Genetic resistance to diet-induced obesity in chromosome substitution strains of mice

Burrage, Lindsay C.; Baskin-Hill, Annie E.; Sinasac, David S.; Singer, Jonathan B.; Croniger, Colleen M.; Kirby, Andrew; Kulbokas, Edward J.; Daly, Mark J.; Lander, Eric S.; Broman, Karl W.; Nadeau, Joseph H.

doi:10.1007/s00335-010-9247-9

Cited by 32 publications

(48 citation statements)

References 57 publications

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“…Traditional backcrosses or intercrosses can be performed with CSSs for higher resolution mapping, thus allowing for only the segregation of alleles on the substituted chromosome as opposed to throughout the entire genome (Matin et al 1999;Burrage et al 2010). This reduces the amount of genetic variation within the cross, allowing for a greater signal from the causal gene(s) on the substituted chromosome.…”

Section: Identified Qtlsmentioning

confidence: 99%

“…Thus, the action of Obrq3b has opposing effects on body weight as determined by an interaction with a second QTL (Obrq2). In fact, a CSS intercross with the Chromosome 6 substitution strain failed to detect Obrq2 because of its close linkage to Obrq3b, even though Obrq2 showed the strongest QTL effect on Chromosome 6 in congenic strains (Shao et al 2008;Burrage et al 2010). This again highlights the inherent difficulty in identifying QTL effects when influenced by unlinked segregating loci as found in the CC, HMDP, and OS, or in CSS crosses.…”

Section: Epistasismentioning

confidence: 99%

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

Buchner

Nadeau

2015

Genome Res.

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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.

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Section: Identified Qtlsmentioning

confidence: 99%

Section: Epistasismentioning

confidence: 99%

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

Buchner

Nadeau

2015

Genome Res.

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“…Therefore, to identify the genetic factors that modulate differential isoform usage, we used the PSI values obtained from the RI mice as quantitative traits, and the corresponding genetic map (containing 934 informative genetic markers) in a genome-wide scan to identify the genomic loci that modulate mRNA splicing (splicing quantitative trait loci [sQTL]) using R/qtl (Broman et al 2003). To correct the QTL P-value of individual isoforms for multiple testing at the 934 genetic markers, we used 1000 permutation tests linked across phenotypes, i.e., permutation on the rows of the phenotype matrix relative to the row of the genotype matrix (Burrage et al 2010) in R/qtl. Next, to correct for testing of multiple isoforms, we calculated the corresponding false-discovery rate (FDR) using the qvalue package (Storey and Tibshirani 2003) and used FDR # 10% to select significant sQTL.…”

Section: Distinct Loci Modulate Isoform Usage In Murine Macrophagesmentioning

confidence: 99%

The genetic basis for individual differences in mRNA splicing and APOBEC1 editing activity in murine macrophages

2013

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Alternative splicing and mRNA editing are known to contribute to transcriptome diversity. Although alternative splicing is pervasive and contributes to a variety of pathologies, including cancer, the genetic context for individual differences in isoform usage is still evolving. Similarly, although mRNA editing is ubiquitous and associated with important biological processes such as intracellular viral replication and cancer development, individual variations in mRNA editing and the genetic transmissibility of mRNA editing are equivocal. Here, we have used linkage analysis to show that both mRNA editing and alternative splicing are regulated by the macrophage genetic background and environmental cues. We show that distinct loci, potentially harboring variable splice factors, regulate the splicing of multiple transcripts. Additionally, we show that individual genetic variability at the Apobec1 locus results in differential rates of C-to-U(T) editing in murine macrophages; with mouse strains expressing mostly a truncated alternative transcript isoform of Apobec1 exhibiting lower rates of editing. As a proof of concept, we have used linkage analysis to identify 36 high-confidence novel edited sites. These results provide a novel and complementary method that can be used to identify C-to-U editing sites in individuals segregating at specific loci and show that, beyond DNA sequence and structural changes, differential isoform usage and mRNA editing can contribute to intra-species genomic and phenotypic diversity. [Supplemental material is available for this article.]Splicing is an obligatory step in the processing of both coding and noncoding RNA precursors (pre-RNA) to mature RNA, and is executed by a ribonucleoprotein megaparticle known as the spliceosome. Even though the sequential assembly of the spliceosome (Kornblihtt et al. 2013) can occur around any splice site that consists of consensus sequences recognized by the spliceosomal components, splice sites that conform better to a consensus sequence are strongly recognized and favored by the spliceosome complex. Besides the consensus sequences, the selection of optimal splice sites is regulated, in part, by a minimal set of conserved cis-acting GU and AG sequences at the 59 and 39 splice sites, respectively , and sequence elements known as intronic/exonic splicing enhancers and silencers

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“…For these strains, each chromosome of the a/J strain was individually transferred into the B6 background [51]. This consomic strain panel is now widely applied to the genetic dissection of complex traits, including anxiety [52], pubertal timing [22], cis-and trans-regulation of transcripts in the kidney and liver [49], obesity [5,25,47,65] and epistatic effects on many complex traits [47].…”

Section: Mouse Consomic Strains As New Tools For the Study Of Quantitmentioning

confidence: 99%

Complex Quantitative Traits Cracked by the Mouse Inter-Subspecific Consomic Strains

Takada

Shiroishi

2012

Exp. Anim.

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Mammalian quantitative traits that are observed at the whole-body level, such as body weight and length and blood biochemical parameters, are determined by the cooperative effects of multiple genetic and epigenetic factors as well as environmental factors. This complexity has hampered the genetic analysis of quantitative traits. To overcome this difficulty, we have established a full set of consomic mouse strains, also known as chromosome substitution strains, by replacing every chromosome of the classical inbred strain C57BL/6J with its counterpart from the Japanese wildmouse-derived inbred strain MSM/Ms. The core components of the genomes of these two strains originated from different mouse subspecies. The inter-subspecific large-genome divergence and phenotypic differences between the two strains allowed the identification of genetic determinants for many quantitative traits by comprehensive phenotype screening. For some quantitative traits, the genetic determinants could be dissected into multiple chromosomes, thereby reflecting strain differences between C57BL/6J and MSM/Ms and their simple additive effects on the background of the consomic host strain. For other quantitative traits, the measured values of some consomic strains often far exceeded the range of the two parental strains, which suggests that nonadditive genetic interactions occur among multiple genes located on the substituted MSM/Ms chromosomes and the consomic host chromosomes. Thus, the inter-subspecific consomic strains are unique tools that can be used to identify both additive and nonadditive genetic effects on quantitative complex traits.

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Genetic resistance to diet-induced obesity in chromosome substitution strains of mice

Cited by 32 publications

References 57 publications

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

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

The genetic basis for individual differences in mRNA splicing and APOBEC1 editing activity in murine macrophages

Complex Quantitative Traits Cracked by the Mouse Inter-Subspecific Consomic Strains

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