Evidence map›Paper›PMID 26464167›Full record

ArticleGenetics, selection, evolution : GSE2015

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

Nicholas J Hudson, Laercio Porto-Neto, James W Kijas, Antonio Reverter

Abstract read
In one paragraph

Article in Genetics, selection, evolution : GSE, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Nicholas J HudsonCSIRO Agriculture, Computational and Systems Biology, 306 Carmody Road, St. Lucia, Brisbane, QLD, 4075, Australia. nick.hudson@csiro.au.
Laercio Porto-NetoCSIRO Agriculture, Computational and Systems Biology, 306 Carmody Road, St. Lucia, Brisbane, QLD, 4075, Australia. Laercio.Portoneto@csiro.au.
James W KijasCSIRO Agriculture, Computational and Systems Biology, 306 Carmody Road, St. Lucia, Brisbane, QLD, 4075, Australia. James.Kijas@csiro.au.
Antonio ReverterCSIRO Agriculture, Computational and Systems Biology, 306 Carmody Road, St. Lucia, Brisbane, QLD, 4075, Australia. toni.reverter-gomez@csiro.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetic 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.

resultsWe 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.

conclusionsFor 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.

Indexed as

BreedingModels, GeneticPedigreeAlgorithmsAllelesAnimalsComputer SimulationGenetic VariationGenome-Wide Association StudyGenomicsGenotypePolymorphism, Single NucleotideReproducibility of Results

Identifiers

PMID26464167
PMCPMC4604992

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.