Efficient count-based models improve power and robustness for large-scale single-cell eQTL mapping DOI Creative Commons
Zixuan Zhang, Artem Kim,

Noah Suboc

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 19, 2025

Abstract Population-scale single-cell transcriptomic technologies (scRNA-seq) enable characterizing variant effects on gene regulation at the cellular level (e.g., eQTLs; sc-eQTLs). However, existing sc-eQTL mapping approaches are either not designed for analyzing sparse counts in scRNA-seq data or can become intractable extremely large datasets. Here, we propose jaxQTL, a flexible and efficient framework using highly count-based models given pseudobulk data. Using extensive simulations, demonstrated that jaxQTL with negative binomial model outperformed other identifying sc-eQTLs, while maintaining calibrated type I error. We applied across 14 cell types of OneK1K ( N =982), identified 11-16% more eGenes compared approaches, primarily driven by ability to identify lowly expressed eGenes. observed fine-mapped sc-eQTLs were further from transcription starting site (TSS) than eQTLs all cells (bulk-eQTLs; P =1×10 −4 ) enriched cell-type-specific enhancers =3×10 −10 ), suggesting improve our distal missed bulk tissues. Overall, genetic effect largely shared types, cell-type-specificity increasing distance TSS. Lastly, explain SNP-heritability h 2 bulk-eQTLs (9.90 ± 0.88% vs. 6.10 0.76% when meta-analyzed 16 blood immune-related traits), improving but closing missing link between GWAS eQTLs. As an example, highlight T (unlike bulk-eQTLs) successfully nominate IL6ST as candidate rheumatoid arthritis. provides powerful approach disease-associated

Language: Английский

Redefining tissue specificity of genetic regulation of gene expression in the presence of allelic heterogeneity DOI Creative Commons
Marios Arvanitis,

Karl Tayeb,

Benjamin J. Strober

et al.

The American Journal of Human Genetics, Journal Year: 2022, Volume and Issue: 109(2), P. 223 - 239

Published: Jan. 31, 2022

Uncovering the functional impact of genetic variation on gene expression is important in understanding tissue biology and pathogenesis complex traits. Despite large efforts to map quantitative trait loci (eQTLs) across many human tissues, our ability translate those findings disease has been incomplete, majority are not explained by association with a target gene. Cell-type specificity presence multiple independent causal variants for eQTLs potential confounders contributing apparent discrepancy loci. In this study, we investigate effects overlap while considering within tissues. We find evidence pervasive eQTLs, often masked linkage disequilibrium that misleads traditional meta-analytic approaches. propose CAFEH (colocalization fine-mapping allelic heterogeneity), Bayesian method integrates data traits, incorporating identify variants. outperforms previous approaches colocalization fine-mapping. Using CAFEH, show genes highly tissue-specific under greater selection, enriched differentiation developmental processes, more likely be involved disease. Last, demonstrate can efficiently leverage widespread heterogeneity regulation prioritize genome-wide loci, thereby improving interpret genetics.

Language: Английский

Citations

56
Methods and Insights from Single-Cell Expression Quantitative Trait Loci DOI Creative Commons

Joyce B. Kang,

Alessandro Raveane, Aparna Nathan

et al.

Annual Review of Genomics and Human Genetics, Journal Year: 2023, Volume and Issue: 24(1), P. 277 - 303

Published: May 17, 2023

Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at resolution. Compared with bulk RNA sequencing, which averages gene cell types and states, assays capture the transcriptional states of individual cells, including fine-grained, transient, difficult-to-isolate populations unprecedented scale Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary some colocalize disease variants identified genome-wide association studies. By uncovering precise contexts these act, approaches unveil previously hidden regulatory effects pinpoint important underlying molecular mechanisms disease. Here, we present an overview recently deployed experimental designs sc-eQTL In process, consider influence study design choices such as cohort, ex vivo perturbations. We then discuss current methodologies, modeling approaches, technical challenges well future opportunities applications.

Language: Английский

Citations

26
Global impact of unproductive splicing on human gene expression DOI Creative Commons
Benjamin Fair, Carlos F. Buen Abad Najar,

Junxing Zhao

et al.

Nature Genetics, Journal Year: 2024, Volume and Issue: 56(9), P. 1851 - 1861

Published: Sept. 1, 2024

Language: Английский

Citations

16
Trans-eQTL mapping in gene sets identifies network effects of genetic variants DOI Creative Commons
Lili Wang,

Nikita Babushkin,

Zhonghua Liu

et al.

Cell Genomics, Journal Year: 2024, Volume and Issue: 4(4), P. 100538 - 100538

Published: April 1, 2024

Nearly all trait-associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these have been extensively characterized, but how they affect gene regulation trans has the subject fewer because difficulty detecting trans-expression quantitative loci (eQTLs). We developed trans-PCO for genetic on networks. Our simulations demonstrate that substantially outperforms existing trans-eQTL mapping methods. applied to two expression datasets from whole blood, DGN (N = 913) and eQTLGen 31,684), 14,985 high-quality trans-eSNP-module pairs associated with 197 co-expression modules biological processes. performed colocalization analyses between GWAS 46 complex traits trans-eQTLs. demonstrated can help us understand networks pathways.

