Biology subjects

Lapinska, S.

Publications and source records attributed to Lapinska, S..

4 recordsLinked to original sources

bioRxiv2025

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblast reveals shared allelic effects between Latin American and European ancestries

Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n=150) and Latin American (n=96) ancestries. Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R{superscript 2} [≥] 0.93 for eQTL effect sizes and R{superscript 2} [≥] 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 high-confidence (posterior probability > 90 %) regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations.

genomics↗

bioRxiv2023

Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders

Genome-wide association studies (GWAS) have uncovered susceptibility loci associated with psychiatric disorders like bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome with unknown causal mechanisms of the link between genetic variation and disease risk. Expression quantitative trait loci (eQTL) analysis of bulk tissue is a common approach to decipher underlying mechanisms, though this can obscure cell-type specific signals thus masking trait-relevant mechanisms. While single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell type proportions and cell type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-Seq from 1,730 samples derived from whole blood in a cohort ascertained for individuals with BP and SCZ this study estimated cell type proportions and their relation with disease status and medication. We found between 2,875 and 4,629 eGenes for each cell type, including 1,211 eGenes that are not found using bulk expression alone. We performed a colocalization test between cell type eQTLs and various traits and identified hundreds of associations between cell type eQTLs and GWAS loci that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on cell type expression regulation and found examples of genes that are differentially regulated dependent on lithium use. Our study suggests that computational methods can be applied to large bulk RNA-Seq datasets of non-brain tissue to identify disease-relevant, cell type specific biology of psychiatric disorders and psychiatric medication.

genomics↗

bioRxiv2021

Fitness effects of CRISPR endonucleases in Drosophila melanogaster populations

CRISPR/Cas9 systems provide a highly efficient and flexible genome editing technology with numerous potential applications in areas ranging from gene therapy to population control. Some proposed applications involve CRISPR/Cas9 endonucleases integrated into an organisms genome, which raises questions about potentially harmful effects to the transgenic individuals. One application where this is particularly relevant are CRISPR-based gene drives, which promise a mechanism for rapid genetic alteration of entire populations. The performance of such drives can strongly depend on fitness costs experienced by drive carriers, yet relatively little is known about the magnitude and causes of these costs. Here, we assess the fitness effects of genomic CRISPR/Cas9 expression in Drosophila melanogaster cage populations by tracking allele frequencies of four different transgenic constructs, designed to disentangle direct fitness costs due to the integration, expression, and target-site activity of Cas9 from costs due to potential off-target cleavage. Using a maximum likelihood framework, we find a moderate level of fitness costs due to off-target effects but do not detect significant direct costs. Costs of off-target effects are minimized for a construct with Cas9HF1, a high-fidelity version of Cas9. We further demonstrate that using Cas9HF1 instead of standard Cas9 in a homing drive achieves similar drive conversion efficiency. Our results suggest that gene drives should be designed with high-fidelity endonucleases and may have implications for other applications that involve genomic integration of CRISPR endonucleases.

evolutionary biology↗

bioRxiv2020

Large uncertainty in individual PRS estimation impacts PRS-based risk stratification

Large-scale genome-wide association studies have enabled polygenic risk scores (PRS), which estimate the genetic value of an individual for a given trait. Since PRS accuracy is typically assessed using cohort-level metrics (e.g., R2), uncertainty in PRS estimates at individual level remains underexplored. Here we show that Bayesian PRS methods can estimate the variance of an individuals PRS and can yield well-calibrated credible intervals for the genetic value of a single individual. For real traits in the UK Biobank (N=291,273 unrelated "white British") we observe large variance in individual PRS estimates which impacts interpretation of PRS-based stratification; for example, averaging across 13 traits, only 0.8% (s.d. 1.6%) of individuals with PRS point estimates in the top decile have their entire 95% credible intervals fully contained in the top decile. We provide an analytical estimator for individual PRS variance--a function of SNP-heritability, number of causal SNPs, and sample size--and observe high concordance with individual variances estimated via posterior sampling. Finally as an example of the utility of individual PRS uncertainties, we explore a probabilistic approach to PRS-based stratification that estimates the probability of an individuals genetic value to be above a prespecified threshold. Our results showcase the importance of incorporating uncertainty in individual PRS estimates into subsequent analyses.

genomics↗