Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.04.04.647121

distQTL: Distribution Quantitative Trait Loci Identification by Population-Scale Single-Cell Data

Coulter, A.·Tong, C. Y.·Ni, Y.·Jiang, Y.
View original source ↗Export metadata ↓

Abstract

Mapping expression quantitative trait loci (eQTLs) is a powerful method to study how genetic variation influences gene expression. Traditional bulk eQTL methods rely on averaged gene expression across a possibly heterogeneous mixture of cells, which can obscure underlying regulatory heterogeneity. Single-cell eQTL methods circumvent the averaging artifacts, providing an immense opportunity to interrogate transcriptional regulation at a much finer resolution. Recent developments in metric space regression methods allow the use of full empirical distributions as response objects instead of simple summary statistics such as mean. Here, we leverage Frechet regression to identify distribution QTLs (distQTLs) using population-scale single-cell RNA sequencing data. We apply distQTL to the OneK1K cohort, consisting of scRNA-seq data of peripheral blood mononuclear cells from 982 donors, and compare results to various eQTL approaches based on summary statistics and mixed effects modeling. We demonstrate the superior performance of distQTL across different gene expression contexts compared to other methods and benchmark our results against findings from the Genotype-Tissue Expression Project. Finally, we orthogonally validate calls from distQTL using cell-type-specific epigenomic profiles.

Source connections

Explore related subjects

genomicsPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Coulter, A., Tong, C. Y., Ni, Y., Jiang, Y.. 2025-04-10. distQTL: Distribution Quantitative Trait Loci Identification by Population-Scale Single-Cell Data. https://doi.org/10.1101/2025.04.04.647121

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Genome-wide diversity across 130 years reveals drastic post-bottleneck genetic erosion in a recovering population of golden eagles (Aquila chrysaetos)

Many wild populations have experienced severe human-induced declines, but the genetic consequences of such bottlenecks are often poorly understood. In Finland, as well as in many other countries, golden eagles were heavily persecuted during the 19th-20th centuries, disappearing from southern regions and reaching their lowest population size in the 1950-1960s. Although conservation efforts facilitated demographic recovery, the long-term genomic consequences of the bottleneck remained unknown. Here, we used whole-genome sequencing data spanning 136 years to evaluate patterns of genetic diversity in 26 Finnish golden eagles before, during, and after the mid-20th century bottleneck. We found substantial loss of genetic variation, including an 82% reduction in genome-wide heterozygosity, a 42% decline in nucleotide diversity, a 67% reduction in Watterson's theta, and a substantial loss of variable sites. Analyses of the site frequency spectrum and Tajima's D confirmed historical population contraction, and runs of homozygosity analysis indicated elevated post-bottleneck inbreeding. These results indicate strong genetic erosion in Finnish golden eagles despite the census size recovery. Therefore, incorporating genomic indicators in conservation monitoring and performing regional assessments are necessary to guide management and preserve biodiversity in line with the Global Biodiversity Framework's goal of maintaining genetic variation.

genomics↗
bioRxiv2026

Long-read analysis of complete human 5S rDNA arrays reveals a zoned organization with two-state unit methylation linked to chromatin architecture

Despite the fundamental importance of the 5S ribosomal DNA (rDNA) to all cellular life, the landscape of its units by position along its array has remained poorly understood. Here, recent telomere-to-telomere long-read sequencing is used to resolve 5S rDNA arrays from flank to flank and to follow the state of each unit along single molecules. The array is zoned at both the sequence and the epigenetic level. Notably, methylation is bimodal at the level of the unit, and the combination of low-methylation and high-methylation units gives rise to the overall methylation pattern of the array. Moreover, the average number of low-methylation units remains relatively constant regardless of array length. Chromatin fiber sequencing (Fiber-seq) data further show that low-methylation units are more accessible, have lower nucleosome occupancy and are more frequently footprinted at the TFIIIB-binding site, consistent with analyses of ATAC-seq and ChIP-seq data from cell lines. Across species, this pattern is shared among apes, whereas other species show diverse patterns. These results provide a unit-resolved view of the human 5S rDNA array and reveal a zone-specific organization of unit methylation that is associated with chromatin architecture.

genomics↗
bioRxiv2026

Using Oyster Genomics to Understand Human Health

As sessile filter feeders that experience continuous environmental exposure, oysters, particularly Crassostrea virginica, offer a unique opportunity to understand how environmental exposure alters the genome and influence health. Furthermore, oysters must be sorted by size for market value for premium size and taste. However, it requires intensive labor, specialized equipment (tumblers), and is susceptible to environmental risks like pollution. Therefore, it is desirable to produce uniform oysters without machines. However, limitations in the previous reference genome [2] have constrained our understanding of how genes are organized and maintained in oyster populations. To this end, we harvested 240 adult oysters in same location, 120 extremely large size and 120 extremely small, controlled with all confounding factors such as age and water temperature. We perform a genome wise associate study (GWAS) using next generation whole genome sequencing, aiming to discover genomic regions associated with oyster size. Using PacBio HiFi, Illumina, and Hi-C technologies, we generated a 99.7% complete chromosome-level genome assembly for C. virginica (NCBI RefSeq GCF_053477285.1) [75]. We identified a ~13 Mb region on chromosome 1 uniquely expanded in C. virginica and enriched for innate immune and stress-response genes. To evaluate whether these structural features are reflected at the population level, we then conducted a k-mer analysis. This revealed differential sequence patterns by size, including enrichment of bacterial DNA in smaller individuals and host variation at the RNF213 locus within this region. By highlighting genome structure as a mediator of immune resilience, this work supports the use of oysters as sentinels to advance out understanding of how the dynamic reassembly of the genome due to environmental exposures influence health in human populations.

genomics↗