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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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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. |
format | Online Article Text |
id | pubmed-4604992 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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