Literature DB >> 19671657

Effects of atherogenic diet on hepatic gene expression across mouse strains.

Keith R Shockley1, David Witmer, Sarah L Burgess-Herbert, Beverly Paigen, Gary A Churchill.   

Abstract

Diets high in fat and cholesterol are associated with increased obesity and metabolic disease in mice and humans. To study the molecular basis of the metabolic response to dietary fat, 10 inbred strains of mice were fed atherogenic high-fat and control low-fat diets. Liver gene expression and whole animal phenotypes were measured and analyzed in both sexes. The effects of diet, strain, and sex on gene expression were determined irrespective of complex processes, such as feedback mechanisms, that could have mediated the genomic responses. Global gene expression analyses demonstrated that animals of the same strain and sex have similar transcriptional profiles on a low-fat diet, but strains may show considerable variability in response to high-fat diet. Functional profiling indicated that high-fat feeding induced genes in the immune response, indicating liver damage, and repressed cholesterol biosynthesis. The physiological significance of the transcriptional changes was confirmed by a correlation analysis of transcript levels with whole animal phenotypes. The results found here were used to confirm a previously identified quantitative trait locus on chromosome 17 identified in males fed a high-fat diet in two crosses, PERA x DBA/2 and PERA x I/Ln. The gene expression data and phenotype data have been made publicly available as an online tool for exploring the effects of atherogenic diet in inbred mouse strains (http://cgd-array.jax.org/DietStrainSurvey).

Entities:  

Mesh:

Year:  2009        PMID: 19671657      PMCID: PMC2789673          DOI: 10.1152/physiolgenomics.90350.2008

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  40 in total

1.  Bootstrapping cluster analysis: assessing the reliability of conclusions from microarray experiments.

Authors:  M K Kerr; G A Churchill
Journal:  Proc Natl Acad Sci U S A       Date:  2001-07-24       Impact factor: 11.205

2.  Improved statistical tests for differential gene expression by shrinking variance components estimates.

Authors:  Xiangqin Cui; J T Gene Hwang; Jing Qiu; Natalie J Blades; Gary A Churchill
Journal:  Biostatistics       Date:  2005-01       Impact factor: 5.899

Review 3.  Bioinformatics toolbox for narrowing rodent quantitative trait loci.

Authors:  Keith DiPetrillo; Xiaosong Wang; Ioannis M Stylianou; Beverly Paigen
Journal:  Trends Genet       Date:  2005-10-13       Impact factor: 11.639

4.  Estimating p-values in small microarray experiments.

Authors:  Hyuna Yang; Gary Churchill
Journal:  Bioinformatics       Date:  2006-10-30       Impact factor: 6.937

5.  Body mass index and the prevalence of hypertension and dyslipidemia.

Authors:  C D Brown; M Higgins; K A Donato; F C Rohde; R Garrison; E Obarzanek; N D Ernst; M Horan
Journal:  Obes Res       Date:  2000-12

6.  A prospective study of body mass index, weight change, and risk of stroke in women.

Authors:  K M Rexrode; C H Hennekens; W C Willett; G A Colditz; M J Stampfer; J W Rich-Edwards; F E Speizer; J E Manson
Journal:  JAMA       Date:  1997-05-21       Impact factor: 56.272

7.  Obesity as an adaptation to a high-fat diet: evidence from a cross-sectional study.

Authors:  A Astrup; B Buemann; P Western; S Toubro; A Raben; N J Christensen
Journal:  Am J Clin Nutr       Date:  1994-02       Impact factor: 7.045

8.  Obesity, fat distribution, and weight gain as risk factors for clinical diabetes in men.

Authors:  J M Chan; E B Rimm; G A Colditz; M J Stampfer; W C Willett
Journal:  Diabetes Care       Date:  1994-09       Impact factor: 19.112

9.  Overweight and mortality.

Authors:  L Garfinkel
Journal:  Cancer       Date:  1986-10-15       Impact factor: 6.860

10.  Entrez Gene: gene-centered information at NCBI.

Authors:  Donna Maglott; Jim Ostell; Kim D Pruitt; Tatiana Tatusova
Journal:  Nucleic Acids Res       Date:  2005-01-01       Impact factor: 16.971

View more
  38 in total

1.  Indigenous American ancestry is associated with arsenic methylation efficiency in an admixed population of northwest Mexico.

