Evidence map›Paper›PMID 31447879›Full record

ArticleFrontiers in genetics2019

Scanning of Genetic Variants and Genetic Mapping of Phenotypic Traits in Gilthead Sea Bream Through ddRAD Sequencing.

Dimitrios Kyriakis, Alexandros Kanterakis, Tereza Manousaki, Alexandros Tsakogiannis, Michalis Tsagris, Ioannis Tsamardinos, Leonidas Papaharisis, Dimitris Chatziplis, George Potamias, Costas S Tsigenopoulos

Abstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Genotyping Strategies Using ddRAD Sequencing in Farmed Arctic Charr (Animals : an open access journal from MDPI · 2021
    Article
  6. Article
  7. Article
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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.

Dimitrios KyriakisSchool of Medicine, University of Crete, Heraklion, Greece.
Alexandros KanterakisFoundation for Research and Technology-Hellas (FORTH), Heraklion, Greece.
Tereza ManousakiInstitute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece.
Alexandros TsakogiannisInstitute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece.
Michalis TsagrisDeparment of Economics, University of Crete, Gallos Campus, Rethymnon, Greece.
Ioannis TsamardinosDepartment of Computer Science, University of Crete, Voutes Campus, Heraklion, Greece.
Leonidas PapaharisisNireus Aquaculture SA, Koropi, Greece.
Dimitris ChatziplisDepartment of Agriculture Technology, Alexander Technological Education Institute of Thessaloniki, Thessaloniki, Greece.
George PotamiasFoundation for Research and Technology-Hellas (FORTH), Heraklion, Greece.
Costas S TsigenopoulosInstitute of Marine Biology, Biotechnology and Aquaculture (IMBBC), Hellenic Center for Marine Research (HCMR) Crete, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gilthead sea bream (Sparus aurata) is a teleost of considerable economic importance in Southern European aquaculture. The aquaculture industry shows a growing interest in the application of genetic methods that can locate phenotype-genotype associations with high economic impact. Through selective breeding, the aquaculture industry can exploit this information to maximize the financial yield. Here, we present a Genome Wide Association Study (GWAS) of 112 samples belonging to seven different sea bream families collected from a Greek commercial aquaculture company. Through double digest Random Amplified DNA (ddRAD) Sequencing, we generated a per-sample genetic profile consisting of 2,258 high-quality Single Nucleotide Polymorphisms (SNPs). These profiles were tested for association with four phenotypes of major financial importance: Fat, Weight, Tag Weight, and the Length to Width ratio. We applied two methods of association analysis. The first is the typical single-SNP to phenotype test, and the second is a feature selection (FS) method through two novel algorithms that are employed for the first time in aquaculture genomics and produce groups with multiple SNPs associated to a phenotype. In total, we identified 9 single SNPs and 6 groups of SNPs associated with weight-related phenotypes (Weight and Tag Weight), 2 groups associated with Fat, and 16 groups associated with the Length to Width ratio. Six identified loci (Chr4:23265532, Chr6:12617755, Chr:8:11613979, Chr13:1098152, Chr15:3260819, and Chr22:14483563) were present in genes associated with growth in other teleosts or even mammals, such as semaphorin-3A and neurotrophin-3. These loci are strong candidates for future studies that will help us unveil the genetic mechanisms underlying growth and improve the sea bream aquaculture productivity by providing genomic anchors for selection programs.

Indexed as

aquaculturedouble digest random amplified DNAfeature selectionGenome Wide Association StudySparus aurata

Identifiers

PMID31447879
PMCPMC6691846

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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.