High-Resolution Genetic Mapping in the Diversity Outbred Mouse Population Identifies Apobec1 as a Candidate Gene for Atherosclerosis
Open accessAbstract
Inbred mice exhibit strain-specific variation in susceptibility to atherosclerosis and dyslipidemia that renders them useful in dissecting the genetic architecture of these complex diseases. Traditional quantitative trait locus (QTL) mapping studies using inbred strains often identify large genomic regions, containing many genes, due to limited recombination and/or sample size. This hampers candidate gene identification and translation of these results into possible risk factors and therapeutic targets. An alternative approach is the use of multiparental outbred lines for genetic mapping, such as the Diversity Outbred (DO) mouse panel, which can be more informative than traditional two-parent crosses and can aid in the identification of causal genes and variants associated with QTL. We fed 292 female DO mice either a high-fat, cholesterol-containing (HFCA) diet, to induce atherosclerosis, or a low-fat, high-protein diet for 18 wk and measured plasma lipid levels before and after diet treatment. We measured markers of atherosclerosis in the mice fed the HFCA diet. The mice were genotyped on a medium-density single-nucleotide polymorphism array and founder haplotypes were reconstructed using a hidden Markov model. The reconstructed haplotypes were then used to perform linkage mapping of atherosclerotic lesion size as well as plasma total cholesterol, triglycerides, insulin, and glucose. Among our highly significant QTL we detected a ~100 kb QTL interval for atherosclerosis on Chromosome 6, as well as a 1.4 Mb QTL interval on Chromosome 9 for triglyceride levels at baseline and a coincident 22.2 Mb QTL interval on Chromosome 9 for total cholesterol after dietary treatment. One candidate gene within the Chromosome 6 peak region associated with atherosclerosis is Apobec1, the apolipoprotein B (ApoB) mRNA-editing enzyme, which plays a role in the regulation of ApoB, a critical component of low-density lipoprotein, by editing ApoB mRNA. This study demonstrates the value of the DO population to improve mapping resolution and to aid in the identification of potential therapeutic targets for cardiovascular disease. Using a DO mouse population fed an HFCA diet, we were able to identify an A/J-specific isoform of Apobec1 that contributes to atherosclerosis.
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QTL mapping in multiparent populations has identified genetic modifiers for viral response, kidney disease, atherosclerosis, and heart size.
“For example, QTL mapping in these multiparent populations resulted in the identi cation of genetic modi ers for the viral response [13,14], kidney disease [15], atherosclerosis [16] and heart size [17].”
From Identification of Genetic Variants Regulating the Abundance of Clinically Relevant Plasma Proteins using the Diversity Outbred Mouse Model (2021) · cites this paper as [16]
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“Importantly, we demonstrated that fewer than 150 DO 146 mice are sufficient to identify statistically significant pQTL compared to the larger number 147 of DO mice used in previous studies [16, 17, 26-30].”
BackgroundResultFifteen years of the Diversity Outbred mouse model: a review
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Self-citationLongevity as a complex genetic trait
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Induction of Autoimmune Myocarditis in Diversity Outbred Mice
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- Authors
- Smallwood, T. L., Gatti, D. M., Quizon, P., Weinstock, G. M., Jung, K.-C., Zhao, L., Hua, K., Pomp, D., & Bennett, B. J.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Jackson Laboratory (US)
- Nutrition Research Institute, University of North Carolina Kannapolis, North Carolina 28081
- The Jackson Laboratory for Genomic Medicine (US)
- Corresponding author
- Bennett, Brian J
- Venue
- G3 Genes|Genomes|Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-12-01
- Volume
- 4
- Issue
- 12
- Pages
- 2353-2363
- ISSN
- 2160-1836 (ISSN-L)
- PMC
- PMC4267931
- OpenAlex
- W2101762508
- Cited by
- 54
- References
- 40
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 2 · 2023: 4 · 2022: 3 · 2021: 9 · 2020: 8 · 2019: 6 · 2018: 4 · 2017: 6 · 2016: 4 · 2015: 4
- FWCI
- 3.07
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- G3 Genes Genomes Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- The Mouseion at the JAXlibrary (Jackson Laboratory) (submittedVersion)
- UNC Libraries
- Funders
- National Heart, Lung, and Blood Institute (R00HL102223)
- National Human Genome Research Institute (U54HG004968)
- National Institute of General Medical Sciences (T32GM007092, R01GM070683)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK056350)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Immunology and Microbiology › Immunology › Atherosclerosis and Cardiovascular Diseases
- Keywords
- atherosclerosis, APOBEC1, Diversity Outbred mice, quantitative trait loci, linkage mapping, high-fat high-cholesterol diet, plasma lipids, triglycerides, total cholesterol, founder haplotype, dyslipidemia, cardiovascular genetics
- MeSH terms
- APOBEC-1 Deaminase, Animals, Blood Glucose, Cholesterol, Chromosome Mapping, Cytidine Deaminase, Female, Genotype, Haplotypes, Insulin, Markov Chains, Mice, Inbred Strains, RNA, Messenger, Triglycerides, Genome, Protein Isoforms, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Atherosclerosis, Mice, Diet, High-Fat
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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