ArticleFrontiers in plant science2021
Multi-Locus Genome-Wide Association Study and Genomic Selection of Kernel Moisture Content at the Harvest Stage in Maize.
Article in Frontiers in plant science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed, 13 citations in OpenAlex.
- Screening Key Genes for Salt Tolerance in Maize Inbred Lines via Time-Series Transcriptomics and Machine Learning.Plants (Basel, Switzerland) · 2026Article
- Exploring the polygenic landscape of wool traits in Turkish merinos through multi-locus GWAS approaches: Karacabey Merino.BMC veterinary research · 2025Article
- Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and agronomic traits under drought and optimum conditions in maize.BMC plant biology · 2025Article
- Genome-wide association analysis and genomic selection for leaf-related traits of maize.PloS one · 2025Article
- Maize heat shock proteins-prospection, validation, categorization and in silico analysis of the different ZmHSP families.Stress biology · 2023Article
- Multi-trait and multi-environment genomic prediction for flowering traits in maize: a deep learning approach.Frontiers in plant science · 2023Article
- Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies.Journal of experimental botany · 2022Article
- Multi-Trait Genomic Prediction Models Enhance the Predictive Ability of Grain Trace Elements in Rice.Frontiers in genetics · 2022Article
- Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Frontiers in plant science · 2022Article
Corrections and comments
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11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kernel moisture content at the harvest stage (KMC) is an important trait that affects the mechanical harvesting of maize grain, and the identification of genetic loci for KMC is beneficial for maize molecular breeding. In this study, we performed a multi-locus genome-wide association study (ML-GWAS) to identify quantitative trait nucleotides (QTNs) for KMC using an association mapping panel of 251 maize inbred lines that were genotyped with an Affymetrix CGMB56K SNP Array and phenotypically evaluated in three environments. Ninety-eight QTNs for KMC were detected using six ML-GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, PLARmEB, PKWmEB, and ISIS EM-BLASSO). Eleven of these QTNs were considered to be stable, as they were detected by at least four ML-GWAS models under a uniformed environment or in at least two environments and BLUP using the same ML-GWAS model. With
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