ArticleGenetics, selection, evolution : GSE2015
Genomic correlation: harnessing the benefit of combining two unrelated populations for genomic selection.
Article in Genetics, selection, evolution : GSE, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- GWAS and genomic prediction of milk urea nitrogen in Australian and New Zealand dairy cattle.Genetics, selection, evolution : GSE · 2022Pooled it
- 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
- Multi-Breed Genomic Predictions for Average Daily Gain in Three Italian Beef Cattle Breeds.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Genomic prediction in a small barley population can benefit from training on related populations.G3 (Bethesda, Md.) · 2025Article
- Improving genomic prediction in pigs by integrating multi-population data and prior knowledge.BMC genomics · 2025Article
- Accuracy of genomic prediction using multiple Atlantic salmon populations.Genetics, selection, evolution : GSE · 2024Article
- Single-Step Genomic Prediction of Superovulatory Response Traits in Japanese Black Donor Cows.Biology · 2023Article
- Multi-breed genomic predictions and functional variants for fertility of tropical bulls.PloS one · 2023Article
- Utility of multi-omics data to inform genomic prediction of heifer fertility traits.Journal of animal science · 2022Article
- The correlation of substitution effects across populations and generations in the presence of nonadditive functional gene action.Genetics · 2021Article
- Genome-Wide Association Study Demonstrates the Role Played by theAnimals : an open access journal from MDPI · 2021Article
- Accounting for Group-Specific Allele Effects and Admixture in Genomic Predictions: Theory and Experimental Evaluation in Maize.Genetics · 2020Article
- Uncovering Sub-Structure and Genomic Profiles in Across-Countries Subpopulations of Angus Cattle.Scientific reports · 2020Article
- The Impact of Non-additive Effects on the Genetic Correlation Between Populations.G3 (Bethesda, Md.) · 2020Article
- GWAS for Meat and Carcass Traits Using Imputed Sequence Level Genotypes in Pooled F2-Designs in Pigs.G3 (Bethesda, Md.) · 2019Article
- Multivariate genomic predictions for age at puberty in tropically adapted beef heifers.Journal of animal science · 2019Article
- Semi-parametric estimates of population accuracy and bias of predictions of breeding values and future phenotypes using the LR method.Genetics, selection, evolution : GSE · 2018Article
- Weighting genomic and genealogical information for genetic parameter estimation and breeding value prediction in tropical beef cattle.Journal of animal science · 2018Article
- Predictive ability of genomic selection models in a multi-population perennial ryegrass training set using genotyping-by-sequencing.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018Article
- Joint Genomic Prediction of Canine Hip Dysplasia in UK and US Labrador Retrievers.Frontiers in genetics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe success of genomic selection in animal breeding hinges on the availability of a large reference population on which genomic-based predictions of additive genetic or breeding values are built. Here, we explore the benefit of combining two unrelated populations into a single reference population.
methodsThe datasets consisted of 1829 Brahman and 1973 Tropical Composite cattle with measurements on five phenotypes relevant to tropical adaptation and genotypes for 71,726 genome-wide single nucleotide polymorphisms (SNPs). The underlying genomic correlation for the same phenotype across the two breeds was explored on the basis of consistent linkage disequilibrium (LD) phase and marker effects in both breeds.
resultsThe proportion of genetic variance explained by the entire set of SNPs ranged from 37.5 to 57.6 %. Estimated genomic correlations were drastically affected by the process used to select SNPs and went from near 0 to more than 0.80 for most traits when using the set of SNPs with significant effects and the same LD phase in the two breeds. We found that, by carefully selecting the subset of SNPs, the missing heritability can be largely recovered and accuracies in genomic predictions can be improved six-fold. However, the increases in accuracy might come at the expense of large biases.
conclusionsOur results offer hope for the effective implementation of genomic selection schemes in situations where the number of breeds is large, the sample size within any single breed is small and the breeding objective includes many phenotypes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.