QIAseq Targeted DNA, RNA and Fusion Gene Panels

QIAseq Targeted RNA Panels for gene expression profiling using Digital RNA sequencing

QIAseq Targeted Sequencing1PowerPoint Style Guide, 07.10.2015Samuel Rulli, Ph.D.Global Product ManagerQIAGEN

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Legal disclaimer2QIAGEN products shown here are intended for molecular biology applications. These products are not intended for the diagnosis, prevention or treatment of a disease.For up-to-date licensing information and product-specific disclaimers, see the respective QIAGEN kit handbook or user manual. QIAGEN kit handbooks and user manuals are available at www.QIAGEN.com or can be requested from QIAGEN Technical Services or your local distributor.

Sample to InsightTumor heterogeneity3

Tumors are notorious for being a mixed population of cancer cells and infiltrating cells

There is often a limited amount of sample available

FFPE samples are a necessary part of most cancer research programs

Sample to InsightTumor heterogeneity4Tumor heterogeneity leads toHighly variable cancersDifferential response to treatmentTargetedNon-targetedA need to be monitored over time, especially during treatmentLow-frequency gene mutations are as important as high-frequency ones The challenge is to identify these low frequency events

Sample to InsightIt is generally agreed that cancer stem cell model must coexists with other sources of tumor heterogeneity including clonal evolution, heterogeneity in micro-environment, and reversible changes in cancer-cell properties that can occur independently of hierarchical properties

What is not clear is what extent is metastasis, therapy resistance and disease progression reflect the intrinsic properties of the cancer stem cells as apposed to genetic evolution or other sources of heterogeneity.

What is certainly clear is that we need to develop integrated multiple experimental approach to distinguish the relative contributions of these different sources of heterogeneity to disease progression.

For easier applications in real world, these have to be easy to implement, robust and 4

Using targeted sequencing to understand tumor heterogeneity5Targeted sequencing is uniquely positioned to address these problemsNeeds a small amount of sample inputRobust even when using FFPE or damaged samplesAccessible to researchers with bench-top NGS instrumentsSimplified bioinformaticsVariant?Fusion?GEX?miRNA?Variant?Fusion?GEX?miRNA?Variant?Fusion?GEX?miRNA?

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Contents6Principles of unique molecular indexes (UMIs)1Single primer extension (SPE) vs. PCR for library construction2UMIs and SPE in action gene expression analysis3DNA variant analysis and novel gene fusion discoveries with UMIs and SPE4Summary/questions5

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Principles of unique molecular indexes (UMIs)8PCR duplication and amplification bias are major issues in current RNAseq workflows, as they result in biased and inaccurate gene expression profiles

mRNA copiescDNAOriginal gene ratio status

mRNA ratio based on reads(reads ratio)Gene ASample 1Gene ASample 2

Raw reads41Number of reads12612

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9Targeted RNAseq is a read-based approach to understanding gene expression

How do we go from reads to counting transcripts?

Principles of unique molecular indexes (UMIs)

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Targeted RNAseq is a read-based approach to understanding gene expression

How do we go from reads to counting transcripts?Principles of unique molecular indexes (UMIs)

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Principles of unique molecular indexes (UMIs)11

mRNA copiescDNAOriginal gene ratio statusmRNA ratio based on readsGene ASample 1Gene ASample 2UMI reads4112Molecular indexes allow the counting of original transcript levels instead of PCR duplicates, thereby enabling digital sequencing and resulting in unbiased and accurate gene expression profilesTag each transcript with UMIsmRNA ratio based on UMIs14Count UMIs, not reads

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12During mRNAseq, each capture event is archived with an UMI

12 random bases16.7 million indexesThe strategy for measuring gene expression uses UMI-gene-specific primer

The strategy for measuring DNA variant and fusion gene is slightly different, but the principle is the same.Principles of unique molecular indexes (UMIs)

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Single primer extension145335cDNA535Captures informationSingle primer

Sample to Insight15Advantages of SPE:Needs only a single region for primer design Unlocks entire transcriptome, genome and fusion genes Having to use half the number of primers lowers cost and allows for greater content during multiplexingAble to adapt to G/C-rich and difficult-to-PCR regionsAllows you to sequence almost everythingUniform reaction Uniform library construction uniform sequencingWorks very well on FFPE, fragmented and low quality samples

Disadvantages of SPE:Extra step in library constructionMay add 1 hour to total workflowSingle primer extension

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17Small molecules/signal transduction applicationExperiment: identify novel compounds that modulate known signal transduction pathways

