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Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping

ABSTRACT: Coordinated regulation of gene expression levels across a series of experimental conditions provides valuable information about the functions of correlated transcripts. To map gene regulatory pathways, we used microarray-derived gene expression measurements in 60 individuals of an F2 sample segregating for diabetes. We performed correlation analysis among ~40,000 expression traits. By combining correlation among expression traits and linkage mapping information, we were able to identify regulatory networks, make functional predictions to uncharacterized genes, and characterize novel members of known pathways. Using 36 seed traits, we found evidence of coordinate regulation of 160 G-protein coupled receptor (GPCR) pathway expression traits. Of the 160 traits, 50 had their major LOD peak within 8 cM of a locus on chromosome 2, and 81 others had a secondary peak in this region. A previously uncharacterized Riken cDNA clone, which showed strong correlation with stearoyl CoA desaturase 1 expression, was experimentally validated to be responsive to conditions that regulate lipid metabolism. Using linkage mapping, we identified multiple genes whose expression is under the control of transcription regulatory loci. Trait-correlation combined with linkage mapping can reveal regulatory networks that would otherwise be missed if we only studied mRNA traits with statistically significant linkages in this small cross. The combined analysis is more sensitive compared with linkage mapping only. References: Kendziorski C., M. Chen, M. Yuan, H. Lan, and A.D. Attie. Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping. Biometrics, to appear, 2005. Lan H, Chen M, Flowers JB, Yandell BS, Stapleton DS, et al. (2006) Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping. PLoS Genet 2(1): e6. Keywords: Genetics of gene expression

ORGANISM(S): Mus musculus

PROVIDER: GSE3330 | GEO | 2005/09/21

SECONDARY ACCESSION(S): PRJNA93233

REPOSITORIES: GEO

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Project description:Coordinated regulation of gene expression levels across a series of experimental conditions provides valuable information about the functions of correlated transcripts. To map gene regulatory pathways, we used microarray-derived gene expression measurements in 60 individuals of an F2 sample segregating for diabetes. We performed correlation analysis among ~40,000 expression traits. By combining correlation among expression traits and linkage mapping information, we were able to identify regulatory networks, make functional predictions to uncharacterized genes, and characterize novel members of known pathways. Using 36 seed traits, we found evidence of coordinate regulation of 160 G-protein coupled receptor (GPCR) pathway expression traits. Of the 160 traits, 50 had their major LOD peak within 8 cM of a locus on chromosome 2, and 81 others had a secondary peak in this region. A previously uncharacterized Riken cDNA clone, which showed strong correlation with stearoyl CoA desaturase 1 expression, was experimentally validated to be responsive to conditions that regulate lipid metabolism. Using linkage mapping, we identified multiple genes whose expression is under the control of transcription regulatory loci. Trait-correlation combined with linkage mapping can reveal regulatory networks that would otherwise be missed if we only studied mRNA traits with statistically significant linkages in this small cross. The combined analysis is more sensitive compared with linkage mapping only. References: ; Kendziorski C., M. Chen, M. Yuan, H. Lan, and A.D. Attie. Statistical Methods for Expression Quantitative Trait Loci (eQTL) Mapping. Biometrics, to appear, 2005. Lan H, Chen M, Flowers JB, Yandell BS, Stapleton DS, et al. (2006) Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping. PLoS Genet 2(1): e6. Experiment Overall Design: The F2-ob/ob mice were chosen from a mapping panel that we created to map diabetes related physiological phenotypes (Stoehr et al. 2000). About 110 of these F2-ob/ob mice were also used to map mRNA abundance traits derived by quantitative real-time RT-PCR (Lan et al. 2003). The sixty F2-ob/ob mice that were used to generate microarray-derived mRNA abundance traits were selected from the 110 mice based on a selective phenotyping algorithm (Jin et al. 2004). The F2-ob/ob mice were housed at weaning at the University of Wisconsin-Madison animal care facility on a 12-h light/dark cycle. Mice were provided Purina Formulab Chow 5008 (6.5% fat) and acidified water ad libitum. Mice were killed at 14 weeks of age by CO2 asphyxiation after a 4-hour fast. The livers, along with other tissues, were immediately foil wrapped and frozen in liquid nitrogen, and subsequently transferred to -80 Â°C freezers for storage. Liver samples were taken from 29 male and 31 females. Total RNA was isolated with RNAzol Reagent (Tel-Test, Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer's protocol. The extracted RNA was purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for concentration. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. RNA samples were converted to cDNA, and then biotin-labeled cRNA according to Affymetrix Expression Analysis Technical Manual. The labeled samples were hybridized to the M430A, and subsequently the M430B array. The hybridization, washing and scanning steps were carried out by Hong Lan using the Affymetrix core facility at the Gene Expression Center of University of Wisconsin-Madison.

