Mismapping of sequencing reads from polymorphic duplications generates spurious trans-eQTLs

Area of Science:

• Genomics
• Statistical Genetics
• Bioinformatics

Background:

• Trans-acting expression quantitative trait loci (trans-eQTLs) discovery is hindered by false positives.
• Polymorphic duplications absent in reference genomes are an unaddressed source of these errors.
• RNA sequencing (RNA-seq) reads from non-reference gene duplicates can erroneously map to reference copies, creating spurious trans-eQTLs.

Purpose of the Study:

• To develop and apply a novel method to identify and filter spurious trans-eQTLs caused by non-reference polymorphic duplications.
• To quantify the proportion of spurious trans-eQTLs in existing datasets (GTEx and MAGE).
• To introduce 'mismapping linkage disequilibrium' as a metric for improving trans-eQTL analysis.

Main Methods:

• Developed a method utilizing 'mismapping linkage disequilibrium' to detect false-positive trans-eQTLs.
• Applied this method to published GTEx and newly generated MAGE trans-eQTL data, already filtered for cross-mappability between reference duplicates.
• Analyzed the characteristics of spurious trans-eQTLs, including their effect sizes and relationship with study sample size.

Main Results:

• Identified that at least 15.4% of trans-eQTLs in GTEx and 6.1% in MAGE are spurious due to non-reference polymorphic duplications.
• Found that spurious trans-eQTLs are more likely to exhibit large effect sizes.
• Demonstrated the utility of the method using the DUSP22 polymorphic duplication, uncovering both false-positive trans-eQTLs and trans-acting splicing QTLs (trans-sQTLs).

Conclusions:

• The developed method effectively flags spurious trans-eQTLs arising from non-reference polymorphic duplications.
• Non-reference duplications represent a significant source of false positives in trans-eQTL studies, particularly in smaller sample cohorts.
• This study provides a practical and valuable metric for enhancing the reliability of trans-eQTL findings.