Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Expression profiling of F2 progenies from C57BL/6J x DBA/2J

ABSTRACT: Expression profiling of a cohort of mice was derived from a standard F2 intercross using two standard inbred strains, C57BL/6J and DBA/2J. In this study, we selected 127 male animals that had been raised on a standard rodent chow diet (Purina Chow from Ralston-Purina Co., St. Louis, MO) for eight weeks and then switched to a high fat diet for sixteen additional weeks. At 20 weeks of age, the mice were euthanized and liver tissues were collected and flash frozen in liquid nitrogen and stored at -80 degrees C prior to RNA isolation. All procedures of housing and treatment of animals were performed in accordance with IACUC regulations. RNA preparation and array hybridizations were performed at Rosetta Inpharmatics. The custom ink-jet microarrays were manufactured by Agilent Technologies (Palo Alto, CA). A custom array was designed for this study and consisted of 39,280 non-control oligonuceotides extracted from the mouse Unigene clusters and combined with RefSeq sequences and RIKEN full-length cDNA clones. Arrays were quantified on the basis of spot intensity relative to background, adjusted for experimental variation between arrays using average intensity over multiple channels, and fitted to a previously described error model to determine significance (type I error).

ORGANISM(S): Mus musculus

SUBMITTER: Wan-Lin Su

PROVIDER: E-GEOD-16886 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques.

Su Wan-Lin WL Kleinhanz Robert R RR Schadt Eric E EE

Molecular systems biology 20110501

Integrative genomics and genetics approaches have proven to be a useful tool in elucidating the complex relationships often found in gene regulatory networks. More importantly, a number of studies have provided the necessary experimental evidence confirming the validity of the causal relationships inferred using such an approach. By integrating messenger RNA (mRNA) expression data with microRNA (miRNA) (i.e. small non-coding RNA with well-established regulatory roles in a myriad of biological pr ...[more]

PMID: 21613979

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Project description:The remarkable success observed in using genome-wide association (GWA) mapping in human cohorts to identify multiple genes linked to a wide number of traits related to complex diseases has renewed interest in applying genome-wide association mapping techniques to model organisms such as inbred laboratory mice. However, unlike humans, the limited genetic diversity present in the ancestry of laboratory mice combined with intense selection pressure over the past decades have yielded an intricate population structure within the genomes of laboratory mouse that could potentially complicate the results obtained from such a study. We sought to empirically assess the viability of genome-wide association studies in inbred mice using hundreds of expression traits where the true location of the eQTL is known a priori. Using data from a previously published experimental mouse cross (C57BL/6J x C3H/HeJ), we selected over a thousand of the strongest cis-acting expression QTLs and measured transcript abundance levels of the associated expression traits in 16 classical and 3 wild-derived inbred strains. We next perform a genome-wide association scan demonstrating the low statistical power of such studies and show empirically the large extent to which high allelic association gives rise to spurious associations. Moreover, we provide evidence illustrating that in a large fraction of cases, the marker with the most significant p-values fails to map to the location of the true eQTL; hence, as a result, selecting the most significant marker may lead to spurious findings. Finally, we demonstrate that combining linkage analysis with association mapping provides significant increases in statistical power over a stand-alone GWA study as well as significantly higher mapping resolution than either study alone. RNA preparation and array hybridizations were performed at Rosetta Inpharmatics. The custom ink-jet microarrays were manufactured by Agilent Technologies (Palo Alto, CA). A custom array was designed for this study and consisted of 39,280 non-control oligonuceotides extracted from the mouse Unigene clusters and combined with RefSeq sequences and RIKEN full-length cDNA clones. Mouse liver tissues were homogenized and total RNA extracted using Trizol reagent (Invitrogen, CA) according to manufacturer’s protocol. Three µg of total RNA was reverse transcribed and labeled with either Cy3 or Cy5 fluorochrome. Labeled complementary RNA (cRNA) from each animal was hybridized against a cross-specific pool of labeled cRNAs constructed from equal aliquots of RNA from representative animals for each strain. The hybridizations were performed in fluor reversal for 24 hours in a hybridization chamber, washed, and scanned using a confocal laser scanner. Arrays were quantified on the basis of spot intensity relative to background, adjusted for experimental variation between arrays using average intensity over multiple channels, and fitted to a previously described error model to determine significance23 (type I error).

