Body composition and gene expression QTL mapping in mice reveals imprinting and interaction effects

Ye Cheng, Satyanarayana Rachagani, Angela Cánovas, Mary S. Mayes, Richard G. Tait, Jack C.M. Dekkers, James M. Reecy

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Background: Shifts in body composition, such as accumulation of body fat, can be a symptom of many chronic human diseases; hence, efforts have been made to investigate the genetic mechanisms that underlie body composition. For example, a few quantitative trait loci (QTL) have been discovered using genome-wide association studies, which will eventually lead to the discovery of causal mutations that are associated with tissue traits. Although some body composition QTL have been identified in mice, limited research has been focused on the imprinting and interaction effects that are involved in these traits. Previously, we found that Myostatin genotype, reciprocal cross, and sex interacted with numerous chromosomal regions to affect growth traits.Results: Here, we report on the identification of muscle, adipose, and morphometric phenotypic QTL (pQTL), translation and transcription QTL (tQTL) and expression QTL (eQTL) by applying a QTL model with additive, dominance, imprinting, and interaction effects. Using an F2 population of 1000 mice derived from the Myostatin-null C57BL/6 and M16i mouse lines, six imprinted pQTL were discovered on chromosomes 6, 9, 10, 11, and 18. We also identified two IGF1 and two Atp2a2 eQTL, which could be important trans-regulatory elements. pQTL, tQTL and eQTL that interacted with Myostatin, reciprocal cross, and sex were detected as well. Combining with the additive and dominance effect, these variants accounted for a large amount of phenotypic variation in this study.Conclusions: Our study indicates that both imprinting and interaction effects are important components of the genetic model of body composition traits. Furthermore, the integration of eQTL and traditional QTL mapping may help to explain more phenotypic variation than either alone, thereby uncovering more molecular details of how tissue traits are regulated.

Original languageEnglish (US)
Article number103
JournalBMC Genetics
Volume14
DOIs
StatePublished - Oct 29 2013

Fingerprint

Quantitative Trait Loci
Body Composition
Gene Expression
Myostatin
Chromosomes, Human, Pair 9
Chromosomes, Human, Pair 6
Genome-Wide Association Study
Genetic Models
Adipose Tissue
Chronic Disease
Genotype
Muscles
Mutation
Growth
Research
Population

Keywords

  • Body composition
  • EQTL mapping
  • Imprinting
  • Interaction
  • Mouse
  • Myostatin
  • QTL mapping

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

Body composition and gene expression QTL mapping in mice reveals imprinting and interaction effects. / Cheng, Ye; Rachagani, Satyanarayana; Cánovas, Angela; Mayes, Mary S.; Tait, Richard G.; Dekkers, Jack C.M.; Reecy, James M.

In: BMC Genetics, Vol. 14, 103, 29.10.2013.

Research output: Contribution to journalArticle

Cheng, Ye ; Rachagani, Satyanarayana ; Cánovas, Angela ; Mayes, Mary S. ; Tait, Richard G. ; Dekkers, Jack C.M. ; Reecy, James M. / Body composition and gene expression QTL mapping in mice reveals imprinting and interaction effects. In: BMC Genetics. 2013 ; Vol. 14.
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