Evidence map›Paper›PMID 26499328›Full record

ArticleBMC genomics2015

Genome-wide association analysis reveals loci associated with resistance against Piscirickettsia salmonis in two Atlantic salmon (Salmo salar L.) chromosomes.

Katharina Correa, Jean P Lhorente, María E López, Liane Bassini, Sudhir Naswa, Nader Deeb, Alex Di Genova, Alejandro Maass, William S Davidson, José M Yáñez

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 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
10.4field-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

50 citing papers in PubMed, 117 citations in OpenAlex.

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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

10 authors at 3 institutions in 3 countries.

Katharina CorreaFacultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Av Santa Rosa 11735, Santiago, Chile. katharinacorrea@gmail.com.
Jean P LhorenteAquainnovo, Talca 60, Puerto Montt, Chile. jean.lhorente@aquainnovo.com.
María E LópezFacultad de Ciencias Agronómicas, Universidad de Chile, Av Santa Rosa 11315, Santiago, Chile. me.lopez.dinamarca@gmail.com.
Liane BassiniFacultad de Ciencias Agronómicas, Universidad de Chile, Av Santa Rosa 11315, Santiago, Chile. lianebassini@gmail.com.
Sudhir NaswaGenus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN, 37075, USA. Sudhir.Naswa@genusplc.com.
Nader DeebGenus plc, 100 Bluegrass Commons Blvd. Suite 2200, Hendersonville, TN, 37075, USA. Joseph.Deeb@genusplc.com.
Alex Di GenovaLaboratory of Bioinformatics and Mathematics of the Genome, Center for Mathematical Modeling (UMI 2807 CNRS) and Center for Genome Regulation, Universidad de Chile, Beauchef 851, Santiago, Chile. digenova@gmail.com.
Alejandro MaassLaboratory of Bioinformatics and Mathematics of the Genome, Center for Mathematical Modeling (UMI 2807 CNRS) and Center for Genome Regulation, Universidad de Chile, Beauchef 851, Santiago, Chile. amaass@dim.uchile.cl.
William S DavidsonDepartment of Molecular Biology and Biochemistry, Simon Fraser University, 8888 University Drive, Burnaby, BC, Canada. wdaviso@sfu.ca.
José M YáñezFacultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Av Santa Rosa 11735, Santiago, Chile. jmayanez@uchile.cl.
University of Chile · CLGenus (United States) · USSimon Fraser University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPisciricketssia salmonis is the causal agent of Salmon Rickettsial Syndrome (SRS), which affects salmon species and causes severe economic losses. Selective breeding for disease resistance represents one approach for controlling SRS in farmed Atlantic salmon. Knowledge concerning the architecture of the resistance trait is needed before deciding on the most appropriate approach to enhance artificial selection for P. salmonis resistance in Atlantic salmon. The purpose of the study was to dissect the genetic variation in the resistance to this pathogen in Atlantic salmon.

methods2,601 Atlantic salmon smolts were experimentally challenged against P. salmonis by means of intra-peritoneal injection. These smolts were the progeny of 40 sires and 118 dams from a Chilean breeding population. Mortalities were recorded daily and the experiment ended at day 40 post-inoculation. Fish were genotyped using a 50K Affymetrix® Axiom® myDesignTM Single Nucleotide Polymorphism (SNP) Genotyping Array. A Genome Wide Association Analysis was performed on data from the challenged fish. Linear regression and logistic regression models were tested.

resultsGenome Wide Association Analysis indicated that resistance to P. salmonis is a moderately polygenic trait. There were five SNPs in chromosomes Ssa01 and Ssa17 significantly associated with the traits analysed. The proportion of the phenotypic variance explained by each marker is small, ranging from 0.007 to 0.045. Candidate genes including interleukin receptors and fucosyltransferase have been found to be physically linked with these genetic markers and may play an important role in the differential immune response against this pathogen.

conclusionsDue to the small amount of variance explained by each significant marker we conclude that genetic resistance to this pathogen can be more efficiently improved with the implementation of genetic evaluations incorporating genotype information from a dense SNP array.

Indexed as

ChromosomesGenome-Wide Association StudyPiscirickettsiaQuantitative Trait LociAllelesAnimalsDisease ResistanceFish DiseasesGene FrequencyGenetic Association StudiesLinkage DisequilibriumPhenotypePolymorphism, Single NucleotideQuantitative Trait, HeritableSalmo salar

Identifiers

PMID26499328
PMCPMC4619534
OpenAlexW2148396262

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.