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Leishmania pp 69-94 | Cite as

A Guide to Next Generation Sequence Analysis of Leishmania Genomes

  • Hideo ImamuraEmail author
  • Jean-Claude Dujardin
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1971)

Abstract

Next generation sequencing (NGS) technology transformed Leishmania genome studies and became an indispensable tool for Leishmania researchers. Recent Leishmania genomics analyses facilitated the discovery of various genetic diversities including single nucleotide polymorphisms (SNPs), copy number variations (CNVs), somy variations, and structural variations in detail and provided valuable insights into the complexity of the genome and gene regulation. Many aspects of Leishmania NGS analyses are similar to those of related pathogens like trypanosomes. However, the analyses of Leishmania genomes face a unique challenge because of the presence of frequent aneuploidy. This makes characterization and interpretation of read depth and somy a key part of Leishmania NGS analyses because read depth affects the accuracy of detection of all genetic variations. However, there are no general guidelines on how to explore and interpret the impact of aneuploidy, and this has made it difficult for biologists and bioinformaticians, especially for beginners, to perform their own analyses and interpret results across different analyses. In this guide we discuss a wide range of topics essential for Leishmania NGS analyses, ranging from how to set up a computational environment for genome analyses, to how to characterize genetic variations among Leishmania samples, and we will particularly focus on chromosomal copy number variation and its impact on genome analyses.

Key words

Next generation sequencing Bioinformatics Somy variation SNP calling Leishmania 

Notes

Acknowledgments

We thank Geraldine De Muylder, Bart Cuypers, and Malgorzata Domagalska for their comments on the manuscript.

