Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.

Genetics, selection, evolution : GSE - 2 Apr 2015

Tiezzi Francesco, Maltecca Christian

Abstract excerpt

BACKGROUND: Genomic BLUP (GBLUP) can predict breeding values for non-phenotyped individuals based on the identity-by-state genomic relationship matrix (G). The G matrix can be constructed from thousands of markers spread across the genome. The strongest assumption of G and consequently of GBLUP is that all markers contribute equally to the genetic variance of a trait. This assumption is violated for traits that...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Breeding
Share to Cattle

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome

Share to Linkage Disequilibrium

Share to Quantitative Trait Loci

Share to Regression Analysis

Share to Selection, Genetic

Source

Open in PubMed Open full text

Identifiers

PMID: 25886167
DOI: 10.1186/s12711-015-0100-1
PMCID: PMC4381547

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Accounting for trait architecture in genomic predictions of US Holstein cattle using a weighted realized relationship matrix.PMID 25886167Read ↗

Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome.Semantic proximity Read ↗

Comparison of genomic predictions using genomic relationship matrices built with different weighting factors to account for locus-specific variances.Semantic proximity Read ↗

Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits.Semantic proximity Read ↗

Use of biological priors enhances understanding of genetic architecture and genomic prediction of complex traits within and between dairy cattle breeds.Semantic proximity Read ↗

Improving Genomic Predictions in Multi-Breed Cattle Populations: A Comparative Analysis of BayesR and GBLUP Models.Semantic proximity Read ↗

Optimizing genomic prediction model given causal genes in a dairy cattle population.Semantic proximity Read ↗

Alternative SNP weighting for multi-step and single-step genomic BLUP in the presence of causative variants.Semantic proximity Read ↗

Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.Semantic proximity Read ↗

Performances of Adaptive MultiBLUP, Bayesian regressions, and weighted-GBLUP approaches for genomic predictions in Belgian Blue beef cattle.Semantic proximity Read ↗

Accuracy of prediction of simulated polygenic phenotypes and their underlying quantitative trait loci genotypes using real or imputed whole-genome markers in cattle.Semantic proximity Read ↗

Comparison of genomic predictions for lowly heritable traits using multi-step and single-step genomic best linear unbiased predictor in Holstein cattle.Semantic proximity Read ↗

Accounting for genetic architecture for body weight improves accuracy of predicting breeding values in a commercial line of broilers.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.