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Novel Insights Into Genetic Responses for Waterlogging Stress in Two Local Wheat Cultivars in Yangtze River Basin

FRONTIERS IN GENETICS(2021)

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Abstract
Wheat (Triticum aestivum L.), the most widely cultivated crop, is affected by waterlogging that limited the wheat production. Given the incompleteness of its genome annotation, PacBio SMRT plus Illumina short-read sequencing strategy provided an efficient approach to investigate the genetic regulation of waterlogging stress in wheat. A total of 947,505 full-length non-chimetric (FLNC) sequences were obtained with two wheat cultivars (XM55 and YM158) with PacBio sequencing. Of these, 5,309 long-non-coding RNAs, 1,574 fusion genes and 739 transcription factors were identified with the FLNC sequences. These full-length transcripts were derived from 49,368 genes, including 47.28% of the genes annotated in IWGSC RefSeq v1.0 and 40.86% genes encoded two or more isoforms, while 27.31% genes in the genome annotation of IWGSC RefSeq v1.0 were multiple-exon genes encoding two or more isoforms. Meanwhile, the individuals with waterlogging treatments (WL) and control group (CK) were selected for Illumina sequencing. Totally, 6,829 differentially expressed genes (DEGs) were detected from four pairwise comparisons. Notably, 942 DEGs were overlapped in the two comparisons (i.e., XM55-WL vs. YM158-WL and YM158-WL vs. YM158-CK). Undoubtedly, the genes involved in photosynthesis were downregulated after waterlogging treatment in two cultivars. Notably, the genes related to steroid biosynthesis, steroid hormone biosynthesis, and downstream plant hormone signal transduction were significantly upregulated after the waterlogging treatment, and the YM158 variety revealed different genetic regulation patterns compared with XM55. The findings provided valuable insights into unveiling regulation mechanisms of waterlogging stress in wheat at anthesis and contributed to molecular selective breeding of new wheat cultivars in future.
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Key words
wheat,waterlogging,transcripts,gene regulation,cultivar
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