Biology subjects

Pique-Regi, R.

Publications and source records attributed to Pique-Regi, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-cell transcriptomics of heterogeneous patient-derived organoids reveals novel therapeutic targets in high-grade serous ovarian cancer

High-grade serous ovarian carcinoma (HGSOC) is characterized by widespread peritoneal dissemination and poor long-term survival, largely driven by metastatic relapse following initial response to chemotherapy. Defining the molecular programs that enable tumor progression from the primary ovarian site to metastatic niches remains a key challenge. Here, we leverage patient-derived organoids (PDOs) coupled with single-cell RNA sequencing (scRNA-seq) to interrogate tumor evolution and identify regulators of metastatic competence in HGSOC. We profiled PDOs and matched formalin-fixed paraffin-embedded (FFPE) tumor samples from ovarian and omental disease sites across seven patients. Single-cell transcriptomic analysis revealed conserved and patient-specific cellular states and enabled reconstruction of inferred trajectories of tumor progression. Comparative trajectory analysis identified gene expression programs associated with metastatic transition from ovarian to omental tumors. Among these, the heparan sulfate proteoglycan AGRIN emerged as a consistently upregulated gene along the metastatic axis. Cell-cell communication analyses suggested that AGRIN-mediated signaling involves both epithelial tumor cells and stromal components, implicating the extracellular matrix in shaping metastatic behavior through mechanotransduction and integrin-associated pathways. Functional validation using genetic depletion of AGRIN in ovarian cancer cell lines demonstrated reduced migratory and invasive capacity, supporting a causal role for AGRIN in promoting metastatic phenotypes. Together, these findings identify AGRIN as a regulator of metastatic competence in HGSOC and highlight extracellular matrix-associated signaling as a key driver of disease progression. More broadly, this study demonstrates that PDO-based single-cell transcriptomic approaches can uncover actionable regulators of metastasis and provide a scalable framework for therapeutic target discovery across cancer types. SignificancePatient-derived organoids analyzed by single-cell transcriptomics reveal dynamic tumor evolution and uncover AGRIN as a regulator of metastatic competence in HGSOC, demonstrating the utility of living tumor models for therapeutic target discovery.

cancer biology↗

bioRxiv2026

fastdemux: Robust SNP-based demultiplexing of single-cell population genomics data

Sample multiplexing reduces cost and batch effects in population based large-scale single-cell genomics studies but requires accurate and scalable computational demultiplexing. Existing genotype-based methods, such as demuxlet, provide high accuracy but can be computationally slow and memory intensive as the number of cells, donors, and informative variants increases. Here, we introduce fastdemux, a scalable genotype-based demultiplexing framework based on a diagonal linear discriminant analysis (DLDA) model that substantially improves computational efficiency while maintaining accurate donor assignment. Using a pooled single-cell RNA-seq dataset from unrelated donors, we benchmarked fastdemux against demuxlet, vireo, and demuxalot.fastdemux achieved comparable or improved demultiplexing accuracy while reducing runtime and peak memory usage by orders of magnitude relative to alternative methods. Performance remained robust across varying sequencing depths and genotype SNP filtering thresholds. In addition, the DLDA framework naturally extends to doublet and higher-order multiplet detection. We also show thatfastdemux works well with scATAC-seq data where genetic variants are more sparsely covered. Together, these results establish fastdemux as an efficient and scalable solution for genetic demultiplexing of pooled single-cell datasets.

bioinformatics↗

bioRxiv2025

Psychological stress and social support are associated with opposing single-cell pro-inflammatory gene regulatory mechanisms in adults

Psychological stress is linked to elevated markers of chronic inflammation, whereas social support is associated with lower levels; yet, the molecular mechanisms mediating these effects are poorly understood. We investigated gene regulatory variation in peripheral blood mononuclear cells (PBMCs) from 165 self-reported African American adults (aged 50-89 years) using single-cell RNA sequencing (scRNA-seq) and single-cell chromatin accessibility (scATAC-seq). Self-reported psychological stress and social support were associated with differential expression of 1,956 and 1,296 genes, respectively (10% FDR), primarily in CD4+ T cells and monocytes. Interferon signaling genes showed high expression in individuals with high psychological stress and low expression in those with high social support; this pattern mirrored gene expression in individuals with elevated circulating inflammatory markers (IFN-{gamma}, TNF-, IL-6). Genome-wide transcription factor (TF) motif analysis identified stress- and social support-associated changes in motif activity for 70 and 116 TFs, respectively, with 87 motifs enriched near differentially expressed genes. In CD4+ T cells, high psychological stress corresponded to increased IRF and STAT TF motif activity (interferon pathway), while social support was associated with reduced activity and expression in these pathways. We used an immune challenge paradigm (i.e., LPS stimulation), which confirmed the biological pathways of these gene regulatory effects. Our results demonstrate that psychological stress and social support modulate immune gene regulation at the single-cell level, revealing mechanistic links between psychosocial factors and inflammation, and suggesting that social support may promote immunological health.

