Evidence map›Paper›PMID 26582102›Full record

ArticleBMC genomics2015

Genome wide association and genomic prediction for growth traits in juvenile farmed Atlantic salmon using a high density SNP array.

Hsin-Yuan Tsai, Alastair Hamilton, Alan E Tinch, Derrick R Guy, Karim Gharbi, Michael J Stear, Oswald Matika, Steve C Bishop, Ross D Houston

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed, 1 pooled it
16.8field-weighted citation impact, top 1% of its field
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

114 citing papers in PubMed, 1 synthesis or guideline pooled it, 270 citations in OpenAlex.

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54 more citing papers are in PubMed but not listed here.

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

9 authors at 5 institutions in 1 country.

Hsin-Yuan TsaiThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. hsin-yuan.tsai@roslin.ed.ac.uk.
Alastair HamiltonLandcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK. Alastair.Hamilton@hendrix-genetics.com.
Alan E TinchLandcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK. Alan.Tinch@hendrix-genetics.com.
Derrick R GuyLandcatch Natural Selection Ltd., 15 Beta Centre, Stirling University Innovation Park, Stirling, FK9 4NF, UK. Derrick.Guy@hendrix-genetics.com.
Karim GharbiEdinburgh Genomics, Ashworth Laboratories, King's Buildings, The University of Edinburgh, Edinburgh, EH9 3JT, UK. Karim.Gharbi@ed.ac.uk.
Michael J StearInstitute of Biodiversity, Animal Health & Comparative Medicine, University of Glasgow, Bearsden Road, Glasgow, G61 1QH, UK. Michael.Stear@glasgow.ac.uk.
Oswald MatikaThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. Oswald.Matika@roslin.ed.ac.uk.
Steve C BishopThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. Stephen.Bishop@roslin.ed.ac.uk.
Ross D HoustonThe Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, Edinburgh, UK. Ross.Houston@roslin.ed.ac.uk.
University of Edinburgh · GBLandcatch (United Kingdom) · GBRoslin Institute · GBUniversity of Glasgow · GBUniversity of Stirling · GB

Funding

Biotechnology and Biological Sciences Research Council BB/F001959/1Biotechnology and Biological Sciences Research Council BB/F002750/1Biotechnology and Biological Sciences Research Council BB/H022007/1Medical Research Council G0900740Medical Research Council MR/K001744/1
6 · The paper itself

Abstract

backgroundThe genetic architecture of complex traits in farmed animal populations is of interest from a scientific and practical perspective. The use of genetic markers to predict the genetic merit (breeding values) of individuals is commonplace in modern farm animal breeding schemes. Recently, high density SNP arrays have become available for Atlantic salmon, which facilitates genomic prediction and association studies using genome-wide markers and economically important traits. The aims of this study were (i) to use a high density SNP array to investigate the genetic architecture of weight and length in juvenile Atlantic salmon; (ii) to assess the utility of genomic prediction for these traits, including testing different marker densities; (iii) to identify potential candidate genes underpinning variation in early growth.

resultsA pedigreed population of farmed Atlantic salmon (n = 622) were measured for weight and length traits at one year of age, and genotyped for 111,908 segregating SNP markers using a high density SNP array. The heritability of both traits was estimated using pedigree and genomic relationship matrices, and was comparable at around 0.5 and 0.6 respectively. The results of the GWA analysis pointed to a polygenic genetic architecture, with no SNPs surpassing the genome-wide significance threshold, and one SNP associated with length at the chromosome-wide level. SNPs surpassing an arbitrary threshold of significance (P < 0.005, ~ top 0.5 % of markers) were aligned to an Atlantic salmon reference transcriptome, identifying 109 SNPs in transcribed regions that were annotated by alignment to human, mouse and zebrafish protein databases. Prediction of breeding values was more accurate when applying genomic (GBLUP) than pedigree (PBLUP) relationship matrices (accuracy ~ 0.7 and 0.58 respectively) and 5,000 SNPs were sufficient for obtaining this accuracy increase over PBLUP in this specific population.

conclusionsThe high density SNP array can effectively capture the additive genetic variation in complex traits. However, the traits of weight and length both appear to be very polygenic with only one SNP surpassing the chromosome-wide threshold. Genomic prediction using the array is effective, leading to an improvement in accuracy compared to pedigree methods, and this improvement can be achieved with only a small subset of the markers in this population. The results have practical relevance for genomic selection in salmon and may also provide insight into variation in the identified genes underpinning body growth and development in salmonid species.

Indexed as

AquacultureGenome-Wide Association StudyGenomicsOligonucleotide Array Sequence AnalysisAnimalsBreedingGenetic MarkersHumansMicePolymorphism, Single NucleotideSalmo salarTranscription, GeneticGenetic Markers

Identifiers

PMID26582102
PMCPMC4652364
OpenAlexW2174827397

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.