Genome-wide identification and characterization of the soybean SOD family during alkaline stress.

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2020
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Abstract
Superoxide dismutase (SOD) proteins, as one kind of the antioxidant enzymes, play critical roles in plant response to various environment stresses. Even though its functions in the oxidative stress were very well characterized, the roles of family genes in regulating alkaline stress response are not fully reported.We identified the potential family members by using Hidden Markov model and soybean genome database. The neighbor-joining phylogenetic tree and exon-intron structures were generated by using software MEGA 5.0 and GSDS online server, respectively. Furthermore, the conserved motifs were analyzed by MEME online server. The syntenic analysis was conducted using Circos-0.69. Additionally, the expression levels of soybean genes under alkaline stress were identified by qRT-PCR.In this study, we identified 13 potential genes in soybean genome. Phylogenetic analysis suggested that genes could be classified into three subfamilies, including MnSODs (), FeSODs () and Cu/ZnSODs (). We further investigated the gene structure, chromosomal locations and gene-duplication, conserved domains and promoter -elements of the soybean genes. We also explored the expression profiles of soybean genes in different tissues and alkaline, salt and cold stresses, based on the transcriptome data. In addition, we detected their expression patterns in roots and leaves by qRT-PCR under alkaline stress, and found that different subfamily genes may play different roles in response to alkaline stress. These results also confirmed the hypothesis that the great evolutionary divergence may contribute to the potential functional diversity in soybean genes. Taken together, we established a foundation for further functional characterization of soybean genes in response to alkaline stress in the future.
Reference Key
lu2020genomewidepeerj Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lu, Wenxiu;Duanmu, Huizi;Qiao, Yanhua;Jin, Xiaoxia;Yu, Yang;Yu, Lijie;Chen, Chao;
Journal PeerJ
Year 2020
DOI
10.7717/peerj.8457
URL
Keywords

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