Skip to main content

Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions, and Improve Genome Assemblies

  • Protocol
Plant Bioinformatics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1374))

Abstract

Genotyping by sequencing (GBS) is an emerging technology to rapidly call an abundance of Single Nucleotide Polymorphisms (SNPs) using genome sequencing technology. Several different methodologies and approaches have recently been established, most of these relying on a specific preparation of data. Here we describe our GBS-pipeline, which uses high coverage reads from two parents and low coverage reads from their double haploid offspring to call SNPs on a large scale. The upside of this approach is the high resolution and scalability of the method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Miller MR, Dunham JP, Amores A et al (2007) Rapid and cost-effective polymorphism identification and genotyping using restriction site associated DNA (RAD) markers. Genome Res 17:240–248. doi:10.1101/gr.5681207

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  2. Davey JW, Cezard T, Fuentes-Utrilla P et al (2013) Special features of RAD sequencing data: implications for genotyping. Mol Ecol 22:3151–3164. doi:10.1111/mec.12084

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  3. Poland JA, Brown PJ, Sorrells ME, Jannink J-L (2012) Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS One 7:e32253. doi:10.1371/journal.pone.0032253

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Chen Y-C, Liu T, Yu C-H et al (2013) Effects of GC bias in next-generation-sequencing data on de novo genome assembly. PLoS One 8:e62856. doi:10.1371/journal.pone.0062856

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Carneiro MO, Russ C, Ross MG et al (2012) Pacific biosciences sequencing technology for genotyping and variation discovery in human data. BMC Genomics 13:375. doi:10.1186/1471-2164-13-375

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  6. Huang X, Feng Q, Qian Q et al (2009) High-throughput genotyping by whole-genome resequencing. Genome Res 19:1068–1076. doi:10.1101/gr.089516.108

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  7. Yang S, Yuan Y, Wang L et al (2012) Great majority of recombination events in Arabidopsis are gene conversion events. Proc Natl Acad Sci U S A 109:20992–20997. doi:10.1073/pnas.1211827110

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  8. Truong HT, Ramos AM, Yalcin F et al (2012) Sequence-based genotyping for marker discovery and co-dominant scoring in germplasm and populations. PLoS One 7:e37565. doi:10.1371/journal.pone.0037565

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  9. Li R, Yu C, Li Y et al (2009) SOAP2: an improved ultrafast tool for short read alignment. Bioinformatics 25:1966–1967. doi:10.1093/bioinformatics/btp336

    Article  CAS  PubMed  Google Scholar 

  10. Li H, Handsaker B, Wysoker A et al (2009) The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078–2079. doi:10.1093/bioinformatics/btp352

    Article  PubMed Central  PubMed  Google Scholar 

  11. Lorenc MT, Hayashi S, Stiller J et al (2012) Discovery of single nucleotide polymorphisms in complex genomes using SGSautoSNP. Biology 1:370–382. doi:10.3390/biology1020370

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  12. Milne I, Shaw P, Stephen G et al (2010) Flapjack—graphical genotype visualization. Bioinformatics 26:3133–3134. doi:10.1093/bioinformatics/btq580

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  13. Milne I, Bayer M, Cardle L et al (2010) Tablet—next generation sequence assembly visualization. Bioinformatics 26:401–402. doi:10.1093/bioinformatics/btp666

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  14. Scott LJ, Mohlke KL, Bonnycastle LL et al (2007) A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants. Science 316:1341–1345. doi:10.1126/science.1142382

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Howie BN, Donnelly P, Marchini J (2009) A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 5:e1000529. doi:10.1371/journal.pgen.1000529

    Article  PubMed Central  PubMed  Google Scholar 

  16. Parra G, Bradnam K, Korf I (2007) CEGMA: a pipeline to accurately annotate core genes in eukaryotic genomes. Bioinformatics 23:1061–1067. doi:10.1093/bioinformatics/btm071

    Article  CAS  PubMed  Google Scholar 

  17. Hunt M, Kikuchi T, Sanders M et al (2013) REAPR: a universal tool for genome assembly evaluation. Genome Biol 14:R47. doi:10.1186/gb-2013-14-5-r47

    Article  PubMed Central  PubMed  Google Scholar 

  18. Hoffmann S, Otto C, Kurtz S et al (2009) Fast mapping of short sequences with mismatches, insertions and deletions using index structures. PLoS Comput Biol 5:e1000502. doi:10.1371/journal.pcbi.1000502

    Article  PubMed Central  PubMed  Google Scholar 

  19. Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25:1105–1111. doi:10.1093/bioinformatics/btp120

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760. doi:10.1093/bioinformatics/btp324

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Yu X, Sun S (2013) Comparing a few SNP calling algorithms using low-coverage sequencing data. BMC bioinformatics 14:274. doi:10.1186/1471-2105-14-274

    Article  PubMed Central  PubMed  Google Scholar 

  22. Farrer RA, Henk DA, MacLean D et al (2013) Using false discovery rates to benchmark SNP-callers in next-generation sequencing projects. Sci Rep 3:1512. doi:10.1038/srep01512

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgement

The author acknowledges funding support from the Australian Research Council (Project LP1f10100200). Support is also acknowledged from the Queensland Cyber Infrastructure Foundation (QCIF) and the Australian Partnership for Advanced Computing (APAC).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Philipp Emanuel Bayer .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media New York

About this protocol

Cite this protocol

Bayer, P.E. (2016). Skim-Based Genotyping by Sequencing Using a Double Haploid Population to Call SNPs, Infer Gene Conversions, and Improve Genome Assemblies. In: Edwards, D. (eds) Plant Bioinformatics. Methods in Molecular Biology, vol 1374. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3167-5_16

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-3167-5_16

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-3166-8

  • Online ISBN: 978-1-4939-3167-5

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics