Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

SAGE tags generated from Triticum aestivum cultivars Scorpion 25 and Xi19 grown under normal and hot/dry conditions

ABSTRACT: Triticum aestivum cultivars Scorpion 25 and Xi 19 were grown under both normal and hot/dry conditions. We compared the effect of these two growth conditions on these two closely related varieties. We sequenced two biological replicates each for both Scorpion 25 and Xi19 grown under normal conditions. One library for hot/dry growth conditions was sequenced for each of these two cultivars.

ORGANISM(S): Triticum aestivum

SUBMITTER: Gary Barker

PROVIDER: E-GEOD-12832 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Analysis of wheat SAGE tags reveals evidence for widespread antisense transcription.

Poole Rebecca L RL Barker Gary L A GL Werner Kay K Biggi Gaia F GF Coghill Jane J Gibbings J George JG Berry Simon S Dunwell Jim M JM Edwards Keith J KJ

BMC genomics 20081010

<h4>Background</h4>Serial Analysis of Gene Expression (SAGE) is a powerful tool for genome-wide transcription studies. Unlike microarrays, it has the ability to detect novel forms of RNA such as alternatively spliced and antisense transcripts, without the need for prior knowledge of their existence. One limitation of using SAGE on an organism with a complex genome and lacking detailed sequence information, such as the hexaploid bread wheat Triticum aestivum, is accurate annotation of the tags ge ...[more]

PMID: 18847483

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Project description:Wheat cultivars ‘TAM 111’ and ‘TAM 112’ have been dominantly grown in the Southern U.S. Great Plains for many years due to their excellent, yet variable, drought tolerance. To identify the molecular basis and genetic control of drought tolerance in these two landmark cultivars, RNA-seq analysis was conducted to compare gene expression difference in flag leaves under fully irrigated (wet) and water deficient (dry) conditions. Of the 122,017 gene sequences assembled, 2,254 genes showed significantly altered expression patterns under dry and wet conditions in the two cultivars. TAM 111 had 593 and 1,532 dry-wet differentially expressed genes (DEGs), and TAM 112 had 777 and 1,670 at heading and grain-filling stages, respectively. The two cultivars have 1,214 (53.9%) dry-wet DEGs in common, which agreed with their excellent adaption to drought, but 438 and 602 dry-wet DEGs were respectively shown only in TAM 111 and TAM 112 suggested that each may have a specific mechanism to cope with drought. Annotation of all 2,254 genes with dry-wet expression difference found 1,855 have functions related to biosynthesis, stress responses, defense responses, transcription factors and cellular components related to ion or protein transportation and signal transduction. Comparing hierarchical structure of biological processes, molecule functions and cellular components revealed the significant regulation differences between TAM 111 and TAM 112, particularly for genes of phosphorylation and adenyl ribonucleotide binding, and proteins located in nucleus and plasma membrane. Comparing gene expressions involved in responses to stresses of water deprivation, heat and oxidative, ABA-induced signal pathway and transcription regulation found TAM 112 have more specific dry-wet DEGs than TAM 111 with most of them up-regulated, indicating that TAM 112 is more active than TAM 111 in response to drought. In addition, 399 dry-wet DEGs with unknown functions included 258 genes encoding predicted uncharacterized proteins and 141 unannotated genes with no similar sequences identified in the databases. These may represent novel genes related to drought response in TAM 111 or TAM 112. This research thus revealed different drought-tolerance mechanisms in TAM 111 and TAM 112 and identified useful drought tolerance genes for wheat adaption.

Dataset Information

SAGE tags generated from Triticum aestivum cultivars Scorpion 25 and Xi19 grown under normal and hot/dry conditions

Publications

Analysis of wheat SAGE tags reveals evidence for widespread antisense transcription.

Similar Datasets

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