Genome-wide association analysis of wheat quality traits in Qinghai Province

As an important cereal crop in the world, quality research is crucial for wheat. It is necessary to further explore the quality genes of wheat and cultivate high-quality wheat to meet market demand. A green, environmentally friendly, high-speed and accurate near-infrared spectroscopy was used to determine wheat quality. Seven quality-related traits, including grain protein content, volume weight, wet gluten content, stability time, development time, grain hardness, and sedimentation value, were detected in 299 wheat samples from the Qinghai Province under six environments. Genome-wide association analysis was performed using 120 K SNP array data. Research has shown that various quality traits exhibit widespread variation in six environments, with the largest variation in sedimentation values ranging from 24.7% to 40.58%. The heritability of each trait is concentrated between 0.71 and 0.95. The results of genome-wide association analysis showed that there were 44 significantly stable loci (P < 0.001) detected, which was distributed on 17 wheat chromosomes, with a contribution rate of 3.86% -10.54%. A total of 44 significantly associated stable SNP loci and 8 multi-effect loci were obtained, and 15 candidate genes that may be related to wheat grain quality were obtained, mainly related to wheat growth and development, carbohydrate transformation and stress response. This study provides a theoretical basis for wheat quality improvement and new variety breeding.

Authors

Institutions

Publication Details

Journal
BMC Plant Biology
Published
2026-01-05
DOI
https://doi.org/10.1186/s12870-025-07990-w
Primary Topic
Wheat and Barley Genetics and Pathology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genome-wide association analysis of wheat quality traits in Qinghai Province

Z. Zhang, Wanwei HOU, Xiaojuan Zhang, Xin Wang
BMC Plant Biology
Wheat and Barley Genetics and Pathology
article

Genome-wide association analysis of wheat quality traits in Qinghai Province

Z. Zhang, Wanwei HOU, Xiaojuan Zhang, Xin Wang
article en

Abstract

As an important cereal crop in the world, quality research is crucial for wheat. It is necessary to further explore the quality genes of wheat and cultivate high-quality wheat to meet market demand. A green, environmentally friendly, high-speed and accurate near-infrared spectroscopy was used to determine wheat quality. Seven quality-related traits, including grain protein content, volume weight, wet gluten content, stability time, development time, grain hardness, and sedimentation value, were detected in 299 wheat samples from the Qinghai Province under six environments. Genome-wide association analysis was performed using 120 K SNP array data. Research has shown that various quality traits exhibit widespread variation in six environments, with the largest variation in sedimentation values ranging from 24.7% to 40.58%. The heritability of each trait is concentrated between 0.71 and 0.95. The results of genome-wide association analysis showed that there were 44 significantly stable loci (P < 0.001) detected, which was distributed on 17 wheat chromosomes, with a contribution rate of 3.86% -10.54%. A total of 44 significantly associated stable SNP loci and 8 multi-effect loci were obtained, and 15 candidate genes that may be related to wheat grain quality were obtained, mainly related to wheat growth and development, carbohydrate transformation and stress response. This study provides a theoretical basis for wheat quality improvement and new variety breeding.

BMC Plant BiologyVol. 26(1)
Qinghai University (CN), Qinghai University for Nationalities (CN)
Openalex Percentile: Top 97%
Wheat and Barley Genetics and Pathology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.