Contrasting genetic architectures in different mouse reference populations used for studying complex traits

Abstract

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 contextdependent 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.

Transcriptome Profiling in Rat Inbred Strains and Experimental Cross Reveals Discrepant Genetic Architecture of Genome-Wide Gene Expression

“…In contrast, the genetic structure of congenic strains allows for a cruder measurement of gene differential expression caused by exchanging genetic polymorphisms present in well-defined genomic intervals in an otherwise uniform background, thereby unambiguously distinguishing between cis - and trans -mediated regulations (Buchner and Nadeau 2015). Differential expression of genes mapped within the genomic regions exchanged in congenics should therefore correspond to cis -regulated effects whereas differential expression of genes mapped outside these regions unambiguously indicates trans -mediated regulation.…”

“…A broad range of experimental mammalian systems developed in the laboratory mouse (Buchner and Nadeau 2015) and rat (Gauguier 2005) allow the collection of organs from large cohorts of individuals maintained in strictly standardized conditions, thus limiting interindividual phenotype variability, and provide powerful tools for eQTL mapping. The inbred Goto–Kakizaki (GK) rat model of type 2 diabetes mellitus was produced over many generations of breeding rats from an outbred Wistar stock, using glucose intolerance as the sole criterion for selecting breeders (Goto et al 1976).…”

Genome Sequencing of Chromosome 1 Substitution Lines Derived from Chinese Wild Mice Revealed a Unique Resource for Genetic Studies of Complex Traits

“…Recent progress in mouse resources have achieved a resolution of a ∼2 Mb interval containing roughly 10–20 genes (Buchner and Nadeau 2015), although the actual resolution varies with other factors, such as gene density. Other complementary methods, such as gene expression analysis and coexpression networks, can sometimes reduce the number of candidates to just one or a few genes and inform the underlying pathways (Mesner et al 2014).…”

“…Recent studies have shown that expanding mice strains and genotyping density would further improve its power and resolution (Rau et al 2015). The Collaborative Cross (CC) panel aims to generate >1000 recombinant inbred strains derived from eight diverse mouse strains, which could provide a mapping resolution of ∼2 Mb (Buchner and Nadeau 2015). It is noteworthy that CC parental strains include three wild-derived strains, thereby dramatically increasing the genetic and phenotypic diversity of this resource.…”

“…However, only 73 strains have been made publicly available so far (http://csbio.unc.edu/CCstatus/). Despite this limitation, investigators have successfully used pre-CC and completed CC strains in genetic studies of complex traits (Aylor et al 2011; Buchner and Nadeau 2015). Another valuable resource is outbred stocks (OS).…”