Evidence map›Paper›PMID 22132191›Full record

ArticlePloS one2011

Novel tools for conservation genomics: comparing two high-throughput approaches for SNP discovery in the transcriptome of the European hake.

Ilaria Milano, Massimiliano Babbucci, Frank Panitz, Rob Ogden, Rasmus O Nielsen, Martin I Taylor, Sarah J Helyar, Gary R Carvalho, Montserrat Espiñeira, Miroslava Atanassova and 5 more

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In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

21 citing papers in PubMed.

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  4. Evolutionary applications · 2021
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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

15 authors.

Ilaria MilanoDepartment of Experimental and Evolutionary Biology, University of Bologna, Bologna, Italy. ilaria.milano2@unibo.it
Massimiliano Babbucci
Frank Panitz
Rob Ogden
Rasmus O Nielsen
Martin I Taylor
Sarah J Helyar
Gary R Carvalho
Montserrat Espiñeira
Miroslava Atanassova
Fausto Tinti
Gregory E Maes
Tomaso Patarnello
FishPopTrace Consortium
Luca Bargelloni

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The growing accessibility to genomic resources using next-generation sequencing (NGS) technologies has revolutionized the application of molecular genetic tools to ecology and evolutionary studies in non-model organisms. Here we present the case study of the European hake (Merluccius merluccius), one of the most important demersal resources of European fisheries. Two sequencing platforms, the Roche 454 FLX (454) and the Illumina Genome Analyzer (GAII), were used for Single Nucleotide Polymorphisms (SNPs) discovery in the hake muscle transcriptome. De novo transcriptome assembly into unique contigs, annotation, and in silico SNP detection were carried out in parallel for 454 and GAII sequence data. High-throughput genotyping using the Illumina GoldenGate assay was performed for validating 1,536 putative SNPs. Validation results were analysed to compare the performances of 454 and GAII methods and to evaluate the role of several variables (e.g. sequencing depth, intron-exon structure, sequence quality and annotation). Despite well-known differences in sequence length and throughput, the two approaches showed similar assay conversion rates (approximately 43%) and percentages of polymorphic loci (67.5% and 63.3% for GAII and 454, respectively). Both NGS platforms therefore demonstrated to be suitable for large scale identification of SNPs in transcribed regions of non-model species, although the lack of a reference genome profoundly affects the genotyping success rate. The overall efficiency, however, can be improved using strict quality and filtering criteria for SNP selection (sequence quality, intron-exon structure, target region score).

Indexed as

AnimalsConservation of Natural ResourcesDatabases, GeneticEuropeGadiformesGene FrequencyGenomicsGeographyHeterozygoteHigh-Throughput Nucleotide SequencingMolecular Sequence AnnotationPolymorphism, Single NucleotideReproducibility of ResultsROC CurveSequence Analysis, DNATranscriptome

Identifiers

PMID22132191
PMCPMC3222667

What OpenQuestion holds

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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.