Authors:  Paulina Gomez-Rubio; Yann C Klimentidis; Ernesto Cantu-Soto; Maria M Meza-Montenegro; Dean Billheimer; Zhenqiang Lu; Zhao Chen; Walter T Klimecki
Journal:  J Toxicol Environ Health A       Date:  2012

2.  Using bioinformatics and systems genetics to dissect HDL-cholesterol genetics in an MRL/MpJ x SM/J intercross.

Authors:  Magalie S Leduc; Rachael Hageman Blair; Ricardo A Verdugo; Shirng-Wern Tsaih; Kenneth Walsh; Gary A Churchill; Beverly Paigen
Journal:  J Lipid Res       Date:  2012-04-11       Impact factor: 5.922

3.  The mouse QTL map helps interpret human genome-wide association studies for HDL cholesterol.

Authors:  Magalie S Leduc; Malcolm Lyons; Katayoon Darvishi; Kenneth Walsh; Susan Sheehan; Sarah Amend; Allison Cox; Marju Orho-Melander; Sekar Kathiresan; Beverly Paigen; Ron Korstanje
Journal:  J Lipid Res       Date:  2011-03-28       Impact factor: 5.922

4.  Recalculation of 23 mouse HDL QTL datasets improves accuracy and allows for better candidate gene analysis.

Authors:  Cheryl Ackert-Bicknell; Beverly Paigen; Ron Korstanje
Journal:  J Lipid Res       Date:  2013-02-07       Impact factor: 5.922

Review 5.  Dietary restriction in rats and mice: a meta-analysis and review of the evidence for genotype-dependent effects on lifespan.

Authors:  William R Swindell
Journal:  Ageing Res Rev       Date:  2011-12-23       Impact factor: 10.895

6.  High-fat diet leads to tissue-specific changes reflecting risk factors for diseases in DBA/2J mice.

Authors:  Rachael S Hageman; Asja Wagener; Claudia Hantschel; Karen L Svenson; Gary A Churchill; Gudrun A Brockmann
Journal:  Physiol Genomics       Date:  2010-03-09       Impact factor: 3.107

7.  One-carbon metabolism nutrient intake and the association between body mass index and urinary arsenic metabolites in adults in the Chihuahua cohort.

Authors:  Paige A Bommarito; Xiaofan Xu; Carmen González-Horta; Blanca Sánchez-Ramirez; Lourdes Ballinas-Casarrubias; René Santos Luna; Susana Román Pérez; Juan Eugenio Hernández Ávila; Gonzalo G García-Vargas; Luz M Del Razo; Mirek Stýblo; Michelle A Mendez; Rebecca C Fry
Journal:  Environ Int       Date:  2018-12-13       Impact factor: 9.621

8.  Mouse strain-dependent variation in obesity and glucose homeostasis in response to high-fat feeding.

Authors:  M K Montgomery; N L Hallahan; S H Brown; M Liu; T W Mitchell; G J Cooney; N Turner
Journal:  Diabetologia       Date:  2013-02-20       Impact factor: 10.122

9.  Arginase activities and global arginine bioavailability in wild-type and ApoE-deficient mice: responses to high fat and high cholesterol diets.

Authors:  Aaron Erdely; Diane Kepka-Lenhart; Rebecca Salmen-Muniz; Rebecca Chapman; Tracy Hulderman; Michael Kashon; Petia P Simeonova; Sidney M Morris
Journal:  PLoS One       Date:  2010-12-06       Impact factor: 3.240

10.  Transcriptional profiles of leukocyte populations provide a tool for interpreting gene expression patterns associated with high fat diet in mice.

Authors:  William R Swindell; Andrew Johnston; Johann E Gudjonsson
Journal:  PLoS One       Date:  2010-07-29       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.