Prediction of genomic breeding values for reproductive traits in Nellore heifers
Theriogenology, ISSN: 0093-691X, Vol: 125, Page: 12-17
2019
- 12Citations
- 35Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Metrics Details
- Citations12
- Citation Indexes12
- 12
- CrossRef9
- Captures35
- Readers35
- 35
Article Description
The objective of this study was to assess the accuracy of genomic predictions for female reproductive traits in Nellore cattle. A total of 1853 genotyped cows and 305,348 SNPs were used for genomic selection analyses. GBLUP, BAYESCπ, and IBLASSO were applied to estimate SNP effects. The pseudo-phenotypes used as dependent variables were: observed phenotype (PHEN), adjusted phenotype (CPHEN), estimated breeding value (EBV), and deregressed estimated breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlation between DEBV and GEBV in the validation population. Regression coefficients of pseudo-phenotypes on GEBV in the validation population were indicators of prediction bias in GEBV. BAYESCπ showed higher predictive ability to estimate SNP effects and GEBV for all traits.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0093691X18309683; http://dx.doi.org/10.1016/j.theriogenology.2018.10.014; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85055276452&origin=inward; http://www.ncbi.nlm.nih.gov/pubmed/30368127; https://linkinghub.elsevier.com/retrieve/pii/S0093691X18309683; https://dx.doi.org/10.1016/j.theriogenology.2018.10.014
Elsevier BV
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