Evidence map›Paper›PMID 21767361›Full record

ArticleBMC genomics2011

Development and implementation of a highly-multiplexed SNP array for genetic mapping in maritime pine and comparative mapping with loblolly pine.

Emilie Chancerel, Camille Lepoittevin, Grégoire Le Provost, Yao-Cheng Lin, Juan Pablo Jaramillo-Correa, Andrew J Eckert, Jill L Wegrzyn, Diana Zelenika, Anne Boland, Jean-Marc Frigerio and 11 more

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

27 citing papers in PubMed, 74 citations in OpenAlex.

  1. Needle and Branch Trait Variation Analysis and Associated SNP Loci Mining inInternational journal of molecular sciences · 2024
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Insights into conifer giga-genomes.Plant physiology · 2014
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2013
    Article
  20. Article
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

21 authors at 10 institutions in 5 countries.

Emilie ChancerelINRA, UMR1202 BIOGECO, F-33610 Cestas, France.
Camille Lepoittevin
Grégoire Le Provost
Yao-Cheng Lin
Juan Pablo Jaramillo-Correa
Andrew J Eckert
Jill L Wegrzyn
Diana Zelenika
Anne Boland
Jean-Marc Frigerio
Philippe Chaumeil
Pauline Garnier-Géré
Christophe Boury
Delphine Grivet
Santiago C González-Martínez
Pierre Rouzé
Yves Van de Peer
David B Neale
Maria T Cervera
Antoine Kremer
Christophe Plomion
CEA CESTA · FRCenter for International Forestry Research · IDUMR BIOdiversity, GEnes & Communities · FRUniversity of California, Davis · USUniversité de Bordeaux · FRVIB-UGent Center for Plant Systems Biology · BECommissariat à l'Énergie Atomique et aux Énergies Alternatives · FRGenoscope · FRGhent University · BEUniversidad Nacional Autónoma de México · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSingle nucleotide polymorphisms (SNPs) are the most abundant source of genetic variation among individuals of a species. New genotyping technologies allow examining hundreds to thousands of SNPs in a single reaction for a wide range of applications such as genetic diversity analysis, linkage mapping, fine QTL mapping, association studies, marker-assisted or genome-wide selection. In this paper, we evaluated the potential of highly-multiplexed SNP genotyping for genetic mapping in maritime pine (Pinus pinaster Ait.), the main conifer used for commercial plantation in southwestern Europe.

resultsWe designed a custom GoldenGate assay for 1,536 SNPs detected through the resequencing of gene fragments (707 in vitro SNPs/Indels) and from Sanger-derived Expressed Sequenced Tags assembled into a unigene set (829 in silico SNPs/Indels). Offspring from three-generation outbred (G2) and inbred (F2) pedigrees were genotyped. The success rate of the assay was 63.6% and 74.8% for in silico and in vitro SNPs, respectively. A genotyping error rate of 0.4% was further estimated from segregating data of SNPs belonging to the same gene. Overall, 394 SNPs were available for mapping. A total of 287 SNPs were integrated with previously mapped markers in the G2 parental maps, while 179 SNPs were localized on the map generated from the analysis of the F2 progeny. Based on 98 markers segregating in both pedigrees, we were able to generate a consensus map comprising 357 SNPs from 292 different loci. Finally, the analysis of sequence homology between mapped markers and their orthologs in a Pinus taeda linkage map, made it possible to align the 12 linkage groups of both species.

conclusionsOur results show that the GoldenGate assay can be used successfully for high-throughput SNP genotyping in maritime pine, a conifer species that has a genome seven times the size of the human genome. This SNP-array will be extended thanks to recent sequencing effort using new generation sequencing technologies and will include SNPs from comparative orthologous sequences that were identified in the present study, providing a wider collection of anchor points for comparative genomics among the conifers.

Indexed as

Polymorphism, Single NucleotideChromosome MappingExpressed Sequence TagsGenotypeOligonucleotide Array Sequence AnalysisPedigreePinusPinus taeda

Identifiers

PMID21767361
PMCPMC3146957
OpenAlexW2138991278

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.