ArticleJournal of animal science2019
Towards multi-breed genomic evaluations for female fertility of tropical beef cattle.
Article in Journal of animal science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 51 citations in OpenAlex.
- Implementation of Metafounders in the Genomic Prediction for the Polled Trait in Brahman Cattle Using a Multi-Breed Population.Animal genetics · 2026Article
- Better Multi-Breed Genomic Predictions for Tropical Bull Fertility Using a Breed-Adjusted Genomic Relationship Matrix.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Ascertainment Bias in Cattle SNP Arrays and Implications for Multibreed Genomic Predictions.Animal genetics · 2026Article
- Leveraging Fst and Genetic Distance to Optimize Reference Sets for Enhanced Cross-Population Genomic Prediction.Animals : an open access journal from MDPI · 2026Article
- Comparison of GBLUP and WGBLUP in genomic selection for beef cattle under different LD patterns and mixed multi-population scenarios: a simulation study.BMC genomics · 2025Article
- Using genotype imputation to integrate Canola populations for genome-wide association and genomic prediction of blackleg resistance.BMC genomics · 2025Article
- Application of Genomic Selection in Beef Cattle Disease Prevention.Animals : an open access journal from MDPI · 2025Review
- Genome-wide association and expression quantitative trait loci in cattle reveals common genes regulating mammalian fertility.Communications biology · 2024Article
- Imputation strategies for genomic prediction using nanopore sequencing.BMC biology · 2023Article
- Developing flexible models for genetic evaluations in smallholder crossbred dairy farms.Journal of dairy science · 2023Article
- Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations.Heredity · 2023Article
- Multi-breed genomic evaluation for tropical beef cattle when no pedigree information is available.Genetics, selection, evolution : GSE · 2023Article
- Sequence level genome-wide associations for bull production and fertility traits in tropically adapted bulls.BMC genomics · 2023Article
- Multi-breed genomic predictions and functional variants for fertility of tropical bulls.PloS one · 2023Article
- Selective genotyping to implement genomic selection in beef cattle breeding.Frontiers in genetics · 2023Article
- Sustainable Intensification of Beef Production in the Tropics: The Role of Genetically Improving Sexual Precocity of Heifers.Animals : an open access journal from MDPI · 2022Review
- Accuracy of Genomic Selection for Important Economic Traits of Cashmere and Meat Goats Assessed by Simulation Study.Frontiers in veterinary science · 2022Article
- Accounting for Group-Specific Allele Effects and Admixture in Genomic Predictions: Theory and Experimental Evaluation in Maize.Genetics · 2020Article
- Genetic control of temperament traits across species: association of autism spectrum disorder risk genes with cattle temperament.Genetics, selection, evolution : GSE · 2020Article
- Use of whole-genome sequence data and novel genomic selection strategies to improve selection for age at puberty in tropically-adapted beef heifers.Genetics, selection, evolution : GSE · 2020Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Developing accurate genomic evaluations of fertility for tropical beef cattle must deal with at least two major challenges (i) recording cow fertility traits in extensive production systems on large numbers of cows and (ii) the genomic evaluations should work across the breeds, crossbreds, and composites used in tropical beef production. Here, we assess accuracy of genomic evaluations for a trait which can be collected on a large scale in extensive conditions, corpus luteum score (CLscore), which is 1 if ovarian scanning indicates a heifer has cycled by 600 d and 0 if not, in a multi-breed population. A total of 3,696 heifers, including 979 Brahmans, 914 Droughtmasters, and 1,803 Santa Gertrudis in seven herds across 3-yr cohorts with CLscores, were genotyped for 24,211 SNPs. Genotypes were imputed to 728,785 SNPs. GBLUP and BayesR were used to predict GEBV. Accuracy of GEBV was evaluated with two validation strategies. In the first strategy, the last year cohort of heifers from each herd was used for validation, such that every herd had heifers in both reference and validation populations. In the second validation strategy, each herd in turn was removed in its entirety from the reference population, and was used for validation. For both validation strategies, accuracy of GEBV for single breed and multi-breed reference populations was assessed. For the first validation strategy, accuracy of GEBV ranged from 0.2 for Brahmans to 0.4 for Droughtmasters. Increasing marker density from 24K SNPs to 728K SNPs resulted in a small increase in accuracy, and including multiple-breeds in the reference did not help improve accuracy. These results suggest that provided a herd has animals in the reference population, the accuracy of the GEBV is largely determined by within herd (linkage) information. The situation was very different when entire herds were predicted in the second validation. In this case accuracy of GEBV using only 24K SNPs and only a within breed reference was close to zero for all breeds. Accuracy increased substantially when 728K SNPs, BayesR, and a multi-breed reference were used, from 0.15 for Brahmans to 0.35 for Santa Gertrudis. Given the second validation strategy is more likely to reflect the situation for many herds in tropical beef production (no animals in the reference), genomic evaluations for fertility in tropical beef cattle should be based on high-density markers (728K SNPs) and should be multi-breed.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.