Acknowledgements CONFIDENTIAL Next Generation Genotyping Workflow - - PowerPoint PPT Presentation

RIPTIDE™ enabled Next Generation Genotyping

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Acknowledgements

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Next Generation Genotyping Workflow (Same for all RIPTIDE Applications)

De-multiplexing Sample Extraction (RNA/DNA) Library Preparation (RNA/DNA) Sequencing Result: Variant Call File for each genome

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RIPTIDE Workflow

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RIPTIDE Workflow: 960 Individually Barcoded Samples

A) B)

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RIPTIDE Size Selection (Included in Kit)

SPRI bead based size selection flexible for multiple insert size ranges

a) Pre-size selected library produces an equimolar amount of product from 200bp-2kb+. b) Example of SPRI bead size selected material with 500bp mean insert length. Options for larger/smaller inserts included in protocol.

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RIPTIDE Data Analysis: Read Structure

Sample Barcode Random Sequence Template Bases Template Bases 8 nt 12 nt 130 nt 142 nt Random Sequence 8 nt P5 Adapter P7 Adapter Bases identifying the sample Plate Barcode (Index) 6 nt Bases identifying the plate Read 1 (150 nt) Read 2 (150 nt) Derived from primer A Insert Derived from primer B

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RIPTIDE: One Technology – Many Applications

Whole Genome Sequencing Microbiome Genotyping by Sequencing Targeted Sequencing

Sample # of Barcodes Mean Coverage (unique) # hets called % hets phased N50 Haplotype block NA128781 1544 153x 2,612,866 99.9963% 16,791,622 Jurkat 6144 21x 2,229,468 99.2557% 2,261,063 NA04510 6144 34x 2,302,366 99.6859% 3,732,649 NA05289 6144 28x 2,165,774 99.5555% 1,149,861 NA11410 6144 30x 2,653,959 99.6975% 4,753,710 NA11629 6144 29x 2,278,703 99.6456% 1,582,026 NA13707 6144 11x 1,646,406 96.7802% 430,602 NA14622 6144 27x 2,318,691 99.8724% 7,255,334

Phasing / Haplotyping RNA Sequencing

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RIPTIDE Generates Uniform Coverage and is Reproducible

Heat map of wheat genomes: Chinese Spring (Reads/Mbp)

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Riptide Enabled Next Generation Genotyping (NGG): Simple Description

Homozygous (inbred) parental lines

• Shallow sequencing of progeny determines

recombination ”boundaries”

• Known (parental) genotypes are “assigned”

Deep Sequencing of parental lines

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Empirical Evidence Shows High Concordance to Arrays: Maize

Cross: B73 and LH82 lines 0.01x coverage shows > 99% concordance to AFFX 600K 2.4Gbp genome @ 0.01x coverage (.024G)=< $6 per sample*

(*Novaseq S4 flow cell, 2x 150, 100K samples per flow cell)

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What about a more complicated scenario?

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NGG for Accurate Human Genotyping Requires a Bit More Evidence (Reads)

How much sequencing is needed to accurately determine the correct haplotype and assign (impute) all the genotypes in a given genomic region?

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Human Data Generation

Samples obtained from Corriel institute 4ul of DNA input into Riptide (no sample QC performed) Multiplex libraries sent to macrogen for sequencing Demux using fgbio… …then Gencove for VCF generation for 38M bi-allelic variants RTGtools VCF eval used for comparison ILMN GSA array variants in NIST high confidence regions used as "truth" set

*Gencove now calls > 80M variants for human

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960 Human Genomes Across a Full NovaSeq S4 Flow Cell

Number of samples per flow cell depends on goals of study.

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384 Human Genomes: (96 Per Lane on NovaSeq S4 Flow Cell)

99.7% 98.2% 98.9% 98.7% 99.0% 99.6% 92.5% 87.5% 90.0% 99.9% 50.0% 55.0% 60.0% 65.0% 70.0% 75.0% 80.0% 85.0% 90.0% 95.0% 100.0% SNV Precision SNV Sensitivity SNV Accuracy MAF <1% Precision MAF 1-5% Precision MAF >5% Precision SV Precision SV Sensitivity SV Accuracy Replicate Precision

Summary Stats (mean) for JPT and YRI samples (n=288) on autosome variant calls

Wellderly (96, right), YRI(96) & JPT(96X2)

Wellderly: NGG vs Illumina 40X WGS Gold Standard

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0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1

Accuracy: f-measure

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1

Sensitivity: TP / (TP + FN)

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99 1

Precision: TP / (TP+FP)

Precision, Sensitivity, and Accuracy for 288 Individual Samples

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Precision (Concordance) by MAF: GSA

98.0% 98.5% 99.0% 99.5% 100.0% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100%

Precision Minor Allele Frequency

Precision: TP / (TP + FP) by Minor Allele Frequency

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Comparison of Human Genotyping Products

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Potential for Single Phase GWAS and Causal Variant Discovery

• Merge FAST Q files from individual

low pass samples (case/control)

• Treat cases and controls as high

coverage individual samples

• Perform genotype calling
• Call novel variants
• Identify causal candidates

Reference: https://doi.org/10.1038/s41576-018-0016-z

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Reference: University of Liege

“Reagent costs to sequence a mammalian genome at 1-fold depth are now <20€ thus making this a cost-effective proposition. As a matter of fact, the method is being deployed in the field in several countries.” SNP-based quantitative deconvolution of biological mixtures: application to the detection of cows with subclinical mastitis by whole genome sequencing of tank milk

− Wouter Coppieters, Latifa Karim, Michel Georges

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RIPTIDE + Gencove Promotion: Purchase a Kit, Get Your Analysis for Free!

Reference: https://docs.gencove.com/main/#data-analysis-configurations

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Back to technology

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RIPTIDE Tunability and Customization

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RIPTIDE Kit Includes Hi/Low GC Primers for Tunability

• Easily tunable to GC content
• Species representation is maintained

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RIPTIDE targeted spike ins: in development

TTR Gene: 17 targeted primer annealing sites spaced 300-600bp across 9.564kb

IGV browser images

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NGS library (rRNA sequences in purple) Total cellular RNA sample NGS library prep

CRISPR-mediated Depletion Protocol: (A JumpCode Technology)

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NGS library (rRNA sequences in purple) CRISPR Cas9 digestion of library (or multiplexed libraries) Size selection to remove short fragments PCR amplfication Total cellular RNA sample NGS library prep Post-library ribodepletion

CRISPR-mediated Depletion Protocol: (A JumpCode Technology)

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CRISPR-mediated Depletion Protocol: (A JumpCode Technology)

Cas9/gRNA RNP formation (10 mins at room temp) Cas9/gRNA digestion of library (1 hr at 37°C) Size Selection (0.6X Ampure Beads) PCR Size Selection (0.6X Ampure Beads)

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0.31% 4.25% 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% Predepletion Post Depletion

% reads coding

15.5 7.3 2 4 6 8 10 12 14 16 Predepletion Post Depletion

Genome size (Gbp)

JumpCode’s CRISPR repeat depletion applied to wheat

Reduction of genome size

(78% goal)

53%

Enrichment increase of CDS coverage

Theoretical max = 8.49%

14x

7.3

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Conclusions

• High quality data
• Simple, cost effective
• Tunable to the data you want
• Just the beginning…