title: Within-generation mutation variance for litter size in inbred mice.
abstract: The mutational input of genetic variance per generation (sigma(m)(2)) is the lower limit of the genetic variability in inbred strains of mice, although greater values could be expected due to the accumulation of new mutations in successive generations. A mixed-model analysis using Bayesian methods was applied to estimate sigma(m)(2) and the across-generation accumulated genetic variability on litter size in 46 generations of a C57BL/6J inbred strain. This allowed for a separate inference on sigma(m)(2) and on the additive genetic variance in the base population (sigma(a)(2)). The additive genetic variance in the base generation was 0.151 and quickly decreased to almost null estimates in generation 10. On the other hand, sigma(m)(2) was moderate (0.035) and the within-generation mutational variance increased up to generation 14, then oscillating between 0.102 and 0.234 in remaining generations. This pattern suggested the existence of a continuous uploading of genetic variability for litter size (h(2)=0.045). Relevant genetic drift was not detected in this population. In conclusion, our approach allowed for separate estimation of sigma(a)(2) and sigma(m)(2) within the mixed-model framework, and the heritability obtained highlighted the significant and continuous influence of new genetic variability affecting the genetic stability of inbred strains.
authors.affiliation: Genetica i Millora Animal, Institut de Recerca i Tecnologia Agroalimentaries-Lleida, Lleida, Spain.
authors.forename: Joaquim
authors.initials: J
authors.lastname: Casellas
authors.forename: Juan F
authors.initials: JF
authors.lastname: Medrano
mesh_terms: D000465:Algorithms; D000818:Animals; D005260:Female; D014644:Genetic Variation; D040582:Inheritance Patterns; D008098:Litter Size / Q000235:genetics*; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL / Q000235:genetics; D008815:Mice, Inbred Strains / Q000235:genetics*; D009154:Mutation; D012641:Selection, Genetic