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Utilization of transcriptome, small RNA, and degradome sequencing to provide insights into drought stress and re-watering treatment in Medicago ruthenica (RNA-seq)

ABSTRACT: Drought is a major limiting factor in foraging grass yield and quality. Medicago ruthenica is a high-quality forage legume with drought resistance, cold tolerance, and strong adaptability. In this study, we integrated transcriptome, small RNA, and degradome sequencing in identifying drought response genes, miRNAs, and key miRNA-target pairs in M. ruthenica under drought and re-watering treatment conditions. A total of 3,905 genes and 50 miRNAs (45 conserved and 5 novel miRNAs) were significantly differentially expressed between the re-watering (RW) vs. drought (DS) comparison and control (CK) groups. The degradome sequencing analysis revealed that 348 miRNAs (37 novel and 311 conserved miRNAs) were identified with 6,912 target transcripts, forming 11,390 miRNA-target pairs in the three libraries. There were 38 differentially expressed targets from 16 miRNAs in DS vs. CK, 31 from 11 miRNAs in DS vs. RW, and 6 from 3 miRNAs in RW vs. CK; 21,18, and 3 miRNA-target gene pairs showed reverse expression patterns in DS vs. CK, DS vs. RW, and RW vs. CK comparison groups, respectively. These findings provide valuable information for further functional characterization of genes and miRNAs in response to abiotic stress, in general, and drought stress in M. ruthenica, and potentially contribute to drought resistance breeding of forage in the future.

ORGANISM(S): Medicago ruthenica

PROVIDER: GSE168920 | GEO | 2021/08/03

REPOSITORIES: GEO

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Project description:Cotton (Gossypium hirsutum L.) is one of the most important cash crops worldwide. In semi-arid/arid regions, drought stress causes growth limitation and decrease of yield. Of all the organs of a plant, fine root is the central part consisting of the root system to contribute to plant water and nutrient taken up. However, the research on the molecular mechanism underlying fine root response to soil drought has not been well understood in cotton. To better characterize the proteomic changes of cotton fine roots under drought stress, 70±5% and 40±5% soil relative water content were designed as control (CK) and drought stress (DS) groups, respectively. Tandem mass tags (TMT) technology was used to determine the proteome profiles in fine roots. The proteomic differences between CK and DS were pairwise compared at 0, 30, and 45 days after drought stress (DAD). A total of 11,628 proteins were identified, of which 10,344 proteins contained quantitative information. According to the morphological, physiological, and biochemical characteristics, 30 and 45 DAD were selected as critical stages for further analysis. Results showed that 118 differentially expressed proteins (DEPs) were up-regulated and 105 down-regulated in DS 30 versus CK 30; 662 DEPs were up-regulated, and 611 were down-regulated in DS 45 versus CK 45. The DEP functions were determined for their classified pathways, mainly associated with carbohydrate metabolism, energy metabolism, fatty acid metabolism, amino acid metabolism, and secondary metabolite biosynthesis. DEPs related to phytohormone and stress/defense response were also identified. To verify the accuracy of the TMT results, 20 DEPs were randomly selected for parallel reaction monitoring (PRM) verification. And results showed that the quantitative results of TMT are consistent with those of PRM, which proved that the TMT results of this study are reliable. In this article we describe changes in the protein profiles occurring in response to drought stress in cotton fine roots. Proteomic analyses of plant responses to stressors could lead to the introduction of cotton cultivars with high resistance to drought stress. Such plants would be valuable for high yielding under drought as well as other unfavorable environmental conditions.

Dataset Information

Utilization of transcriptome, small RNA, and degradome sequencing to provide insights into drought stress and re-watering treatment in Medicago ruthenica (RNA-seq)

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