CellsTreated cellsRNAUMIs and SPE in action: a gene expression example

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18Small molecules/signal transduction applicationCells are treated with different chemical inhibitorsRNA is isolatedLibraries are built using QIAseq Targeted RNA PanelsHuman Signal Transduction Panel 421 targets/10 ng total RNA

CellsTreated cellsRNAUMIs and SPE in action: a gene expression example Experiment: identify novel compounds that modulate known signal transduction pathways

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6 hoursGSP1, GSP2 are used at different stages

They never interact, which minimizes primer dimers

UMIs and SPE in action: a gene expression example

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Leave no scientist behindUMIs and SPE in action: a gene expression example

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Included in panel kitLibrary Quant KitIncludedin cloudIndex Kit

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Included in panel kitLibrary Quant KitIncludedin cloudIndex Kit

CLC Biomedical workbench with MT plugin

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Customer criteriaDifferential gene expression by QIAseq NGSSpecies coverageHuman catalog, extended, virtual and custom panelsMouse and rat custom Biological replicatesEssential for robustness of experimental design (and statistics!)Short reads for FFPE and exosomal RNAAverage amplicon 97 bps; range 95-130 basesCoverage across transcript (i.e. cover every exon)We are counting single common regions per gene. Same design philosophy as RT2 PCR ArraysDepth of sequencingHigh enough to infer accurate statistics determined by UMI: ~2-5 reads per UMI is enough.Role of sequencing depthCapture enough unique tags of each transcript such that statistical inferences can be made (>10 tags per gene)Stranded library prepNot required, amplicons do not overlap lncRNAType of reads (paired or Unpaired?)Not necessary; 150 base single reads more than enough for accurate datamRNA and lncRNAsQIAseq was designed against database containing lncRNA and mRNA. Assay are specific for lncRNA or mRNA. Currently 54,881 genes from Ensembl version 81

23UMIs and SPE in action: a gene expression example

Sample to InsightSome features of quantitative RNAseq

Replicates (same as any proper expression experiment)Can count using a small regionDepth has to allow statistical accuracy, but much shallower than transcriptomeStrandedness is not needed assays target unique regionsPaired end reads not required but nice to have must read from universal end or through it to capture barcode.23

Free circulating nucleic acidsRNA and DNA from dead cells shed into the bloodstream, can contain cancer-related mutations.ExosomesTiny microvesicles found in body fluids that transport RNA between cells.Circulating tumor cellsTumor cells shed from a tumor into the bloodstream carrying genetic information.24

Tissue samplesFresh tissue or archived FFPE samplesQIAGENs comprehensive sample isolation portfolio is compatible with QIAseq RNA Kits and allows you to use as little as 100 pg (10 cells) to 25 ng RNA


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26Flexible experiment design for any research interest Catalog panel options:

Comprehensive panels (available for 12, 96 or 384 samples)Cancer Transcriptome (395)Inflammation & Immunity Transcriptome (475)Signal Transduction PathwayFinder (406)Stem Cell & Differentiation Markers (293)Molecular Toxicology Transcriptome (370)Angiogenesis & Endothelial Cell Biology (340)Apoptosis & Cell Death (264)ECM & Adhesion Molecules (421)


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lnc13ADAMTS9CAHMDLEU2GAS5GAS6-AS1GNASLINC00261MEG3MIR31HGMIR7-3HGNAMAPTCSC1PTCSC3TERCZFAS1LINC00312DLX6NEATGACAT1What is the role of tumor suppressor lncRNAs?Find out!Flexible experiment design for any research interestUMIs and SPE in action: a gene expression example Extended panels:

Add 25 of your favorite targets (mRNA or lncRNA) to QIAGENs comprehensive panel

Sample to Insight28Catalog panel options:

QIAseq Targeted RNA Virtual Panels (available for 12, 96 or 384 samples)

Each panel contains 84 genes + controls and house keeping genesChoose from over 180 panels!

Diseases

Pathways

miRNA TargetsUMIs and SPE in action: a gene expression example Flexible experiment design for any research interest

Sample to Insight29Online custom builderChoose your own gene content from 54,881 human genes and lncRNAsEasy to use online Custom Panel Builder to tailor panel to your research needsInput list of genesSelect proper controls (genomic DNA contamination control, HKGs or your own)Output: list of genomic coordinates for primers designed specifically for your genes of interest


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Download zip file containing:Summary fileBed fileAll your custom designs are saved for easy retrievalHave questions?Contact us easilyConfigure and orderCustom panel numberUMIs and SPE in action: a gene expression example

