Benchmarking Bayesian genome enabled-prediction models for age at first calving in Nellore cows

Mota, Rodrigo Reis; Silva, Fabyano Fonseca e; Guimarães, Simone Eliza Facioni; Hayes, Ben J.; Fortes, M. R. S.; Kelly, Matthew; Guimarães, José Domingos; Penitente-Filho, Jurandy Mauro; Ventura, Henrique Torres; Moore, S. S.

doi:10.1016/j.livsci.2018.03.009

Cited by 8 publications

(11 citation statements)

References 23 publications

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“…Moreover, this focus on ranking appeared as an appealing feature in the context of poplar breeding. Although less frequent in the literature than Pearson-based predicting abilities, a few authors used Spearman correlation to evaluate the prediction quality and to serve as criterion to select evaluation approaches (González-Recio et al, 2009;Mota et al, 2018). Some other authors suggest that individual ranking strategies could be more efficient (Blondel et al, 2015).…”

Section: Genomic Prediction Enables the Ranking Of Candidates To Selementioning

confidence: 99%

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar

Pégard¹,

Segura

Muñoz³

et al. 2020

Front. Plant Sci.

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Section: Genomic Prediction Enables the Ranking Of Candidates To Selementioning

confidence: 99%

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar

Pégard¹,

Segura

Muñoz³

et al. 2020

Front. Plant Sci.

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“…In the Nellore breed, the accuracy of prediction for AFC was 0.64 ( Boddhireddy et al, 2014 ); however, another scholarly journal reported that the accuracy ranged between 0.38 and 0.42 by three different models ( Costa et al, 2019 ). The prediction accuracy is around 0.23–0.33 in another Nellore cow population ( Mota et al, 2018 ). Using the ssGBLUP model, the accuracy of prediction for AFC was 0.299 in the Thai native breed ( Laodim et al, 2019 ), and was 0.56 in the Gyr dairy cattle breed ( Boison et al, 2017 ).…”

Section: Genomic Selection For Reproductive Traits In Bovine and Buffmentioning

confidence: 95%

Genetic Features of Reproductive Traits in Bovine and Buffalo: Lessons From Bovine to Buffalo

et al. 2021

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Bovine and buffalo are important livestock species that have contributed to human lives for more than 1000 years. Improving fertility is very important to reduce the cost of production. In the current review, we classified reproductive traits into three categories: ovulation, breeding, and calving related traits. We systematically summarized the heritability estimates, molecular markers, and genomic selection (GS) for reproductive traits of bovine and buffalo. This review aimed to compile the heritability and genome-wide association studies (GWASs) related to reproductive traits in both bovine and buffalos and tried to highlight the possible disciplines which should benefit buffalo breeding. The estimates of heritability of reproductive traits ranged were from 0 to 0.57 and there were wide differences between the populations. For some specific traits, such as age of puberty (AOP) and calving difficulty (CD), the majority beef population presents relatively higher heritability than dairy cattle. Compared to bovine, genetic studies for buffalo reproductive traits are limited for age at first calving and calving interval traits. Several quantitative trait loci (QTLs), candidate genes, and SNPs associated with bovine reproductive traits were screened and identified by candidate gene methods and/or GWASs. The IGF1 and LEP pathways in addition to non-coding RNAs are highlighted due to their crucial relevance with reproductive traits. The distribution of QTLs related to various traits showed a great differences. Few GWAS have been performed so far on buffalo age at first calving, calving interval, and days open traits. In addition, we summarized the GS studies on bovine and buffalo reproductive traits and compared the accuracy between different reports. Taken together, GWAS and candidate gene approaches can help to understand the molecular genetic mechanisms of complex traits. Recently, GS has been used extensively and can be performed on multiple traits to improve the accuracy of prediction even for traits with low heritability, and can be combined with multi-omics for further analysis.

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“…In Nellore cattle, accuracies ranging from 0.23 to 0.63 were reported for age first calving [ 83 , 84 ] and from 0.25 to 0.67 for heifer early pregnancy, respectively [ 84 , 85 ]. Evaluations of age at puberty in Brahman and Tropical Composite indicated prediction accuracies varying between 0.20 and 0.50 [ 8 , 17 , 86 ].…”

Section: The Genetics Of Heifers Sexual Precocitymentioning

confidence: 99%

Sustainable Intensification of Beef Production in the Tropics: The Role of Genetically Improving Sexual Precocity of Heifers

Júnior

Silva

Mota

et al. 2022

Animals

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Increasing productivity through continued animal genetic improvement is a crucial part of implementing sustainable livestock intensification programs. In Zebu cattle, the lack of sexual precocity is one of the main obstacles to improving beef production efficiency. Puberty-related traits are complex, but large-scale data sets from different “omics” have provided information on specific genes and biological processes with major effects on the expression of such traits, which can greatly increase animal genetic evaluation. In addition, genetic parameter estimates and genomic predictions involving sexual precocity indicator traits and productive, reproductive, and feed-efficiency related traits highlighted the feasibility and importance of direct selection for anticipating heifer reproductive life. Indeed, the case study of selection for sexual precocity in Nellore breeding programs presented here show that, in 12 years of selection for female early precocity and improved management practices, the phenotypic means of age at first calving showed a strong decreasing trend, changing from nearly 34 to less than 28 months, with a genetic trend of almost −2 days/year. In this period, the percentage of early pregnancy in the herds changed from around 10% to more than 60%, showing that the genetic improvement of heifer’s sexual precocity allows optimizing the productive cycle by reducing the number of unproductive animals in the herd. It has a direct impact on sustainability by better use of resources. Genomic selection breeding programs accounting for genotype by environment interaction represent promising tools for accelerating genetic progress for sexual precocity in tropical beef cattle.

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Benchmarking Bayesian genome enabled-prediction models for age at first calving in Nellore cows

Cited by 8 publications

References 23 publications

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar

Genetic Features of Reproductive Traits in Bovine and Buffalo: Lessons From Bovine to Buffalo

Sustainable Intensification of Beef Production in the Tropics: The Role of Genetically Improving Sexual Precocity of Heifers

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