Characterization of the Regulatory Network under Waterlogging Stress in Soybean Roots via Transcriptome Analysis
Yo-Han Yoo,
Seung-Yeon Cho,
Inhye Lee,
Namgeol Kim,
Seuk-Ki Lee,
Kwang-Soo Cho,
Eun Young Kim,
Ki-Hong Jung,
Woo-Jong Hong
Affiliations
Yo-Han Yoo
Central Area Crop Breeding Division, Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration, Suwon 16429, Republic of Korea
Seung-Yeon Cho
Department of Smart Farm Science, Kyung Hee University, Yongin 17104, Republic of Korea
Inhye Lee
Central Area Crop Breeding Division, Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration, Suwon 16429, Republic of Korea
Namgeol Kim
Central Area Crop Breeding Division, Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration, Suwon 16429, Republic of Korea
Seuk-Ki Lee
Central Area Crop Breeding Division, Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration, Suwon 16429, Republic of Korea
Kwang-Soo Cho
Central Area Crop Breeding Division, Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration, Suwon 16429, Republic of Korea
Eun Young Kim
Department of Smart Farm Science, Kyung Hee University, Yongin 17104, Republic of Korea
Ki-Hong Jung
Graduate School of Green Bio-Science & Crop Biotech Institute, Kyung Hee University, Yongin 17104, Republic of Korea
Woo-Jong Hong
Department of Smart Farm Science, Kyung Hee University, Yongin 17104, Republic of Korea
Flooding stress caused by climate change is a serious threat to crop productivity. To enhance our understanding of flooding stress in soybean, we analyzed the transcriptome of the roots of soybean plants after waterlogging treatment for 10 days at the V2 growth stage. Through RNA sequencing analysis, 870 upregulated and 1129 downregulated differentially expressed genes (DEGs) were identified and characterized using Gene Ontology (GO) and MapMan software (version 3.6.0RC1). In the functional classification analysis, “alcohol biosynthetic process” was the most significantly enriched GO term in downregulated DEGs, and phytohormone-related genes such as ABA, cytokinin, and gibberellin were upregulated. Among the transcription factors (TFs) in DEGs, AP2/ERFs were the most abundant. Furthermore, our DEGs encompassed eight soybean orthologs from Arabidopsis and rice, such as 1-aminocyclopropane-1-carboxylate oxidase. Along with a co-functional network consisting of the TF and orthologs, the expression changes of those genes were tested in a waterlogging-resistant cultivar, PI567343. These findings contribute to the identification of candidate genes for waterlogging tolerance in soybean, which can enhance our understanding of waterlogging tolerance.