Differences in DBA/1J and DBA/2J reveal lipid QTL genes

Abstract

Recent advances in mouse genomics have revealed considerable variation in the form of single-nucleotide polymorphisms (SNPs) among common inbred strains. This has made it possible to characterize closely related strains and to identify genes that differ; such genes may be causal for quantitative phenotypes. The mouse strains DBA/1J and DBA/2J differ by just 5.6% at the SNP level. These strains exhibit differences in a number of metabolic and lipid phenotypes, such as plasma levels of triglycerides (TGs) and HDL. A cross between these strains revealed multiple quantitative trait loci (QTLs) in 294 progeny. We identified significant TG QTLs on chromosomes (Chrs) 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 16, and 19, and significant HDL QTLs on Chrs 3, 9, and 16. Some QTLs mapped to chromosomes with limited variability between the two strains, thus facilitating the identification of candidate genes. We suggest that The leading cause of mortality in developed nations is ischemic cardiovascular disease, and the pathological basis is atherosclerosis. Major risk factors for atherosclerosis are high plasma levels of triglycerides (TGs) (1) and LDL, as well as low levels of HDL cholesterol (2). High levels of plasma HDL provide protection against heart disease, as shown in both human (3-5) and animal studies (6-11). Many genes and pathways controlling LDL levels are known; however, those that control TG and HDL levels are less well characterized. A successful route toward identifying genes that affect quantitative phenotypes is through the use of inbred mouse strains and quantitative trait locus (QTL) analysis. A combination of genetic tools and databases, along with improved mapping techniques (12), are helping to identify these QTL genes (13-15).When mapping QTLs in mouse models, it is important to use strains that differ in the phenotype of interest and to capture a large proportion of the genetic variation present in the inbred strains (16). However, in this study we used two mouse strains that differ in phenotype but are genetically closely related, demonstrating that QTL genes can be identified by using models of limited genetic variability. The strains used are DBA/1J (D1) and DBA/2J (D2).The DBA strain was developed by Clarence Cook Little in 1909 and is the oldest of all inbred strains of mice. In 1929-30, crosses were made between substrains, and several new substrains were established, including D1 and D2. Differences between the substrains are too large to be accounted for by mutation and probably result from residual heterozygosity following the crosses between substrains (www.informatics.jax.org/external/festing/search_ form.cgi). D1 and D2 have been assayed for ?140,000 single-nucleotide polymorphisms (SNPs) (17). Less than 6% of these differed between D1 and D2, and regions that are not identical by descent (IBD) contained just 1,697 known or predicted genes. Genes that are in polymorphic locations between D1 and D2 and underlie a QTL would be regarded as candidate genes.The D1 and D2 strains exhibit...

Influence of genetic background on ex vivo and in vivo cardiac function in several commonly used inbred mouse strains

“…Future studies could center on tracking and identification of QTL that modify particular cardiac disease-related physiological processes. Previous studies have demonstrated the feasibility of using the genetic homogeneity of inbred mouse strains to isolate and identify physiologically significant QTL (2,6,13,20,21,48,49). In this study, we observed significant functional differences between inbred strains that were evident when subjected to the stresses of ischemia/reperfusion, ␤-blockade, and acute hypoxia.…”

“…Even in the absence of engineered or known naturally occurring mutations, different inbred mouse strains can vary drastically in their susceptibility to clinically relevant diseases. Previous reports have taken advantage of this naturally occurring variation in susceptibility to a particular disease to identify quantitative trait loci (QTL) that modify disease pathogenesis (2,6,13,48,49).…”

High-Resolution Identity by Descent Mapping Uncovers the Genetic Basis for Blood Pressure Differences Between Spontaneously Hypertensive Rat Lines

“…While the contrast in parental blood pressure phenotype would be less than in contrasts between SHR and normotensive strains 5–7 genetic background effects may be much smaller 8 and the shared IBD would reduce the total region of the genome in which differences in blood pressure could arise. The same approach has recently been used in closely related mouse lines to yield high resolution mapping of trait genes 9 .…”

QTL analysis of clinical-chemical traits in an F2intercross between Landrace and Korean native pigs

“…There have been many studies on the QTL affecting lipid and glucose levels in both humans and rodents (1,29,49). However, studies on QTL for clinical-chemical traits other than lipid levels are still scarce when it comes to pigs.…”