Project description:Unbiased in vivo genome-wide genetic screening is a powerful approach to elucidate new molecular mechanisms, but such screening has not been possible to perform in the mammalian central nervous system (CNS). Here we report the results of the first genome-wide genetic screens in the CNS using both shRNA and CRISPR libraries. Our screens identify many classes of CNS neuronal essential genes, and demonstrate that CNS neurons are particularly sensitive not only to perturbations to synaptic processes, but also autophagy, proteostasis, mRNA processing, and mitochondrial function. These results reveal a molecular logic for the common implication of these pathways across multiple neurodegenerative diseases. To further identify disease-relevant genetic modifiers, we applied our screening approach to two mouse models of Huntington’s disease (HD). Top mutant Huntingtin toxicity modifier genes included several Nme genes and several genes involved in methylation-dependent chromatin silencing and dopamine signaling, results that reveal new HD therapeutic target pathways.
Project description:Sigurdsson2010 - Genome-scale metabolic model
of Mus Musculus (iMM1415)
This model is described in the article:
A detailed genome-wide
reconstruction of mouse metabolism based on human Recon 1.
Sigurdsson MI, Jamshidi N,
Steingrimsson E, Thiele I, Palsson BØ.
BMC Syst Biol 2010; 4: 140
Abstract:
BACKGROUND: Well-curated and validated network
reconstructions are extremely valuable tools in systems
biology. Detailed metabolic reconstructions of mammals have
recently emerged, including human reconstructions. They raise
the question if the various successful applications of
microbial reconstructions can be replicated in complex
organisms. RESULTS: We mapped the published, detailed
reconstruction of human metabolism (Recon 1) to other mammals.
By searching for genes homologous to Recon 1 genes within
mammalian genomes, we were able to create draft metabolic
reconstructions of five mammals, including the mouse. Each
draft reconstruction was created in compartmentalized and
non-compartmentalized version via two different approaches.
Using gap-filling algorithms, we were able to produce all
cellular components with three out of four versions of the
mouse metabolic reconstruction. We finalized a functional model
by iterative testing until it passed a predefined set of 260
validation tests. The reconstruction is the largest, most
comprehensive mouse reconstruction to-date, accounting for
1,415 genes coding for 2,212 gene-associated reactions and
1,514 non-gene-associated reactions.We tested the mouse model
for phenotype prediction capabilities. The majority of
predicted essential genes were also essential in vivo. However,
our non-tissue specific model was unable to predict gene
essentiality for many of the metabolic genes shown to be
essential in vivo. Our knockout simulation of the lipoprotein
lipase gene correlated well with experimental results,
suggesting that softer phenotypes can also be simulated.
CONCLUSIONS: We have created a high-quality mouse genome-scale
metabolic reconstruction, iMM1415 (Mus Musculus, 1415 genes).
We demonstrate that the mouse model can be used to perform
phenotype simulations, similar to models of microbe metabolism.
Since the mouse is an important experimental organism, this
model should become an essential tool for studying metabolic
phenotypes in mice, including outcomes from drug screening.
This model is hosted on
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and identified by:
MODEL1507180055.
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Project description:We collected whole genome testis expression data from hybrid zone mice. We integrated GWAS mapping of testis expression traits and low testis weight to gain insight into the genetic basis of hybrid male sterility.
Project description:To characterize the genetic basis of hybrid male sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven ‘hotspots,’ seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL - but not cis eQTL - were substantially lower when mapping was restricted to a ‘fertile’ subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility.