Identifying SNPs without a Reference Genome by Comparing Raw Reads

  • Pierre Peterlongo
  • Nicolas Schnel
  • Nadia Pisanti
  • Marie-France Sagot
  • Vincent Lacroix
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6393)

Abstract

Next generation sequencing (NGS) technologies are being applied to many fields of biology, notably to survey the polymorphism across individuals of a species. However, while single nucleotide polymorphisms (SNPs) are almost routinely identified in model organisms, the detection of SNPs in non model species remains very challenging due to the fact that almost all methods rely on the use of a reference genome. We address here the problem of identifying SNPs without a reference genome. For this, we propose an approach which compares two sets of raw reads. We show that a SNP corresponds to a recognisable pattern in the de Bruijn graph built from the reads, and we propose algorithms to identify these patterns, that we call mouths. We outline the potential of our method on real data. The method is tailored to short reads (typically Illumina), and works well even when the coverage is low where it reports few but highly confident SNPs. Our program, called KisSnp, can be downloaded here: http://alcovna.genouest.org/kissnp/.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Pierre Peterlongo
    • 1
  • Nicolas Schnel
    • 1
  • Nadia Pisanti
    • 2
  • Marie-France Sagot
    • 3
  • Vincent Lacroix
    • 3
  1. 1.INRIA Rennes - Bretagne Atlantique, EPI SymbioseRennesFrance
  2. 2.Dipartimento di InformaticaUniversità di PisaItaly
  3. 3.INRIA Rhône-Alpes, 38330 Montbonnot Saint-Martin, France and Université de Lyon, F-69000 Lyon, Université Lyon 1, CNRS, UMR5558, Laboratoire de Biométrie et Biologie EvolutiveVilleurbanneFrance

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