Literature DB >> 32975230

High-throughput sequencing reveals the molecular mechanisms determining the stay-green characteristic in soybeans.

Cheng Wang1, L E Gao, Run Zhi Li, Y E Wang, Yang Ying Liu, Xin Zhang, Hao Xie.   

Abstract

Senescence is an internally systematized degeneration process leading to death in plants. Leaf yellowing, one of the most prominent features of plant aging may lead to reduced crop yields. The molecular mechanism of responses to senescence in soybean leaves is not completely clear. In our research, two soybean varieties were selected with different stay-green traits: stay-green variety (BN106) and non-stay-green variety (KF14). RNA samples extracted from the leaves of two varieties were sequenced and compared using high-throughput sequencing. Six key enzyme genes in chlorophyll degradation pathways were studied to analyze the changes in their expression at seedling, flowering and maturation stage. Meanwhile, the construction of the genetic transformation process had been constructed to identify the function of putative gene by RNA-interference. A total of 4329 DEGs were involved in 52 functional groups and 254 KEGG pathways. Twelve genes encoding senescence-associated and inducible chloroplast stay-green protein showed significant differential expression. MDCase and PAO have a significant expression in BN106 that may be the key factors affecting the maintenance of green characteristics. In addition, the function of GmSGRs has been identified by genetic transformation. The loss of GmSGRs may cause soybean seeds to change from yellow to green. In summary, our results revealed fundamental information about the molecular mechanism of aging in soybeans with different stay-green characteristics. The work of genetic transformation lays a foundation for putative gene function studies that could contribute to postpone aging in soybeans.

Entities:  

Mesh:

Substances:

Year:  2020        PMID: 32975230

Source DB:  PubMed          Journal:  J Biosci        ISSN: 0250-5991            Impact factor:   1.826


  1 in total

1.  Uncovering Novel Genomic Regions and Candidate Genes for Senescence-Related Traits by Genome-Wide Association Studies in Upland Cotton (Gossypium hirsutum L.).

Authors:  Qibao Liu; Libei Li; Zhen Feng; Shuxun Yu
Journal:  Front Plant Sci       Date:  2022-01-05       Impact factor: 5.753

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.