Regulation of protein abundance in genetically diverse mouse populations

Keele, Gregory R.; Zhang, Tian; Pham, Duy T.; Vincent, Matthew; Bell, Timothy A.; Hock, Pablo; Shaw, Ginger D; Paulo, João A.; Munger, Steven C.; Villena, Fernando Pardo-Manuel de; Ferris, Martin T.; Gygi, Steven P.; Churchill, Gary A.

doi:10.1016/j.xgen.2021.100003

Cited by 30 publications

(73 citation statements)

References 88 publications

(100 reference statements)

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“…On the other hand, the immonoproteasome becomes more anti-correlated with their constitutive partners (PSMB5-7) with age. The anti-correlation between immunoproteasome and the constitutive subunits was also observed in the liver tissue from DO, Collaborative Cross and founder mice, and it was shown to be partially modulated by genetic factors (Keele et al 2021). The immunoproteasome supports the generation of peptides for antigen presentation by MHC class I molecules (Basler et al 2013), and plays a role in the activation of adaptive immune pathways (Basler et al 2013).…”

Section: Discussionmentioning

confidence: 81%

“…To maximize usage of the Cold Spring Harbor Laboratory Press on March 20, 2022 -Published by genome.cshlp.org Downloaded from data, we first refined the set of polymorphic peptides to be filtered out by confirming that data from polymorphic peptides from the heart clearly matched our expectations based on the founder strain genomes. We used our previous approach of correlating allele effects at putative local QTL for each peptide in the polymorphic set with the B6 alllele's distribution pattern among the eight founder strains (Keele et al 2021). Peptides with a correlation 0.7, thus matching the expected polymorphism signal, were filtered from the data.…”

Section: Mass Spectrometry and Protein Quantificationmentioning

confidence: 99%

“…As we did previously (Keele et al 2021), batch effects were removed using a linear mixed effect model (LMM) fit with the lme4 package (Bates et al 2015). The batch effect, estimated as a best linear unbiased predictor (BLUP), was subtracted from each protein abundance, while age (as a categorical variable with three levels) and sex were included as fixed effect covariates in the model.…”

Section: Mass Spectrometry and Protein Quantificationmentioning

confidence: 99%

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Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart

et al. 2022

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Investigation of the molecular mechanisms of aging in the human heart is challenging due to confounding factors, such as diet and medications, as well as limited access to tissues from healthy aging individuals. The laboratory mouse provides an ideal model to study aging in healthy individuals in a controlled environment. However, previous mouse studies have examined only a narrow range of the genetic variation that shapes individual differences during aging. Here, we analyze transcriptome and proteome data from 185 genetically diverse male and female mice at ages 6, 12 and 18 months to characterize molecular changes that occur in the aging heart. Transcripts and proteins reveal activation of pathways related to exocytosis and cellular transport with age, while processes involved in protein folding decrease with age. Additional changes are apparent only in the protein data including reduced fatty acid oxidation and increased autophagy. For proteins that form complexes, we see a decline in correlation between their component subunits with age, suggesting age-related loss of stoichiometry. The most affected complexes are themselves involved in protein homeostasis, which potentially contributes to a cycle of progressive breakdown in protein quality control with age. Our findings highlight the important role of post-transcriptional regulation in aging. In addition, we identify genetic loci that modulate age-related changes in protein homeostasis, suggesting that genetic variation can alter the molecular aging process.