References

  1. 1.
    Leprohon P, Fernandez-Prada C, Gazanion É et al (2015) Drug resistance analysis by next generation sequencing in Leishmania. Int J Parasitol Drugs Drug Resist 5(1):26–35CrossRefGoogle Scholar
  2. 2.
    Mardis ER (2017) DNA sequencing technologies: 2006–2016. Nat Protoc 12(2):213PubMedCrossRefGoogle Scholar
  3. 3.
    Imamura H, Downing T, Van den Broeck F et al (2016) Evolutionary genomics of epidemic visceral leishmaniasis in the Indian subcontinent. Elife 5:e12613PubMedPubMedCentralCrossRefGoogle Scholar
  4. 4.
    Downing T, Imamura H, Decuypere S et al (2011) Whole genome sequencing of multiple Leishmania donovani clinical isolates provides insights into population structure and mechanisms of drug resistance. Genome Res 21(12):2143–2156PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Rogers MB, Hilley JD, Dickens NJ et al (2011) Chromosome and gene copy number variation allow major structural change between species and strains of Leishmania. Genome Res 21(12):2129–2142PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Dumetz F, Imamura H, Sanders M et al (2017) Modulation of aneuploidy in Leishmania donovani during adaptation to different in vitro and in vivo environments and its impact on gene expression. MBio 8(3):e00599–e00517PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Barja PP, Pescher P, Bussotti G et al (2017) Haplotype selection as an adaptive mechanism in the protozoan pathogen Leishmania donovani. Nat Ecol Evol 1(12):1961CrossRefGoogle Scholar
  8. 8.
    Jones NG, Catta-Preta CM, Lima AP, Mottram JC (2018) Genetically validated drug targets in Leishmania: current knowledge and future prospects. ACS Infect Dis 4(4):467–477PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Mannaert A, Downing T, Imamura H, Dujardin JC (2012) Adaptive mechanisms in pathogens: universal aneuploidy in Leishmania. Trends Parasitol 28(9):370–376PubMedCrossRefGoogle Scholar
  10. 10.
    Sterkers Y, Lachaud L, Bourgeois N et al (2012) Novel insights into genome plasticity in Eukaryotes: mosaic aneuploidy in Leishmania. Mol Microbiol 86(1):15–23PubMedCrossRefGoogle Scholar
  11. 11.
    Iantorno SA, Durrant C, Khan A et al (2017) Gene expression in Leishmania is regulated predominantly by gene dosage. MBio 8(5):e01393–e01317PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Tihon E, Imamura H, Dujardin JC et al (2017) Discovery and genomic analyses of hybridization between divergent lineages of Trypanosoma congolense, causative agent of Animal African Trypanosomiasis. Mol Ecol 26(23):6524–6538PubMedCrossRefGoogle Scholar
  13. 13.
    Tihon E, Imamura H, Dujardin JC, Van Den Abbeele J (2017) Evidence for viable and stable triploid Trypanosoma congolense parasites. Parasit Vectors 10(1):468PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Head SR, Komori HK, LaMere SA et al (2014) Library construction for next-generation sequencing: overviews and challenges. Biotechniques 56(2):61PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Vincent AT, Derome N, Boyle B et al (2017) Next-generation sequencing (NGS) in the microbiological world: how to make the most of your money. J Microbiol Methods 138:60–71PubMedCrossRefGoogle Scholar
  16. 16.
    Haddock SHD, Dunn CW (2011) Practical computing for biologists. Sinauer, SunderlandGoogle Scholar
  17. 17.
    Aslett M, Aurrecoechea C, Berriman M et al (2009) TriTrypDB: a functional genomic resource for the Trypanosomatidae. Nucleic Acids Res 38(suppl_1):D457–D462PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30(15):2114–2120PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Cuypers B, Domagalska MA, Meysman P et al (2017) Multiplexed spliced-leader sequencing: a high-throughput, selective method for RNA-seq in Trypanosomatids. Sci Rep 7(1):3725PubMedPubMedCentralCrossRefGoogle Scholar
  20. 20.
    Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25(14):1754–1760PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9(4):357PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Li H, Homer N (2010) A survey of sequence alignment algorithms for next-generation sequencing. Brief Bioinform 11(5):473–483PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Zackay A, Cotton JA, Sanders M et al (2018) Genome wide comparison of Ethiopian Leishmania donovani strains reveals differences potentially related to parasite survival. PLoS Genet 14(1):e1007133PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Coughlan S, Mulhair P, Sanders M et al (2017) The genome of Leishmania adleri from a mammalian host highlights chromosome fission in Sauroleishmania. Sci Rep 7:43747PubMedPubMedCentralCrossRefGoogle Scholar
  25. 25.
    Coughlan S, Taylor AS, Feane E et al (2018) Leishmania naiffi and Leishmania guyanensis reference genomes highlight genome structure and gene evolution in the Viannia subgenus. R Soc Open Sci 5(4):172212PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Rastrojo A, García-Hernández R, Vargas P et al (2018) Genomic and transcriptomic alterations in Leishmania donovani lines experimentally resistant to antileishmanial drugs. Int J Parasitol Drugs Drug Resist 8(2):246–264PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Valdivia HO, Reis-Cunha JL, Rodrigues-Luiz GF et al (2015) Comparative genomic analysis of Leishmania (Viannia) peruviana and Leishmania (Viannia) braziliensis. BMC Genomics 16(1):715PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Dumetz F, Cuypers B, Imamura H et al (2018) Molecular preadaptation to antimony resistance in Leishmania donovani on the Indian subcontinent. mSphere 3(2):e00548–e00517PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Shaw CD, Lonchamp J, Downing T et al (2016) In vitro selection of miltefosine resistance in promastigotes of Leishmania donovani from Nepal: genomic and metabolomic characterization. Mol Microbiol 99(6):1134–1148PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Reis-Cunha JL, Rodrigues-Luiz GF, Valdivia HO et al (2015) Chromosomal copy number variation reveals differential levels of genomic plasticity in distinct Trypanosoma cruzi strains. BMC Genomics 16(1):499PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Schwabl P, Imamura H, Van den Broeck F et al (2018) Parallel sexual and parasexual population genomic structure in Trypanosoma cruzi. bioRxiv.  https://doi.org/10.1101/338277
  32. 32.
    Rogers MB, Downing T, Smith BA et al (2014) Genomic confirmation of hybridisation and recent inbreeding in a vector-isolated Leishmania population. PLoS Genet 10(1):e1004092PubMedPubMedCentralCrossRefGoogle Scholar
  33. 33.
    McKenna A, Hanna M, Banks E et al (2010) The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20(9):1297–1303PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Marth GT, Korf I, Yandell MD et al (1999) A general approach to single-nucleotide polymorphism discovery. Nat Genet 23(4):452PubMedCrossRefGoogle Scholar
  35. 35.
    Li H, Handsaker B, Wysoker A et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Iqbal Z, Caccamo M, Turner I et al (2012) De novo assembly and genotyping of variants using colored de Bruijn graphs. Nat Genet 44(2):226PubMedPubMedCentralCrossRefGoogle Scholar
  37. 37.
    Frith MC (2010) A new repeat-masking method enables specific detection of homologous sequences. Nucleic Acids Res 39(4):e23PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Derrien T, Estelln J, Sola SM et al (2012) Fast computation and applications of genome mappability. PLoS One 7(1):e30377PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Otto TD, Sanders M, Berriman M, Newbold C (2010) Iterative correction of reference nucleotides (iCORN) using second generation sequencing technology. Bioinformatics 26(14):1704–1707PubMedPubMedCentralCrossRefGoogle Scholar
  40. 40.
    Gonznformaticssecond S, Peirnformati R et al (2017) Resequencing of the Leishmania infantum (strain JPCM5) genome and de novo assembly into 36 contigs. Sci Rep 7(1):18050CrossRefGoogle Scholar
  41. 41.
    Cingolani P, Platts A, Wang LL et al (2012) program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly 6(2):80–92PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Ewing B, Green P (1998) Base-calling of automated sequencer traces using phred. II. Error probabilities. Genome Res 8(3):186–194PubMedCrossRefGoogle Scholar
  43. 43.
    Schurch NJ, Schofield P, Gierliński M et al (2016) How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? RNA 22(6):839–851PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Fiebig M, Kelly S, Gluenz E (2015) Comparative life cycle transcriptomics revises Leishmania mexicana genome annotation and links a chromosome duplication with parasitism of vertebrates. PLoS Pathog 11(10):e1005186PubMedPubMedCentralCrossRefGoogle Scholar
  45. 45.
    Patino LH, Ramírez JD (2017) RNA-seq in kinetoplastids: A powerful tool for the understanding of the biology and host-pathogen interactions. Infect Genet Evol 49:273–282PubMedCrossRefGoogle Scholar
  46. 46.
    Dobin A, Davis CA, Schlesinger F et al (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29(1):15–21PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Biomedical SciencesInstitute of Tropical MedicineAntwerpBelgium
  2. 2.Department of Biomedical Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary SciencesUniversity of AntwerpAntwerpBelgium

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