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Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice.

ABSTRACT: Background:Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology. Methods:Liver weight of 506 mice generated from 39 different Collaborative Cross (CC) lines with both sexes at age 20 weeks old was determined using an electronic balance. Genomic DNA of the CC lines was genotyped with high-density single nucleotide polymorphic markers. Results:Statistical analysis revealed a significant (P < 0.05) variation of liver weight between the CC lines, with broad sense heritability (H 2) of 0.32 and genetic coefficient of variation (CVG) of 0.28. Subsequently, quantitative trait locus (QTL) mapping was performed, and results showed a significant QTL only for females on chromosome 8 at genomic interval 88.61-93.38 Mb (4.77 Mb). Three suggestive QTL were mapped at chromosomes 4, 12 and 13. The four QTL were designated as LWL1-LWL4 referring to liver weight loci 1-4 on chromosomes 8, 4, 12 and 13, respectively. Conclusion:To our knowledge, this report presents, for the first time, the utilization of the CC for mapping QTL associated with baseline liver weight in mice. Our findings demonstrate that liver weight is a complex trait controlled by multiple genetic factors that differ significantly between sexes.

SUBMITTER: Abu-Toamih Atamni HJ

PROVIDER: S-EPMC6388055 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice.

Abu-Toamih Atamni Hanifa J HJ Botzman Maya M Mott Richard R Gat-Viks Irit I Iraqi Fuad A FA

Animal models and experimental medicine 20180901 3

<h4>Background</h4>Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology.<h4>Methods</h4>Liver weight of 506 mice generated from 39 different Collaborative Cross (CC) lines with both sexes at age 20 weeks old was determined using an elect ...[more]

PMID: 30891567

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Project description:ObjectiveAnimal studies remain essential for understanding mechanisms of epilepsy and identifying new therapeutic targets. However, existing animal models of epilepsy do not reflect the high level of genetic diversity found in the human population. The Collaborative Cross (CC) population is a genetically diverse recombinant inbred panel of mice. The CC offers large genotypic and phenotypic diversity, inbred strains with stable genomes that allow for repeated phenotypic measurements, and genomic tools including whole genome sequence to identify candidate genes and candidate variants.MethodsWe evaluated multiple complex epileptic traits in a sampling of 35 CC inbred strains using the flurothyl-induced seizure and kindling paradigm. We created an F2 population of 297 mice with extreme seizure susceptibility and performed quantitative trait loci (QTL) mapping to identify genomic regions associated with seizure sensitivity. We used quantitative RNA sequencing from CC hippocampal tissue to identify candidate genes and whole genome sequence to identify genetic variants likely affecting gene expression.ResultsWe identified new mouse models with extreme seizure susceptibility, seizure propagation, epileptogenesis, and SUDEP (sudden unexpected death in epilepsy). We performed QTL mapping and identified one known and seven novel loci associated with seizure sensitivity. We combined whole genome sequencing and hippocampal gene expression to pinpoint biologically plausible candidate genes (eg, Gabra2) and variants associated with seizure sensitivity.SignificanceNew mouse models of epilepsy are needed to better understand the complex genetic architecture of seizures and to identify therapeutics. We performed a phenotypic screen utilizing a novel genetic reference population of CC mice. The data we provide enable the identification of protective/risk genes and novel molecular mechanisms linked to complex seizure traits that are currently challenging to study and treat.

Project description:BackgroundFamilial adenomatous polyposis is an inherited genetic disease, characterized by colorectal polyps. It is caused by inactivating mutations in the Adenomatous polyposis coli (Apc) gene. Mice carrying a nonsense mutation in the Apc gene at R850, which is designated ApcMin/+ (Multiple intestinal neoplasia), develop intestinal adenomas. Several genetic modifier loci of Min (Mom) were previously mapped, but so far, most of the underlying genes have not been identified. To identify novel modifier loci associated with ApcMin/+, we performed quantitative trait loci (QTL) analysis for polyp development using 49 F1 crosses between different Collaborative Cross (CC) lines and C57BL/6 J-ApcMin/+mice. The CC population is a genetic reference panel of recombinant inbred lines, each line independently descended from eight genetically diverse founder strains. C57BL/6 J-ApcMin/+ males were mated with females from 49 CC lines. F1 offspring were terminated at 23 weeks and polyp counts from three sub-regions (SB1-3) of small intestinal and colon were recorded.ResultsThe number of polyps in all these sub-regions and colon varied significantly between the different CC lines. At 95% genome-wide significance, we mapped nine novel QTL for variation in polyp number, with distinct QTL associated with each intestinal sub-region. QTL confidence intervals varied in width between 2.63-17.79 Mb. We extracted all genes in the mapped QTL at 90 and 95% CI levels using the BioInfoMiner online platform to extract, significantly enriched pathways and key linker genes, that act as regulatory and orchestrators of the phenotypic landscape associated with the ApcMin/+ mutation.ConclusionsGenomic structure of the CC lines has allowed us to identify novel modifiers and confirmed some of the previously mapped modifiers. Key genes involved mainly in metabolic and immunological processes were identified. Future steps in this analysis will be to identify regulatory elements - and possible epistatic effects - located in the mapped QTL.

Dataset Information

Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice.

Publications

Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice.

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