ArticleFrontiers in genetics2015
Artificial selection with traditional or genomic relationships: consequences in coancestry and genetic diversity.
Article in Frontiers in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- From family trials to genomic mate allocation: statistical and genomic strategies to accelerate sugarcane genetic improvement.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Review
- Linkage- and ROH-based genomic relationship matrices for IBD based management of genetic diversity.Genetics, selection, evolution : GSE · 2026Article
- Heterosis and Hybrid Crop Breeding: A Multidisciplinary Review.Frontiers in genetics · 2021Review
- Estimation of Linkage Disequilibrium and Effective Population Size in Three Italian Autochthonous Beef Breeds.Animals : an open access journal from MDPI · 2020Article
- Genetic Improvement in Dromedary Camels: Challenges and Opportunities.Frontiers in genetics · 2019Article
- Predicting Growth Traits with Genomic Selection Methods in Zhikong Scallop (Chlamys farreri).Marine biotechnology (New York, N.Y.) · 2018Article
- Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015.Genetics, selection, evolution : GSE · 2018Article
- Long-Term Impact of Optimum Contribution Selection Strategies on Local Livestock Breeds with Historical Introgression Using the Example of German Angler Cattle.G3 (Bethesda, Md.) · 2017Article
- Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2017Article
- Characterization and management of long runs of homozygosity in parental nucleus lines and their associated crossbred progeny.Genetics, selection, evolution : GSE · 2016Article
- Editorial: Advances in Farm Animal Genomic Resources.Frontiers in genetics · 2015Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Estimated breeding values (EBVs) are traditionally obtained from pedigree information. However, EBVs from high-density genotypes can have higher accuracy than EBVs from pedigree information. At the same time, it has been shown that EBVs from genomic data lead to lower increases in inbreeding compared with traditional selection based on genealogies. Here we evaluate the performance with BLUP selection based on genealogical coancestry with three different genome-based coancestry estimates: (1) an estimate based on shared segments of homozygosity, (2) an approach based on SNP-by-SNP count corrected by allelic frequencies, and (3) the identity by state methodology. We evaluate the effect of different population sizes, different number of genomic markers, and several heritability values for a quantitative trait. The performance of the different measures of coancestry in BLUP is evaluated in the true breeding values after truncation selection and also in terms of coancestry and diversity maintained. Accordingly, cross-performances were also carried out, that is, how prediction based on genealogical records impacts the three other measures of coancestry and inbreeding, and viceversa. Our results show that the genetic gains are very similar for all four coancestries, but the genomic-based methods are superior to using genealogical coancestries in terms of maintaining diversity measured as observed heterozygosity. Furthermore, the measure of coancestry based on shared segments of the genome seems to provide slightly better results on some scenarios, and the increase in inbreeding and loss in diversity is only slightly larger than the other genomic selection methods in those scenarios. Our results shed light on genomic selection vs. traditional genealogical-based BLUP and make the case to manage the population variability using genomic information to preserve the future success of selection programmes.
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