Heritability and genomics of gene expression in peripheral blood

Abstract

We assessed gene expression profiles in 2,752 twins, using a classic twin design to quantify expression heritability and quantitative trait loci (eQTL) in peripheral blood. The most highly heritable genes (~777) were grouped into distinct expression clusters, enriched in gene-poor regions, associated with specific gene function/ontology classes, and strongly associated with disease designation. The design enabled a comparison of twin-based heritability to estimates based on dizygotic IBD sharing and distant genetic relatedness. Consideration of sampling variation suggests that previous heritability estimates have been upwardly biased. Genotyping of 2,494 twins enabled powerful identification of eQTLs, which were further examined in a replication set of 1,895 unrelated subjects. A large number of local eQTLs (6,988) met replication criteria, while a relatively small number of distant eQTLs (165) met quality control and replication standards. Our results provide an important new resource toward understanding the genetic control of transcription.

Genetic effects on gene expression across human tissues

“…Despite the scope of these data, we remain underpowered to detect trans -eQTLs. Larger cohorts of individuals with a smaller number of tissues have yielded hundreds of trans -eGenes 4,6,8,9 , and we similarly expect trans -eQTL discoveries to increase with additional samples in the final phase of GTEx. Furthermore, some genetic effects may manifest only within a specific cell type, rather than an entire heterogeneous tissue.…”

“…Recent large-scale studies have characterized the regulatory function of the genome across a diverse array of cell types, each from a small number of samples 1–3 . Measuring how gene regulation and expression vary across individuals has further expanded our understanding of the functions of healthy tissues and the molecular origins of complex traits and diseases 4–9 . However, these studies have been conducted in limited, accessible cell types, thus restricting the utility of these studies in informing regulatory biology and human health.…”

Functional Architectures of Local and Distal Regulation of Gene Expression in Multiple Human Tissues

“…1,2 In particular, researchers have gained new insights into the functional effects of genetic variants on many complex diseases and traits. [3][4][5][6][7][8][9][10][11][12] In parallel, large-scale expression quantitative trail locus (eQTL) mapping studies in multiple human tissues have revealed a large number of genetic variants that affect gene expression [13][14][15][16][17][18][19] (reviewed by Albert and Kruglyak 20 ). Gene expression serves as an important intermediate cellular phenotype that affects complex diseases and traits, [21][22][23][24] and the functional effects of eQTLs provide another lens through which researchers can investigate molecular mechanisms.…”

Person-Specific Non-shared Environmental Influences in Intra-individual Variability: A Preliminary Case of Daily School Feelings in Monozygotic Twins

“…First, stochastic intra-individual developmental noise can lead to inter-individual differences in genetic and environmental influences as a third source, which however cannot be distinguished from non-shared environmental influences in conventional behavioural genetic studies (e.g., Molenaar et al 1993;Molenaar and Raijmakers 1999). Second, epigenetic processes (e.g., DNA methylation) involving interactions between genes, environment, and other processes could also affect gene expression to lead to interindividual heterogeneity (e.g., Bell and Saffery 2012;Bell and Spector 2011;Dolan et al 2015;Fraga et al 2005;Kan et al 2010;Petronis 2010;Wright et al 2014). These person-specific non-shared environmental influences offer a unique angle to examine twin concordance, not in their phenotypes per se (e.g., levels of happiness), but in their respective individual patterns of how nonshared environment influences them.…”

“…For example, behavioural genetic studies adopting mixture modelling have demonstrated population heterogeneity regarding genetic and environmental influences (e.g., Eaves et al 1993;Gillespie and Neale 2006;Muthén et al 2006;Neale 2014). Stochastic intra-individual developmental noise (e.g., Molenaar et al 1993;Molenaar and Raijmakers 1999), gene expression and epigenetic processes (e.g., DNA methylation) can also result in substantial inter-individual differences in genetic and environmental influences (e.g., Bell and Saffery 2012;Bell and Spector 2011;Dolan et al 2015;Fraga et al 2005;Kan et al 2010;Petronis 2010;Wright et al 2014). Therefore, investigation of intra-individual variability could potentially provide unique and important information regarding genetic and environmental influences on intra-individual developmental processes that conventional behavioural genetic studies focusing on inter-individual differences could not offer, especially at the individual level.…”