Genetic Variants Contribute to Gene Expression Variability in Humans

Hulse, Amanda M.; Cai, James J.

doi:10.1534/genetics.112.146779

Cited by 102 publications

(124 citation statements)

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“…To systematically assess the genetic influence on expression variability, we identified genome-wide evQTL using the method we previously established (Hulse and Cai 2013). We focused on cis-acting evQTL by limiting our search to those SNPs that flanked probes within 1.0 Mb on either side.…”

Section: Genetic Variants Underlying Expression Variabilitymentioning

confidence: 99%

“…On average, each probe corresponded to 1212 SNPs in the 2-Mb cis-region (i.e., 6 SNPs per 10 kb). For each SNP-probe pair, we conducted a three-step test to determine the evQTL relationship as described previously (Hulse and Cai 2013). Briefly, we first tested for the homogeneity of variances in gene expression among different genotype groups using the Fligner-Killeen (F-K) test (Fligner and Killeen 1976).…”

Section: Genetic Variants Underlying Expression Variabilitymentioning

confidence: 99%

“…However, there is increasing evidence across species for genetic loci that affect the variance of phenotype (Queitsch et al 2002; JimenezGomez et al 2011;Ronnegard and Valdar 2011;Perry et al 2012;Shen et al 2012;Yang et al 2012). Recently we introduced the concept of expression variability QTL, or evQTL (Hulse and Cai 2013). By definition, an evQTL is a genetic locus linked to or associated with genetic variation influencing the variance of gene expression in a population.…”

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confidence: 99%

“…A significant result of a dglm test shows the nonrandom association between genotypes and gene expression variances. Using this method, we have conducted a genome-wide scan for evQTL in the human genome (Hulse and Cai 2013).…”

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confidence: 99%

“…The first possibility is that specific genetic variants disrupt the stabilizing genetic architecture that buffers stochastic variation in phenotype. As a result of such an effect of decanalization, along with the sensitization of the stabilizer (e.g., heat-shock protein 90), the phenotype becomes more sensitive to external environment and varies more greatly between individuals (Ronnegard and Valdar 2011; Hulse and Cai 2013).…”

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Additive, Epistatic, and Environmental Effects Through the Lens of Expression Variability QTL in a Twin Cohort

et al. 2014

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The expression of a gene can vary across individuals in the general population, as well as between monozygotic twins. This variable expression is assumed to be due to the influence of both genetic and nongenetic factors. Yet little evidence supporting this assumption has been obtained from empirical data. In this study, we used expression data from a large twin cohort to investigate the influences of genetic and nongenetic factors on variable gene expression. We focused on a set of expression variability QTL (evQTL)-i.e., genetic loci associated with the variance, as opposed to the mean, of gene expression. We identified evQTL for 99, 56, and 79 genes in lymphoblastoid cell lines, skin, and fat, respectively. The differences in gene expression, measured by the relative mean difference (RMD), tended to be larger between pairs of dizygotic (DZ) twins than between pairs of monozygotic (MZ) twins, showing that genetic background influenced the expression variability. Furthermore, a more profound RMD was observed between pairs of MZ twins whose genotypes were associated with greater expression variability than the RMD found between pairs of MZ twins whose genotypes were associated with smaller expression variability. This suggests that nongenetic (e.g., environmental) factors contribute to the variable expression. Lastly, we demonstrated that the formation of evQTL is likely due to partial linkages between eQTL SNPs that are additively associated with the mean of gene expression; in most cases, no epistatic effect is involved. Our findings have implications for understanding divergent sources of gene expression variability.V ARIATION and variability are central concepts in biology (Hallgrímsson and Hall 2005). Although often used interchangeably in the scientific literature, the two are not synonymous. Variation refers to the differences among individuals, whereas variability refers to the potential of a population to vary (Wagner 1995;Wagner and Altenberg 1996). In many cases, greater phenotypic variability (e.g., transcriptional noise) is disadvantageous (Kemkemer et al. 2002;Bahar et al. 2006;Wang and Zhang 2011) unless it gives rise to greater organismal plasticity-first at the level of an individual organism and eventually at the population level. Genetic factors resulting in more variable phenotypes become favored when they enable a population to more effectively respond to environmental changes (Hill and Zhang 2004;Kaern et al. 2005;Acar et al. 2008;Zhang et al. 2009). Thus, understanding to what extent and in what ways genotypes influence phenotypic variability is of fundamental importance.Much effort has been focused on identifying genetic loci such as expression quantitative trait loci, or eQTL (Stranger et al. 2005(Stranger et al. , 2007Choy et al. 2008;Montgomery et al. 2010;Pickrell et al. 2010;Montgomery and Dermitzakis 2011), that affect the average value of a phenotype, while ignoring those that affect the variance of a phenotype. However, there is increasing evidence across species for genet...

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Section: Genetic Variants Underlying Expression Variabilitymentioning

confidence: 99%

Section: Genetic Variants Underlying Expression Variabilitymentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Additive, Epistatic, and Environmental Effects Through the Lens of Expression Variability QTL in a Twin Cohort

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Interindividual epigenetic variability: Sound or noise?

Tejedor

Fraga

2017

BioEssays

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Interindividual variability is an inherent characteristic of biological systems. Whereas the underlying molecular sources of interindividual variability remain poorly understood, recent work by Ecker et al. (Ecker S, Chen L, Pancaldi V, Bagger FO, et al. 2017. Genome Biol 18: 18.) sheds light on the characterization of this phenomenon in a complex biological scenario. By combining data from the BLUEPRINT Epigenome Project with a novel analytical approach, these authors were able to measure the degree of transcriptional and epigenetic variability across a wide panel of samples and types of immune cell. Interestingly, neutrophils displayed increased variability compared to monocytes and T cells, which may be related to the crucial role of the former as an initial mediator of immune responses. Here we review recent literature in this area, and discuss some important issues raised by these innovative analyses. Furthermore, we summarize other potential sources of epigenetic variability, such as epigenetic drift and the epigenetic clock, as well as the current ongoing direction of the field. Differential molecular variability of immune cell typesA recent report by Ecker and co-workers has unraveled, in a genome-wide manner, the extent of transcriptional and epigenetic variability in three major immune cell types [11]. Taking advantage of the publicly available BLUEPRINT Human Variation Panel, the authors analyzed RNA-seq and array-based DNA methylation data from 125 donors using transcriptomic and epigenomic datasets matched across

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Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

et al. 2017

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Epigenetic and transcriptional variability contribute to the vast diversity of cellular and organismal phenotypes and are key in human health and disease. In this review, we describe different types, sources, and determinants of epigenetic and transcriptional variability, enabling cells and organisms to adapt and evolve to a changing environment. We highlight the latest research and hypotheses on how chromatin structure and the epigenome influence gene expression variability. Further, we provide an overview of challenges in the analysis of biological variability. An improved understanding of the molecular mechanisms underlying epigenetic and transcriptional variability, at both the intra- and inter-individual level, provides great opportunity for disease prevention, better therapeutic approaches, and personalized medicine.

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Genetic Variants Contribute to Gene Expression Variability in Humans

Cited by 102 publications

References 74 publications

Additive, Epistatic, and Environmental Effects Through the Lens of Expression Variability QTL in a Twin Cohort

Additive, Epistatic, and Environmental Effects Through the Lens of Expression Variability QTL in a Twin Cohort

Interindividual epigenetic variability: Sound or noise?

Epigenetic and Transcriptional Variability Shape Phenotypic Plasticity

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