Evidence map›Paper›PMID 24063757›Full record

ArticleBMC genetics2013

Improved estimation of inbreeding and kinship in pigs using optimized SNP panels.

Marcos S Lopes, Fabyano F Silva, Barbara Harlizius, Naomi Duijvesteijn, Paulo S Lopes, Simone Ef Guimarães, Egbert F Knol

Open access · diamondAbstract read
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Article in BMC genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 50 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Marcos S LopesTOPIGS Research Center IPG B,V,, P,O, Box 43, 6640 AA, Beuningen, the Netherlands. Marcos.Lopes@TOPIGS.com.
Fabyano F Silva
Barbara Harlizius
Naomi Duijvesteijn
Paulo S Lopes
Simone Ef Guimarães
Egbert F Knol
Topigs Norsvin (Netherlands) · NLUniversidade Federal de Viçosa · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTraditional breeding programs consider an average pairwise kinship between sibs. Based on pedigree information, the relationship matrix is used for genetic evaluations disregarding variation due to Mendelian sampling. Therefore, inbreeding and kinship coefficients are either over or underestimated resulting in reduction of accuracy of genetic evaluations and genetic progress. Single nucleotide polymorphism (SNPs) can be used to estimate pairwise kinship and individual inbreeding more accurately. The aim of this study was to optimize the selection of markers and determine the required number of SNPs for estimation of kinship and inbreeding.

resultsA total of 1,565 animals from three commercial pig populations were analyzed for 28,740 SNPs from the PorcineSNP60 Beadchip. Mean genomic inbreeding was higher than pedigree-based estimates in lines 2 and 3, but lower in line 1. As expected, a larger variation of genomic kinship estimates was observed for half and full sibs than for pedigree-based kinship reflecting Mendelian sampling. Genomic kinship between father-offspring pairs was lower (0.23) than the estimate based on pedigree (0.26). Bootstrap analyses using six reduced SNP panels (n = 500, 1000, 1500, 2000, 2500 and 3000) showed that 2,000 SNPs were able to reproduce the results very close to those obtained using the full set of unlinked markers (n = 7,984-10,235) with high correlations (inbreeding r > 0.82 and kinship r > 0.96) and low variation between different sets with the same number of SNPs.

conclusionsVariation of kinship between sibs due to Mendelian sampling is better captured using genomic information than the pedigree-based method. Therefore, the reduced sets of SNPs could generate more accurate kinship coefficients between sibs than the pedigree-based method. Variation of genomic kinship of father-offspring pairs is recommended as a parameter to determine accuracy of the method rather than correlation with pedigree-based estimates. Inbreeding and kinship coefficients can be estimated with high accuracy using ≥2,000 unlinked SNPs within all three commercial pig lines evaluated. However, a larger number of SNPs might be necessary in other populations or across lines.

Indexed as

GenomeInbreedingModels, GeneticPolymorphism, Single NucleotideAnimalsGenotypeLinkage DisequilibriumPedigreeSelection, GeneticSwine

Identifiers

PMID24063757
PMCPMC3849284
OpenAlexW2007998522

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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.