A training and research lab for Nanopore sequencing

Data analysis for SME derived use cases

PoreLab

PoreLab Project Explore Nanopore sequencing needs within SME

  Applications   Genomics   Metagenomics Transcriptomics

  Data analysis Basecalling Quality Control   Assembly Classification Transcriptomics Conclusions

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pitchbyNIOZpitchbyDutchDNABiotech

pitchbyNSure

Nanopore Technology

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How accurate is basecalling?

4 Comparison of Oxford Nanopore basecalling tools. Ryan R. Wick, Louise M. Judd and Kathryn E Holt. Doi. 10.5281/zendo.1188469

88%

Polishing without methylation awereness

Polishing with methylation awereness

99,7%

Readidentity Assembleidentity Rel.readlength

QC of data   Sequencing process

  Sequencing data   Read distribution   Q score   Read Statistics (NanoPack)

5 NanoPack: visualizing and processing long-read sequencing data. De Coster W, D'Hert S, Schultz DT, Cruts M, Van Broeckhoven C. Bioinformatics. 2018 Aug 1;34(15):2666-2669. doi: 10.1093/bioinformatics/bty149.

Number of reads and fraction above quality cutoffs

Genomics Assembly Work Flow

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DNA reads

Overlaps

Raw assembly

Mapping reads to draft assembly

Rawsignal

Optimal Assembly

Base Calling

Read to Read Finding

Assembly

Read Mapping

Polishing

Albacore/Guppy

Minimap2, OLC assembler

Minimap2, BWA-MEM

Miniasm, MECAT

RACON, Nanopolish

Senol Cali D. et.al. Nanopore sequencing technology and tools for genome assembly: computational analysis of the current state, bottlenecks and future directions. Brief Bioinform. 2018

Genomics

Amount of contigs   Total length   N50   Q value

  Pitch by Dutch DNA Biotech

7 Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies.

Bioinformatics. 2013 Apr 15;29(8):1072-5. doi: 10.1093/bioinformatics/btt086. Epub 2013 Feb 19.

•  % GC •  Coverage •  % identity •  % Genome fraction if reference is available

Shotgun MetaGenomics: Classification

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Index of genomen Taxonomic relationship Genoom/ reads

Winclove,Soiltech,GroenAgro,BKD,pitchbyNIOZ

Data analysis transcriptomics

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Raw Nanopore

reads

QC (NanoPlot)

PoreChop demultiplex

reads

Align against reference: minimap2

Transcripts quantification

Statistical analysis

edgeR/limma

Significant up/down regulation

Transcriptomics – Read mapping

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  Reads of low quality align to a lesser extent   Filtering based on quality is not a good idea

Differential expression

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Transcriptomics – Coverage plot

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  Transcript UN79269 komt ± 6x differentiele expressie hoger tot expressie in BC09 tov BC08

Conclusion

Basecalling is very accurate for consensus sequences, but less on a per read basis

  Genomics data analysis of micro-organisms yields good

assemblies, detects transgenes in genome and could be

combined with Illumina data

  Shotgun metagenomics enables accurate detection of

organisms but ratio’s are an approximation.

Transcriptomics is still at it’s infancy but will have a great future

after some adjustments in wet lab procedures

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Acknowledgement:   FG   Ron Dirks   Hans Jansen

  Hogeschool Leiden   Floyd Wittink   Koen Bossers Nikola Petrusevski   Stef Pieterman   Jasper Oudenkerk

  Consortiumpartners PoreLab

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  Jeroen Pijpe   Brian Piepenbroek   Casper Prins   Stef Janson