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Custom builder31

Gene ID and symbolGenome strand on which gene is locatedAmplicon coordinatesDesignated controlsSingle exon (1): both primers are within one exon# Gencode basic RNAs: total number of RNA transcripts found for the gene in Gencode# Gencode basic RNAs matched: # of RNA transcripts targeted by the designed amplicon# off target genes: rough prediction of number of off-target genes that will also get enriched by the primer pair for the target geneAmplicon not genome unique: reads that will not be able to be uniquely mapped to the genome, so some MT counts might come from another loci

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Custom builder32Bed file

Location of designed amplicon

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QIAGEN: Automating Sample to Insight

Real timePCR + HRMPCR FragmentAnalysisPyro-sequencingHybridcapture

Bench topassay setupIntegrated assay setup

Low-throughputHigh-throughputSample disruptionPurificationAssaysetupDetection and analysis

Medium-throughput

Quality Control

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GeneReader NGS

Sample to InsightQIAGEN: Automating Sample to Insight

Purification

Quality Control

34Cells in 96 well platesRNA isolation from 96 samplesRNA Integrity(96 samples done automatically while at lunch!)RNA quantification(16 samples per 90 secs)

Sample to InsightQIAGEN: Automating Sample to Insight

Purification

Quality Control

35Cells in 96 well platesRNA isolation from 96 samplesSample disruptionAssaysetupDetection and analysis

Library quantificationLibrary integrity

RNA Integrity(96 samples done automatically while at lunch!)RNA quantification(16 samples per 90 secs)

Sample to Insight36Small molecules/signal transduction application

CellsTreated cellsRNAQIAseq targeted application data

Normalized, pooled libraries

Indexed librariesHEK293T cells were treated with 90 different chemical inhibitorsThe 421 Signal Transduction Gene QIAseq Panel was interrogated In one day, we went from total RNA to sequence-ready libraries for 96 samples The final libraries were quantified, normalized, and pooled. Prior to loading onto a NextSeq, the denatured libraries were diluted to the appropriate input concentration to generate suitable clusters on the NextSeq. The parameters of the NextSeq sequencing run were: A single 151 bp readA custom sequencing primer (included in kit)

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Primary data analysis for QIAseq targeted RNA sequencing37QIAseq targeted RNA data analysis automated workflowRead MappingIdentify the possible position of the read within the reference genomeAlign the read sequence to reference sequencesPrimer TrimmingRemove primer sequences from the readsUMI CountingGo get coffee!

Read mappingPrimer trimmingUMI count

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Small molecule application data38

Primary data analysis for QIAseq targeted RNA sequencing

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Small molecule application data39Primary data analysis for QIAseq targeted RNA sequencingQIAseq RNA quantification - read details: unique captures per target gene count

Differential gene expression, inter- and intra-samples

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Controls: take the guesswork out of your analysis!40Built-in controlsAssays to control for any gDNA contamination in the RNA sample

Mean tags per target calculated and mRNA counts near this number flagged during analysis as close to noise level Multiple HKG assays normalize data to make sample-to-sample and run-to-run comparisons possible

Flexible use none, one, two or any other number of genes to normalize

HKG efficacy evaluation built into secondary data analysisHKG

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QIAseq secondary data analysis setupWhat kinds of things get flagged?Low tag #, high gDNA, poor normalizer performance

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42Changes in gene expression due to chemical perturbation were quantified by QIAseq RNA NGS and characterized

Secondary data analysis for QIAseq targeted RNA sequencing

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43Scatter plot and clustergram (HDAC sample compared to control)

Secondary data analysis for QIAseq targeted RNA sequencing

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HDAC mechanistic network in HEK293T cells treated with trichostatin A44HDAC is predicted to be inhibited by trichostatin A and drives a mechanistic network with 18 other regulators

Ingenuity IPA analysisCell cycleNHR, proliferationTranscriptionalactivator

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QIAseq sample multiplexing guidelines on NGS platforms45Where can you run these panels?

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Unparalleled efficiency and flexibility vs PCR46An example: 96 samples, 421 genesParameterQIAseq Targeted RNA PanelsRT-PCRMaterial requiredOne pool of primersOne hundred and five 384-well platesRun time14 hours for NextSeq run310 hours (2 hours per plate)Hands-on time3 hours (for 96 samples)105 hours (one hour per plate)Sample10 ng each sample4000 ng each sample

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48QIAseq Targeted DNA PanelsUnique molecular indexMutation /SNP analysisCNVInsertions/deletions2 ng fresh DNA QIAseq Targeted RNAscan PanelsUnique molecular indexKnown fusion genes (validation)Unknown partners (discovery)QIAseq miRNAseq KitsUMIsGel free library prepComplete miRNomeQIAseq Targeted RNA PanelsUMIsGene expressionStart with 100 pg/10 cellsDNA variant analysis and novel gene fusion discovery