genomics↗

bioRxiv2024

Probabilistic Fine-mapping of Putative Causal Genes

Integrative genetic analysis of molecular and complex trait data, including colocalization analysis and transcriptome-wide association studies (TWAS), has shown promise in linking GWAS findings to putative causal genes (PCGs) underlying complex diseases. However, existing methods have notable limitations: TWAS tend to produce an excess of false-positive PCGs, while colocalization analysis often lacks sufficient statistical power, resulting in many false negatives. This paper introduces a probabilistic fine-mapping method, INTERFACE, which is designed to identify putative causal genes while accounting for direct variant-to-trait effects within genomic regions harboring multiple gene candidates. INTERFACE lever-ages interpretable, data-informed priors that incorporate both colocalization and TWAS evidence, enhancing the sensitivity and specificity of PCG inference and setting it apart from existing methods. Additionally, INTERFACE implements analytical measures to improve the accuracy of gene-to-trait effect estimation. We apply INTERFACE to METSIM plasma metabolite GWASs and UK Biobank pQTL data to identify causal genes regulating blood metabolite levels and demonstrate the unique biological insights INTERFACE provides.

genetics↗

bioRxiv2024

Integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits.

We present multi-integration of transcriptome-wide association studies and colocalization (Multi-INTACT), an algorithm that models multiple gene products (e.g. encoded RNA transcript and protein levels) to implicate causal genes and relevant gene products. In simulations, Multi-INTACT achieves higher power than existing methods, maintains calibrated false discovery rates, and detects the true causal gene product(s). We apply Multi-INTACT to GWAS on 1,408 metabolites, integrating the GTEx expression and UK Biobank protein QTL datasets. Multi-INTACT infers 52% to 109% more metabolite causal genes than protein-alone or expression-alone analyses and indicates both gene products are relevant for most gene nominations.

bioinformatics↗

bioRxiv2023

Functional characterization of eQTLs and asthma risk loci with scATAC-seq across immune cell types and contexts

Cis-regulatory elements (CREs) control gene transcription dynamics across cell types and in response to the environment. In asthma, multiple immune cell types play an important role in the inflammatory process. Genetic variants in CREs can also affect gene expression response dynamics and contribute to asthma risk. However, the regulatory mechanisms underlying control of transcriptional dynamics across different environmental contexts and cell-types at single cell resolution remains to be elucidated. To resolve this question, we performed scATAC-seq in activated peripheral blood mononuclear cells (PBMC) from 16 children with asthma with phytohemagglutinin (PHA) or lipopolysaccharide (LPS), and treated with dexamethasone (DEX), an antiinflammatory glucocorticoid. We analyzed changes in chromatin accessibility, measured transcription factor motif activity, and identified treatment and cell-type specific transcription factors that drive changes in both gene expression mean and variability. We observed strong positive linear dependence between motif response and their target gene expression changes, but negative in variability changes. This result suggests that an increase of transcription factor binding tightens the variability of gene expression around the mean. We then annotated genetic variants in chromatin accessibility peaks and response motifs followed by computational fine-mapping of eQTL signals from a pediatric asthma cohort. We found that eQTLs were 5-fold enriched in peaks with response motifs and refined the credible set for 410 asthma risk genes, with 191 having the causal variant in response motifs. In conclusion, scATAC-seq enhances the understanding of molecular mechanisms for asthma risk variants mediated by gene expression.

genomics↗

bioRxiv2023

Comprehensive analysis of the functional impact of single nucleotide variants of human CHEK2

Loss of function mutations in the checkpoint kinase gene CHEK2 are associated with increased risk of breast and other cancers. Most of the 3,188 unique amino acid changes that can result from non-synonymous single nucleotide variants (SNVs) of CHEK2, however, have not been tested for their impact on the function of the CHEK2-enocded protein (CHK2). One successful approach to testing the function of variants has been to test for their ability to complement mutations in the yeast ortholog of CHEK2, RAD53. This approach has been used to provide functional information on over 100 CHEK2 SNVs and the results align with functional assays in human cells and known pathogenicity. Here we tested all but two of the 4,887 possible SNVs in the CHEK2 open reading frame for their ability to complement RAD53 mutants using a novel high throughput technique. Among the non-synonymous changes, 770 were damaging to protein function while 2,417 were tolerated. The results correlate well with previous structure and function data and provide a first or additional functional assay for all the variants of uncertain significance identified in clinical databases. Combined, this approach can be used to help predict the pathogenicity of CHEK2 variants of uncertain significance that are found in patient screening and could be applied to other cancer risk genes.

