Skip to main content
Genetics logoLink to Genetics
. 1997 Feb;145(2):395–408. doi: 10.1093/genetics/145.2.395

Bayesian Statistical Analyses for Presence of Single Genes Affecting Meat Quality Traits in a Crossed Pig Population

LLG Janss 1, JAM Van-Arendonk 1, E W Brascamp 1
PMCID: PMC1207804  PMID: 9071593

Abstract

Presence of single genes affecting meat quality traits was investigated in F(2) individuals of a cross between Chinese Meishan and Western pig lines using phenotypic measurements on 11 traits. A Bayesian approach was used for inference about a mixed model of inheritance, postulating effects of polygenic background genes, action of a biallelic autosomal single gene and various nongenetic effects. Cooking loss, drip loss, two pH measurements, intramuscular fat, shearforce and back-fat thickness were traits found to be likely influenced by a single gene. In all cases, a recessive allele was found, which likely originates from the Meishan breed and is absent in the Western founder lines. By studying associations between genotypes assigned to individuals based on phenotypic measurements for various traits, it was concluded that cooking loss, two pH measurements and possibly backfat thickness are influenced by one gene, and that a second gene influences intramuscular fat and possibly shearforce and drip loss. Statistical findings were supported by demonstrating marked differences in variances of families of fathers inferred as carriers and those inferred as noncarriers. It is concluded that further molecular genetic research effort to map single genes affecting these traits based on the same experimental data has a high probability of success.

Full Text

The Full Text of this article is available as a PDF (1.4 MB).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Elston R. C., Stewart J. A general model for the genetic analysis of pedigree data. Hum Hered. 1971;21(6):523–542. doi: 10.1159/000152448. [DOI] [PubMed] [Google Scholar]
  2. Guo S. W., Thompson E. A. Monte Carlo estimation of variance component models for large complex pedigrees. IMA J Math Appl Med Biol. 1991;8(3):171–189. doi: 10.1093/imammb/8.3.171. [DOI] [PubMed] [Google Scholar]
  3. Hasstedt S. J. A mixed-model likelihood approximation on large pedigrees. Comput Biomed Res. 1982 Jun;15(3):295–307. doi: 10.1016/0010-4809(82)90064-7. [DOI] [PubMed] [Google Scholar]
  4. Knott S. A., Haley C. S., Thompson R. Methods of segregation analysis for animal breeding data: a comparison of power. Heredity (Edinb) 1992 Apr;68(Pt 4):299–311. doi: 10.1038/hdy.1992.44. [DOI] [PubMed] [Google Scholar]
  5. Le Roy P., Naveau J., Elsen J. M., Sellier P. Evidence for a new major gene influencing meat quality in pigs. Genet Res. 1990 Feb;55(1):33–40. doi: 10.1017/s0016672300025179. [DOI] [PubMed] [Google Scholar]
  6. Morton N. E., MacLean C. J. Analysis of family resemblance. 3. Complex segregation of quantitative traits. Am J Hum Genet. 1974 Jul;26(4):489–503. [PMC free article] [PubMed] [Google Scholar]
  7. Otsu K., Phillips M. S., Khanna V. K., de Leon S., MacLennan D. H. Refinement of diagnostic assays for a probable causal mutation for porcine and human malignant hyperthermia. Genomics. 1992 Jul;13(3):835–837. doi: 10.1016/0888-7543(92)90163-m. [DOI] [PubMed] [Google Scholar]
  8. Sheehan N., Thomas A. On the irreducibility of a Markov chain defined on a space of genotype configurations by a sampling scheme. Biometrics. 1993 Mar;49(1):163–175. [PubMed] [Google Scholar]
  9. Thomas D. C., Cortessis V. A Gibbs sampling approach to linkage analysis. Hum Hered. 1992;42(1):63–76. doi: 10.1159/000154046. [DOI] [PubMed] [Google Scholar]
  10. Zhang Y., Proenca R., Maffei M., Barone M., Leopold L., Friedman J. M. Positional cloning of the mouse obese gene and its human homologue. Nature. 1994 Dec 1;372(6505):425–432. doi: 10.1038/372425a0. [DOI] [PubMed] [Google Scholar]

Articles from Genetics are provided here courtesy of Oxford University Press

RESOURCES