Literature DB >> 17542012

Genome-level analysis of genetic regulation of liver gene expression networks.

Daniel Gatti1, Akira Maki, Elissa J Chesler, Roumyana Kirova, Oksana Kosyk, Lu Lu, Kenneth F Manly, Robert W Williams, Andy Perkins, Michael A Langston, David W Threadgill, Ivan Rusyn.   

Abstract

UNLABELLED: The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are 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. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL.
CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.

Entities:  

Mesh:

Year:  2007        PMID: 17542012      PMCID: PMC3518845          DOI: 10.1002/hep.21682

Source DB:  PubMed          Journal:  Hepatology        ISSN: 0270-9139            Impact factor:   17.425


  43 in total

1.  Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.

Authors:  M Ashburner; C A Ball; J A Blake; D Botstein; H Butler; J M Cherry; A P Davis; K Dolinski; S S Dwight; J T Eppig; M A Harris; D P Hill; L Issel-Tarver; A Kasarskis; S Lewis; J C Matese; J E Richardson; M Ringwald; G M Rubin; G Sherlock
Journal:  Nat Genet       Date:  2000-05       Impact factor: 38.330

2.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

Authors:  Yee Hwa Yang; Sandrine Dudoit; Percy Luu; David M Lin; Vivian Peng; John Ngai; Terence P Speed
Journal:  Nucleic Acids Res       Date:  2002-02-15       Impact factor: 16.971

Review 3.  RNA interference.

Authors:  Gregory J Hannon
Journal:  Nature       Date:  2002-07-11       Impact factor: 49.962

4.  Clustering of hepatotoxins based on mechanism of toxicity using gene expression profiles.

Authors:  J F Waring; R A Jolly; R Ciurlionis; P Y Lum; J T Praestgaard; D C Morfitt; B Buratto; C Roberts; E Schadt; R G Ulrich
Journal:  Toxicol Appl Pharmacol       Date:  2001-08-15       Impact factor: 4.219

5.  Genetic dissection of transcriptional regulation in budding yeast.

Authors:  Rachel B Brem; Gaël Yvert; Rebecca Clinton; Leonid Kruglyak
Journal:  Science       Date:  2002-03-28       Impact factor: 47.728

Review 6.  Gene regulation of the serine proteinase inhibitors alpha1-antitrypsin and alpha1-antichymotrypsin.

Authors:  Noor Kalsheker; S Morley; K Morgan
Journal:  Biochem Soc Trans       Date:  2002-04       Impact factor: 5.407

7.  Genetics of gene expression surveyed in maize, mouse and man.

Authors:  Eric E Schadt; Stephanie A Monks; Thomas A Drake; Aldons J Lusis; Nam Che; Veronica Colinayo; Thomas G Ruff; Stephen B Milligan; John R Lamb; Guy Cavet; Peter S Linsley; Mao Mao; Roland B Stoughton; Stephen H Friend
Journal:  Nature       Date:  2003-03-20       Impact factor: 49.962

Review 8.  A review and comparison of the murine alpha1-antitrypsin and alpha1-antichymotrypsin multigene clusters with the human clade A serpins.

Authors:  Sharon Forsyth; Anita Horvath; Paul Coughlin
Journal:  Genomics       Date:  2003-03       Impact factor: 5.736

9.  Phenotypic anchoring of acetaminophen-induced oxidative stress with gene expression profiles in rat liver.

Authors:  Christine L Powell; Oksana Kosyk; Pamela K Ross; Robert Schoonhoven; Gunnar Boysen; James A Swenberg; Alexandra N Heinloth; Gary A Boorman; Michael L Cunningham; Richard S Paules; Ivan Rusyn
Journal:  Toxicol Sci       Date:  2006-06-02       Impact factor: 4.849

10.  GoMiner: a resource for biological interpretation of genomic and proteomic data.

Authors:  Barry R Zeeberg; Weimin Feng; Geoffrey Wang; May D Wang; Anthony T Fojo; Margot Sunshine; Sudarshan Narasimhan; David W Kane; William C Reinhold; Samir Lababidi; Kimberly J Bussey; Joseph Riss; J Carl Barrett; John N Weinstein
Journal:  Genome Biol       Date:  2003-03-25       Impact factor: 13.583

