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Contrasting genetic architectures in different mouse reference populations used for studying complex traits
Quantitative trait loci (QTLs) are being used to study genetic networks, protein functions, and systems properties that underlie phenotypic variation and disease risk in humans, model organisms, agricultural species, and natural populations. The challenges are many, beginning with the seemingly simp...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4448675/ https://www.ncbi.nlm.nih.gov/pubmed/25953951 http://dx.doi.org/10.1101/gr.187450.114 |
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author | Buchner, David A. Nadeau, Joseph H. |
author_facet | Buchner, David A. Nadeau, Joseph H. |
author_sort | Buchner, David A. |
collection | PubMed |
description | Quantitative trait loci (QTLs) are being used to study genetic networks, protein functions, and systems properties that underlie phenotypic variation and disease risk in humans, model organisms, agricultural species, and natural populations. The challenges are many, beginning with the seemingly simple tasks of mapping QTLs and identifying their underlying genetic determinants. Various specialized resources have been developed to study complex traits in many model organisms. In the mouse, remarkably different pictures of genetic architectures are emerging. Chromosome Substitution Strains (CSSs) reveal many QTLs, large phenotypic effects, pervasive epistasis, and readily identified genetic variants. In contrast, other resources as well as genome-wide association studies (GWAS) in humans and other species reveal genetic architectures dominated with a relatively modest number of QTLs that have small individual and combined phenotypic effects. These contrasting architectures are the result of intrinsic differences in the study designs underlying different resources. The CSSs examine context-dependent phenotypic effects independently among individual genotypes, whereas with GWAS and other mouse resources, the average effect of each QTL is assessed among many individuals with heterogeneous genetic backgrounds. We argue that variation of genetic architectures among individuals is as important as population averages. Each of these important resources has particular merits and specific applications for these individual and population perspectives. Collectively, these resources together with high-throughput genotyping, sequencing and genetic engineering technologies, and information repositories highlight the power of the mouse for genetic, functional, and systems studies of complex traits and disease models. |
format | Online Article Text |
id | pubmed-4448675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Cold Spring Harbor Laboratory Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-44486752015-12-01 Contrasting genetic architectures in different mouse reference populations used for studying complex traits Buchner, David A. Nadeau, Joseph H. Genome Res Review Quantitative trait loci (QTLs) are being used to study genetic networks, protein functions, and systems properties that underlie phenotypic variation and disease risk in humans, model organisms, agricultural species, and natural populations. The challenges are many, beginning with the seemingly simple tasks of mapping QTLs and identifying their underlying genetic determinants. Various specialized resources have been developed to study complex traits in many model organisms. In the mouse, remarkably different pictures of genetic architectures are emerging. Chromosome Substitution Strains (CSSs) reveal many QTLs, large phenotypic effects, pervasive epistasis, and readily identified genetic variants. In contrast, other resources as well as genome-wide association studies (GWAS) in humans and other species reveal genetic architectures dominated with a relatively modest number of QTLs that have small individual and combined phenotypic effects. These contrasting architectures are the result of intrinsic differences in the study designs underlying different resources. The CSSs examine context-dependent phenotypic effects independently among individual genotypes, whereas with GWAS and other mouse resources, the average effect of each QTL is assessed among many individuals with heterogeneous genetic backgrounds. We argue that variation of genetic architectures among individuals is as important as population averages. Each of these important resources has particular merits and specific applications for these individual and population perspectives. Collectively, these resources together with high-throughput genotyping, sequencing and genetic engineering technologies, and information repositories highlight the power of the mouse for genetic, functional, and systems studies of complex traits and disease models. Cold Spring Harbor Laboratory Press 2015-06 /pmc/articles/PMC4448675/ /pubmed/25953951 http://dx.doi.org/10.1101/gr.187450.114 Text en © 2015 Buchner and Nadeau; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Review Buchner, David A. Nadeau, Joseph H. Contrasting genetic architectures in different mouse reference populations used for studying complex traits |
title | Contrasting genetic architectures in different mouse reference populations used for studying complex traits |
title_full | Contrasting genetic architectures in different mouse reference populations used for studying complex traits |
title_fullStr | Contrasting genetic architectures in different mouse reference populations used for studying complex traits |
title_full_unstemmed | Contrasting genetic architectures in different mouse reference populations used for studying complex traits |
title_short | Contrasting genetic architectures in different mouse reference populations used for studying complex traits |
title_sort | contrasting genetic architectures in different mouse reference populations used for studying complex traits |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4448675/ https://www.ncbi.nlm.nih.gov/pubmed/25953951 http://dx.doi.org/10.1101/gr.187450.114 |
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