Data imputation and machine learning improve association analysis and genomic prediction for resistance to fish photobacteriosis in the gilthead sea bream

Data imputation and machine learning improve association analysis and genomic prediction for resistance to fish photobacteriosis in the gilthead sea bream

Disease resistance represents a key trait for breeding programs in aquaculture species. Here we re-analysed 2bRAD sequence data from two experimental challenges of gilthead sea bream with Photobacterium damsealae piscicida. Using a high quality reference genome, we carried out variant calling and da...

Full description

Bibliographic Details
Main Authors: Luca Bargelloni, Oronzo Tassiello, Massimiliano Babbucci, Serena Ferraresso, Rafaella Franch, Ludovica Montanucci, Paolo Carnier
Format: Article
Language:English
Published: Elsevier 2021-07-01
Series:Aquaculture Reports
Subjects:
Disease resistance
Genomic prediction
Data imputation
Machine learning
Sea bream
Online Access:http://www.sciencedirect.com/science/article/pii/S2352513421000776

Internet

http://www.sciencedirect.com/science/article/pii/S2352513421000776

Similar Items