Evidence map›Paper›PMID 22284269›Full record

ArticleBMC research notes2012

SNP markers retrieval for a non-model species: a practical approach.

Arwa Shahin, Thomas van Gurp, Sander A Peters, Richard Gf Visser, Jaap M van Tuyl, Paul Arens

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.7field-weighted citation impact, top 16% 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

11 citing papers in PubMed, 30 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

6 authors at 2 institutions in 1 country.

Arwa ShahinWageningen University and Research Centre, Plant Breeding, P,O, Box 16, 6700 AJ Wageningen, The Netherlands. Arwa.shahin@wur.nl.
Thomas van Gurp
Sander A Peters
Richard Gf Visser
Jaap M van Tuyl
Paul Arens
Wageningen University & Research · NLNetherlands Institute of Ecology · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSNP (Single Nucleotide Polymorphism) markers are rapidly becoming the markers of choice for applications in breeding because of next generation sequencing technology developments. For SNP development by NGS technologies, correct assembly of the huge amounts of sequence data generated is essential. Little is known about assembler's performance, especially when dealing with highly heterogeneous species that show a high genome complexity and what the possible consequences are of differences in assemblies on SNP retrieval. This study tested two assemblers (CAP3 and CLC) on 454 data from four lily genotypes and compared results with respect to SNP retrieval.

resultsCAP3 assembly resulted in higher numbers of contigs, lower numbers of reads per contig, and shorter average read lengths compared to CLC. Blast comparisons showed that CAP3 contigs were highly redundant. Contrastingly, CLC in rare cases combined paralogs in one contig. Redundant and chimeric contigs may lead to erroneous SNPs. Filtering for redundancy can be done by blasting selected SNP markers to the contigs and discarding all the SNP markers that show more than one blast hit. Results on chimeric contigs showed that only four out of 2,421 SNP markers were selected from chimeric contigs.

conclusionIn practice, CLC performs better in assembling highly heterogeneous genome sequences compared to CAP3, and consequently SNP retrieval is more efficient. Additionally a simple flow scheme is suggested for SNP marker retrieval that can be valid for all non-model species.

Identifiers

PMID22284269
PMCPMC3298514
OpenAlexW2110178739

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.