Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing

Background: Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. // Results: We systematically investigate both dominance—here representing any non-additive within-locus interaction—and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. // Conclusions: Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality

Dominance is common in mammals and is associated with trans-acting gene expression and alternative splicing

Abstract Background Dominance and other non-additive genetic effects arise from the interaction between alleles, and historically these phenomena play a major role in quantitative genetics. However, most genome-wide association studies (GWAS) assume alleles act additively. Results We systematically investigate both dominance—here representing any non-additive within-locus interaction—and additivity across 574 physiological and gene expression traits in three mammalian stocks: F2 intercross pigs, rat heterogeneous stock, and mice heterogeneous stock. Dominance accounts for about one quarter of heritable variance across all physiological traits in all species. Hematological and immunological traits exhibit the highest dominance variance, possibly reflecting balancing selection in response to pathogens. Although most quantitative trait loci (QTLs) are detectable as additive QTLs, we identify 154, 64, and 62 novel dominance QTLs in pigs, rats, and mice respectively that are undetectable as additive QTLs. Similarly, even though most cis-acting expression QTLs are additive, gene expression exhibits a large fraction of dominance variance, and trans-acting eQTLs are enriched for dominance. Genes causal for dominance physiological QTLs are less likely to be physically linked to their QTLs but instead act via trans-acting dominance eQTLs. In addition, thousands of eQTLs are associated with alternatively spliced isoforms with complex additive and dominant architectures in heterogeneous stock rats, suggesting a possible mechanism for dominance. Conclusions Although heritability is predominantly additive, many mammalian genetic effects are dominant and likely arise through distinct mechanisms. It is therefore advantageous to consider both additive and dominance effects in GWAS to improve power and uncover causality

A resource for the simultaneous high-resolution mapping of multiple quantitative trait loci in rats: The NIH heterogeneous stock

The laboratory rat (Rattus norvegicus) is a key tool for the study of medicine and pharmacology for human health. A large database of phenotypes for integrated fields such as cardiovascular, neuroscience, and exercise physiology exists in the literature. However, the molecular characterization of the genetic loci that give rise to variation in these traits has proven to be difficult. Here we show how one obstacle to progress, the fine-mapping of quantitative trait loci (QTL), can be overcome by using an outbred population of rats. By use of a genetically heterogeneous stock of rats, we map a locus contributing to variation in a fear-related measure (two-way active avoidance in the shuttle box) to a region on chromosome 5 containing nine genes. By establishing a protocol measuring multiple phenotypes including immunology, neuroinflammation, and hematology, as well as cardiovascular, metabolic, and behavioral traits, we establish the rat HS as a new resource for the fine-mapping of QTLs contributing to variation in complex traits of biomedical relevance

Homomorphisms and Ramsey properties of antimatroids

SIGLEBibliothek Weltwirtschaft Kiel C132,202 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Combined sequence-based and genetic mapping analysis of complex traits in outbred rats

<p>Genetic mapping on fully sequenced individuals is transforming understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We identify 35 causal genes involved in 31 phenotypes, implicating new genes in models of anxiety, heart disease and multiple sclerosis. The relationship between sequence and genetic variation is unexpectedly complex: at approximately 40% of quantitative trait loci, a single sequence variant cannot account for the phenotypic effect. Using comparable sequence and mapping data from mice, we show that the extent and spatial pattern of variation in inbred rats differ substantially from those of inbred mice and that the genetic variants in orthologous genes rarely contribute to the same phenotype in both species.</p>

Supplementary Table 1. Results of proteomics data including phosphoproteomics and cytokine level measurements for primary normal human bronchial epithelial cells (NHBE) and normal rat bronchial epithelial cells (NRBE) cells exposed to 52 stimuli.

Supplementary Table 1. Results of proteomics data including phosphoproteomics and cytokine level measurements for primary normal human bronchial epithelial cells (NHBE) and normal rat bronchial epithelial cells (NRBE) cells exposed to 52 stimuli. The file contains the median of bead fluorescence intensities measured for each protein in every sample (cell lysate and corresponding supernatant for phosphoproteins and cytokines, respectively). For each stimulus, sample replicates have been extracted from 3 independent wells. The results are reported for (a) 19 phosphoproteins, with in addition the measurements for 2 control beads (Control A: Phycoerythrin-coated beads used as positive control bead; Control B: BSA-coated beads devoid of antibody used as negative control bead), and for the actin; (b) 22 cytokines

measures.txt

216 phenotypes and experimental covariates measured in 2,006 NIH Heterogeneous Stock rat

haplotype_dosages_Rnor50.tar.gz

Probabilities of descent (haplotype dosages) of 1,407 Heterogenous Stock rat from each of the eight progenitors of the Stock, at each locus in the genom

merge_factors.RData

sequence variants (SNPs and indels) in all eight founder strains of the Heterogeneous Stock, formatted in an R object for merge analysi