Shuping Lang

Jiaxing Academy of Agricultural Sciences, Jiaxing, 314016, Zhejiang, China
Author    Correspondence author
Molecular Plant Breeding, 2025, Vol. 16, No. 1   doi: 10.5376/mpb.2025.16.0009
Received: 13 Jan., 2025    Accepted: 19 Jan., 2025    Published: 26 Feb., 2025

Lang S.P., Ma Y.X., and Yang S., 2025, Research in wheat heat tolerance breeding, Molecular Plant Breeding, 16(1): 82-92 (doi: 10.5376/mpb.2025.16.0009)

With the global warming, heat stress has become one of the primary factors limiting wheat yield and quality. Developing heat-tolerant wheat varieties is crucial for stabilizing wheat production and adapting to climate change. This study summarizes current progress in wheat heat tolerance breeding, analyzing the effectiveness of traditional and modern breeding technologies such as marker-assisted selection (MAS), genomic selection (GS), and gene editing. It also explores the role of omics technologies in improving wheat heat tolerance, in-tegrating case analyses, and proposing future directions to address challenges in wheat heat tolerance breed-ing. The research indicates that the complexity of heat tolerance traits in wheat and their polygenic regulatory nature make it difficult for traditional breeding methods alone to effectively counteract the effects of heat stress. MAS and GS have significantly enhanced breeding efficiency, while gene editing technology provides a new pathway for precise improvement of heat tolerance genes. Additionally, the integrated application of transcriptomics, metabolomics, and proteomics has facilitated a deep understanding of heat tolerance mecha-nisms in wheat, promoting the identification and precise selection of candidate genes. This study provides a systematic reference for wheat heat tolerance breeding, revealing the potential of multi-technology integra-tion in improving heat tolerance and accelerating the development of wheat varieties that can adapt to climate change, thereby offering crucial support for global food security.

Wheat; Heat tolerance; Marker-assisted selection; Genomic selection; Omics integration