Evidence map›Paper›PMID 42098268›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2026

Mining QTLs and candidate genes in bread wheat associated with kernel hardness through GWAS.

Qinglin Wen, Dezheng Liu, Shan Lu, Xue Wang, Linzhou Huang, Liang Chen, Yin-Gang Hu

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Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Qinglin Wen *State Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
Dezheng Liu *State Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.ORCID http://orcid.org/0009-0006-5711-1512
Shan LuState Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
Xue WangState Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China.
Linzhou HuangState Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China. lzhuang@nwafu.edu.cn.
Liang ChenState Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China. chenliang9117@nwafu.edu.cn.
Yin-Gang HuState Key Laboratory of Crop Stress Resistance and High-Efficiency Production and College of Agronomy, Northwest A&F University, Yangling, Shaanxi, China. huyingang@nwsuaf.edu.cn.

Funding

Natural Science Support Program of XPCC 2023CB009-08Natural Science Support Program of XPCC 2024AB008
6 · The paper itself

Abstract

key message35 candidate quantitative trait loci (QTLs) and 12 key candidate genes have been identified as associated with kernel hardness in wheat. They encode γ-gliadins, Avenin-3, glutenin subunits, β-glucosidase, α-galactosidase, 1,4-α-glucan-branching enzyme. Kernel hardness constitutes a core indicator of wheat quality, reflecting endosperm texture characteristics and playing a decisive role in milling performance. This study employed 189 genetically diverse bread wheat accessions, integrating genome-wide association studies (GWAS) with genomic prediction techniques to elucidate the genetic mechanisms underlying kernel hardness. Kernel hardness index (KHI) exhibited significant phenotypic variation across four environments and best linear unbiased estimation (BLUE) values within the test population. GWAS conducted using wheat 660 K SNP chip genotyping data identified 67 quantitative trait locis (QTLs) consistently associated with KHI in at least two environments (includes BLUE values). Among these, 35 QTLs showed significant KHI differences across environments based on their different haplotypes. Functional annotation of genes within QTL regions identified 12 key candidate genes encoding γ-amylopectin, Avenin-3, glutenin sub-units, β-glucosidase, α-galactosidase, 1,4-α-glucan-branching enzyme, which are presumed to be closely associated with KHI. Genomic prediction using Bayesian ridge regression achieved over 75% accuracy across all three SNP matrices. These findings provide theoretical and technical support for understanding the genetic basis of wheat KHI and for screening innovative wheat germplasm resources with distinct kernel hardness.

Indexed as

Genes, PlantQuantitative Trait LociSeedsTriticumBreadChromosome MappingGenetic Association StudiesGenome-Wide Association StudyGenotypeHardnessPhenotypePolymorphism, Single Nucleotide

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.