ArticleJournal of applied genetics2015
Bayesian GWAS and network analysis revealed new candidate genes for number of teats in pigs.
Article in Journal of applied genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-Wide Association Study Meta-Analysis Elucidates Genetic Structure and Identifies Candidate Genes of Teat Number Traits in Pigs.International journal of molecular sciences · 2023Pooled it
- Genome-wide analysis of genetic loci and candidate genes related to teat number traits in Dongliao black pigs.Frontiers in genetics · 2025Article
- Comprehensive genome-wide analysis of genetic loci and candidate genes associated with litter traits in purebred Berkshire pigs of Korea.Animal bioscience · 2024Article
- Identification of Signatures of Positive Selection That Have Shaped the Genomic Landscape of South African Pig Populations.Animals : an open access journal from MDPI · 2024Article
- Genome-wide association studies for economically important traits in mink using copy number variation.Scientific reports · 2024Article
- Genomic Prediction and Genome-Wide Association Study for Boar Taint Compounds.Animals : an open access journal from MDPI · 2023Article
- Identification of New Candidate Genes Related to Semen Traits in Duroc Pigs through Weighted Single-Step GWAS.Animals : an open access journal from MDPI · 2023Article
- Genomic evaluation and genome-wide association studies for total number of teats in a combined American and Danish Yorkshire pig populations selected in China.Journal of animal science · 2022Article
- Genome-Wide Association Study for Lactation Performance in the Early and Peak Stages of Lactation in Holstein Dairy Cows.Animals : an open access journal from MDPI · 2022Article
- Haplotype genomic prediction of phenotypic values based on chromosome distance and gene boundaries using low-coverage sequencing in Duroc pigs.Genetics, selection, evolution : GSE · 2021Article
- Revealing New Candidate Genes for Teat Number Relevant Traits in Duroc Pigs Using Genome-Wide Association Studies.Animals : an open access journal from MDPI · 2021Article
- Genome-wide association for milk production and lactation curve parameters in Holstein dairy cows.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2020Article
- Article
- Assessment of Autozygosity Derived From Runs of Homozygosity in Jinhua Pigs Disclosed by Sequencing Data.Frontiers in genetics · 2019Article
- Weighted single-step GWAS and gene network analysis reveal new candidate genes for semen traits in pigs.Genetics, selection, evolution : GSE · 2018Article
- Identification of novel candidate genes for the inverted teat defect in sows using a genome-wide marker panel.Journal of applied genetics · 2017Article
- Verification of Three-Phase Dependency Analysis Bayesian Network Learning Method for Maize Carotenoid Gene Mining.BioMed research international · 2017Article
- Regularized quantile regression for SNP marker estimation of pig growth curves.Journal of animal science and biotechnology · 2017Article
- Revealing new candidate genes for reproductive traits in pigs: combining Bayesian GWAS and functional pathways.Genetics, selection, evolution : GSE · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
The genetic improvement of reproductive traits such as the number of teats is essential to the success of the pig industry. As opposite to most SNP association studies that consider continuous phenotypes under Gaussian assumptions, this trait is characterized as a discrete variable, which could potentially follow other distributions, such as the Poisson. Therefore, in order to access the complexity of a counting random regression considering all SNPs simultaneously as covariate under a GWAS modeling, the Bayesian inference tools become necessary. Currently, another point that deserves to be highlighted in GWAS is the genetic dissection of complex phenotypes through candidate genes network derived from significant SNPs. We present a full Bayesian treatment of SNP association analysis for number of teats assuming alternatively Gaussian and Poisson distributions for this trait. Under this framework, significant SNP effects were identified by hypothesis tests using 95% highest posterior density intervals. These SNPs were used to construct associated candidate genes network aiming to explain the genetic mechanism behind this reproductive trait. The Bayesian model comparisons based on deviance posterior distribution indicated the superiority of Gaussian model. In general, our results suggest the presence of 19 significant SNPs, which mapped 13 genes. Besides, we predicted gene interactions through networks that are consistent with the mammals known breast biology (e.g., development of prolactin receptor signaling, and cell proliferation), captured known regulation binding sites, and provided candidate genes for that trait (e.g., TINAGL1 and ICK).
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