Biology subjects

Estonian Biobank Research Team,

Publications and source records attributed to Estonian Biobank Research Team,.

3 recordsLinked to original sources

bioRxiv2022

Omics-informed CNV calls reduce false positive rate and improve power for CNV-trait associations

Copy number variations (CNV) are believed to play an important role in a wide range of complex traits but discovering such associations remains challenging. Whilst whole genome sequencing (WGS) is the gold standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV), however these calls suffer from elevated false positive and negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNV) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (P < 3.0-10-90), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 34% compared to raw pCNVs or previous quality scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls and demonstrated its utility by improving the statistical power for downstream association analyses.

bioinformatics↗

bioRxiv2021

Prioritising Autoimmunity Risk Variants for Functional Analyses by Fine-Mapping Mutations Under Natural Selection

Pathogens imposed selective pressure on humans and shaped genetic variation in immunity genes. This can also be true for a fraction of causal variants implicated in chronic inflammatory disorders. Hence, locating adaptive mutations among candidate variants for these disorders can be a promising way to prioritize and decipher their functional response to microbial stimuli and contribution to pathogenesis. This idea has been discussed for decades, but challenges in locating adaptive SNPs hindered its application in practice. Our study addresses this issue and shows that a fraction of candidate variants for inflammatory conditions evolved under moderate and weak selection regimes (sweeps), and such variants are mappable. Using a novel powerful local-tree-based methodology, we show that 204 out of 593 risk loci for 21 autoimmune disorders contain at least one candidate SNP with strong evidence of selection. More importantly, in 28% of cases, these candidates for causal variants colocalize with SNPs under natural selection that we fine-mapped in this study. Causal SNPs under selection represent promising targets for functional experiments. Such experiments will help decipher molecular events triggered by infectious agents, a likely early event in autoimmunity. Finally, we show that a large fraction (60%) of candidate variants are either hitchhikers or linked with the selected mutation. Our findings, thus, support both hitchhiking and natural selection models, with the latter having important practical implications in medicine.

genetics↗

bioRxiv2021

Long-range regulatory effects of Neandertal DNA in modern humans

The admixture between modern humans and Neandertals has resulted in [~]2% of the genomes of present-day non-Africans being composed of Neandertal DNA. Association studies have shown that introgressed DNA significantly influences phenotypic variation in people today and that several of the phenotype-associated archaic variants had links to expression regulation as well. In general, introgressed DNA has been demonstrated to significantly affect the transcriptomic landscape in people today. However, little is known about how much of that impact is mediated through long-range regulatory effects that have been shown to explain [~]20% of expression variation. Here we identified 60 transcription factors (TFs) with their top cis-eQTL SNP being of Neandertal ancestry in GTEx and predicted long-range Neandertal DNA-induced regulatory effects by screening for the predicted target genes of those TFs. We show that genes in regions devoid of Neandertal DNA are enriched among the target genes of some of these TFs. Furthermore, archaic cis-eQTLs for these TFs included multiple candidates for local adaptation and have associations with various immune traits, schizophrenia, blood cell type composition and anthropometric measures. Finally, we show that our results can be replicated in empirical trans-eQTLs with Neandertal variants. Our results suggest that the regulatory reach of Neandertal DNA goes beyond the 40% of genomic sequence that it still covers in present-day non-Africans and that via this mechanism Neandertal DNA additionally influences the phenotypic variation in people today.

genomics↗