ArticleGenetics, selection, evolution : GSE2017
Using a very low-density SNP panel for genomic selection in a breeding program for sheep.
Article in Genetics, selection, evolution : GSE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed.
- Efficiency under epistasis of haplotype-based genomic selection for pure line breeding.Heredity · 2026Article
- Study of Genetic Progress in the Context of Disconnection Between Two Originally Connected Populations.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2026Article
- Estimation of genetic parameters and genetic trends for ewe longevity indicators in U.S. Katahdin sheep.Journal of animal science · 2025Article
- Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens.BMC genomics · 2023Article
- Article
- Applying genetic technologies to combat infectious diseases in aquaculture.Reviews in aquaculture · 2023Review
- Article
- Quality of breeding value predictions from longitudinal analyses, with application to residual feed intake in pigs.Genetics, selection, evolution : GSE · 2022Article
- Genomic Prediction of Complex Traits, Principles, Overview of Factors Affecting the Reliability of Genomic Prediction, and Algebra of the Reliability.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Interest of using imputation for genomic evaluation in layer chicken.Poultry science · 2020Article
- Development of a low-density panel for genomic selection of pigs in Russia.Translational animal science · 2020Article
- NanoGBS: A Miniaturized Procedure for GBS Library Preparation.Frontiers in genetics · 2020Article
- 1k-RiCA (1K-Rice Custom Amplicon) a novel genotyping amplicon-based SNP assay for genetics and breeding applications in rice.Rice (New York, N.Y.) · 2019Article
- The impact of reducing the frequency of animals genotyped at higher density on imputation and prediction accuracies using ssGBLUP1.Journal of animal science · 2019Article
- Improving Genomic Selection With Quantitative Trait Loci and Nonadditive Effects Revealed by Empirical Evidence in Maize.Frontiers in plant science · 2019Article
- Phenotypic Variation and Genetic Architecture for Photosynthesis and Water Use Efficiency in Soybean (Frontiers in plant science · 2019Article
- Linkage disequilibrium in Brazilian Santa Inês breed, Ovis aries.Scientific reports · 2018Article
- Genomic Prediction of Breeding Values Using a Subset of SNPs Identified by Three Machine Learning Methods.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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBuilding an efficient reference population for genomic selection is an issue when the recorded population is small and phenotypes are poorly informed, which is often the case in sheep breeding programs. Using stochastic simulation, we evaluated a genomic design based on a reference population with medium-density genotypes [around 45 K single nucleotide polymorphisms (SNPs)] of dams that were imputed from very low-density genotypes (≤ 1000 SNPs).
methodsA population under selection for a maternal trait was simulated using real genotypes. Genetic gains realized from classical selection and genomic selection designs were compared. Genomic selection scenarios that differed in reference population structure (whether or not dams were included in the reference) and genotype quality (medium-density or imputed to medium-density from very low-density) were evaluated.
resultsThe genomic design increased genetic gain by 26% when the reference population was based on sire medium-density genotypes and by 54% when the reference population included both sire and dam medium-density genotypes. When medium-density genotypes of male candidates and dams were replaced by imputed genotypes from very low-density SNP genotypes (1000 SNPs), the increase in gain was 22% for the sire reference population and 42% for the sire and dam reference population. The rate of increase in inbreeding was lower (from - 20 to - 34%) for the genomic design than for the classical design regardless of the genomic scenario.
conclusionsWe show that very low-density genotypes of male candidates and dams combined with an imputation process result in a substantial increase in genetic gain for small sheep breeding programs.
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.