cancer biology↗

bioRxiv2023

Single Nucleus Transcriptomics Reveals Pervasive Glial Activation in Opioid Overdose Cases

Dynamic interactions of neurons and glia in the ventral midbrain (VM) mediate reward and addiction behavior. We studied gene expression in 212,713 VM single nuclei from 95 human opioid overdose cases and drug-free controls. Chronic exposure to opioids left numerical proportions of VM glial and neuronal subtypes unaltered, while broadly affecting glial transcriptomes, involving 9.5 - 6.2% of expressed genes within microglia, oligodendrocytes, and astrocytes, with prominent activation of the immune response including interferon, NFkB signaling, and cell motility pathways, sharply contrasting with down-regulated expression of synaptic signaling and plasticity genes in VM non-dopaminergic neurons. VM transcriptomic reprogramming in the context of opioid exposure and overdose included 325 genes with genetic variation linked to substance use traits in the broader population, thereby pointing to heritable risk architectures in the genomic organization of the brains reward circuitry.

neuroscience↗

bioRxiv2022

Poverty shapes the transcriptome of immune cells

Social factors influence health outcomes and life expectancy. Individuals living in poverty often have adverse health outcomes related to chronic inflammation that affect the cardiovascular, renal, and pulmonary systems. Negative psychosocial experiences are associated with transcriptional changes in genes associated with complex traits. However, the underlying molecular mechanisms by which poverty increases the risk of disease and health disparities are still not fully understood. To bridge the gap in our understanding of the link between living in poverty and adverse health outcomes, we performed RNA sequencing of blood immune cells from 204 participants of the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS) study in Baltimore, Maryland. We identified 138 genes differentially expressed in association with poverty. Genes differentially expressed were enriched in wound healing and coagulation processes. Of the genes differentially expressed in individuals living in poverty, EEF1DP7 and VIL1 are also associated with hypertension in transcriptome-wide association studies. Our results suggest that living in poverty influences inflammation and the risk for cardiovascular disease through gene expression changes in immune cells.

genomics↗

bioRxiv2022

Characterization of caffeine response regulatory variants in vascular endothelial cells

Genetic variants in gene regulatory sequences can modify gene expression and mediate the molecular response to environmental stimuli. In addition, genotype-environment interactions (GxE) contribute to complex traits such as cardiovascular disease. Caffeine is the most widely consumed stimulant and is known to produce a vascular response. To investigate GxE for caffeine, we treated vascular endothelial cells with caffeine and used a massively parallel reporter assay to measure allelic effects on gene regulation for over 43,000 genetic variants. We identified 665 variants with allelic effects on gene regulation and 29 variants that regulate the gene expression response to caffeine (GxE, FDR<10%). When overlapping our GxE results with eQTLs colocalized with CAD and hypertension, we dissected their regulatory mechanisms and showed a modulatory role for caffeine. Our results demonstrate that massively parallel reporter assay is a powerful approach to identify and molecularly characterize GxE in the specific context of caffeine consumption.

genomics↗

bioRxiv2022

Environmental and genetic drivers of population differences in SARS-CoV-2 immune responses

Humans display vast clinical variability upon SARS-CoV-2 infection1-3, partly due to genetic and immunological factors4. However, the magnitude of population differences in immune responses to SARS-CoV-2 and the mechanisms underlying such variation remain unknown. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells from 222 healthy donors of various ancestries stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces a weaker, but more heterogeneous interferon-stimulated gene activity than influenza A virus, and a unique pro-inflammatory signature in myeloid cells. We observe marked population differences in transcriptional responses to viral exposure that reflect environmentally induced cellular heterogeneity, as illustrated by higher rates of cytomegalovirus infection, affecting lymphoid cells, in African-descent individuals. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell proportions on population differences in immune responses, with genetic variants having a narrower but stronger effect on specific loci. Additionally, natural selection has increased immune response differentiation across populations, particularly for variants associated with SARS-CoV-2 responses in East Asians. We document the cellular and molecular mechanisms through which Neanderthal introgression has altered immune functions, such as its impact on the myeloid response in Europeans. Finally, colocalization analyses reveal an overlap between the genetic architecture of immune responses to SARS-CoV-2 and COVID-19 severity. Collectively, these findings suggest that adaptive evolution targeting immunity has also contributed to current disparities in COVID-19 risk.

