Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Platform Comparison Study

ABSTRACT: Microarray technology is a powerful tool able to measure RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross platform meta-analysis studies rapidly increase, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we notice that none of the previously published papers consider differences between labs. For this paper, a consortium of ten labs from the DC and Baltimore area was formed to compare three heavily used platforms using identical RNA samples. Each lab was given identical RNA samples (A1 and B1) which were processed according to what each lab considered best practice. Five of the labs used Affymetrix GeneChips, three used two-color spotted cDNA arrays, and two used two-color long oligo arrays. Samples 1 and 2 represent unique mixtures of total RNA from four knockout cell lines: PEX1, PEX6, PEX7, and PEX12. Each of the four cell lines is deficient for one of four PEX genes (required for peroxisome biogenesis/mutations cause peroxisome biogenesis disorders). Appropriate statistical analysis demonstrates that relatively large differences exist between labs using the same platform, but that the results from the best performing labs agree rather well. Keywords: other

ORGANISM(S): Homo sapiens

SUBMITTER: Rafael Irizarry

PROVIDER: E-GEOD-2521 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Multiple-laboratory comparison of microarray platforms.

Irizarry Rafael A RA Warren Daniel D Spencer Forrest F Kim Irene F IF Biswal Shyam S Frank Bryan C BC Gabrielson Edward E Garcia Joe G N JG Geoghegan Joel J Germino Gregory G Griffin Constance C Hilmer Sara C SC Hoffman Eric E Jedlicka Anne E AE Kawasaki Ernest E Martínez-Murillo Francisco F Morsberger Laura L Lee Hannah H Petersen David D Quackenbush John J Scott Alan A Wilson Michael M Yang Yanqin Y Ye Shui Qing SQ Yu Wayne W

Nature methods 20050421 5

Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over t ...[more]

PMID: 15846361

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Project description:Peroxisome biogenesis diseases (PBDs) are characterized by global defects in peroxisomal function and can result in severe brain, liver, kidney, and bone malfunctions. PBDs are due to mutations in peroxisome biogenesis factors (PEX genes) that are responsible for peroxisome assembly and function. Increasing evidence suggests that peroxisome import functions decline during aging. However, the transcriptome profiling of peroxisome import defects and how they affect disease development are still lacking. PEX5 encodes the cytoplasmic receptors for peroxisome-targeting signal types 1. We generate knock-in human HEK293 cells mutant using CRISPR to transiently express PEX5 cysteine 11 to alanine mutant (PEX5C11A), which blocks PEX5 recycling and exerts dominant negative effect on PEX5 mediated peroxisome import. To identify conserved responses, we perform transcriptomic analysis on Drosophila oenocyte-specific Pex1, Pex12 and Pex5 knockdowns and on human cells with impaired peroxisome import (through expressing PEX5C11A and applying PEX5 siRNA respectively). PEX5C11A induction triggers vast transcriptomic changes, including decreased oxidative phosphorylation, increased MAPK signaling and HIPPO signaling. PEX5 siRNA specifically decreases spliceosome activity and increases cholesterol metabolism. Using gene set enrichment analysis (GSEA), we identify protein processing in endoplasmic reticulum pathway, specifically ER-associated protein degradation (ERAD) pathway is induced in all PEX knockdowns in Drosophila. Peroxisome dysfunction elevates eIF2α phosphorylation in both Drosophila and human cell culture independent of XBP1 activation, suggesting increased integrative stress response (ISR). Moreover, peroxisome stress decreases ribosome biogenesis genes and impairs ribosome biogenesis in flies and human cells. Specifically, peroxisome stress impairs the 5'-ETS cleavage activity during the ribosome biogenesis and dampens 40S small ribosomal export in both flies and human. Our results suggest that reduced ribosome biogenesis and elevated ISR could be conserved cellular response to peroxisome import stress.

Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf

Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition, artificial DNA For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf

Dataset Information

Platform Comparison Study

Publications

Multiple-laboratory comparison of microarray platforms.

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