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Transcriptomics analyses of soybean leaf and root samples during water-deficit.

ABSTRACT: Drought being a major challenge for crop productivity and yield affects multigenic and quantitative traits. It is also well documented that water stress shows a cross talk with other abiotic stresses such as high temperature and high light intensities (Tripathi et al., 2013) [1]. In this report, we documented the details of the methods and quality controls used and considered in our time course-based transcriptome profile of soybean plants under water deficit conditions using microarray technology. The findings of this study are recently published by the Rushton lab in BMC Genomics for a comparative study of tobacco and Soybean (Rabara et al., 2015) [2]. The raw microarray data set is deposited in GEO database with accession number GSE49537.

SUBMITTER: Tripathi P

PROVIDER: S-EPMC4583655 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

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Transcriptomics analyses of soybean leaf and root samples during water-deficit.

Tripathi Prateek P Rabara Roel C RC Shen Qingxi J QJ Rushton Paul J PJ

Genomics data 20150604

Drought being a major challenge for crop productivity and yield affects multigenic and quantitative traits. It is also well documented that water stress shows a cross talk with other abiotic stresses such as high temperature and high light intensities (Tripathi et al., 2013) [1]. In this report, we documented the details of the methods and quality controls used and considered in our time course-based transcriptome profile of soybean plants under water deficit conditions using microarray technolo ...[more]

PMID: 26484247

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Project description:BackgroundSince drought can seriously affect plant growth and development and little is known about how the oscillations of gene expression during the drought stress-acclimation response in soybean is affected, we applied Illumina technology to sequence 36 cDNA libraries synthesized from control and drought-stressed soybean plants to verify the dynamic changes in gene expression during a 24-h time course. Cycling variables were measured from the expression data to determine the putative circadian rhythm regulation of gene expression.ResultsWe identified 4866 genes differentially expressed in soybean plants in response to water deficit. Of these genes, 3715 were differentially expressed during the light period, from which approximately 9.55% were observed in both light and darkness. We found 887 genes that were either up- or down-regulated in different periods of the day. Of 54,175 predicted soybean genes, 35.52% exhibited expression oscillations in a 24 h period. This number increased to 39.23% when plants were submitted to water deficit. Major differences in gene expression were observed in the control plants from late day (ZT16) until predawn (ZT20) periods, indicating that gene expression oscillates during the course of 24 h in normal development. Under water deficit, dissimilarity increased in all time-periods, indicating that the applied stress influenced gene expression. Such differences in plants under stress were primarily observed in ZT0 (early morning) to ZT8 (late day) and also from ZT4 to ZT12. Stress-related pathways were triggered in response to water deficit primarily during midday, when more genes were up-regulated compared to early morning. Additionally, genes known to be involved in secondary metabolism and hormone signaling were also expressed in the dark period.ConclusionsGene expression networks can be dynamically shaped to acclimate plant metabolism under environmental stressful conditions. We have identified putative cycling genes that are expressed in soybean leaves under normal developmental conditions and genes whose expression oscillates under conditions of water deficit. These results suggest that time of day, as well as light and temperature oscillations that occur considerably affect the regulation of water deficit stress response in soybean plants.

Dataset Information

Transcriptomics analyses of soybean leaf and root samples during water-deficit.

Publications

Transcriptomics analyses of soybean leaf and root samples during water-deficit.

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