AUTHOR=Wu Jiuyun , Zhang Fuchun , Liu Guohong , Abudureheman Riziwangguli , Bai Shijian , Wu Xinyu , Zhang Chuan , Ma Yaning , Wang Xiping , Zha Qian , Zhong Haixia TITLE=Transcriptome and coexpression network analysis reveals properties and candidate genes associated with grape (Vitis vinifera L.) heat tolerance JOURNAL=Frontiers in Plant Science VOLUME=14 YEAR=2023 URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2023.1270933 DOI=10.3389/fpls.2023.1270933 ISSN=1664-462X ABSTRACT=
Temperature is one of the most important environmental factors affecting grape season growth and geographical distribution. With global warming and the increasing occurrence of extreme high-temperature weather, the impact of high temperatures on grape production has intensified. Therefore, identifying the molecular regulatory networks and key genes involved in grape heat tolerance is crucial for improving the resistance of grapes and promoting sustainable development in grape production. In this study, we observed the phenotypes and cellular structures of four grape varieties, namely, Thompson Seedless (TS), Brilliant Seedless (BS), Jumeigui (JMG), and Shine Muscat (SM), in the naturally high-temperature environment of Turpan. Heat tolerance evaluations were conducted. RNA-seq was performed on 36 samples of the four varieties under three temperature conditions (28°C, 35°C, and 42°C). Through differential expression analysis revealed the fewest differentially expressed genes (DEGs) between the heat-tolerant materials BS and JMG, and the DEGs common to 1890 were identified among the four varieties. The number of differentially expressed genes within the materials was similar, with a total of 3767 common DEGs identified among the four varieties. KEGG enrichment analysis revealed that fatty acid metabolism, starch and sucrose metabolism, plant hormone signal transduction, the MAPK signaling pathway, and plant-pathogen interactions were enriched in both between different temperatures of the same material, and between different materials of the same temperature. We also conducted statistical and expression pattern analyses of differentially expressed transcription factors. Based on Weighted correlation network analysis (WGCNA), four specific modules highly correlated with grape heat tolerance were identified by constructing coexpression networks. By calculating the connectivity of genes within the modules and expression analysis, six candidate genes (