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Automated SNP detection in expressed sequence tags: statistical considerations and application to maritime pine
Loïck Le Dantec1, David Chagné, David Pot
1Unité de Recherche sur les Espèces Fruitières et la Vigne, INRA, 71 avenue Edouard Bourlaux, BP 81, 33883 Villenave d'Ornon Cedex, France.
Plant Molecular Biology
|July 31, 2004
Summary
We created an automated pipeline to detect single nucleotide polymorphisms (SNPs) in maritime pine (Pinus pinaster Ait.) expressed sequence tag (EST) data. This method efficiently identifies SNPs, with detection probability influenced by allele frequency.
Area of Science:
- Genomics
- Bioinformatics
- Plant Science
Background:
- Single nucleotide polymorphisms (SNPs) are crucial genetic markers for various applications, including population genetics and breeding.
- Expressed sequence tags (ESTs) provide valuable gene expression information but require robust methods for SNP discovery.
- Developing efficient SNP detection pipelines is essential for large-scale genetic resource development in forest tree species.
Purpose of the Study:
- To develop and optimize an automated pipeline for detecting SNPs in maritime pine (Pinus pinaster Ait.) EST data.
- To evaluate the efficiency and accuracy of the developed SNP detection method.
- To identify and make available a set of candidate SNPs for maritime pine genetic research.
Main Methods:
- An automated pipeline was developed by integrating Phred, Phrap, and PolyBayes DNA sequence analysis programs.
- Parameters were optimized to maximize true SNP detection while minimizing false positives, using individual electrophoregram traces.
- A reference set of SNPs was generated from sequencing 30 gametes in 13 maritime pine gene fragments.
Main Results:
- The pipeline achieved an overall true SNP detection efficiency of 83.1%.
- Detection efficiency varied with SNP allele frequency, from 41% for rare alleles (<10%) to 98% for common alleles (>10%).
- A total of 1400 candidate SNPs were identified in 18498 assembled maritime pine ESTs, and these resources were made publicly available.
Conclusions:
- The developed automated pipeline is effective for SNP discovery in maritime pine EST data.
- SNP allele frequency is the primary factor influencing detection probability.
- The identified SNPs represent a valuable genetic resource for maritime pine research and breeding.