ArticleHeredity2020
Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data.
Article in Heredity, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed, 65 citations in OpenAlex.
- Causal variants in animal genomes: approaches to identification, phenotypic impact, and implications for selective breeding.BMC genomics · 2026Review
- Assessing the effect of bovine MSTN variants on pre-mRNA splicing.Animal genetics · 2026Article
- A 17.1 kb duplication downstream GATA6 is strongly associated with egg weight in chicken.BMC genomics · 2025Article
- Functional impact of splicing variants in the elaboration of complex traits in cattle.Nature communications · 2025Article
- Genetic Associations ofAnimals : an open access journal from MDPI · 2025Article
- Erosion of estimated genomic breeding values with generations is due to long distance associations between markers and QTL.Genetics, selection, evolution : GSE · 2025Article
- Evaluation of genomic selection models using whole genome sequence data and functional annotation in Belgian Blue cattle.Genetics, selection, evolution : GSE · 2025Article
- Integrating Significant SNPs Identified by GWAS for Genomic Prediction of the Number of Ribs and Carcass Length in Suhuai Pigs.Animals : an open access journal from MDPI · 2025Article
- Bioinformatic approach to identifying causative missense polymorphisms in animal genomes.BMC genomics · 2024Article
- Identification of Genetic Associations ofLife (Basel, Switzerland) · 2024Article
- Development and validation of a 5K low-density SNP chip for Hainan cattle.BMC genomics · 2024Article
- Imputation strategies for genomic prediction using nanopore sequencing.BMC biology · 2023Article
- A breed-of-origin of alleles model that includes crossbred data improves predictive ability for crossbred animals in a multi-breed population.Genetics, selection, evolution : GSE · 2023Article
- Utility of multi-omics data to inform genomic prediction of heifer fertility traits.Journal of animal science · 2022Article
- Genome-wide association study and genomic prediction for intramuscular fat content in Suhuai pigs using imputed whole-genome sequencing data.Evolutionary applications · 2022Article
- Genomic Selection in Chinese Holsteins Using Regularized Regression Models for Feature Selection of Whole Genome Sequencing Data.Animals : an open access journal from MDPI · 2022Article
- Genotyping, the Usefulness of Imputation to Increase SNP Density, and Imputation Methods and Tools.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing.Genetics, selection, evolution : GSE · 2021Article
- An evaluation of the predictive performance and mapping power of the BayesR model for genomic prediction.G3 (Bethesda, Md.) · 2021Article
- Genomic prediction using a reference population of multiple pure breeds and admixed individuals.Genetics, selection, evolution : GSE · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The availability of whole genome sequencing (WGS) data enables the discovery of causative single nucleotide polymorphisms (SNPs) or SNPs in high linkage disequilibrium with causative SNPs. This study investigated effects of integrating SNPs selected from imputed WGS data into the data of 54K chip on genomic prediction in Danish Jersey. The WGS SNPs, mainly including peaks of quantitative trait loci, structure variants, regulatory regions of genes, and SNPs within genes with strong effects predicted with variant effect predictor, were selected in previous analyses for dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA). Animals genotyped with 54K chip, standard LD chip, and customized LD chip which covered selected WGS SNPs and SNPs in the standard LD chip, were imputed to 54K together with DFS and FRA SNPs. Genomic best linear unbiased prediction (GBLUP) and Bayesian four-distribution mixture models considering 54K and selected WGS SNPs as one (a one-component model) or two separate genetic components (a two-component model) were used to predict breeding values. For milk production traits and mastitis, both DFS (0.025) and FRA (0.029) sets of additional WGS SNPs improved reliabilities, and inclusions of all selected WGS SNPs generally achieved highest improvements of reliabilities (0.034). A Bayesian four-distribution model yielded higher reliabilities than a GBLUP model for milk and protein, but extra gains in reliabilities from using selected WGS SNPs were smaller for a Bayesian four-distribution model than a GBLUP model. Generally, no significant difference was observed between one-component and two-component models, except for using GBLUP models for milk.
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.