High-specificity detection of rare alleles with Paired-End Low Error Sequencing (PELE-Seq)

Jessica L. Preston, Ariel E. Royall, Melissa A. Randel, Kristin L. Sikkink, Patrick C. Phillips, Eric A. Johnson

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Background: Polymorphic loci exist throughout the genomes of a population and provide the raw genetic material needed for a species to adapt to changes in the environment. The minor allele frequencies of rare Single Nucleotide Polymorphisms (SNPs) within a population have been difficult to track with Next-Generation Sequencing (NGS), due to the high error rate of standard methods such as Illumina sequencing. Results: We have developed a wet-lab protocol and variant-calling method that identifies both sequencing and PCR errors, called Paired-End Low Error Sequencing (PELE-Seq). To test the specificity and sensitivity of the PELE-Seq method, we sequenced control E. coli DNA libraries containing known rare alleles present at frequencies ranging from 0.2-0.4% of the total reads. PELE-Seq had higher specificity and sensitivity than standard libraries. We then used PELE-Seq to characterize rare alleles in a Caenorhabditis remanei nematode worm population before and after laboratory adaptation, and found that minor and rare alleles can undergo large changes in frequency during lab-adaptation. Conclusion: We have developed a method of rare allele detection that mitigates both sequencing and PCR errors, called PELE-Seq. PELE-Seq was evaluated using control E. coli populations and was then used to compare a wild C. remanei population to a lab-adapted population. The PELE-Seq method is ideal for investigating the dynamics of rare alleles in a broad range of reduced-representation sequencing methods, including targeted amplicon sequencing, RAD-Seq, ddRAD, and GBS. PELE-Seq is also well-suited for whole genome sequencing of mitochondria and viruses, and for high-throughput rare mutation screens.

Original languageEnglish (US)
Article number464
JournalBMC Genomics
Volume17
Issue number1
DOIs
StatePublished - Jun 14 2016

Bibliographical note

Publisher Copyright:
© 2016 Preston et al.

Keywords

  • De novo mutations
  • Genetic heterogeneity
  • Laboratory adaptation
  • Minor alleles
  • Next-generation sequencing
  • PELE analysis
  • SNPs

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