Evidence map›Paper›PMID 40866809›Full record

ArticleBMC genomics2025

Improving genomic prediction in pigs by integrating multi-population data and prior knowledge.

Junliang Wang, Yujin Lu, Wenjing Zhang, Xiaodian Cai, Shuihua Xie, Yahui Gao, Jiaqi Li, Changguang Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Junliang Wang *State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
Yujin Lu *State Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
Wenjing ZhangState Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
Xiaodian CaiState Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
Shuihua XieAgriculture Technology Extension Centre of Guangdong Province, Guangzhou, 510520, China.
Yahui GaoState Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
Jiaqi LiState Key Laboratory of Swine and Poultry Breeding Industry, National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
Changguang LinInstitute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Sciences, Fuzhou, 350013, China. lincg111@163.com.

Funding

the Basic Scientific Research Projects of Provincial Public Welfare Scientific Research Institutions (Fujian Province), China 2023R1024009the earmarked fund for the China Agriculture Research System CARS-35
6 · The paper itself

Abstract

Genomic selection (GS) has become an essential tool for improving economically important traits in pigs. However, its accuracy depends heavily on the size and composition of the reference population. This study explores strategies for optimizing multi-population genomic evaluations by integrating prior biological knowledge and leveraging advanced genomic models. We assessed population similarities based on phenotypic distribution, linkage disequilibrium (LD) consistency, heritability, and genetic variance. Three genomic prediction models-GBLUP, bivariate GBLUP, and GFBLUP-were applied to evaluate the joint reference populations. The results indicated that differences in phenotypic means and genetic variance between populations significantly affected the prediction accuracy of joint evaluations, particularly for fat thickness traits. The GFBLUP model, integrating meta-GWAS priors, improved prediction accuracy when the genetic contributions were similar between target and reference populations. These findings highlight the importance of carefully selecting reference populations and integrating biological priors into genomic evaluations. The study offers valuable insights for optimizing genomic selection strategies in pig breeding programs.

Indexed as

GenomicsAnimalsBreedingGenetics, PopulationLinkage DisequilibriumModels, GeneticPhenotypePolymorphism, Single NucleotideSelection, GeneticSwineGenomic selectionJoint evaluationPrior biological knowledgeReference populationYorkshire pig

Identifiers

PMID40866809
PMCPMC12382205

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.