Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome
Stay-green syndrome (SGS) is an important factor that causes soybean (<i>Glycine max</i>) yield reduction. Despite progress being made, the regulatory mechanism remains largely unclear. Therefore, in this study, an SGS-sensitive soybean variety, “HD0702”, was employed to investigate the...
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MDPI AG
2024-12-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/15/1/82 |
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| author | Dagang Wang Yanan Wang Ruidong Sun Yong Yang Wei Zhao Guoyi Yu Yueying Wang Feng Wang Lin Zhou Zhiping Huang |
| author_facet | Dagang Wang Yanan Wang Ruidong Sun Yong Yang Wei Zhao Guoyi Yu Yueying Wang Feng Wang Lin Zhou Zhiping Huang |
| author_sort | Dagang Wang |
| collection | DOAJ |
| description | Stay-green syndrome (SGS) is an important factor that causes soybean (<i>Glycine max</i>) yield reduction. Despite progress being made, the regulatory mechanism remains largely unclear. Therefore, in this study, an SGS-sensitive soybean variety, “HD0702”, was employed to investigate the underlying mechanism. Transcriptomic analyses were performed in a tissue-specific manner to investigate differentially expressed genes (DEGs) in soybeans impacted by SGS and in those without SGS. A total of 1858 DEGs were identified in the pods, and 2814 DEGs were identified in the leaves. Further investigation revealed that SGS mainly affected the expression levels of key genes involved in the regulation of photosynthesis, starch and sucrose metabolism, and plant hormone signal transduction. To support this finding, the chlorophyll content of the pods was to be found increased by 320% for chlorophyll <i>a</i> and 260% for chlorophyll <i>b</i>. In leaves, soluble sugar levels significantly increased, whereas phytohormones IAA and ABA decreased in SGS pods. DEGs were classified using gene ontology (GO) terms, and photosynthesis-related genes <i>α-glucosidase</i>, <i>β-mannosidase</i>, <i>β-amylase 5</i> (<i>GmBAM5</i>), and <i>starch synthase 2</i> (<i>GmSS2</i>) were up-regulated. This study demonstrates a molecular and physiological basis for SGS that merits further investigation to allow for SGS management. |
| format | Article |
| id | doaj-art-763b6537a87f47e5b1e71833d44cdf13 |
| institution | Kabale University |
| issn | 2073-4395 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Agronomy |
| spelling | doaj-art-763b6537a87f47e5b1e71833d44cdf132025-01-24T13:16:39ZengMDPI AGAgronomy2073-43952024-12-011518210.3390/agronomy15010082Transcriptomics and Physiological Analyses of Soybean Stay-Green SyndromeDagang Wang0Yanan Wang1Ruidong Sun2Yong Yang3Wei Zhao4Guoyi Yu5Yueying Wang6Feng Wang7Lin Zhou8Zhiping Huang9Crop Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaCrop Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaCrop Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaCrop Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaInstitute of Plant Protection and Agro-Products Safety, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaAnhui Longkang Farm of Land-Reclamation, Bengbu 233426, ChinaSoybean Research Institute, Suzhou Academy of Agricultural Sciences, Suzhou 234000, ChinaAgricultural Technology Promotion Center of Jieshou, Jieshou 230065, ChinaAgricultural Technology Promotion Center of Jieshou, Jieshou 230065, ChinaCrop Research Institute, Anhui Academy of Agricultural Sciences, Hefei 230031, ChinaStay-green syndrome (SGS) is an important factor that causes soybean (<i>Glycine max</i>) yield reduction. Despite progress being made, the regulatory mechanism remains largely unclear. Therefore, in this study, an SGS-sensitive soybean variety, “HD0702”, was employed to investigate the underlying mechanism. Transcriptomic analyses were performed in a tissue-specific manner to investigate differentially expressed genes (DEGs) in soybeans impacted by SGS and in those without SGS. A total of 1858 DEGs were identified in the pods, and 2814 DEGs were identified in the leaves. Further investigation revealed that SGS mainly affected the expression levels of key genes involved in the regulation of photosynthesis, starch and sucrose metabolism, and plant hormone signal transduction. To support this finding, the chlorophyll content of the pods was to be found increased by 320% for chlorophyll <i>a</i> and 260% for chlorophyll <i>b</i>. In leaves, soluble sugar levels significantly increased, whereas phytohormones IAA and ABA decreased in SGS pods. DEGs were classified using gene ontology (GO) terms, and photosynthesis-related genes <i>α-glucosidase</i>, <i>β-mannosidase</i>, <i>β-amylase 5</i> (<i>GmBAM5</i>), and <i>starch synthase 2</i> (<i>GmSS2</i>) were up-regulated. This study demonstrates a molecular and physiological basis for SGS that merits further investigation to allow for SGS management.https://www.mdpi.com/2073-4395/15/1/82soybeanstay-green syndromeRNA-seqregulation pathway |
| spellingShingle | Dagang Wang Yanan Wang Ruidong Sun Yong Yang Wei Zhao Guoyi Yu Yueying Wang Feng Wang Lin Zhou Zhiping Huang Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome Agronomy soybean stay-green syndrome RNA-seq regulation pathway |
| title | Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome |
| title_full | Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome |
| title_fullStr | Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome |
| title_full_unstemmed | Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome |
| title_short | Transcriptomics and Physiological Analyses of Soybean Stay-Green Syndrome |
| title_sort | transcriptomics and physiological analyses of soybean stay green syndrome |
| topic | soybean stay-green syndrome RNA-seq regulation pathway |
| url | https://www.mdpi.com/2073-4395/15/1/82 |
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