Biology subjects

Amundadottir, L. T.

Publications and source records attributed to Amundadottir, L. T..

3 recordsLinked to original sources

bioRxiv2026

Functional characterization of a multi-cancer risk locus on chromosome band 2q33.1 near CASP8

Genome-wide association studies (GWAS) of melanoma have identified numerous susceptibility loci. However, causal genes and variants underlying risk have yet to be established for most. It is becoming apparent that many functional variants underlying complex traits act via cis-regulation that may be context-specific, dependent on availability of specific transcription factors/complexes in specific cell types and cell-states. To characterize a risk locus on chromosome band 2q33.1 associated with melanoma, breast cancer, and keratinocyte cancers, we integrated fine-mapping, cell-type specific expression quantitative trait locus (eQTL) analysis, a massively parallel reporter assay, individual luciferase assays, and SNP-based proteomics. Integrated analysis implicates the presence of multiple functional variants lying primarily within a promoter for CASP8. A haplotype containing rs3769823 appeared have the largest effect on expression. Strikingly, both tumor/normal context and this risk-associated haplotype play critical roles in mediating allelic cis-regulatory activity. Quantitative mass spectrometry for rs3769823 identified both E4F1, a transcriptional repressor, and IRF2, a transcriptional activator, as binding preferentially to risk-associated rs3969823-A. The binding of these transcription factors was validated via EMSA, supershift, and chromatin immunoprecipitation (ChIP) assays. The relative levels of E4F1 and IRF2 differ by cell-type and play a role in mediating transcriptional activity in a cell-type specific manner. Our results indicate that the top credible causal set variant rs3769823 likely influences expression of CASP8 and FLACC1 in a cell-type specific manner and may be a relevant functional variant for multiple cancers associated with this locus.

genetics↗

bioRxiv2024

Predictive Prioritization of Enhancers Associated with Pancreas Disease Risk

Genetic and epigenetic variations in regulatory enhancer elements increase susceptibility to a range of pathologies. Despite recent advances, linking enhancer elements to target genes and predicting transcriptional outcomes of enhancer dysfunction remain significant challenges. Using 3D chromatin conformation assays, we generated an extensive enhancer interaction dataset for the human pancreas, encompassing more than 20 donors and five major cell types, including both exocrine and endocrine compartments. We employed a network approach to parse chromatin interactions into enhancer-promoter tree models, facilitating a quantitative, genome-wide analysis of enhancer connectivity. With these tree models, we developed a machine learning algorithm to estimate the impact of enhancer perturbations on cell type-specific gene expression in the human pancreas. Orthogonal to our computational approach, we perturbed enhancer function in primary human pancreas cells using CRISPR interference and quantified the effects at the single-cell level through RNA FISH coupled with high-throughput imaging. Our enhancer tree models enabled the annotation of common germline risk variants associated with pancreas diseases, linking them to putative target genes in specific cell types. For pancreatic ductal adenocarcinoma, we found a stronger enrichment of disease susceptibility variants within acinar cell regulatory elements, despite ductal cells historically being assumed as the primary cell-of-origin. Our integrative approach--combining cell type-specific enhancer-promoter interaction mapping, computational models, and single-cell enhancer perturbation assays--produced a robust resource for studying the genetic basis of pancreas disorders.

genomics↗

bioRxiv2017

Cell-type specific eQTL of primary melanocytes facilitates identification of melanoma susceptibility genes

Most expression quantitative trait loci (eQTL) studies to date have been performed in heterogeneous tissues as opposed to specific cell types. To better understand the cell-type specific regulatory landscape of human melanocytes, which give rise to melanoma but account for <5% of typical human skin biopsies, we performed an eQTL analysis in primary melanocyte cultures from 106 newborn males. We identified 597,335 cis-eQTL SNPs prior to LD-pruning and 4,997 eGenes (FDR<0.05), which are higher numbers than in any GTEx tissue type with a similar sample size. Melanocyte eQTLs differed considerably from those identified in the 44 GTEx tissues, including skin. Over a third of melanocyte eGenes, including key genes in melanin synthesis pathways, were not observed to be eGenes in two types of GTEx skin tissues or TCGA melanoma samples. The melanocyte dataset also identified cell-type specific trans-eQTLs with a pigmentation-associated SNP for four genes, likely through its cis-regulation of IRF4, encoding a transcription factor implicated in human pigmentation phenotypes. Melanocyte eQTLs are enriched in cis-regulatory signatures found in melanocytes as well as melanoma-associated variants identified through genome-wide association studies (GWAS). Co-localization of melanoma GWAS variants and eQTLs from melanocyte and skin eQTL datasets identified candidate melanoma susceptibility genes for six known GWAS loci including unique genes identified by the melanocyte dataset. Further, a transcriptome-wide association study using published melanoma GWAS data uncovered four new loci, where imputed expression levels of five genes (ZFP90, HEBP1, MSC, CBWD1, and RP11-383H13.1) were associated with melanoma at genome-wide significant P-values. Our data highlight the utility of lineage-specific eQTL resources for annotating GWAS findings and present a robust database for genomic research of melanoma risk and melanocyte biology.

genetics↗