Genome-wide approach to measure variant-based heritability of drug outcome phenotypes
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PROVIDER: PRJNA748790 | ENA |
REPOSITORIES: ENA
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Project description:Genome-wide approach to measure variant-based heritability of drug outcome phenotypes
| PRJNA748789 | ENA
Project description:Pharmacogenomic studies have successfully identified variants-typically with large effect sizes in drug target and metabolism enzymes-that predict drug outcome phenotypes. However, these variants may account for a limited proportion of phenotype variability attributable to the genome. Using genome-wide common variation, we measured the narrow-sense heritability ( hSNP2 ) of seven pharmacodynamic and five pharmacokinetic phenotypes across three cardiovascular drugs, two antibiotics, and three immunosuppressants. We used a Bayesian hierarchical mixed model, BayesR, to model the distribution of genome-wide variant effect sizes for each drug phenotype as a mixture of four normal distributions of fixed variance (0, 0.01%, 0.1%, and 1% of the total additive genetic variance). This model allowed us to parse hSNP2 into bins representing contributions of no-effect, small-effect, moderate-effect, and large-effect variants, respectively. For the 12 phenotypes, a median of 969 (range 235-6,304) unique individuals of European ancestry and a median of 1,201,626 (range 777,427-1,514,275) variants were included in our analyses. The number of variants contributing to hSNP2 ranged from 2,791 to 5,356 (median 3,347). Estimates for hSNP2 ranged from 0.05 (angiotensin-converting enzyme inhibitor-induced cough) to 0.59 (gentamicin concentration). Small-effect and moderate-effect variants contributed a majority to hSNP2 for every phenotype (range 61-95%). We conclude that drug outcome phenotypes are highly polygenic. Thus, larger genome-wide association studies of drug phenotypes are needed both to discover novel variants and to determine how genome-wide approaches may improve clinical prediction of drug outcomes.
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2021-05-31 | GSE151506 | GEO
Project description:Inferring the heritability of gene expression is one of the main areas of the field of genetical genomics. With the possibility to treat the abundances of gene transcripts as a suite of quantitative traits, genetical genomics can make an extensive use of the microarray technology. Here we extended a major method for estimating the heritability of a quantitative trait, single parent-offspring regression, to assess the heritability of the expression of genes with two-channel microarrays. In a series of maternal parent-offspring pairs of Interior spruce (Picea glauca x engelmannii, our focus in the outer stem tissues is the expression of defense-related genes, the heritability of which can affect fitness and necessary for evolution by natural selection.
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Project description:Inferring the heritability of gene expression is one of the main areas of the field of genetical genomics. With the possibility to treat the abundances of gene transcripts as a suite of quantitative traits, genetical genomics can make an extensive use of the microarray technology. Here we extended a major method for estimating the heritability of a quantitative trait, single parent-offspring regression, to assess the heritability of the expression of genes with two-channel microarrays. In a series of maternal parent-offspring pairs of Interior spruce (Picea glauca x engelmannii, our focus in the outer stem tissues is the expression of defense-related genes, the heritability of which can affect fitness and necessary for evolution by natural selection. Parent-offspring pairs of Interior spruce planted as a part of Tree Breeding and Improvement Program of the Forest Genetics Section, British Columbia Ministry of Forests and Range, Prince George, BC, Canada (http://www.for.gov.bc.ca/hre/forgen/interior/spruce.htm#1) were used. A total of 30 trees, comprising 15 parent-offpsring pairs were sampled. These include15 offsprings and 15 maternal parents (grafts), which were planted within ~ 1Km range west (122º 42’ 43’’W, 53º 45’41’’N) of the offsprings, hence grown in a relatively similar environment. The bark and the attached phloem were separated from inner layers in the mid-morning hours of June 25, 2008, flash-frozen in liquid nitrogen, and transferred into separate containers. A chain design was decided for gene expression profiling (a total of 45 slides) using the Treenomix third generation cDNA microarray platform (GEO accession #: GPL5423). Array350 kit (Genisphere, Hatfield, USA) was chosen for the microarray hybridizations. The slides were scanned with a ProScanArray scanner (PerkinElmer, Downers Grove, IL, USA), and the scanned TIF images were processed by ImaGene software (BioDiscovery, Inc., El Segundo, CA, USA) to quantify spot signals. Normalization was done between arrays using variance stabilizing (VSN) method for ratio based analysis of the expression data.
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