genomics↗

bioRxiv2022

Probabilistic integration of transcriptome-wide association studies and colocalization analysis prioritizes molecular pathways of complex traits

Transcriptome-wide association studies (TWAS) and colocalization analysis are complementary integrative genetic association approaches routinely used to identify functional units underlying complex traits in post-genome-wide association study (post-GWAS) analyses. Recent studies suggest that both approaches are individually imperfect, but joint usage can yield robust and powerful inference results. This paper introduces a new statistical framework, INTACT, to perform probabilistic integration of TWAS and colocalization evidence for implicating putative causal genes. This procedure is flexible and can work with a wide range of existing TWAS and colocalization approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly-desirable feature, we describe an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated TWAS and colocalization analysis results. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. Finally, we apply the proposed methods to the GTEx data and a variety of GWAS summary statistics derived from complex and molecular traits previously analyzed by Hukku et al. and Sinnott-Armstrong et al. We find empirical evidence that the proposed methods improve and complement existing putative gene implication methods and are advantageous in evaluating and identifying key gene sets and biological pathways.

genetics↗

bioRxiv2022

Deconstructing cold-induced brown adipocyte neogenesis in mice

Cold-exposure triggers neogenesis in classic interscapular brown adipose tissue (BAT) that involves activation of b1-adrenergic receptors, proliferation of PDGFRA+ adipose tissue stromal cells (ASCs), and recruitment of immune cells whose phenotypes are presently unknown. Single- cell RNA-sequencing (scRNA-seq) identified three ASC subpopulations that occupied distinct tissue locations. Of these, interstitial ASC1 were found to be direct precursors of new brown adipocytes (BA). Surprisingly, knockout of b1-adrenergic receptors in ASCs did not prevent cold- induced neogenesis, whereas pharmacological activation of the b3-adrenergic receptor on BAs was sufficient, suggesting that signals derived from mature BAs indirectly trigger ASC proliferation and differentiation. In this regard, cold exposure induced the delayed appearance of multiple macrophage and dendritic cell populations whose recruitment strongly correlated with the onset and magnitude of neogenesis across diverse experimental conditions. High resolution immunofluorescence and single molecule fluorescence in situ hybridization demonstrated that cold-induced neogenesis involves dynamic interactions between ASC1 and recruited immune cells that occur on the micrometer scale in distinct tissue regions. Our results indicate that neogenesis is not a reflexive response of progenitors to b-adrenergic signaling, but rather is a complex adaptive response to elevated metabolic demands within brown adipocytes.

cell biology↗

bioRxiv2022

The single-cell atlas of the murine reproductive tissues during preterm labor

Preterm birth, the leading cause of perinatal morbidity and mortality worldwide, frequently results from the syndrome of preterm labor. Intra-amniotic infection is the best-established causal link to preterm labor, and involves premature activation of the parturition cascade in the reproductive tissues. Herein, we utilized single-cell RNA-sequencing (scRNA-seq) to generate a single-cell atlas of the murine uterus, decidua, and cervix in a model of infection-induced preterm labor. We show that preterm labor affects the transcriptomic profiles of specific immune and non-immune cell subsets. Shared and tissue-specific gene expression signatures were identified among affected cells. Importantly, determination of intercellular communications implicates specific cell types preterm labor-associated signaling pathways across tissues. Last, in silico comparison of murine and human uterine cell-cell interactions reveals conserved signaling pathways implicated in labor. Thus, scRNA-seq provides new insights into the preterm labor-driven cellular landscape and communications in the reproductive tissues.

immunology↗

bioRxiv2021

Analysis of transcriptional changes associated with pubertal development

Puberty is an important developmental period marked by hormonal, metabolic and immune changes. Puberty also marks a shift in sex differences in susceptibility to asthma. Yet, little is known about the gene expression changes in immune cells that occur during pubertal development. Here we assess pubertal development and leukocyte gene expression in a longitudinal cohort of 251 children with asthma. We identify substantial gene expression changes associated with age and pubertal development. Gene expression changes between pre- and post-menarcheal females suggest a shift from predominantly innate to adaptive immunity. We show that genetic effects on gene expression change dynamically during pubertal development. Gene expression changes during puberty are correlated with gene expression changes associated with asthma and may explain sex differences in prevalence. Our results show that molecular data used to study the genetics of early onset diseases should consider pubertal development as an important factor that modifies the transcriptome.

