The Landscapes of Gluten Regulatory Network in Elite Wheat Cultivars Contrasting in Gluten Strength

• Published in: International journal of molecular sciences 2023-05, Vol.24 (11), p.9447
• Main Authors: Liu, Jiajun, Li, Dongsheng, Zhu, Peng, Qiu, Shi, Yao, Kebing, Zhuang, Yiqing, Chen, Chen, Liu, Guanqing, Wen, Mingxing, Guo, Rui, Yao, Weicheng, Deng, Yao, Shen, Xueyi, Li, Tao
• Format: Article
• Language: English
• Subjects: Alternative splicing; Annotations; Chromosomes; Cultivars; DNA binding proteins; Edible Grain - genetics; Flour; full-length sequencing; gene set enrichment analysis (GSEA); Genes; Gluten; Glutens - genetics; Glutens - metabolism; Grain; grain quality; Heat shock proteins; Isoforms; Molecular weight; multiscale embedded gene coexpression network analysis (MEGENA); Network analysis; Nitrogen; Nitrogen - metabolism; Plant Breeding; Post-translation; Sedimentation & deposition; Transcription factors; Transcriptomes; Triticum - genetics; Triticum - metabolism; weighted gene coexpression network analysis (WGCNA); Wheat
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms24119447

Yangmai-13 (YM13) is a wheat cultivar with weak gluten fractions. In contrast, Zhenmai-168 (ZM168) is an elite wheat cultivar known for its strong gluten fractions and has been widely used in a number of breeding programs. However, the genetic mechanisms underlying the gluten signatures of ZM168 remain largely unclear. To address this, we combined RNA-seq and PacBio full-length sequencing technology to unveil the potential mechanisms of ZM168 grain quality. A total of 44,709 transcripts were identified in Y13N (YM13 treated with nitrogen) and 51,942 transcripts in Z168N (ZM168 treated with nitrogen), including 28,016 and 28,626 novel isoforms in Y13N and Z168N, respectively. Five hundred and eighty-four differential alternative splicing (AS) events and 491 long noncoding RNAs (lncRNAs) were discovered. Incorporating the sodium-dodecyl-sulfate (SDS) sedimentation volume (SSV) trait, both weighted gene coexpression network analysis (WGCNA) and multiscale embedded gene coexpression network analysis (MEGENA) were employed for network construction and prediction of key drivers. Fifteen new candidates have emerged in association with SSV, including 4 transcription factors (TFs) and 11 transcripts that partake in the post-translational modification pathway. The transcriptome atlas provides new perspectives on wheat grain quality and would be beneficial for developing promising strategies for breeding programs.