QTLbase: an integrative resource for quantitative trait loci across multiple human molecular phenotypes

Abstract

Recent advances in genome sequencing and functional genomic profiling have promoted many large-scale quantitative trait locus (QTL) studies, which connect genotypes with tissue/cell type-specific cellular functions from transcriptional to post-translational level. However, no comprehensive resource can perform QTL lookup across multiple molecular phenotypes and investigate the potential cascade effect of functional variants. We developed a versatile resource, named QTLbase, for interpreting the possible molecular functions of genetic variants, as well as their tissue/cell-type specificity. Overall, QTLbase has five key functions: (i) curating and compiling genome-wide QTL summary statistics for 13 human molecular traits from 233 independent studies; (ii) mapping QTL-relevant tissue/cell types to 78 unified terms according to a standard anatomogram; (iii) normalizing variant and trait information uniformly, yielding >170 million significant QTLs; (iv) providing a rich web client that enables phenome- and tissue-wise visualization; and (v) integrating the most comprehensive genomic features and functional predictions to annotate the potential QTL mechanisms. QTLbase provides a one-stop shop for QTL retrieval and comparison across multiple tissues and multiple layers of molecular complexity, and will greatly help researchers interrogate the biological mechanism of causal variants and guide the direction of functional validation. QTLbase is freely available at http://mulinlab.org/qtlbase.

New insights into genetic susceptibility of COVID-19: an ACE2 and TMPRSS2 polymorphism analysis

“…In addition to these four variants, p.Leu731Phe has the highest allele frequency in the AFR and EUR populations. We further inspected the expression quantitative trait loci (eQTL) for ACE2 using the GTEx [ 13 ] and QTLbase [ 14 ] databases. We did not find any eQTLs for ACE2 from the GTEx, while we found one weak eQTL associated with ACE2 non-synonymous SNP (rs41303171) in the kidney from the QTLbase [ 14 ].…”

“…We further evaluated the eQTL profile of TMPRSS2 using the GTEx [ 13 ] and QTLbase databases [ 14 ] as well. We found two eQTLs associated with TMPRSS2 non-synonymous SNPs (rs12329760 (encoding p.Val160Met), p = 4.54 × 10 −5 ; rs75603675, p = 0.009) in the kidney and bone, respectively, using the QTLbase database [ 14 ], while there are no known eQTLs associated with TMPRSS2 non-synonymous SNPs from GTEx [ 13 ]. Notably, all populations carry p.Val160Met variants with the highest allele frequency (~ 25%), especially for the EAS population at a 40% allele frequency.…”

eQTL Catalogue: a compendium of uniformly processed human gene expression and splicing QTLs

“…The largest collection of eQTLs is currently hosted by the QTLbase [5] database. Although QTLbase contains some splicing QTLs, this is limited to the summary statistics provided by the original study authors.…”

“…Despite efforts by large-scale consortia such as GTEx [1] and eQTLGen [2] to provide comprehensive eQTL annotations for a large number of human tissues, most eQTL datasets are still scattered across individual publications. Multiple databases have been developed that collect eQTL summary statistics [3][4][5][6][7][8][9]; however, these efforts have relied on the heterogeneous set of summary statistics calculated by the original authors.…”

Breeding for Abiotic Stress Adaptation in Chickpea (Cicer arietinum L.): A Comprehensive Review

“…QTLBase database that catalogues identified QTLs from human genome research is availalable and data can be readily searched, queried, visualized, retrieved and compared across multiple tissues [190]. Such an approach can certainly be applied for chickpea and other grain crops and will ensure that QTLs reported in numerous studies and information regarding their respective map positions, alleles with positive effects and variance explained, are readily available to researchers.…”