Managing genetic diversity in breeding programs of small populations: the case of French local chicken breeds.

Background: On-going climate change will drastically modify agriculture in the future, with a need for more sustainable systems, in particular regarding animal production. In this context, genetic diversity is a key factor for adaptation to new conditions: local breeds likely harbor unique adaptive features and represent a key component of diversity to reach resilience. However, local breeds often suffer from small population sizes, which puts these valuable resources at risk of extinction.

Corrigendum: Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, The European Sea Bass () and the Gilthead Sea Bream ().

[This corrects the article DOI: 10.3389/fgene.2021.

Optimization of Genomic Selection to Improve Disease Resistance in Two Marine Fishes, the European Sea Bass () and the Gilthead Sea Bream ().

Disease outbreaks are a major threat to the aquaculture industry, and can be controlled by selective breeding. With the development of high-throughput genotyping technologies, genomic selection may become accessible even in minor species. Training population size and marker density are among the main drivers of the prediction accuracy, which both have a high impact on the cost of genomic selection.

Genetic architecture and genomic selection of female reproduction traits in rainbow trout.

Background: Rainbow trout is a significant fish farming species under temperate climates. Female reproduction traits play an important role in the economy of breeding companies with the sale of fertilized eggs. The objectives of this study are threefold: to estimate the genetic parameters of female reproduction traits, to determine the genetic architecture of these traits by the identification of quantitative trait loci (QTL), and to assess the expected efficiency of a pedigree-based selection (BLUP) or genomic selection for these traits.

APIS: An auto-adaptive parentage inference software that tolerates missing parents.

In the context of parentage assignment using genomic markers, key issues are genotyping errors and an absence of parent genotypes because of sampling, traceability or genotyping problems. Most likelihood-based parentage assignment software programs require a priori estimates of genotyping errors and the proportion of missing parents to set up meaningful assignment decision rules. We present here the R package APIS, which can assign offspring to their parents without any prior information other than the offspring and parental genotypes, and a user-defined, acceptable error rate among assigned offspring.