aboutsummaryrefslogtreecommitdiff
path: root/general/datasets/Epflbxdprothfd0513/summary.rtf
diff options
context:
space:
mode:
Diffstat (limited to 'general/datasets/Epflbxdprothfd0513/summary.rtf')
-rw-r--r--general/datasets/Epflbxdprothfd0513/summary.rtf5
1 files changed, 5 insertions, 0 deletions
diff --git a/general/datasets/Epflbxdprothfd0513/summary.rtf b/general/datasets/Epflbxdprothfd0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/summary.rtf
@@ -0,0 +1,5 @@
+<p>Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by&nbsp;<em>cis</em>-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates&nbsp;a novel&nbsp;animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit&nbsp;2-aminoadipic and 2-oxoadipic aciduria&nbsp;like&nbsp;seen in affected patients.&nbsp;Together, these&nbsp;findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.</p>
+
+<p>Note: please see associated dataset&nbsp;&ldquo;Liver Proteome&rdquo;&nbsp;EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN&rdquo;&nbsp;for protein data in the&nbsp;same&nbsp;animals.&nbsp;[NB: Data in review, but still unpublished as of Nov 2013, please contact&nbsp;<a href="mailto:admin.auwerx@epfl.ch" target="_blank">admin.auwerx@epfl.ch</a>&nbsp;for access]</p>
+
+<p>Note: please see associated dataset&nbsp;&ldquo;LISP2&rdquo;&nbsp;in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact&nbsp;<a href="mailto:admin.auwerx@epfl.ch" target="_blank">admin.auwerx@epfl.ch</a>&nbsp;for access]</p>