A systematic heritability analysis of the human whole blood transcriptome

• Published in: Human genetics 2015-03, Vol.134 (3), p.343-358
• Main Authors: Huan, Tianxiao, Liu, Chunyu, Joehanes, Roby, Zhang, Xiaoling, Chen, Brian H., Johnson, Andrew D., Yao, Chen, Courchesne, Paul, O’Donnell, Christopher J., Munson, Peter J., Levy, Daniel
• Format: Article
• Language: English
• Subjects: Adult; Aged; Analysis; Biomedical and Life Sciences; Biomedicine; Blood pressure; Body Mass Index; Cardiovascular disease; Case studies; Female; Gene expression; Gene Function; Genome-Wide Association Study; Genomes; Genomics; Genotype & phenotype; Heart; Human Genetics; Humans; Male; Metabolic Diseases; Metabolism; Middle Aged; Molecular Medicine; Original Investigation; Polymorphism, Single Nucleotide; Quantitative Trait Loci; RNA, Messenger - blood; RNA, Messenger - genetics; Single nucleotide polymorphisms; Transcriptome
• ISSN: 0340-6717; 1432-1203
• DOI: 10.1007/s00439-014-1524-3

Genome-wide expressio n quantitative trait locus (eQTL) mapping may reveal common genetic variants regulating gene expression. In addition to mapping eQTLs, we systematically evaluated the heritability of the whole blood transcriptome in 5,626 participants from the Framingham Heart Study. Of all gene expression measurements, about 40 % exhibit evidence of being heritable [ h geneExp 2  > 0, ( p   0.2. To identify the role of eQTLs in promoting phenotype differences and disease susceptibility, we investigated the proportion of cis / trans eQTLs in different heritability categories and discovered that genes with higher heritability are more likely to have cis eQTLs that explain large proportions of variance in the expression of the corresponding genes. Single cis eQTLs explain 0.33–0.53 of variance in transcripts on average, whereas single trans eQTLs only explain 0.02–0.07. The top cis eQTLs tend to explain more variance in the corresponding gene when its h geneExp 2 is greater. Taking body mass index (BMI) as a case study, we cross-linked cis / trans eQTLs with both GWAS SNPs and differentially expressed genes for BMI. We discovered that BMI GWAS SNPs in 16p11.2 (e.g., rs7359397) are associated with several BMI differentially expressed genes in a cis manner (e.g. SULT1A1, SPNS1, and TUFM ). These BMI signature genes explain a much larger proportion of variance in BMI than do the GWAS SNPs. Our results shed light on the impact of eQTLs on the heritability of the human whole blood transcriptome and its relations to phenotype differences.