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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

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.

Details

Title
Characterization of the Regulatory Network under Waterlogging Stress in Soybean Roots via Transcriptome Analysis
Author
Yo-Han Yoo 1 ; Cho, Seung-Yeon 2 ; Lee, Inhye 1   VIAFID ORCID Logo  ; Kim, Namgeol 1   VIAFID ORCID Logo  ; Lee, Seuk-Ki 1 ; Cho, Kwang-Soo 1   VIAFID ORCID Logo  ; Eun Young Kim 2   VIAFID ORCID Logo  ; Ki-Hong, Jung 3   VIAFID ORCID Logo  ; Woo-Jong, Hong 4   VIAFID ORCID Logo 

 Central Area Crop Breeding Division, Department of Central Area Crop Science, National Institute of Crop Science, Rural Development Administration, Suwon 16429, Republic of Korea; [email protected] (Y.-H.Y.); [email protected] (I.L.); [email protected] (N.K.); [email protected] (S.-K.L.); [email protected] (K.-S.C.) 
 Department of Smart Farm Science, Kyung Hee University, Yongin 17104, Republic of Korea; [email protected] (S.-Y.C.); [email protected] (E.Y.K.) 
 Graduate School of Green Bio-Science & Crop Biotech Institute, Kyung Hee University, Yongin 17104, Republic of Korea; [email protected] 
 Department of Smart Farm Science, Kyung Hee University, Yongin 17104, Republic of Korea; [email protected] (S.-Y.C.); [email protected] (E.Y.K.); Graduate School of Green Bio-Science & Crop Biotech Institute, Kyung Hee University, Yongin 17104, Republic of Korea; [email protected] 
First page
2538
Publication year
2024
Publication date
2024
Publisher
MDPI AG
e-ISSN
22237747
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3110667562
Copyright
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.