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Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values

BACKGROUND: Genetic relatedness is currently estimated by a combination of traditional pedigree-based approaches (i.e. numerator relationship matrices, NRM) and, given the recent availability of molecular information, using marker genotypes (via genomic relationship matrices, GRM). To date, GRM are...

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Autores principales: Hudson, Nicholas J., Porto-Neto, Laercio, Kijas, James W., Reverter, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4604992/
https://www.ncbi.nlm.nih.gov/pubmed/26464167
http://dx.doi.org/10.1186/s12711-015-0158-9
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author Hudson, Nicholas J.
Porto-Neto, Laercio
Kijas, James W.
Reverter, Antonio
author_facet Hudson, Nicholas J.
Porto-Neto, Laercio
Kijas, James W.
Reverter, Antonio
author_sort Hudson, Nicholas J.
collection PubMed
description BACKGROUND: Genetic relatedness is currently estimated by a combination of traditional pedigree-based approaches (i.e. numerator relationship matrices, NRM) and, given the recent availability of molecular information, using marker genotypes (via genomic relationship matrices, GRM). To date, GRM are computed by genome-wide pair-wise SNP (single nucleotide polymorphism) correlations. RESULTS: We describe a new estimate of genetic relatedness using the concept of normalised compression distance (NCD) that is borrowed from Information Theory. Analogous to GRM, the resultant compression relationship matrix (CRM) exploits numerical patterns in genome-wide allele order and proportion, which are known to vary systematically with relatedness. We explored properties of the CRM in two industry cattle datasets by analysing the genetic basis of yearling weight, a phenotype of moderate heritability. In both Brahman (Bos indicus) and Tropical Composite (Bos taurus by Bos indicus) populations, the clustering inferred by NCD was comparable to that based on SNP correlations using standard principal component analysis approaches. One of the versions of the CRM modestly increased the amount of explained genetic variance, slightly reduced the ‘missing heritability’ and tended to improve the prediction accuracy of breeding values in both populations when compared to both NRM and GRM. Finally, a sliding window-based application of the compression approach on these populations identified genomic regions influenced by introgression of taurine haplotypes. CONCLUSIONS: For these two bovine populations, CRM reduced the missing heritability and increased the amount of explained genetic variation for a moderately heritable complex trait. Given that NCD can sensitively discriminate closely related individuals, we foresee CRM having possible value for estimating breeding values in highly inbred populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-015-0158-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-46049922015-10-15 Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values Hudson, Nicholas J. Porto-Neto, Laercio Kijas, James W. Reverter, Antonio Genet Sel Evol Research Article BACKGROUND: Genetic relatedness is currently estimated by a combination of traditional pedigree-based approaches (i.e. numerator relationship matrices, NRM) and, given the recent availability of molecular information, using marker genotypes (via genomic relationship matrices, GRM). To date, GRM are computed by genome-wide pair-wise SNP (single nucleotide polymorphism) correlations. RESULTS: We describe a new estimate of genetic relatedness using the concept of normalised compression distance (NCD) that is borrowed from Information Theory. Analogous to GRM, the resultant compression relationship matrix (CRM) exploits numerical patterns in genome-wide allele order and proportion, which are known to vary systematically with relatedness. We explored properties of the CRM in two industry cattle datasets by analysing the genetic basis of yearling weight, a phenotype of moderate heritability. In both Brahman (Bos indicus) and Tropical Composite (Bos taurus by Bos indicus) populations, the clustering inferred by NCD was comparable to that based on SNP correlations using standard principal component analysis approaches. One of the versions of the CRM modestly increased the amount of explained genetic variance, slightly reduced the ‘missing heritability’ and tended to improve the prediction accuracy of breeding values in both populations when compared to both NRM and GRM. Finally, a sliding window-based application of the compression approach on these populations identified genomic regions influenced by introgression of taurine haplotypes. CONCLUSIONS: For these two bovine populations, CRM reduced the missing heritability and increased the amount of explained genetic variation for a moderately heritable complex trait. Given that NCD can sensitively discriminate closely related individuals, we foresee CRM having possible value for estimating breeding values in highly inbred populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-015-0158-9) contains supplementary material, which is available to authorized users. BioMed Central 2015-10-13 /pmc/articles/PMC4604992/ /pubmed/26464167 http://dx.doi.org/10.1186/s12711-015-0158-9 Text en © Hudson et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Hudson, Nicholas J.
Porto-Neto, Laercio
Kijas, James W.
Reverter, Antonio
Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
title Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
title_full Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
title_fullStr Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
title_full_unstemmed Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
title_short Compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
title_sort compression distance can discriminate animals by genetic profile, build relationship matrices and estimate breeding values
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4604992/
https://www.ncbi.nlm.nih.gov/pubmed/26464167
http://dx.doi.org/10.1186/s12711-015-0158-9
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