Project description:71 liver RNA samples from three mouse strains - DBA/2J, C57BL/6J and C3H/HeJ - were profiled using a custom-designed microarray monitoring exon and exon-junction expression of 1,020 genes representing 9,406 exons. Gene expression was calculated via two different methods, using the 3'-most exon probe ("3' gene expression profiling") and using all probes associated with the gene ("whole-transcript gene expression profiling"), while exon expression was determined using exon probes and flanking junction probes that spanned across the neighboring exons("exon expression profiling"). Widespread strain and sex influences were detected using a two-way Analysis of Variance (ANOVA) regardless of the profiling method used. However, over 90% of the genes identified in 3' gene expression profiling or whole transcript profiling were identified in exon profiling, along with 75% and 38% more genes, respectively, showing evidence of differential isoform expression. Overall, 55% and 32% of genes, respectively, exhibited strain- and sex-bias differential gene or exon expression. Keywords: Grouped Hybridization material was generated through a random-priming amplification of poly[A]+ purified RNA using primers with a random sequence at the 3' end and a fixed motif at the 5' end that was optimized to generate strand-specific cDNA copies of full-length mRNA transcripts [32]. Since the region used for exon and junction probe selection is constrained to a smaller region, more probes contain sequence with suboptimal characteristics (e.g. high GC content or higher homology to other genes). The hybridization of cDNA, rather than cRNA as commonly done, partially mitigates this issue due to higher specificity and lower background levels [24]. Hybridization conditions were as previously described [33]. All 71 samples were hybridized in a two-channel experiment, where one channel was a common reference, generated by pooling all 71 samples in equal mass. Array hybridizations were done in duplicate with fluor reversal to systematically correct for Cy3/Cy5 dye bias. Array images were processed as described to obtain background noise, single channel intensity and associated measurement error estimates [34]. Expression changes between samples and pool were quantified as mean log10(expression ratio), and associated error.

Project description:To map the genetics of gene expression in metabolically relevant tissues and investigate the diversity of expression SNPs (eSNPs) in multiple tissues from the same individual, we collected four tissues from approximately 1,000 patients undergoing Roux-en-y gastric bypass and clinical traits associated with their weight loss and co-morbidities. We then performed high-throughput genotyping and gene expression profiling and carried out a genome-wide association analyses for more than one hundred thousand gene expression traits representing four metabolically relevant tissues; liver, omental adipose, subcutaneous adipose and stomach. We successfully identified 24,531 eSNPs corresponding to ~10,000 distinct genes. This represents the greatest number of eSNPs identified to our knowledge by any study to date and the first study to identify eSNPs from stomach tissue. We then demonstrate how these eSNPs provide a high quality disease map for each tissue in morbidly obese patients to not only inform genetic associations indentified in this cohort, but in previously published genome wide association studies as well. eSNPs and gene co-expression modules identification in morbidly obese patients represent a great resource that will aid in elucidating the key networks associated with morbid obesity, response to RYGB and disease as a whole. Keywords: Tissue profiling in a human cohort. Liver tissue was collected from patients at the time of RYGB surgery at Massachusetts General Hospital between 2000 and 2007. Samples were collected in RNAlater (Ambion/Applied Biosystems), stored at -80° and shipped to Rosetta Inpharmatics Gene Expression Laboratory Seattle, WA for extraction, amplification, labeling, and microarray processing. Samples processed ranged in size from 100-200mg. Total RNA extracted from liver was converted to fluorescently labeled cRNA that was hybridized to custom 44K DNA oligonucleotide microarrays manufactured by Agilent Technologies as described previously (Hughes et al. 2001; Schadt et al. 2008). Successful gene expression profiling results were collected from 651 liver samples.

