Co-expression analysis reveals interpretable gene modules controlled by<i>trans</i>-acting genetic variants

Kolberg, Liis; Kerimov, Nurlan; Peterson, Hedi; Alasoo, Kaur

doi:10.1101/2020.04.22.055335

Cited by 3 publications

(3 citation statements)

References 78 publications

(130 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CD14 þ cell DHS: Hints to a monocyte-specific pleiotropic activity in LYZ We first focus on the LYZ pleiotropic region. Previous studies have highlighted distinct lead hotspots around LYZ, 33 yet none provided a functional characterization that would allow a clear prioritization of one variant over another. The lead hotspots revealed by the M-EPISPOT and EPISPOT runs are intergenic variants, rs10784774 (size 154) and rs2168029 (size 109, r 2 ¼ 0:89 with rs10784774; see Figure 5D-i).…”

Section: A Focus On Two Susceptibility Locimentioning

confidence: 99%

EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

Ruffieux

Fairfax

Nassiri

et al. 2021

The American Journal of Human Genetics

View full text Add to dashboard Cite

We present EPISPOT, a fully joint framework which exploits large panels of epigenetic annotations as variant-level information to enhance molecular quantitative trait locus (QTL) mapping. Thanks to a purpose-built Bayesian inferential algorithm, EPISPOT accommodates functional information for both cis and trans actions, including QTL hotspot effects. It effectively couples simultaneous QTL analysis of thousands of genetic variants and molecular traits with hypothesis-free selection of biologically interpretable annotations which directly contribute to the QTL effects. This unified, epigenome-aided learning boosts statistical power and sheds light on the regulatory basis of the uncovered hits; EPISPOT therefore marks an essential step toward improving the challenging detection and functional interpretation of trans-acting genetic variants and hotspots. We illustrate the advantages of EPISPOT in simulations emulating real-data conditions and in a monocyte expression QTL study, which confirms known hotspots and finds other signals, as well as plausible mechanisms of action. In particular, by highlighting the role of monocyte DNase-I sensitivity sites from >150 epigenetic annotations, we clarify the mediation effects and cell-type specificity of major hotspots close to the lysozyme gene. Our approach forgoes the daunting and underpowered task of one-annotation-at-a-time enrichment analyses for prioritizing cis and trans QTL hits and is tailored to any transcriptomic, proteomic, or metabolomic QTL problem. By enabling principled epigenome-driven QTL mapping transcriptome-wide, EPISPOT helps progress toward a better functional understanding of genetic regulation.

show abstract

Section: A Focus On Two Susceptibility Locimentioning

confidence: 99%

EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

Ruffieux

Fairfax

Nassiri

et al. 2021

The American Journal of Human Genetics

View full text Add to dashboard Cite

show abstract

“…CD14 + cell DHS: hints to a monocyte-specific pleiotropic activity in LYZ We first focus on the LYZ pleiotropic region. Previous studies have highlighted distinct lead hotspots around LYZ (see [27] for a list), yet none provided a functional characterisation that would allow a clear prioritisation of one variant over another. The lead hotspots revealed by the M-EPISPOT and EPISPOT runs are intergenic variants, rs10784774 (size 154) and rs2168029 (size 109, r 2 = 0.89 with rs10784774; see Figure 5D-i).…”

Section: The Selected Epigenetic Annotations Reveal Possible Genetic mentioning

confidence: 99%

EPISPOT: an epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

Ruffieux

Fairfax

Nassiri

et al. 2020

Preprint

View full text Add to dashboard Cite

We present EPISPOT, a fully joint framework which exploits large panels of epigenetic marks as variant-level information to enhance molecular quantitative trait locus (QTL) mapping. Thanks to a purpose-built Bayesian inferential algorithm, our approach effectively couples simultaneous QTL analysis of thousands of genetic variants and molecular traits genome-wide, and hypothesis-free selection of biologically interpretable marks which directly contribute to the QTL effects. This unified learning approach boosts statistical power and sheds light on the regulatory basis of the uncovered associations. EPISPOT is also tailored to the modelling of trans-acting genetic variants, including QTL hotspots, whose detection and functional interpretation are challenging with standard approaches. We illustrate the advantages of EPISPOT in simulations emulating real-data conditions and in an epigenome-driven monocyte expression QTL study which confirms known hotspots and reveals new ones, as well as plausible mechanisms of action. In particular, based on monocyte DNase-I sensitivity site annotations selected by the method from > 150 epigenetic annotations, we clarify the mediation effects and cell-type specificity of well-known master hotspots in the vicinity of the lyzosyme gene. EPISPOT is radically new in that it makes it possible to forgo the daunting and underpowered task of one-mark-at-a-time enrichment analyses for the prioritisation of QTL hits. Our method can be used to enhance the discovery and functional understanding of signals in QTL problems with all types of outcomes, be they transcriptomic, proteomic, lipidomic, metabolic or clinical.

show abstract

“…Recently, eQTL hotspots have been identified in human blood cells 31,32 , as well as in cell lines 33 . These results suggest hotspot and trans eQTL discovery is facilitated by expression studies that can distinguish cell types and point to a larger role of hotspots in the genetics of gene expression in animals.…”

Section: Discussionmentioning

confidence: 99%

Whole-organism eQTL mapping at cellular resolution with single-cell sequencing

Ben-David

Boocock

Guo

et al. 2020

Preprint

View full text Add to dashboard Cite

Genetic variants affecting gene expression, termed expression quantitative trait loci (eQTLs), underlie phenotypic variation in complex traits and disease risk 1–3. Studies in purified blood cell populations 4–6 and computational analyses in human tissues 7,8 suggest that many eQTLs are cell-type specific. Single-cell RNA sequencing (scRNA-seq) has shown promise for eQTL mapping in blood cells and cell lines 9–11. However, the complexity of mammalian tissues makes studying cell-type eQTLs with scRNA-seq highly challenging. Here, we report a novel approach in the model nematode Caenorhabditis elegans that uses scRNA-seq to map eQTLs at cellular resolution in a single one-pot experiment. We studied an extremely large population of hundreds of thousands of genetically distinct individuals and mapped both cis and trans eQTLs across the different cell types of C. elegans. We find cell-type-specific trans-eQTL hotspots and show that they affect the expression of core pathways in the relevant cell types. Finally, we find single-cell-specific eQTL effects in the nervous system, including an eQTL with opposite effects in two individual neurons. Our results show that eQTL effects can be specific down to the level of single cells.

show abstract

Co-expression analysis reveals interpretable gene modules controlled bytrans-acting genetic variants

Cited by 3 publications

References 78 publications

EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

EPISPOT: an epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

Whole-organism eQTL mapping at cellular resolution with single-cell sequencing

Contact Info

Product

Resources

About