genomics↗

bioRxiv2021

Genetic control of the dynamic transcriptional response to immune stimuli and glucocorticoids at single cell resolution

Synthetic glucocorticoids, such as dexamethasone, have been used as treatment for many immune conditions, such as asthma and more recently severe COVID-19. Single cell data can capture more fine-grained details on transcriptional variability and dynamics to gain a better understanding of the molecular underpinnings of inter-individual variation in drug response. Here, we used single cell RNA-seq to study the dynamics of the transcriptional response to glucocorticoids in activated Peripheral Blood Mononuclear Cells from 96 African American children. We employed novel statistical approaches to calculate a mean-independent measure of gene expression variability and a measure of transcriptional response pseudotime. Using these approaches, we demonstrated that glucocorticoids reverse the effects of immune stimulation on both gene expression mean and variability. Our novel measure of gene expression response dynamics, based on the diagonal linear discriminant analysis, separated individual cells by response status on the basis of their transcriptional profiles and allowed us to identify different dynamic patterns of gene expression along the response pseudotime. We identified genetic variants regulating gene expression mean and variability, including treatment-specific effects, and demonstrated widespread genetic regulation of the transcriptional dynamics of the gene expression response.

genomics↗

bioRxiv2021

A signature of Neanderthal introgression on molecular mechanisms of environmental responses

Ancient human migrations led to the settlement of population groups in varied environmental contexts worldwide. The extent to which adaptation to local environments has shaped human genetic diversity is a longstanding question in human evolution. Recent studies have suggested that introgression of archaic alleles in the genome of modern humans may have contributed to adaptation to environmental pressures such as pathogen exposure. Functional genomic studies have demonstrated that variation in gene expression across individuals and in response to environmental perturbations is a main mechanism underlying complex trait variation. We considered gene expression response to in vitro treatments as a molecular phenotype to identify genes and regulatory variants that may have played an important role in adaptations to local environments. We investigated if Neanderthal introgression in the human genome may contribute to the transcriptional response to environmental perturbations. To this end we used eQTLs for genes differentially expressed in a panel of 52 cellular environments, resulting from 5 cell types and 26 treatments, including hormones, vitamins, drugs, and environmental contaminants. We found that SNPs with introgressed Neanderthal alleles (N-SNPs) disrupt binding of transcription factors important for environmental responses, including ionizing radiation and hypoxia, and for glucose metabolism. We identified an enrichment for N-SNPs among eQTLs for genes differentially expressed in response to 8 treatments, including glucocorticoids, caffeine, and vitamin D. Using Massively Parallel Reporter Assays (MPRA) data, we validated the regulatory function of 21 introgressed Neanderthal variants in the human genome, corresponding to 8 eQTLs regulating 15 genes that respond to environmental perturbations. These findings expand the set of environments where archaic introgression may have contributed to adaptations to local environments in modern humans and provide experimental validation for the regulatory function of introgressed variants.

evolutionary biology↗

bioRxiv2021

Environmental enrichment induces epigenomic and genome organization changes relevant for cognitive function

In early development, the environment triggers mnemonic epigenomic programs resulting in memory and learning experiences to confer cognitive phenotypes into adulthood. To uncover how environmental stimulation impacts the epigenome and genome organization, we used the paradigm of environmental enrichment (EE) in young mice constantly receiving novel stimulation. We profiled epigenome and chromatin architecture in whole cortex and sorted neurons by deep-sequencing techniques. Specifically, we studied chromatin accessibility, gene and protein regulation, and 3D genome conformation, combined with predicted enhancer and chromatin interactions. We identified increased chromatin accessibility, transcription factor binding including CTCF-mediated insulation, differential occupancy of H3K36me3 and H3K79me2, and changes in transcriptional programs required for neuronal development. EE stimuli led to local genome re-organization by inducing increased contacts between chromosomes 7 and 17 (inter-chromosomal). Our findings support the notion that EE-induced learning and memory processes are directly associated with the epigenome and genome organization. Highlights- Environmental enrichment (EE) alters chromatin conformation, CTCF binding, and spatially 3D genome changes, thereby regulating cognitive function during the first steps of life after birth. - Transcription-associated gene body marks H3K79me2 and H3K36me3 are differently influenced by EE in cortical brain cells and binding is exacerbated upon stimulation in an age-dependent manner. - EE-induced changes of 3D genome organization increase inter-chromosomal interactions of genes associated with synaptic transmission and AMPA receptor genes on chromosomes 7 and 17.

neuroscience↗