Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of yeast to analyse mRNAs regulated by the nonsense-mediated and 5 to 3 mRNA Decay Pathways

ABSTRACT: Genome-wide analysis of mRNAs regulated by the nonsense-mediated and 5' to 3' mRNA Decay Pathways in Yeast

ORGANISM(S): Saccharomyces cerevisiae

SUBMITTER: Phyllis Spatrick

PROVIDER: E-MEXP-26 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genome-wide analysis of mRNAs regulated by the nonsense-mediated and 5' to 3' mRNA decay pathways in yeast.

He Feng F Li Xiangrui X Spatrick Phyllis P Casillo Ryan R Dong Shuyun S Jacobson Allan A

Molecular cell 20031201 6

Transcripts regulated by the yeast nonsense-mediated and 5' to 3' mRNA decay pathways were identified by expression profiling of wild-type, upf1Delta, nmd2Delta, upf3Delta, dcp1Delta, and xrn1Delta cells. This analysis revealed that inactivation of Upf1p, Nmd2p, or Upf3p has identical effects on global RNA accumulation; inactivation of Dcp1p or Xrn1p exhibits both common and unique effects on global RNA accumulation but causes upregulation of only a small fraction of transcripts; and the majorit ...[more]

PMID: 14690598

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Project description:Recent discovery reveals HFD insult can cause insulin resistance very rapidly, but the underlying mechanism is still not well understood. We performed a short term experiment in a Diet Induced Insulin resistance mouse model. Objective: Insulin resistance (IR) is one of the earliest predictors of type 2 diabetes. However, diagnosis of IR is limited. High fat fed mouse models provide key insights into IR. We hypothesized that early features of IR are associated with persistent changes in gene expression (GE) and endeavoured to (a) develop novel methods for improving signal:noise in analysis of human GE using mouse models; (b) identify a GE motif that accurately diagnoses IR in humans; and (c) identify novel biology associated with IR in humans. Methods: We integrated human muscle GE data with longitudinal mouse GE data and developed an unbiased three-level cross-species analysis platform (single-gene, gene-set and networks) to generate a gene expression motif (GEM) indicative of IR. A logistic regression classification model validated GEM in 3 independent human datasets (n =115). Results: This GEM of 93 genes substantially improved diagnosis of IR compared to routine clinical measures across multiple independent datasets. Individuals misclassified by GEM possessed other metabolic features raising the possibility that they represent a separate metabolic subclass. The GEM was enriched in pathways previously implicated in insulin action and revealed novel associations between Î²-catenin and Jak1 and IR. Functional analyses using small molecule inhibitors showed an important role for these proteins in insulin action. Conclusions: This study shows that systems approaches for identifying molecular signatures provides a powerful way to stratify individuals into discrete metabolic groups. Moreover, we speculate that the Î²-catenin pathway may represent a novel biomarker for IR in humans that warrant future investigation. Comparison of gene expression in muscle tissue during High Fat Diet (HFD) time course (day 5 and day 42). Chow diet will serve as control for HFD. 4 samples per group serve as experimental replicates.

Dataset Information

Transcription profiling of yeast to analyse mRNAs regulated by the nonsense-mediated and 5 to 3 mRNA Decay Pathways

Publications

Genome-wide analysis of mRNAs regulated by the nonsense-mediated and 5' to 3' mRNA decay pathways in yeast.

Similar Datasets

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