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Section: Discussionmentioning

confidence: 81%

Section: Mass Spectrometry and Protein Quantificationmentioning

confidence: 99%

Section: Mass Spectrometry and Protein Quantificationmentioning

confidence: 99%

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Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart

et al. 2022

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“…Although these TWASs shed light on potential mechanisms through which genetic loci associated with SUTs exert their effects, the evidence they provide of expression quantitative trait loci (eQTL) effects are at the level of messenger RNA (mRNA), rather than protein abundance. Genetic variation can influence protein abundance by altering the rate and stability of gene expression 16 , though it remains to be determined whether the identified genetic loci exert their effects on SUTs by modulating protein abundance in the brain. The importance of this question lies in the fact that proteins, as the final products of gene expression, are the main functional components of cells and biological processes 17 , and comprise most drug targets and biomarkers 17,18 .…”

Section: Introductionmentioning

confidence: 99%

Integrating Human Brain Proteomic Data with Genome-Wide Association Study Findings Identifies Novel Brain Proteins in Substance Use Traits

Toikumo

Kember

et al. 2022

Preprint

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Background: Despite the growing number of genetic risk loci identified for substance use traits (SUTs), the impact of these loci on protein abundance and their potential as therapeutic targets are unknown. Methods: To address this, we performed a proteome-wide association study (PWAS) by integrating human brain proteomes from discovery (Banner; N = 152) and validation (ROSMAP; N = 376) datasets with genome-wide association study (GWAS) summary statistics for 4 SUTs. The sample comprised 4 GWAS of European-ancestry individuals for smoking initiation [Smk] (N = 1,232,091), alcohol use disorder [AUD] (N = 313,959), cannabis use disorder [CUD] (N = 384,032), and opioid use disorder [OUD] (N = 302,585). We conducted transcriptome-wide association studies (TWAS) with human brain transcriptomic data to examine the overlap of genetic effects at the proteomic and transcriptomic levels and tested significant genes for causality through Colocalization analysis. Results: Twenty-seven genes (Smk=21, AUD=3, CUD=2, OUD=1) were significantly associated with cis-regulated brain protein abundance. There was evidence for causality in 6 genes (Smk: NT5C2, GMPPB, NQO1, SRR, and ACTR1B; AUD: CTNND1), which act by regulating brain protein abundance. Cis-regulated transcript levels for 8 genes (Smk=6, CUD=1, OUD=1) were associated with SUTs, indicating that genetic loci could confer risk for these SUTs by modulating both gene expression and proteomic abundance. Conclusions: Functional studies of the high-confidence risk proteins (SRR for Smk and CTNND1 for AUD) identified here are needed to determine whether they are modifiable targets and useful in developing medications and biomarkers for these SUTs.

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“…Finally, the QTLViewer can perform mediation analysis for additive QTL to identify candidate causal mediators (Chick et al 2016; Keele et al 2021; Keller et al 2018) if -omic data, such as gene expression, have been collected on the same mice. Briefly, Equation 1 is re-used (with the kinship term excluded for computational efficiency) and the QTL of interest re-tested, but now conditioning one-by-one on candidate mediators.…”

Section: Methodsmentioning

confidence: 99%

QTLViewer: An interactive webtool for genetic analysis in the Collaborative Cross and Diversity Outbred mouse populations

Vincent

Gyuricza

Keele

et al. 2022

Preprint

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The Collaborative Cross (CC) and the Diversity Outbred (DO) mouse populations are related multiparental populations (MPPs), derived from the same eight isogenic founder strains. They carry >50M known genetic variants, which makes them ideal tools for mapping genetic loci that regulate phenotypes, including physiological and molecular traits. Mapping quantitative trait loci (QTLs) requires statistical and computational training, which can present a barrier to access for some researchers. The QTLViewer software is graphical user interface webtool for CC and DO studies that performs QTL mapping through the R/qtl2 package. Additionally, the QTLViewer website serves as a repository for published CC and DO studies, allowing users to explore QTL mapping results interactively and increasing the accessibility of these genetic resources to the broader scientific community.

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Regulation of protein abundance in genetically diverse mouse populations

Cited by 30 publications

References 88 publications

Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart

Genome-wide transcript and protein analysis highlights the role of protein homeostasis in the aging mouse heart

Integrating Human Brain Proteomic Data with Genome-Wide Association Study Findings Identifies Novel Brain Proteins in Substance Use Traits

QTLViewer: An interactive webtool for genetic analysis in the Collaborative Cross and Diversity Outbred mouse populations

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