Dataset Information

Solexa / Illumina deep sequencing of the hippocampal transcriptome of wild-type and DLCK transgenic mice

ABSTRACT: The hippocampal expression profiles of wild-type mice and mice transgenic for deltaC-doublecortin-like kinase were compared with Solexa/Illumina deep sequencing technology and five different microarray platforms. With Illumina's digital gene expression assay, we obtained approximately 2.4 million sequence tags per sample, their abundance spanning four orders of magnitude. Results were highly reproducible, even across laboratories. With a dedicated Bayesian model, we found differential expression of 3179 transcripts with an estimated false-discovery rate of 8.5%. This is a much higher figure than found for microarrays. The overlap in differentially expressed transcripts found with deep sequencing and microarrays was most significant for Affymetrix. The changes in expression observed by deep sequencing were larger than observed by microarrays or quantitative PCR. Relevant processes such as calmodulin-dependent protein kinase activity and vesicle transport along microtubules were found affected by deep sequencing but not by microarrays. While undetectable by microarrays, antisense transcription was found for 51% of all genes and alternative polyadenylation for 47%. We conclude that deep sequencing provides a major advance in robustness, comparability and richness of expression profiling data and is expected to boost collaborative, comparative and integrative genomics studies. Keywords: SAGE, 17mer, NlaIII, mRNA expression, transgenic mice

ORGANISM(S): Mus musculus

PROVIDER: GSE10782 | GEO | 2008/10/17

SECONDARY ACCESSION(S): PRJNA107467

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Sensitivity and throughput of transcriptomics and proteomomics technologies have advanced tremendously in recent years. With the use of deep sequencing of RNA samples (RNAseq) and mass spectrometry technology for protein identification and quantitation, it is now feasible to compare gene and protein expression on a massive scale and on any organism for which genomic data is available. Although these technologies are currently applied to many research questions in various model systems ranging from cell cultures to the entire organism level, there are few comparative studies of these technologies in the same system, let alone on the same samples. Here we present a comparison between gene and protein expression in zebrafish embryos, which is an upcoming model in disease studies. We compared Agilent custom made expression microarrays with Illumina deep sequencing for RNA analysis, showing as expected a high degree of correlation of expression of a common set of 15,927 genes. Gene expression was also found to correlate with the abundance of 1,017 quantified proteins, with several categories of genes as exceptions. These exceptions include ribosomal proteins, histones and vitellogenins, for which biological and technical explanations are discussed. By comparing state of the art transcriptomic and proteomic technologies on samples derived from the same group of organisms we have for the first time benchmarked the differences in these technologies with regard to sensitivity and bias towards detection of particular gene categories. Our datasets submitted to public repositories are a good starting point for researchers interested in disease progression in zebrafish at a stage of development highly suited for high throughput screening technologies. The transcriptomics data is deposited in NCBI GEO. Proteomics informatics: Spectra were identified by Mascot and validated by PeptideProphet and ProteinProphet in the Trans-Proteomic Pipeline (TPP). The main search parameters are: full tryptic specificity, precursor mass searched within -0.5 to +2.5 Da, product ions within [-0.5,0.5] Da and allowing for one missed cleavage. Carbamidomethylation was assumed as the only and fixed PTM.

Dataset Information

Solexa / Illumina deep sequencing of the hippocampal transcriptome of wild-type and DLCK transgenic mice

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets