From b2feda451ccfbeaed02dce9088d6dd228cf15861 Mon Sep 17 00:00:00 2001 From: Bonface Date: Tue, 13 Feb 2024 23:52:26 -0600 Subject: Update dataset RTF Files. --- general/datasets/Epflmouseliverhfdrma0818/summary.rtf | 1 + 1 file changed, 1 insertion(+) create mode 100644 general/datasets/Epflmouseliverhfdrma0818/summary.rtf (limited to 'general/datasets/Epflmouseliverhfdrma0818/summary.rtf') diff --git a/general/datasets/Epflmouseliverhfdrma0818/summary.rtf b/general/datasets/Epflmouseliverhfdrma0818/summary.rtf new file mode 100644 index 0000000..77c5606 --- /dev/null +++ b/general/datasets/Epflmouseliverhfdrma0818/summary.rtf @@ -0,0 +1 @@ +

The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.

-- cgit v1.2.3