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

Area of Science:

• Genomics
• Systems Biology
• Bioinformatics

Background:

• Large-scale quantitative trait locus (QTL) studies link genetic variations to cellular functions.
• Existing resources lack comprehensive QTL lookup across multiple molecular phenotypes and cascade effect analysis.

Purpose of the Study:

• To develop QTLbase, a versatile resource for interpreting genetic variant functions and tissue specificity.
• To provide a unified platform for QTL data retrieval, comparison, and mechanism interrogation.

Main Methods:

• Curated and compiled genome-wide QTL summary statistics from 233 studies for 13 human molecular traits.
• Mapped QTL-relevant tissue/cell types to 78 unified terms using a standard anatomogram.
• Normalized variant and trait information, generating over 170 million significant QTLs.
• Integrated genomic features and functional predictions for QTL mechanism annotation.

Main Results:

• QTLbase offers five key functions: data compilation, tissue mapping, data normalization, visualization, and functional annotation.
• The resource provides a comprehensive view of QTLs across multiple tissues and molecular layers.
• Over 170 million significant QTLs are available, linked to 13 human molecular traits.

Conclusions:

• QTLbase serves as a centralized hub for QTL data, facilitating the investigation of genetic variant functions.
• It aids researchers in understanding the biological mechanisms of causal variants and guides functional validation efforts.
• The resource is freely accessible at http://mulinlab.org/qtlbase.