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Gene expression profiling in drought tolerant Acala 1517-99 cotton (Gossypium hirsutum L.) under reduced irrigation field conditions

ABSTRACT: Cotton productivity is affected by water deficit and little is known about the molecular basis of drought tolerance in cotton. In this study, microarray analysis was carried out to identify drought responsive genes in functional leaves of the field-grown drought stressed cotton (Gossypium hirsutum L.) Acala 1517-99. The water stress was imposed after withholding irrigation for 9 days in the early squaring stage, which resulted in 10-15% reduction in plant growth compared to the well watered plants. A total of 110 drought responsive genes (0.5% of the total genes represented in the microarray) were identified, 79% (88 genes) of which were down-regulated and 21% (22 genes) were up-regulated by water stress. The responsiveness of 19 selected drought responsive genes was validated by real time PCR. The drought inducible genes were grouped into six functional categories only including stress related (10 genes, 9 of which are heat shock proteins), metabolism (3) and one each for transcription factor, proline biosynthesis and cellular transport. The down-regulated genes were classified into 14 functional categories including metabolism (20 genes), cellular transport (12), stress related (12), and regulation of gene expression (9) and transcription factor (4), signal transduction (7) and 2 genes each for biosynthesis of secondary compounds, cell wall, fatty acids/lipids and chlorophyll, and protein degradation. Most of the genes have been reported in other plants as drought tolerant/responsive and only 21 drought responsive genes (19%) were functionally unknown. The genes identified provides the first glimpse into the molecular basis of drought response in cotton.

ORGANISM(S): Gossypium raimondii Gossypium arboreum Gossypium hirsutum Gossypium barbadense

PROVIDER: GSE18253 | GEO | 2009/09/25

SECONDARY ACCESSION(S): PRJNA119593

REPOSITORIES: GEO

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Project description:Purpose: to screen the candidate genes involved in the peanut drought stress response, we conducted global transcriptome analysis of peanut plants challenged with water deficit and ABA, using the Illumina HiSeq2000 sequencing platform. Methods: a sequences library of Yueyou7 were constructed at first. Then the profile of diffentialy expressed genes (DEGs) under three different treatments (control, water deficit without ABA, and water deficit with ABA) were conducted based on above sequence library. For sequencing library construction, plants were grown under normal conditions, as described previously , Seeds were planted in soil and kep in the greenhouse at temperature of 25-30℃ and water well. Three tissues (leaves, roots, and stems) were collected at three development stages (four-leaf, flowering and podding stages), respectively. Then all of these tissues were mixed to extract the total RNA for sequence library construction. For DEGs study, two-week-old plants were divided into three groups with three independent replication: (1). Water deficit without ABA groups. Plants directly steeped in water containing 30% PEG600 for 30 min in this groups. (2) Water deficit with ABA groups. Plant was subjected to 100 µmol/L ABA for 30 min and then steeped in water containing 30% PEG6000 for 30 min in this groups, (3) Control. Plants steeped in H2O. All treatments were conducted in parallel. After treatments, Total RNA was extracted from 100 mg of plant material, and RNA integrity was checked by gel electrophoresis. Also RNA quality was checked and RNA was quantified using the Agilent 2100 Bioanalyzer (Agilent technologies, Santa Clara, CA) and Nanodrop ND-1000 (Thermo Scientific, Waltham, USA). Results: we generated 4.96×107 raw sequence reads and assembled the high quality reads into 92,390 unique genes. Compared with the control, we found that 621 genes (≥1.5 fold change) responded rapidly to water deficit and 2665 genes (≥1.5 fold change) responded rapidly to ABA. We found 279 genes that overlapped between water deficit and ABA responses, 264 genes that showed the same trend in expression while 15 genes expression that showed opposite trend. Among the identified genes, 257 showed high induction by ABA (>5 fold), and 19 showed high induction by drought (>5 fold). In addition, we identified 100 transcription factor genes among the ABA-inducible genes but only 22 transcription factor genes among the water deficit-inducible genes. Conclusions: we identified genes differentially expressed in the early response to water deficit or ABA. These genes were annotated with GO functional categories for water deficit (33 categories) or ABA (31 categories). We found that only 19 genes were highly induced by water deficit, but 257 genes were highly induced by ABA. Our previous work has examined many of these genes and our future work will reveal their functions and relationships. These data will facilitate functional genomic studies and have established a biotechnological platform for examination of the early drought- and ABA-responsive transcriptome regulatory network in peanut.

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Gene expression profiling in drought tolerant Acala 1517-99 cotton (Gossypium hirsutum L.) under reduced irrigation field conditions

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