数字农科院2.0

Genome-wide association mapping and candidate genes analysis of high-throughput image descriptors for wheat frost tolerance

文献类型: 外文期刊

作者: Rui Yu;Yixue Liu;Meng Yuan;Pingtao Jiang;Jiwen Zhao;Chuanliang Zhang;Xiaowan Xu;Qilin Wang;Yuze Wang;Tiantian Chen;Jingrui Ou;Yihang Luo;Haitao Dong;Zhensheng Kang;Qingdong Zeng;Yusheng Zhao;Shouyang Liu;Baofeng Su;Dejun Han;Jianhui Wu

作者机构:

关键词: Frost;GS (genomic selection);GWAS (genome-wide association study);Image;Wheat

期刊名称: Stress Biology

ISSN:

年卷期: 2025 年 5 卷 1 期

页码:

收录情况: CSCD(2025-2026年度) ; ; ESCI(2025版)

摘要: Repeated occurrences of extreme weather events, such as low temperatures, due to global warming present a serious risk to the safety of wheat production. Quantitative assessment of frost damage can facilitate the analysis of key genetic factors related to wheat tolerance to abiotic stress. We collected 491 wheat accessions and selected four image-based descriptors (BLUE band, RED band, NDVI, and GNDVI) to quantitatively assess their frost damage. Image descriptors can complement the visual estimation of frost damage. Combined with genome-wide association study (GWAS), a total of 107 quantitative trait loci (QTL) (r2 ranging from 0.75% to 9.48%) were identified, including the well-known frost-resistant locus Frost Resistance (FR)-A1/ Vernalization (VRN)-A1. Additionally, through quantitative gene expression data and mutation experience verification experiments, we identified two other frost tolerance candidate genes TraesCS2A03G1077800 and TraesCS5B03G1008500. Furthermore, when combined with genomic selection (GS), image-based descriptors can predict frost damage with high accuracy (r ≤ 0.84). In conclusion, our research confirms the accuracy of image-based high-throughput acquisition of frost damage, thereby supplementing the exploration of the genetic structure of frost tolerance in wheat within complex field environments.

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