Mapping molecular responses to xenoestrogens through Gene Ontology and pathway analysis of toxicogenomic data

被引:19
作者
Currie, RA [1 ]
Orphanides, G [1 ]
Moggs, JG [1 ]
机构
[1] Syngenta Cent Toxicol Lab, Macclesfield SK10 4TJ, Cheshire, England
关键词
xenoestrogen; gene ontology; genomics; phenotypic anchoring; mouse uterotrophic assay;
D O I
10.1016/j.reprotox.2005.03.014
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The recent sequencing of mammalian genomes has driven the development of genomic technologies, including microarray-based gene expression profiling, that allow simultaneous measurement of the expression levels of thousands of genes. Gene expression profiling applied to toxicology (toxicogenomics) has the potential to reveal, holistically, the molecular pathways and cellular processes that mediate the adverse responses to a toxicant. However, the initial output of a toxicogenomics experiment consists of a list of genes whose expression is altered upon toxicant exposure. In order to interpret these data in a biological context, new biomformatic methods must be developed to place gene expression changes in the context of the underlying pathways and processes affected. One emerging approach is the application of Gene Ontology (GO) mapping and pathway analysis to gene expression profiling data. The utility of this in mechanistic toxicology will be illustrated using examples in which GO mapping of toxicogenomic data has provided novel insights into the molecular mechanisms induced by exposure to xenoestrogens. (c) 2005 Elsevier Inc. All rights reserved.
引用
收藏
页码:433 / 440
页数:8
相关论文
共 32 条
[1]   Gene Ontology: tool for the unification of biology [J].
Ashburner, M ;
Ball, CA ;
Blake, JA ;
Botstein, D ;
Butler, H ;
Cherry, JM ;
Davis, AP ;
Dolinski, K ;
Dwight, SS ;
Eppig, JT ;
Harris, MA ;
Hill, DP ;
Issel-Tarver, L ;
Kasarskis, A ;
Lewis, S ;
Matese, JC ;
Richardson, JE ;
Ringwald, M ;
Rubin, GM ;
Sherlock, G .
NATURE GENETICS, 2000, 25 (01) :25-29
[2]   An ontology for cell types [J].
Bard, J ;
Rhee, SY ;
Ashburner, M .
GENOME BIOLOGY, 2005, 6 (02)
[3]   GOstat: find statistically overrepresented Gene Ontologies within a group of genes [J].
Beissbarth, T ;
Speed, TP .
BIOINFORMATICS, 2004, 20 (09) :1464-1465
[4]   NetAffx gene ontology mining tool: A visual approach for microarray data analysis [J].
Cheng, J ;
Sun, S ;
Tracy, A ;
Hubbell, E ;
Morris, J ;
Valmeekam, V ;
Kimbrough, A ;
Cline, MS ;
Liu, GY ;
Shigeta, R ;
Kulp, D ;
Siani-Rose, MA .
BIOINFORMATICS, 2004, 20 (09) :1462-1463
[5]  
Clark James H., 1994, P1011
[6]  
Deavall DG, 2005, HANDBOOK OF TOXICOGENOMICS: STRATEGIES AND APPLICATIONS, P413, DOI 10.1002/3527603719.ch17
[7]   MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data [J].
Doniger, SW ;
Salomonis, N ;
Dahlquist, KD ;
Vranizan, K ;
Lawlor, SC ;
Conklin, BR .
GENOME BIOLOGY, 2003, 4 (01)
[8]   Global approaches to protein-protein interactions [J].
Drewes, G ;
Bouwmeester, T .
CURRENT OPINION IN CELL BIOLOGY, 2003, 15 (02) :199-205
[9]   Identification of temporal patterns of gene expression in the uteri of immature, ovariectomized mice following exposure to ethynylestradiol [J].
Fertuck, KC ;
Eckel, JE ;
Gennings, C ;
Zacharewski, TR .
PHYSIOLOGICAL GENOMICS, 2003, 15 (02) :127-141
[10]   Challenges and limitations of gene expression profiling in mechanistic and predictive toxicology [J].
Fielden, MR ;
Zacharewski, TR .
TOXICOLOGICAL SCIENCES, 2001, 60 (01) :6-10