Project description:To map the genetics of gene expression in metabolically relevant tissues and investigate the diversity of expression SNPs (eSNPs) in multiple tissues from the same individual, we collected four tissues from approximately 1,000 patients undergoing Roux-en-y gastric bypass and clinical traits associated with their weight loss and co-morbidities. We then performed high-throughput genotyping and gene expression profiling and carried out a genome-wide association analyses for more than one hundred thousand gene expression traits representing four metabolically relevant tissues; liver, subcutaneous adipose, omental adipose and stomach. We successfully identified 24,531 eSNPs corresponding to ~10,000 distinct genes. This represents the greatest number of eSNPs identified to our knowledge by any study to date and the first study to identify eSNPs from stomach tissue. We then demonstrate how these eSNPs provide a high quality disease map for each tissue in morbidly obese patients to not only inform genetic associations indentified in this cohort, but in previously published genome wide association studies as well. eSNPs and gene co-expression modules identification in morbidly obese patients represent a great resource that will aid in elucidating the key networks associated with morbid obesity, response to RYGB and disease as a whole. Keywords: Tissue profiling in a human cohort. Subcutaneous adipose tissue was collected from patients at the time of RYGB surgery at Massachusetts General Hospital between 2000 and 2007. Samples were collected in RNAlater (Ambion/Applied Biosystems), stored at -80° and shipped to Rosetta Inpharmatics Gene Expression Laboratory Seattle, WA for extraction, amplification, labeling, and microarray processing. Samples processed ranged in size from 100-200mg. Total RNA extracted from subcutaneous adipose was converted to fluorescently labeled cRNA that was hybridized to custom 44K DNA oligonucleotide microarrays manufactured by Agilent Technologies as described previously (Hughes et al. 2001; Schadt et al. 2008). Successful gene expression profiling results were collected from 701 subcutaneous adipose samples.

Project description:To map the genetics of gene expression in metabolically relevant tissues and investigate the diversity of expression SNPs (eSNPs) in multiple tissues from the same individual, we collected four tissues from approximately 1,000 patients undergoing Roux-en-y gastric bypass and clinical traits associated with their weight loss and co-morbidities. We then performed high-throughput genotyping and gene expression profiling and carried out a genome-wide association analyses for more than one hundred thousand gene expression traits representing four metabolically relevant tissues; liver, omental adipose, subcutaneous adipose and stomach. We successfully identified 24,531 eSNPs corresponding to ~10,000 distinct genes. This represents the greatest number of eSNPs identified to our knowledge by any study to date and the first study to identify eSNPs from stomach tissue. We then demonstrate how these eSNPs provide a high quality disease map for each tissue in morbidly obese patients to not only inform genetic associations indentified in this cohort, but in previously published genome wide association studies as well. eSNPs and gene co-expression modules identification in morbidly obese patients represent a great resource that will aid in elucidating the key networks associated with morbid obesity, response to RYGB and disease as a whole. Keywords: Tissue profiling in a human cohort. Omental adipose tissue was collected from patients at the time of RYGB surgery at Massachusetts General Hospital between 2000 and 2007. Samples were collected in RNAlater (Ambion/Applied Biosystems), stored at -80° and shipped to Rosetta Inpharmatics Gene Expression Laboratory Seattle, WA for extraction, amplification, labeling, and microarray processing. Samples processed ranged in size from 100-200mg. Total RNA extracted from omental adipose was converted to fluorescently labeled cRNA that was hybridized to custom 44K DNA oligonucleotide microarrays manufactured by Agilent Technologies as described previously (Hughes et al. 2001; Schadt et al. 2008). Successful gene expression profiling results were collected from 848 omental adipose samples.

Dataset Information

Expression profiling of F2 progenies from C57BL/6J x DBA/2J

Publications

Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques.

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