title: Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.
abstract: The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.
authors.affiliation: Departamento de Mejora Genética Animal, INIA Madrid, Spain.
authors.forename: Jesús
authors.initials: J
authors.lastname: Fernández
authors.affiliation: Departamento de Producción Animal, ETSI Agrónomos, Universidad Politécnica de Madrid Madrid, Spain.
authors.forename: Miguel Á
authors.initials: MÁ
authors.lastname: Toro
authors.affiliation: Nofima Ås, Norway.
authors.forename: Anna K
authors.initials: AK
authors.lastname: Sonesson
authors.affiliation: Departamento de Mejora Genética Animal, INIA Madrid, Spain.
authors.forename: Beatriz
authors.initials: B
authors.lastname: Villanueva
keywords: SNP markers; aquaculture breeding programs; base populations; fish genomics; optimal contributions