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  33 in total

1.  Evaluation of an in vitro toxicogenetic mouse model for hepatotoxicity.

Authors:  Stephanie M Martinez; Blair U Bradford; Valerie Y Soldatow; Oksana Kosyk; Amelia Sandot; Rafal Witek; Robert Kaiser; Todd Stewart; Kirsten Amaral; Kimberly Freeman; Chris Black; Edward L LeCluyse; Stephen S Ferguson; Ivan Rusyn
Journal:  Toxicol Appl Pharmacol       Date:  2010-09-24       Impact factor: 4.219

Review 2.  Computational tools for discovery and interpretation of expression quantitative trait loci.

Authors:  Fred A Wright; Andrey A Shabalin; Ivan Rusyn
Journal:  Pharmacogenomics       Date:  2012-02       Impact factor: 2.533

3.  Peroxisomal L-bifunctional enzyme (Ehhadh) is essential for the production of medium-chain dicarboxylic acids.

Authors:  Sander M Houten; Simone Denis; Carmen A Argmann; Yuzhi Jia; Sacha Ferdinandusse; Janardan K Reddy; Ronald J A Wanders
Journal:  J Lipid Res       Date:  2012-04-25       Impact factor: 5.922

Review 4.  Genome-wide association studies and genetic risk assessment of liver diseases.

Authors:  Marcin Krawczyk; Roman Müllenbach; Susanne N Weber; Vincent Zimmer; Frank Lammert
Journal:  Nat Rev Gastroenterol Hepatol       Date:  2010-11-02       Impact factor: 46.802

5.  Systems genetics of metabolism: the use of the BXD murine reference panel for multiscalar integration of traits.

Authors:  Pénélope A Andreux; Evan G Williams; Hana Koutnikova; Riekelt H Houtkooper; Marie-France Champy; Hugues Henry; Kristina Schoonjans; Robert W Williams; Johan Auwerx
Journal:  Cell       Date:  2012-08-30       Impact factor: 41.582

6.  Functional coding variation in recombinant inbred mouse lines reveals multiple serotonin transporter-associated phenotypes.

Authors:  Ana M D Carneiro; David C Airey; Brent Thompson; Chong-Bin Zhu; Lu Lu; Elissa J Chesler; Keith M Erikson; Randy D Blakely
Journal:  Proc Natl Acad Sci U S A       Date:  2009-01-28       Impact factor: 11.205

7.  Moderation of breastfeeding effects on the IQ by genetic variation in fatty acid metabolism.

Authors:  Avshalom Caspi; Benjamin Williams; Julia Kim-Cohen; Ian W Craig; Barry J Milne; Richie Poulton; Leonard C Schalkwyk; Alan Taylor; Helen Werts; Terrie E Moffitt
Journal:  Proc Natl Acad Sci U S A       Date:  2007-11-05       Impact factor: 11.205

8.  Replication and narrowing of gene expression quantitative trait loci using inbred mice.

Authors:  Daniel M Gatti; Alison H Harrill; Fred A Wright; David W Threadgill; Ivan Rusyn
Journal:  Mamm Genome       Date:  2009-07-17       Impact factor: 2.957

9.  Genetics of the hippocampal transcriptome in mouse: a systematic survey and online neurogenomics resource.

Authors:  Rupert W Overall; Gerd Kempermann; Jeremy Peirce; Lu Lu; Dan Goldowitz; Fred H Gage; Shirlean Goodwin; August B Smit; David C Airey; Glenn D Rosen; Leonard C Schalkwyk; Thomas R Sutter; Richard S Nowakowski; Stephen Whatley; Robert W Williams
Journal:  Front Neurosci       Date:  2009-11-10       Impact factor: 4.677

10.  SYSGENET: a meeting report from a new European network for systems genetics.

Authors:  Klaus Schughart
Journal:  Mamm Genome       Date:  2010-07-11       Impact factor: 2.957

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