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Title: Genome-level analysis of genetic regulation of liver gene expression networks

Abstract

Liver is the primary site for metabolism of nutrients, drugs and chemical agents. While metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variation in gene expression levels, introduces complexity into research on liver disease. This study aimed to dissect genetic networks that control liver gene expression by combining largescale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive SNP, haplotype and phenotypic data is publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. This data was used to map quantitative trait loci (QTLs) responsible for variation in expression of about 19,000 transcripts. We identified polymorphic cis- and trans-acting loci, including several loci that control expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. The data is available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of co-regulated transcripts and correlated phenotypes, cross-tissue and -species comparisons, as well as testing of a broad array of hypotheses.

Authors:
 [1];  [1];  [2];  [3];  [1];  [4];  [4];  [5];  [4];  [4];  [6];  [6];  [1];  [1]
  1. University of North Carolina, Chapel Hill
  2. ORNL
  3. Oak Ridge National Laboratory (ORNL)
  4. University of Tennessee Health Science Center, Memphis
  5. University of Memphis
  6. University of Tennessee, Knoxville (UTK)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
930884
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Journal Article
Resource Relation:
Journal Name: Hepatology; Journal Volume: 46; Journal Issue: 2
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; BIOLOGICAL PATHWAYS; GENES; GENETIC MAPPING; GENETICS; LIVER; METABOLISM; MICE; MINING; NUTRIENTS; OLIGONUCLEOTIDES; REGULATIONS; STRAINS; TESTING; eQTL; microarray; liver; mouse; genetical genomics

Citation Formats

Gatti, Daniel, Maki, Akira, Chesler, Elissa J, Kirova, Roumyana, Kosyk, Oksana, Lu, Lu, Manly, Kenneth, Matthews, Douglas B., Qu, Yanhua, Williams, Robert, Perkins, Andy, Langston, Michael A, Threadgill, David, and Rusyn, Ivan. Genome-level analysis of genetic regulation of liver gene expression networks. United States: N. p., 2007. Web. doi:10.1002/hep.21682.
Gatti, Daniel, Maki, Akira, Chesler, Elissa J, Kirova, Roumyana, Kosyk, Oksana, Lu, Lu, Manly, Kenneth, Matthews, Douglas B., Qu, Yanhua, Williams, Robert, Perkins, Andy, Langston, Michael A, Threadgill, David, & Rusyn, Ivan. Genome-level analysis of genetic regulation of liver gene expression networks. United States. doi:10.1002/hep.21682.
Gatti, Daniel, Maki, Akira, Chesler, Elissa J, Kirova, Roumyana, Kosyk, Oksana, Lu, Lu, Manly, Kenneth, Matthews, Douglas B., Qu, Yanhua, Williams, Robert, Perkins, Andy, Langston, Michael A, Threadgill, David, and Rusyn, Ivan. Mon . "Genome-level analysis of genetic regulation of liver gene expression networks". United States. doi:10.1002/hep.21682.
@article{osti_930884,
title = {Genome-level analysis of genetic regulation of liver gene expression networks},
author = {Gatti, Daniel and Maki, Akira and Chesler, Elissa J and Kirova, Roumyana and Kosyk, Oksana and Lu, Lu and Manly, Kenneth and Matthews, Douglas B. and Qu, Yanhua and Williams, Robert and Perkins, Andy and Langston, Michael A and Threadgill, David and Rusyn, Ivan},
abstractNote = {Liver is the primary site for metabolism of nutrients, drugs and chemical agents. While metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variation in gene expression levels, introduces complexity into research on liver disease. This study aimed to dissect genetic networks that control liver gene expression by combining largescale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive SNP, haplotype and phenotypic data is publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. This data was used to map quantitative trait loci (QTLs) responsible for variation in expression of about 19,000 transcripts. We identified polymorphic cis- and trans-acting loci, including several loci that control expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. The data is available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of co-regulated transcripts and correlated phenotypes, cross-tissue and -species comparisons, as well as testing of a broad array of hypotheses.},
doi = {10.1002/hep.21682},
journal = {Hepatology},
number = 2,
volume = 46,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}
  • Here, while a few studies on the variations in mRNA expression and half-lives measured under different growth conditions have been used to predict patterns of regulation in bacterial organisms, the extent to which this information can also play a role in defining metabolic phenotypes has yet to be examined systematically. Here we present the first comprehensive study for a model methanogen. As a result, we use expression and half-life data for the methanogen Methanosarcina acetivorans growing on fast- and slow-growth substrates to examine the regulation of its genes. Unlike Escherichia coli where only small shifts in half-lives were observed, wemore » found that most mRNA have significantly longer half-lives for slow growth on acetate compared to fast growth on methanol or trimethylamine. Interestingly, half-life shifts are not uniform across functional classes of enzymes, suggesting the existence of a selective stabilization mechanism for mRNAs. Using the transcriptomics data we determined whether transcription or degradation rate controls the change in transcript abundance. Degradation was found to control abundance for about half of the metabolic genes underscoring its role in regulating metabolism. Genes involved in half of the metabolic reactions were found to be differentially expressed among the substrates suggesting the existence of drastically different metabolic phenotypes that extend beyond just the methanogenesis pathways. By integrating expression data with an updated metabolic model of the organism (iST807) significant differences in pathway flux and production of metabolites were predicted for the three growth substrates. In conclusion, this study provides the first global picture of differential expression and half-lives for a class II methanogen, as well as provides the first evidence in a single organism that drastic genome-wide shifts in RNA half-lives can be modulated by growth substrate. We determined which genes in each metabolic pathway control the flux and classified them as regulated by transcription (e.g. transcription factor) or degradation (e.g. post-transcriptional modification). We found that more than half of genes in metabolism were controlled by degradation. Our results suggest that M. acetivorans employs extensive post-transcriptional regulation to optimize key metabolic steps, and more generally that degradation could play a much greater role in optimizing an organism’s metabolism than previously thought.« less
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