Single QTL Effects, Epistasis, and Pleiotropy Account for Two-thirds of the Phenotypic F2 Variance of Growth and Obesity in DU6i x DBA/2 Mice

Brockmann, Gudrun A.; Kratzsch, Jürgen; Haley, Chris; Renne, Ulla; Schwerin, Manfred; Karle, Steffanie

doi:10.1101/gr.gr1499r

Cited by 130 publications

(151 citation statements)

References 48 publications

Supporting

Mentioning

129

Contrasting

Order By: Relevance

“…The general lack of many significant epistatic interactions in this cross is in contrast to results of several studies (e.g., Routman and Cheverud 1997; Brockmann et al 2000). However, this finding is not unusual (Clark 2000), as attempts to detect epistasis with these types of linear models raise a number of issues of difficult resolution (e.g., The lack of statistical detection of epistatic interactions in the context of these models does not preclude the existence or the importance of epistasis, as our results (especially for WT3wk) seem to confirm.…”

Section: Discussioncontrasting

confidence: 99%

“…While some previous large QTL studies have focused on a single end-point measurement of growth (e.g., Brockmann et al 1998bBrockmann et al , 2000, others (Cheverud et al 1996;Vaughn et al 1999) have conducted comprehensive experiments evaluating growth at different age periods. Although the sample size used by Cheverud et al (1996) was smaller (n = 535), the Vaughn et al (1999) study used an F 2 population with power similar to that in the present study (n = 1045).…”

Section: Discussionmentioning

confidence: 99%

“…Marker-based GLM models were used to test all pair-wise and higher-order epistatic interactions among markers included in the final selected models (Brockmann et al 2000), and also to test all interactions between these markers and the fixed effects. To examine the possibility of marker X sex interac-tions, separate CIM analyses were conducted for each gender.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A large-sample QTL study in mice: I. Growth

et al. 2004

View full text Add to dashboard Cite

Section: Discussioncontrasting

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A large-sample QTL study in mice: I. Growth

et al. 2004

View full text Add to dashboard Cite

“…Despite the huge recessive jObes1 effect, this study confirmed, with the identification of additional QTLs on five chromosomes, that most genetic variance contributing to body weight and obesity as complex traits is additive. 30,31 Although the mouse genome is multi-saturated with many QTLs for body weight-and obesity-related traits, 11 32 Abfp4 was only significant when interacting with a locus on Chr 5, but it was another hint for a QTL for abdominal white adipose tissue percentage in this population. The QTL allele originating from DU6i had an additive genetic effect and decreased fat deposition in all cases.…”

Section: Discussionmentioning

confidence: 89%

A unique genetic defect on chromosome 3 is responsible for juvenile obesity in the Berlin Fat Mouse

et al. 2010

View full text Add to dashboard Cite

Objective: This study aimed at the mapping and estimation of genetic and sex effects contributing to the obese phenotype of the Berlin Fat Mouse Inbred line 860 (BFMI860). This mouse line is predisposed for juvenile obesity. BFMI860 mice accumulate 24% total fat mass at 10 weeks of age under a standard maintenance diet. Design: A total of 471 mice of a (BFMI860 Â C57BL/6NCrl) F 2 intercross population were fed a standard maintenance diet and were analysed for body composition at 10 weeks when they finished their rapid growth phase. Results: The most striking result was the identification of a novel obesity locus on chromosome 3 (Chr 3) at 40 Mb, explaining 39% of the variance of total fat mass in the F 2 population under a standard diet. This locus was named jObes1 (juvenile obesity 1). The BFMI860 allele effect was recessive. Males and females homozygous at jObes1 had on average 3.0 and 3.3 g more total fat mass at 10 weeks than the other two genotype classes, respectively. The effect was evident in all white adipose tissues, brown adipose tissue and also in liver. The position of the Chr 3 effect is syntenic to an obesity locus in humans. Additional loci for total fat mass and different white adipose tissue weights with minor effects were detected on mouse Chr 5 and 6. Another locus on Chr 4 had influence especially on liver weight. Many loci including jObes1 affected males and females to a different extent. Conclusion:The major locus on Chr 3 for juvenile obesity and its interaction with sex is unique and makes the BFMI860 mice an interesting resource for the discovery of novel genetic factors predisposing obesity, which might also contribute to obesity in humans. The results suggested that metabolic and regulatory pathways differed between the sexes.

show abstract

“…Quantitative trait locus (QTL) analysis has been used to successfully identify chromosomal regions affecting the quantitative traits, including obesity, bone density, and cerebellum size (Beamer et al 1999;Brockmann et al 2000;Airey et al 2001). The jaw apparatus, one of the most thoroughly investigated craniofacial components, has recently been analyzed as a quantitative trait, and QTL analysis has identified several genomic regions responsible for the size and shape of the mandible in mice (Klingenberg et al 2001(Klingenberg et al , 2004Dohmoto et al 1 2002).…”

mentioning

confidence: 99%

Genetic Analysis of Craniofacial Traits in the Medaka

et al. 2007

View full text Add to dashboard Cite

Family and twin studies suggest that a substantial genetic component underlies individual differences in craniofacial morphology. In the current study, we quantified 444 craniofacial traits in 100 individuals from two inbred medaka (Oryzias latipes) strains, HNI and Hd-rR. Relative distances between defined landmarks were measured in digital images of the medaka head region. A total of 379 traits differed significantly between the two strains, indicating that many craniofacial traits are controlled by genetic factors. Of these, 89 traits were analyzed via interval mapping of 184 F 2 progeny from an intercross between HNI and Hd-rR. We identified quantitative trait loci for 66 craniofacial traits. The highest logarithm of the odds score was 6.2 for linkage group (LG) 9 and 11. Trait L33, which corresponds to the ratio of head length to head height at eye level, mapped to LG9; trait V15, which corresponds to the ratio of snout length to head width measured behind the eyes, mapped to LG11. Our initial results confirm the potential of the medaka as a model system for the genetic analysis of complex traits such as craniofacial morphology.

show abstract

Single QTL Effects, Epistasis, and Pleiotropy Account for Two-thirds of the Phenotypic F2 Variance of Growth and Obesity in DU6i x DBA/2 Mice

Cited by 130 publications

References 48 publications

A large-sample QTL study in mice: I. Growth

A large-sample QTL study in mice: I. Growth

A unique genetic defect on chromosome 3 is responsible for juvenile obesity in the Berlin Fat Mouse

Genetic Analysis of Craniofacial Traits in the Medaka

Contact Info

Product

Resources

About