Language: Английский

Citations

9
Integration of functional genomics and statistical fine-mapping systematically characterizes adult-onset and childhood-onset asthma genetic associations. DOI Creative Commons
Xiaoyuan Zhong,

Robert D. Mitchell,

Christine Billstrand

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 17, 2025

Abstract Background Genome-wide association studies (GWAS) have identified hundreds of loci underlying adult-onset asthma (AOA) and childhood-onset (COA). However, the causal variants, regulatory elements, effector genes at these are largely unknown. Methods We performed heritability enrichment analysis to determine relevant cell types for AOA COA, respectively. Next, we fine-mapped putative variants COA loci. To improve resolution fine-mapping, integrated ATAC-seq data in blood lung annotate candidate cis -regulatory elements (CREs). then computationally prioritized CREs risk, experimentally assessed their enhancer activity by massively parallel reporter assay (MPRA) bronchial epithelial cells (BECs) further validated a subset luciferase assays. Combining chromatin interaction expression quantitative trait loci, nominated targeted COA. Results Heritability suggested shared role immune development both while highlighting distinct contribution structural Functional fine-mapping uncovered 21 67 credible sets respectively, with only 16% between two. Notably, one-third contained multiple sets. Our CRE prioritization strategy 62 169 Over 60% showed open lineages, suggesting potential pleiotropic effects different types. Furthermore, were enriched enhancers MPRA BECs. The included many involved inflammatory responses. genes, including TNFSF4 , drug target undergoing clinical trials, supported two independent GWAS signals, indicating widespread allelic heterogeneity. Four out six selected demonstrated allele-specific properties assays Conclusions present comprehensive characterization genetics. results genetic basis highlighted complexity marked extensive pleiotropy

Language: Английский

Citations

1
Implications of gene × environment interactions in post-traumatic stress disorder risk and treatment DOI Creative Commons
Carina Seah, Anne Elizabeth Sidamon‐Eristoff, Laura M. Huckins

et al.

Journal of Clinical Investigation, Journal Year: 2025, Volume and Issue: 135(5)

Published: March 2, 2025

Exposure to traumatic stress is common in the general population. Variation brain's molecular encoding of potentially contributes heterogeneous clinical outcomes response experiences. For instance, only a minority those exposed trauma will develop post-traumatic disorder (PTSD). Risk for PTSD at least partially heritable, with growing number genetic factors identified through GWAS. A major limitation studies that they capture component risk, whereas by definition requires an environmental exposure. Furthermore, extent, timing, and type affects susceptibility. Here, we discuss mechanisms risk together gene × environment interactions, focus on how either might inform screening individuals high disease, reveal biological one day yield novel therapeutics, impact best practices even today. To close, interaction sex, gender, race, implications treatment. Altogether, suggest predicting, preventing, treating require integrating both genotypic information.

Language: Английский

Citations

1
Cell type-specific and disease-associated eQTL in the human lung DOI Creative Commons
Heini M. Natri, Christina B. Azodi,

Lance Peter

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: March 21, 2023

Abstract Common genetic variants confer substantial risk for chronic lung diseases, including pulmonary fibrosis (PF). Defining the control of gene expression in a cell-type-specific and context-dependent manner is critical understanding mechanisms through which variation influences complex traits disease pathobiology. To this end, we performed single-cell RNA-sequencing tissue from 67 PF 49 unaffected donors. Employing pseudo-bulk approach, mapped quantitative trait loci (eQTL) across 38 cell types, observing both shared type-specific regulatory effects. Further, identified disease-interaction eQTL demonstrated that class associations more likely to be cell-type specific linked cellular dysregulation PF. Finally, connected their targets disease-relevant types. These results indicate context determines impact on expression, implicates context-specific as key regulators homeostasis disease.

Language: Английский

Citations

17
Integrated single-cell transcriptomics and epigenomics reveals strong germinal center–associated etiology of autoimmune risk loci DOI
Hamish W. King, Kristen L. Wells,

Zohar Shipony

et al.

Science Immunology, Journal Year: 2021, Volume and Issue: 6(64)

Published: Oct. 13, 2021

The germinal center (GC) response is critical for both effective adaptive immunity and establishing peripheral tolerance by limiting autoreactive B cells. Dysfunction in these processes can lead to defective immune responses infection or contribute autoimmune disease. To understand the gene regulatory principles underlying GC response, we generated a single-cell transcriptomic epigenomic atlas of human tonsil, widely studied representative lymphoid tissue. We characterize diverse cell subsets build trajectory dynamic expression transcription factor activity during activation, formation, plasma differentiation. subsequently leverage type–specific maps interpret potential impact genetic variants implicated autoimmunity, revealing that many exhibit their greatest GC-associated cellular populations. These included loci linked with known roles biology (

Language: Английский

Citations

36
Allelic imbalance of chromatin accessibility in cancer identifies candidate causal risk variants and their mechanisms DOI
Dennis Grishin, Alexander Gusev

Nature Genetics, Journal Year: 2022, Volume and Issue: 54(6), P. 837 - 849

Published: June 1, 2022

Language: Английский

Citations

25
Gene expression and splicing QTL analysis of blood cells in African American participants from the Jackson Heart Study DOI

Jia Wen,

Quan Sun, Le Huang

et al.

Genetics, Journal Year: 2024, Volume and Issue: 228(1)

Published: July 26, 2024

Abstract Most gene expression and alternative splicing quantitative trait loci (eQTL/sQTL) studies have been biased toward European ancestry individuals. Here, we performed eQTL sQTL analyses using TOPMed whole-genome sequencing-derived genotype data RNA-sequencing from stored peripheral blood mononuclear cells in 1,012 African American participants the Jackson Heart Study (JHS). At a false discovery rate of 5%, identified 17,630 unique credible sets covering 16,538 genes; 24,525 9,605 genes, with lead QTL at P < 5e−8. About 24% independent eQTLs sQTLs minor allele frequency > 1% JHS were rare (minor 0.1%), therefore unlikely to be detected, Finally, created an open database, which is freely available online, allowing fast query bulk download our results.

Language: Английский

Citations

6