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-<HTML><HEAD><TITLE>MDC/CAS/UCL Liver 230v2 (Dec08) RMA **</TITLE>
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-<P class="title">MDC/CAS/UCL Liver 230v2 (Dec08) RMA **  <A HREF="/webqtl/main.py?FormID=editHtml"><img src="/images/modify.gif" alt="modify this page" border= 0 valign="middle"></A><BR><BR>Accession number: <A HREF="/webqtl/main.py?FormID=sharinginfo&GN_AccessionId=222">GN222</A></P>
-<P><font color="#FF0000">Waiting for the data provider to submit their info file</font></P>
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-<P class="subtitle">Summary:</P>
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-<B>SUBTITLE</B>Expression data for normal liver of the HXB/BXH rat RI strains generated using the Affymetrix Rat Genome 230 2.0 array <A HREF="http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GPL1355>GEO GPL1355</A></P>
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-<P>Grieve IC, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J.
-MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
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-<P>http://www.ncbi.nlm.nih.gov/pubmed/19112506
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-<P>PLoS One. 2008;3(12):e4033. Epub 2008 Dec 29.
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-<P>Expression quantitative trait loci (eQTLs) represent genetic control points of gene expression, and can be categorized as cis- and trans-acting, reflecting local and distant regulation of gene expression respectively. Although there is evidence of co-regulation within clusters of trans-eQTLs, the extent of co-expression patterns and their relationship with the genotypes at eQTLs are not fully understood. We have mapped thousands of cis- and trans-eQTLs in four tissues (fat, kidney, adrenal and left ventricle) in a large panel of rat recombinant inbred (RI) strains. Here we investigate the genome-wide correlation structure in expression levels of eQTL transcripts and underlying genotypes to elucidate the nature of co-regulation within cis- and trans-eQTL datasets. Across the four tissues, we consistently found statistically significant correlations of cis-regulated gene expression to be rare (<0.9% of all pairs tested). Most (>80%) of the observed significant correlations of cis-regulated gene expression are explained by correlation of the underlying genotypes. In comparison, co-expression of trans-regulated gene expression is more common, with significant correlation ranging from 2.9%-14.9% of all pairs of trans-eQTL transcripts. We observed a total of 81 trans-eQTL clusters (hot-spots), defined as consisting of > or =10 eQTLs linked to a common region, with very high levels of correlation between trans-regulated transcripts (77.2-90.2%). Moreover, functional analysis of large trans-eQTL clusters (> or =30 eQTLs) revealed significant functional enrichment among genes comprising 80% of the large clusters. The results of this genome-wide co-expression study show the effects of the eQTL genotypes on the observed patterns of correlation, and suggest that functional relatedness between genes underlying trans-eQTLs is reflected in the degree of co-expression observed in trans-eQTL clusters. Our results demonstrate the power of an integrative, systematic approach to the analysis of a large gene expression dataset to uncover underlying structure, and inform future eQTL studies.
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-<P>Users of these this data set may also find the following complementary resources extremely useful:
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-<LI> <A HREF="http://www.genenetwork.org" target="_blank" class="fs14">Link 1</A>.
-<LI> <A HREF="http://www.genenetwork.org" target="_blank" class="fs14">Link 2</A>.
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-<P class="subtitle">About the cases used to generate this set of data:</P>
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-<P class="subtitle">About the tissue used to generate this set of data:</P>
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-<td><font color=#FFFFFF>Index</font></td><td><font color=#FFFFFF>TubeID</font></td><td><font color=#FFFFFF>Group</font></td><td><font color=#FFFFFF>Strain</font></td><td><font color=#FFFFFF>Age</font></td><td><font color=#FFFFFF>Sex</font></td><td><font color=#FFFFFF>Source</font></td></tr>
-<tr bgcolor="#eeeeee"><td>1</td><td>R2595E.1</td><td>GDP</td><td>129S1/SvImJ</td><td>59</td><td>F</td><td>UTHSC RW</td></tr>
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-<td><font color=#FFFFFF>Index</font></td><td><font color=#FFFFFF>TubeID</font></td><td><font color=#FFFFFF>Strain</font></td><td><font color=#FFFFFF>Original CEL</font></td><td><font color=#FFFFFF>Scale factor</font></td><td><font color=#FFFFFF>Background Average</font></td><td><font color=#FFFFFF>Present</font></td><td><font color=#FFFFFF>Absent</font></td><td><font color=#FFFFFF>Marginal</font></td><td><font color=#FFFFFF>AFFX-b-ActinMur (3'/5')</font></td><td><font color=#FFFFFF>AFFX-GapdhMur (3'/5')</font></td><td><font color=#FFFFFF>Batch Id</font></td><td><font color=#FFFFFF>Used for batch control</font></td></tr>
-<tr bgcolor="#eeeeee"><td>1</td><td>R2595E.1</td><td>129S1/SvImJ</td><td>R2595E.1.CEL</td><td>1.79</td><td>115</td><td>61.00%</td><td>37.50%</td><td>1.50%</td><td>1.46</td><td>0.77</td><td>1</td><td>Y</td></tr>
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