A Bayesian model selection approach to mediation analysis

Crouse, Wesley L.; Keele, Gregory R.; Gastonguay, Madeleine S; Churchill, Gary A.; Valdar, William

doi:10.1101/2021.07.19.452969

Cited by 4 publications

(8 citation statements)

References 55 publications

(88 reference statements)

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“…Although variant association mapping sacrifices some of the information present in the founder haplotypes, it does enable researchers to potentially identify specific variants of interests and prioritize candidate genes. 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.…”

Section: Methodsmentioning

confidence: 99%

“…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.…”

Section: Methodsmentioning

confidence: 99%

“…We are in the process of adding a new method for mediation analysis based on Bayesian model selection (Crouse et al 2021) that can provide richer inference for mediators of interest. We continue to expand the QTLViewer for new types of genomic data, such as chromatin profiling data, which will be incorporated and layered onto the genome browser tracks.…”

Section: Future Directionsmentioning

confidence: 99%

“…The copyright holder for this preprint this version posted March 15, 2022. ; https://doi.org/10.1101/2022.03.15.484471 doi: bioRxiv preprint 2 quantitative trait loci (QTL), which can be powerful in studies of -omic traits, including gene expression, protein abundance, and chromatin accessibility (Abu Toamih Atamni et al 2018;Aylor et al 2011;Chick et al 2016;Gerdes Gyuricza et al 2022;Keele et al 2020;Keele et al 2021;Keller et al 2018;Takemon et al 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The Collaborative Cross (CC) and Diversity Outbred (DO) mouse populations are related MPPs that have been used to genetically dissect complex traits, including obesity (Svenson et al 2012), bone strength (Al-Barghouthi et al 2021), short-term memory (Hsiao et al 2020), and arsenic response (French et al 2015). As recombinant populations, the CC and DO are well-suited for mapping 2 quantitative trait loci (QTL), which can be powerful in studies of -omic traits, including gene expression, protein abundance, and chromatin accessibility (Abu Toamih Atamni et al 2018;Aylor et al 2011;Chick et al 2016;Gerdes Gyuricza et al 2022;Keele et al 2020;Keele et al 2021;Keller et al 2018;Takemon et al 2021).…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Future Directionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Vincent

Gyuricza

Keele

et al. 2022

Preprint

Self Cite

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Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain

et al. 2022

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Structural variants (SVs), genomic rearrangements of >50 bp, are an important source of genetic diversity and have been linked to many diseases. However, it remains unclear how they modulate human brain function and disease risk. Here, we report 170,996 SVs discovered using 1,760 short-read whole genomes from aged adults and Alzheimer’s disease individuals. By applying quantitative trait locus (SV-xQTL) analyses, we quantified the impact of cis -acting SVs on histone modifications, gene expression, splicing, and protein abundance in post-mortem brain tissues. More than 3,200 SVs were associated with at least one molecular phenotype. We found reproducibility of 65–99% SV-eQTLs across cohorts and brain regions. SV associations with mRNA and proteins shared the same direction of effect in more than 87% of SV-gene pairs. Mediation analysis showed ~8% of SV-eQTLs mediated by histone acetylation, and ~11% by splicing. Additionally, associations of SVs with progressive supranuclear palsy identified previously known and novel SVs.

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Inferring cell-type-specific causal gene regulatory networks during human neurogenesis

Aygün

Liang

Crouse

et al. 2022

Preprint

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BackgroundGenetic variation influences both chromatin accessibility, assessed in chromatin accessibility quantitative trait loci (caQTL) studies, and gene expression, assessed in expression QTL (eQTL) studies. Genetic variants can impact either nearby genes (local eQTLs) or distal genes (trans eQTLs). Colocalization between caQTL and eQTL, or local- and distant-eQTLs suggests that they share causal variants. However, pairwise colocalization between these molecular QTLs does not guarantee a causal relationship. Mediation analysis can be applied to assess the evidence supporting causality versus independence between molecular QTLs. Given that the function of QTLs can be cell-type-specific, we performed mediation analyses to find epigenetic and distal regulatory causal pathways for genes within two major cell types of the developing human cortex, progenitors and neurons.ResultsWe found that expression of 168 and 38 genes were mediated by chromatin accessibility in progenitors and neurons, respectively. We also found that the expression of 781 and 200 downstream genes were mediated by upstream genes in progenitors and neurons. Moreover, we discovered that a genetic locus associated with inter-individual differences in brain structure showed evidence for mediation of SLC26A7 through chromatin accessibility, identifying molecular mechanisms of a common variant association to a brain trait.ConclusionsIn this study, we identified cell-type-specific causal gene regulatory networks whereby the impacts of variants on gene expression were mediated by chromatin accessibility or distal gene expression. Identification of these causal paths will enable identifying and prioritizing actionable regulatory targets perturbing these key processes during neurodevelopment.

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A Bayesian model selection approach to mediation analysis

Cited by 4 publications

References 55 publications

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

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

Integrating whole-genome sequencing with multi-omic data reveals the impact of structural variants on gene regulation in the human brain

Inferring cell-type-specific causal gene regulatory networks during human neurogenesis

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