ArticleBMC genomics2022
Identification of two new QTLs of maize (Zea mays L.) underlying kernel row number using the HNAU-NAM1 population.
Article in BMC genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 10 citations in OpenAlex.
- A Breeding-Informed Regulatory Screen Identifies ZmSPL19 as a Negative Regulator of Nitrogen-Sufficient Growth in Maize (Plants (Basel, Switzerland) · 2026Article
- Genetic Dissection of Shelling Percentage in Maize via QTL Mapping Using a Maize-Teosinte Population.Genes · 2026Article
- Article
- Towards smart agriculture: AI-driven prediction of key genes for revolutionizing crop breeding.Planta · 2025Review
- Identification of key candidate genes regulating hundred-grain weight in the maize inbred line Ye107 from Southern China.Plant cell reports · 2025Article
- Identification of yield-related QTLs and their applications using DH population in maize.BMC genomics · 2025Article
- Comparative transcriptome analysis identified candidate genes associated with kernel row number in maize.PeerJ · 2025Article
- Combined Genome-Wide Association Study and Linkage Analysis for Mining Candidate Genes for the Kernel Row Number in Maize (Plants (Basel, Switzerland) · 2024Article
- Genome-Wide Association Studies on the Kernel Row Number in a Multi-Parent Maize Population.International journal of molecular sciences · 2024Article
- Genome-wide association study of agronomic traits related to nitrogen use efficiency in Henan wheat.BMC genomics · 2024Article
- GWAS and Meta-QTL Analysis of Yield-Related Ear Traits in Maize.Plants (Basel, Switzerland) · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundMaize kernel row number (KRN) is one of the most important yield traits and has changed greatly during maize domestication and selection. Elucidating the genetic basis of KRN will be helpful to improve grain yield in maize.
resultsHere, we measured KRN in four environments using a nested association mapping (NAM) population named HNAU-NAM1 with 1,617 recombinant inbred lines (RILs) that were derived from 12 maize inbred lines with a common parent, GEMS41. Then, five consensus quantitative trait loci (QTLs) distributing on four chromosomes were identified in at least three environments along with the best linear unbiased prediction (BLUP) values by the joint linkage mapping (JLM) method. These QTLs were further validated by the separate linkage mapping (SLM) and genome-wide association study (GWAS) methods. Three KRN genes cloned through the QTL assay were found in three of the five consensus QTLs, including qKRN1.1, qKRN2.1 and qKRN4.1. Two new QTLs of KRN, qKRN4.2 and qKRN9.1, were also identified. On the basis of public RNA-seq and genome annotation data, five genes highly expressed in ear tissue were considered candidate genes contributing to KRN.
conclusionsThis study carried out a comprehensive analysis of the genetic architecture of KRN by using a new NAM population under multiple environments. The present results provide solid information for understanding the genetic components underlying KRN and candidate genes in qKRN4.2 and qKRN9.1. Single-nucleotide polymorphisms (SNPs) closely linked to qKRN4.2 and qKRN9.1 could be used to improve inbred yield during molecular breeding in maize.
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