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In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species?
BACKGROUND: There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (P...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2882948/ https://www.ncbi.nlm.nih.gov/pubmed/20543950 http://dx.doi.org/10.1371/journal.pone.0011034 |
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author | Lepoittevin, Camille Frigerio, Jean-Marc Garnier-Géré, Pauline Salin, Franck Cervera, María-Teresa Vornam, Barbara Harvengt, Luc Plomion, Christophe |
author_facet | Lepoittevin, Camille Frigerio, Jean-Marc Garnier-Géré, Pauline Salin, Franck Cervera, María-Teresa Vornam, Barbara Harvengt, Luc Plomion, Christophe |
author_sort | Lepoittevin, Camille |
collection | PubMed |
description | BACKGROUND: There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (∼23.8 Gb/C). METHODOLOGY/PRINCIPAL FINDINGS: A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). CONCLUSIONS/SIGNIFICANCE: This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome. |
format | Text |
id | pubmed-2882948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28829482010-06-11 In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? Lepoittevin, Camille Frigerio, Jean-Marc Garnier-Géré, Pauline Salin, Franck Cervera, María-Teresa Vornam, Barbara Harvengt, Luc Plomion, Christophe PLoS One Research Article BACKGROUND: There is considerable interest in the high-throughput discovery and genotyping of single nucleotide polymorphisms (SNPs) to accelerate genetic mapping and enable association studies. This study provides an assessment of EST-derived and resequencing-derived SNP quality in maritime pine (Pinus pinaster Ait.), a conifer characterized by a huge genome size (∼23.8 Gb/C). METHODOLOGY/PRINCIPAL FINDINGS: A 384-SNPs GoldenGate genotyping array was built from i/ 184 SNPs originally detected in a set of 40 re-sequenced candidate genes (in vitro SNPs), chosen on the basis of functionality scores, presence of neighboring polymorphisms, minor allele frequencies and linkage disequilibrium and ii/ 200 SNPs screened from ESTs (in silico SNPs) selected based on the number of ESTs used for SNP detection, the SNP minor allele frequency and the quality of SNP flanking sequences. The global success rate of the assay was 66.9%, and a conversion rate (considering only polymorphic SNPs) of 51% was achieved. In vitro SNPs showed significantly higher genotyping-success and conversion rates than in silico SNPs (+11.5% and +18.5%, respectively). The reproducibility was 100%, and the genotyping error rate very low (0.54%, dropping down to 0.06% when removing four SNPs showing elevated error rates). CONCLUSIONS/SIGNIFICANCE: This study demonstrates that ESTs provide a resource for SNP identification in non-model species, which do not require any additional bench work and little bio-informatics analysis. However, the time and cost benefits of in silico SNPs are counterbalanced by a lower conversion rate than in vitro SNPs. This drawback is acceptable for population-based experiments, but could be dramatic in experiments involving samples from narrow genetic backgrounds. In addition, we showed that both the visual inspection of genotyping clusters and the estimation of a per SNP error rate should help identify markers that are not suitable to the GoldenGate technology in species characterized by a large and complex genome. Public Library of Science 2010-06-09 /pmc/articles/PMC2882948/ /pubmed/20543950 http://dx.doi.org/10.1371/journal.pone.0011034 Text en Lepoittevin et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Lepoittevin, Camille Frigerio, Jean-Marc Garnier-Géré, Pauline Salin, Franck Cervera, María-Teresa Vornam, Barbara Harvengt, Luc Plomion, Christophe In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? |
title |
In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? |
title_full |
In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? |
title_fullStr |
In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? |
title_full_unstemmed |
In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? |
title_short |
In Vitro vs In Silico Detected SNPs for the Development of a Genotyping Array: What Can We Learn from a Non-Model Species? |
title_sort | in vitro vs in silico detected snps for the development of a genotyping array: what can we learn from a non-model species? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2882948/ https://www.ncbi.nlm.nih.gov/pubmed/20543950 http://dx.doi.org/10.1371/journal.pone.0011034 |
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