Biology subjects

Margoliash, J.

Publications and source records attributed to Margoliash, J..

5 recordsLinked to original sources

bioRxiv2026

Haplotype-based fine-mapping of variant associations for complex traits

Genome-wide association studies (GWAS) have identified tens of thousands of associations between genomic regions and complex traits in humans, but identifying the causal variants underlying these associations is challenging. Statistical fine-mapping techniques attempt to quantify the probability of causality of individual variants while accounting for the correlation induced by linkage disequilibrium (LD) between nearby variants. Existing fine-mapping solutions are limited to considering additive and independent contributions of individual variants, and also assume the causal variant is included in the analysis. Here, we introduce a novel fine-mapping method, happler, which models the effects of variant haplotypes (sets of alleles of two or more variants in cis) in addition to individual variants. By identifying haplotype proxies for causal variants, happler can infer additional effects including those driven by combinations of variants in cis and ungenotyped causal variants, such as complex structural variants, which are in some cases better tagged by one or more haplotypes than by individual SNPs. Simulation experiments show that whereas happler can correctly identify causal haplotype effects, traditional methods based on individual variants can produce inconclusive results in such cases. We applied happler to identify 32 haplotypes associated with gene expression using 359 individuals from the Geuvadis dataset. Of these, five are confidently fine-mapped, with stronger posterior inclusion probabilities than any individual variant, in an external cohort from the Genotype Tissue Expression (GTEx) project. Finally, we used the AoU dataset to demonstrate the utility of haplotypes for tagging rare causal variants that are absent from the input dataset.

bioinformatics↗

bioRxiv2026

The contribution of short tandem repeats to splicing variation in the human cortex

BackgroundSplicing disruption has been implicated in a range of heritable phenotypes, including numerous psychiatric and neurological disorders. Recent studies have identified thousands of common genetic variants impacting splicing in brain and other tissues, but have focused largely on single nucleotide polymorphisms or short indels. Despite growing evidence that genetic variation at short tandem repeats (STRs) influences splicing, large-scale studies of STR-mediated splicing in brain have been limited by low sample sizes of available RNA-seq data or exclusion of certain classes of STRs, such as homopolymers which account for around half of all STRs. ResultsIn this study, we leveraged deep RNA-seq and SNP array data from 336 human dorsolateral prefrontal cortex (DLPFC) samples collected by the Human Brain Collection Core (HBCC). We imputed 445,720 STRs into available genotype data and identified 51,343 unique STRs for which copy number is significantly associated with one or multiple alternative splicing events of nearby genes (spliceSTRs). We prioritized and characterized candidate causal spliceSTRs using three orthogonal fine-mapping strategies which identified 1,313 high-confidence fine-mapped spliceSTRs. Our analyses revealed strong associations between copy number of certain repeat units and binding of specific RNA-binding proteins (RBPs), including a previously known relationship between HNRNPL and AC repeat length, suggesting that the functional impact of some spliceSTRs may be mediated through their binding affinity for RBPs. Finally, co-localization analyses using summary statistics from genome-wide association studies (GWAS) for 6 brain-related disorders identified multiple signals that may be driven by spliceSTRs, including a previously identified GTn repeat that is a spliceSTR for PLEKHA1 associated with Alzheimers disease as well as a newly identified AGGn spliceSTR in SEPTIN3 co-localized with schizophrenia. ConclusionsTogether, our findings highlight the role of STRs in regulating alternative splicing in the human brain, suggest a general relationship between STR polymorphism and RBP-mediated splicing events, and identify specific spliceSTRs detected by co-localization analysis as candidate causal variants for brain-related disorders.

genomics↗

bioRxiv2024

Polymorphic tandem repeats shape single-cell gene expression across the immune landscape

Tandem repeats (TRs) - highly polymorphic, repetitive sequences across the human genome - are important regulators of gene expression but remain underexplored due to challenges in accurate genotyping and analysis1. Here, we generate new whole genome and single-cell RNA sequencing from >5.4 million blood-derived cells across 1,925 individuals in two cohorts [Cuomo et al., accompanying manuscript], and perform meta-analysis to characterize the impact of variation in >1.7 million TR loci on immune cell type-specific gene expression. We identify >69,000 single-cell expression TR loci (sc-eTRs), 30.7% of which are specific to one of 28 immune cell types, and reveal dynamic regulatory effects using cell-state inference. Matched single-cell ATAC sequencing profiles from >3.4 million nuclei in 922 individuals [Xue et al., accompanying manuscript]. uncover chromatin accessibility QTLs for nearly one-third of expression-associated TRs, supporting coordinated effects on cis-regulatory architecture. Fine-mapping implicates 1,490 TRs as candidate causal drivers of gene expression in 6.1% of tested genes, and colocalization analyses highlight >200 genes in which TRs likely mediate genetic associations with immune and hematological traits. Together, these results provide a genome-wide, multiomic view of TR-mediated regulation in the human immune system, establishing TRs as key contributors to cell type-specific regulatory variation and complex trait architecture.

genomics↗

bioRxiv2022

Polymorphic short tandem repeats make widespread contributions to blood and serum traits

Short tandem repeats (STRs), genomic regions each consisting of a sequence of 1-6 base pairs repeated in succession, represent one of the largest sources of human genetic variation. However, many STR effects are not captured well by standard genome-wide association studies (GWAS) or downstream analyses that are mostly based on single nucleotide polymorphisms (SNPs). To study the involvement of STRs in complex traits, we imputed genotypes for 445,720 autosomal STRs into genotype array data from 408,153 White British UK Biobank participants and tested for association with 44 blood and serum biomarker phenotypes. We used two fine-mapping methods, SuSiE and FINEMAP, to identify 119 high-confidence STR-trait associations across 93 unique STRs predicted as causal variants under all fine-mapping settings tested. Using these results, we estimate that STRs account for 5.2-7.6% of causal variants identifiable from GWAS signals for these traits. Our high confidence STR-trait associations implicate STRs in some of the strongest hits for multiple phenotypes, including a CTG repeat in APOB associated with circulating apolipoprotein B levels, a CGG repeat in the promoter of CBL associated with multiple platelet traits and a poly-A repeat in TAOK1 associated with mean platelet volume. Replication analyses in additional population groups and orthogonal expression data further support the role of a subset of the candidate STRs we identify. Together, our study suggests that polymorphic tandem repeats make widespread contributions to complex traits, provides a set of stringently selected candidate causal STRs, and demonstrates the need to routinely consider a more complete view of human genetic variation in GWAS.

genetics↗

bioRxiv2020

TRTools: a toolkit for genome-wide analysis of tandem repeats

SummaryA rich set of tools have recently been developed for performing genome-wide genotyping of tandem repeats (TRs). However, standardized tools for downstream analysis of these results are lacking. To facilitate TR analysis applications, we present TRTools, a Python library and a suite of command-line tools for filtering, merging, and quality control of TR genotype files. TRTools utilizes an internal harmonization module making it compatible with outputs from a wide range of TR genotypers. AvailabilityTRTools is freely available at https://github.com/gymreklab/TRTools. Contactmgymrek@eng.ucsd.edu Supplementary informationSupplementary data are available at bioRxiv.

bioinformatics↗