A characterization of cis- and trans-heritability of RNA-Seq-based gene expression

Area of Science:

• Genetics and Genomics
• Molecular Biology
• Bioinformatics

Background:

• Understanding individual differences in gene expression heritability (h² ) is crucial for linking DNA to observable traits.
• Previous heritability estimates for gene expression were primarily based on microarray data, potentially limiting accuracy.

Purpose of the Study:

• To estimate the total, cis- (h²cis), and trans- (h²res) heritability of gene expression in whole blood using a large RNA-Seq twin dataset.
• To compare these estimates with previous microarray-based studies and explore the genetic architecture of gene expression.

Main Methods:

• Utilized classical twin modeling and identity-by-state approaches on RNA-Seq data from 1497 individuals (459 MZ, 150 DZ twin pairs).
• Estimated heritability for 52,844 genes, differentiating between cis-acting variants and genome-wide trans-acting variants.

Main Results:

• Mean total heritability (h²total) was 0.26, significantly higher than previous microarray-based estimates (mean h² = 0.14).
• Mean cis-heritability (h²cis) was 0.06, showing a strong correlation with cis-expression quantitative loci (eQTL) effect sizes.
• Mean trans-heritability (h²res) was 0.20, higher for genes in immune pathways and those implicated in GWAS for various traits, including behavioral disorders and cancer.

Conclusions:

• RNA-Seq data in large twin cohorts provide more accurate heritability estimates for gene expression compared to microarrays.
• Trans-acting genetic variants contribute substantially to the heritability of gene expression, particularly for immune-related genes.
• These detailed cis- and trans-heritability estimates are valuable for interpreting findings from Genome-Wide Association Studies (GWAS) and gene expression studies.