Sample to Insight49QIAseq Targeted DNA PanelsUnique molecular indexMutation /SNP analysisCNVInsertions/deletions2 ng fresh DNA DNA variant analysis and novel gene fusion discovery

Sample to Insight50PCR and sequencing errors (artifacts) limit variant calling accuracy

Not possible to discern whether the mutation is:1. A PCR or sequencing error (artifact/false positive)OR2. A true low-frequency mutationTraditional targeted DNA sequencingEGFR exon 21*Variant calling based on non-unique reads does not reflect the mutational status of original DNA molecules

Applies to a wide range of panels

DNA variant analysis and novel gene fusion discoveryA mutation is seen in 1 out of 5 reads that map to EGFR exon 21

Sample to InsightA variant identified in a sample represents one of two events: a true or false variant. False variants can be introduced at any step during the workflow, including sequencing reactions. This results in the inability to accurately and confidently call rare variants (those present at 1% of the sample). Due to PCR duplicates generated in amplification steps, all DNA fragments look exactly the same, and there is no way to tell whether a specific DNA fragment is a unique DNA molecule or a duplicate of a DNA molecule. With molecular barcodes, since each unique DNA molecule is barcoded before any amplification takes place, unique DNA molecules are identified by their unique barcodes, and PCR duplicates carrying the same barcode are removed, thereby increasing the sensitivity of the panel.50

Krishnan Allampallam (KA) - I have modified the text slightly

OK51Digital sequencing = count and analyze each original molecule (not total reads)

Not possible to discern between:1. Five unique DNA moleculesOR2. Quintuplets of the same DNA molecule (PCR artifact)Traditional targeted DNA sequencingEGFR exon 21DNA variant analysis and novel gene fusion discoveryFive reads or library fragments that look exactly the same

Five unique DNA moleculessince five UMIs are detectedQuintuplets of the same DNA molecule (PCR duplicates) since only one UMI is detectedUMIDigital sequencing with UMIsAdd UMIsbefore amplificationUMIs


52Digital sequencing = count and analyze each original molecule (not total reads)

Traditional targeted DNA sequencingEGFR exon 21DNA variant analysis and novel gene fusion discoveryAdd UMIsbefore amplification*A mutation is seen in 1 out of 5 reads that map to EGFR exon 21

Not possible to discern whether the mutation is:1. A PCR or sequencing error (artifact/false positive)OR2. A true low-frequency mutation

A false variant is present in only some fragments with the same UMIA true variant is present in all fragments with the same UMIUMI******Digital sequencing with UMIsUMI


53QIAseq Targeted DNA Panel WorkflowDNA variant analysis and novel gene fusion discovery

Sample to Insight54QIAseq Targeted RNAscan PanelsUnique molecular indexKnown fusion genes (validation)Unknown partners (discovery)DNA variant analysis and novel gene fusion discovery

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RPS6KB1-VMP1ARFGEF2-SULF2

QIASeq Targeted RNAscan is a RNA target enrichment method that allows verification of known fusions and discovery of novel fusions with next-generation sequencing (NGS).DNA variant analysis and novel gene fusion discovery55

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DNA variant analysis and novel gene fusion discovery

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Summary: biomarkers come in many flavors58BiomarkersGene expressionCopy number variantsIndelsMutationsmiRNA expressionFusions

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QIAseq solutions to detect several kinds of biomarkers using NGS59BiomarkersGene expressionCopy number variantsIndelsMutationsmiRNA expressionFusions

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60NGSSummary: NGS can be used for several kinds of biomarkersBiomarkersGene expressionCopy number variantsIndelsMutationsmiRNA expressionFusions

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Adityarup Chakravorty (AC) - Modified title slightlyPlug & play: many flavors, same Sample-to-Insight workflow61Different panels can be plugged into the same targeted NGS workflowSampleInsightDNA panels for variant analysisRNA panels for differential gene expressionRNA panels for fusion gene profilingmiRNome panel for miRNA expressionMutations, indels, copy number variantsGene expression levels

Fusions

miRNA levelsSample isolationLibraryconstruction & targeted enrichmentNGS runData analysisInterpretation

Sample to Insight62BiomarkersGene expressionCopy number variantsIndelsMutationsmiRNA expressionFusionsQIAseq solutions to detect several kinds of biomarkers using NGSQIAseq targeted DNA Panels

QIAseq-targeted RNA PanelsQIAseq miRNA sequencing systemQIAseq-targeted RNAscan Panels

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Healthcare

QIAseq Targeted DNA, RNA and Fusion Gene Panels