Relative impact of nucleotide and copy number variation on gene expression phenotypes

By Barbara E. Stranger, M. S. Forrest, M. Dunning, Catherine E. Ingle, C. Beazley, N. Thorne, R. Redon, C. Bird, Anna De Grassi, Charles Lee and 7 more. Science, 2007

1,794 citations recorded by the source corpus.

Extensive studies are currently being performed to associate disease susceptibility with one form of genetic variation, namely, single-nucleotide polymorphisms (SNPs). In recent years, another type of common genetic variation has been characterized, namely, structural variation, including copy number variants (CNVs). To determine the overall contribution of CNVs to complex phenotypes, we have performed association analyses of expression levels of 14,925 transcripts with SNPs and CNVs in individuals who are part of the International HapMap project. SNPs and CNVs captured 83.6% and 17.7% of the total detected genetic variation in gene expression, respectively, but the signals from the two types of variation had little overlap. Interrogation of the genome for both types of variants may be an effective way to elucidate the causes of complex phenotypes and disease in humans.

Subfields: Genetics

View Paper: https://www.semanticscholar.org/paper/cb1fe7d128e1fce5acf1d72143f076311ce5aea0

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Citations in the corpus

The human splicing code reveals new insights into the genetic determinants of disease (2014, methodology): “Our approach contrasts with techniques that use functional annotations of the genome (2, 8, 46), tools that are trained using existing disease annotations and thus suffer from overfitting to known mutations or severe selection bias (7–9, 47, 48); genome-wide association studies (GWAS) (49, 50); and ”
Progress and Promise of Genome-Wide Association Studies for Human Complex Trait Genetics (2011, background): “Recently, GWASs have been conducted on mRNA levels, themselves quantitative traits, in expression QTL (eQTL) mapping studies (see Table 1) (e.g., Dixon et al. 2007; Goring et al. 2007; Stranger et al. 2007a,b; Dimas et al. 2009).”
Variance estimation in high-dimensional linear models (2014, methodology): “In Stranger et al. (2007b), the authors identified 341 genes that were significantly associated L.H. Dicker/Variance estimation in high-dimensional linear models 17 with single nucleotide polymorphisms from 45 individuals in the Japanese HapMap population.”
A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis (2010, methodology): “In addition, a total of 72 out of the 100 previously reported cis -associa- tions [31] were identified with V-Bay (Additional file 1, Table S1 ).”