ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2015
Genetic architecture of maize kernel row number and whole genome prediction.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- Genetic architecture of seed protein composition in grain amaranth (Frontiers in nutrition · 2026Article
- Integrated genomic analysis of a diverse maize population reveals novel genes and superior predictive models for ear diameter.BMC genomics · 2025Article
- Decades' progress and prospects on maize functional genomics and molecular breeding.Science China. Life sciences · 2025Review
- Article
- Identification of yield-related QTLs and their applications using DH population in maize.BMC genomics · 2025Article
- Genetic dissection of hundred-kernel weight through combined genome-wide association study and linkage analysis in tropical maize.BMC genomics · 2025Article
- Genome-wide association studies and genomic selection for leaf-related traits in maize.Frontiers in plant science · 2025Article
- Comparative transcriptome analysis identified candidate genes associated with kernel row number in maize.PeerJ · 2025Article
- Dissecting the genetic architecture of yield-related traits by QTL mapping in maize.Frontiers in plant science · 2025Article
- Combined Genome-Wide Association Study and Linkage Analysis for Mining Candidate Genes for the Kernel Row Number in Maize (Plants (Basel, Switzerland) · 2024Article
- Identification and segregation of two closely linked major QTLs for kernel row number in advanced maize-teosinte populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Mining of Oil Content Genes in Recombinant Maize Inbred Lines with Introgression from Temperate and Tropical Germplasm.International journal of molecular sciences · 2024Article
- Genome-Wide Association Studies on the Kernel Row Number in a Multi-Parent Maize Population.International journal of molecular sciences · 2024Article
- Profiling the selected hotspots for ear traits in two maize-teosinte populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genome-Wide Association Study and Prediction of Tassel Weight of Tropical Maize Germplasm in Multi-Parent Population.International journal of molecular sciences · 2024Article
- Genome-Wide Association Study for Maize Hybrid Performance in a Typical Breeder Population.International journal of molecular sciences · 2024Article
- GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize.Plants (Basel, Switzerland) · 2023Article
- Article
- Identification of Candidate QTLs and Genes for Ear Diameter by Multi-Parent Population in Maize.Genes · 2023Article
- Multivariate Interaction Analysis ofPlants (Basel, Switzerland) · 2023Article
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10 authors.
Funding
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Abstract
key messageMaize kernel row number might be dominated by a set of large additive or partially dominant loci and several small dominant loci and can be accurately predicted by fewer than 300 top KRN-associated SNPs. Kernel row number (KRN) is an important yield component in maize and directly affects grain yield. In this study, we combined linkage and association mapping to uncover the genetic architecture of maize KRN and to evaluate the phenotypic predictability using these detected loci. A genome-wide association study 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 quantitative trait loci (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. Furthermore, the 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. The results suggest that the KRN-associated loci and QTLs that were detected in this study show great potential for improving the KRN with genomic selection in maize breeding.
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