changing weight per kernel.We found that a ~3-Kb intergenic region about 60 Kb downstream from the SBP-box gene Unbranched3(UB3)was responsible for quantitative variation in KRN by regulating the level of expression of the UB3 gene. The biological function of UB3 was identified by UB3::Mu mutant analysis and expression analysis. The results demonstrated that UB3 is a negative regulator of KRN and tassel branches.4. A novel polymorphism, the 1.2-Kb presence-absence variant or 1.2-Kb PAV, was found to be strongly associated with quantitative variation in KRN in diverse maize inbred lines, and we suggest that this 1.2 Kb transposon-containing insertion is responsible for increased KRN. The previously identified A/G SNP(S35, also known as Ser220Asn) in UB3 was also found to be significantly associated with KRN in our association-mapping panel. Although no visible genetic effect of S35 alone could be detected in our linkage mapping population, S35 was found to genetically interact with 1.2-Kb PAV to modulate KRN.5. The 1.2-Kb PAV was under strong selection during maize domestication and the favorable allele for 1.2-Kb PAV has been significantly enriched in modern maize germplasms. However, S35 was a mutation that arose during modern maize improvement. The favourable haplotype(Hap1) of 1.2-Kb-PAV-S35 was selected during temperate maize improvement, but is still rare in tropical and subtropical maize germplasms.KRN-associated loci and QTLs that were detected in this study show great potential for improving the KRN with genomic selection in maize breeding.The dissection of the KRN4 locus also improves our understanding of the genetic basis of quantitative variation in complex traits in maize.