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Chinese Agricultural Science Bulletin ›› 2023, Vol. 39 ›› Issue (9): 106-114.doi: 10.11924/j.issn.1000-6850.casb2022-0335

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Information Mining of SNP Sites in the Leaf Transcriptome of Sunflower Drought-resistant Inbred Lines

WEN Yujie1(), ZHAO Yajie2, ZHU Kongyan1, ZHAO Rong1, WANG Meng1, QIAO Yimin3, BAO Haizhu1(), GAO Julin1()   

  1. 1 College of Agriculture, Inner Mongolia Agricultural University, Hohhot 010019
    2 Inner Mongolia Academy of Agriculture and Animal Husbandry, Hohhot 010031
    3 Inner Mongolia Hangjinhou Banner Yimin Seed Co., LTD., Hangjinhou Banner, Inner Mongolia 015400
  • Received:2022-05-07 Revised:2022-08-15 Online:2023-03-25 Published:2023-03-23

Abstract:

In order to explore the transcriptome SNP markers in response to drought stress in sunflower, with the sunflower drought resistant inbred line 17062 as the experimental material, RNA-seq technology combined with bioinformatics analysis method was used to statistically analyze SNP markers. The results showed that in SNP type analysis, the conversion rate accounted for 62.82%, and the inversion rate accounted for 37.17%. In the conversion, the frequency of C/T was the highest, which was 31.51%. In the distribution of functional elements, the number of SNP distributed in exons was 178744.3, which was significantly more than that of other functional elements. The sequence annotation of SNP sites found that 76678 SNP genes had GO annotation and 4379 had KEGG annotation. The repeated SNP gene sequences in the Top30 GO annotation ranking (Top30) differential genes (DEGs) were screened, and 1542 genes were obtained, of which 650 gene sequences had GO annotation. These differential genes are involved in multiple biological functions and important metabolic pathways, which are of great significance for the development of SNP markers in sunflower transcriptome, the identification of drought resistant germplasm resources, and the selection of drought resistant “three-line” hybrids.

Key words: sunflower (Helianthus annuus L.), drought stress, leaf, SNP