Project description:The control of gene expression in Toxoplasma is not well understood. As we and others have shown, this organism does contain bipartite promoters that are sufficient to induce gene expression. This information can be used in downstream experiments to identify proteins that bind to experimentally confirmed cis elements. One of these methods, yeast one-hybrid is currently being employed to identify proteins which bind to the BAG1 and B-NTPase promoter elements. Another powerful method that can be used to identify genomic regions containing controllers of gene expression takes advantage of genetic linkage mapping provided by genetic crosses, called expression quantitative trait locus (eQTL) mapping. In the eQTL approach, one uses gene expression as quantitative traits, or phenotypes, in QTL mapping. QTL mapping is a proven method in Toxoplasma that has recently identified apicomplexan-specific virulence factors in both the Type II X III and Type I X III crosses (Saeij et al., 2006, Taylor et al., 2006, Su et al., 2002). With the recent design of the Affymetrix Toxoplasma GeneChip one can gather gene expression profiles for all predicted genes in the Toxoplasma genome in a rapid and reproducible way. Combining the power of Affymetrix gene expression technology and QTL mapping can lead to the identification of genes with differential expression in the parents and progeny of a genetic cross and then to the identification of the genomic regions that contain mechanisms that have an effect on expression. The first description of combining global gene expression profiles with QTL mapping was published by Brem et al. using the model organism Saccharomyces cerevisiae (Brem et al., 2002). Since that time, eQTL projects have been described for several other organisms including human, mouse, rat, maize, Arabidopsis, barley, eucalyptus, and wheat (Gibson & Weir, 2005). There are two mapping location types expected when using gene expression profiles as phenotypes. Mapping of gene expression profiles can lead to linkage of a locus (region) containing the gene being mapped, thus cis to the gene. Although the boundaries of the locus will contain many genes, it is presumed that for most cis QTLs sequence polymorphisms in the regulatory region(s) of the gene being mapped are the cause of the observed expression differences. The other mapping location type expected is one where the expression profile maps to a locus not containing the gene being mapped, or trans to the gene (Ronald et al., 2005). The most interesting trans loci are those that have multiple genes mapping to the same locus in trans, or to a trans hotspot. These hotspots likely contain factor(s) that regulate many genes, such as transcription factors or factors involved in upstream signal transduction pathways that can eventually lead to a number of transcriptional changes (Yvert et al., 2003). Here we describe the results of an eQTL project using the gene expression profiles for the parents and 34 informative progeny of the type I-GT1-Fudr X type III-CTGara cross for both the tachyzoite and bradyzoite stages. This is the first time global gene expression profiles have been used to determine linkage to regions presumed to be controllers of transcription using the Affymetrix Toxoplasma GeneChip. The dominant genomic associations found were those mapping cis and there were several regions, or hotspots, where multiple genes map in trans. In addition, we observed an unexpected finding suggesting there are several duplication events in the parasites of the Type I X III cross which may also have consequences on gene expression levels.

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Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping

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