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NEXT-GENERATION SEQUENCING (NGS) WORKSHOPNovember 10-11, 2016

Embassy Suites by Hilton Dallas - DFW Airport South

Is NGS for everyone?

Lee Ann Baxter-LoweUniversity of Southern CaliforniaChildren’s Hospital Los Angeles

NEXT-GENERATION SEQUENCING (NGS) WORKSHOPNovember 10-11, 2016

Embassy Suites by Hilton Dallas - DFW Airport SouthCONFLICT OF INTERESTLee Ann Baxter-Lowe, Ph.D.

Clinical Professor

University of Southern California

Los Angeles, CA USA

I have no financial relationships with commercial interests to disclose.

My presentation does not include discussion of off-label or investigational use of drugs.

My presentation includes discussion of investigational laboratory tests.

• Factors to consider in selecting a platform and approach.

• Costs as incentive and barrier

• Strategies for integrating NGS into lab workflow

Is NGS for everyone?

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Is NGS for my lab?• Typing indications

• Typing volume and turn-around-time

• Local environment

• Cost

Clinical Typing: 1, 2, 3, or 4 fields?• BMT

• Today: 2 field • Tomorrow? 3-4 field

• Solid organ transplant – esp defining DSA, virtual crossmatches• Today: 1-2 field • Tomorrow? 2-4 field

• Disease association and pharmacogenetics• Today: 1-2 field • Tomorrow? 3-4 field

The next advance: HLA expression

Petersdorf et al Blood 2014

HLA-C expression levels define permissible mismatches in hematopoietic cell transplantation

GvHDNon-relapse mortality

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More reasons for 3 or 4 fields • Any indication where genetic factors affecting expression could be important

• Research (clinical trials, basic & translational)• More information is better• Competition for funding

Expectations for being state-of-the art• Reference lab• Academia

• Transition to future?• Typing entire MHC• Widespread use of NGS (ID, cancer)

Is NGS for my lab?

• Typing indications

• Typing volume and turn-around-time• Local environment

• NGS users in institution• Access to equipment

• Laboratory staff

• Bioinformatics support• Institutional support

• Alternative typing methods• Costs

Balancing cost and turn-around-time

Run frequency Time /run

CostTAT

Samples/runApproach

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TAT: run frequency is critical factor

Run Frequency

Time/run TAT

2/week 3 days 3-5 working days

2/week 2 days 2-4 working days

Weekly 3 days 3-10 working days

Weekly 2 days 2-9 working days

Every 2 weeks

3 days 17-20 working days

Every 2 weeks

2 days 16-19 working days

Balancing frequency (samples/run) and cost

Samples per run Cost

Calculating Reagent Costs per Sample

Fixed Sample Prep Reagent Cost:

Variable Sequencing Reagent Cost:

Sequencing Reagents Kit ($)

# Samples per sequencing run

Amplification & Library Prep Kit Cost ($)

# Tests per kit

Slide provided by Curt Lind, Thermo Fisher

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Total Reagent Cost per sample decreases in a decreasing amountSample prep cost remains the same however sequencing cost decreases

Slide provided by Curt Lind, Thermo Fisher

Is NGS for my lab?• Typing indications

• Typing volume and turn-around-time

• Local environment

• Cost

Equipment access

• In lab

• Purchase

• Lease• Reagent purchase

• Shared equipment

• Institutional core laboratory

• Send to high volume sequencing facility

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Laboratory staff• Expertise with HLA/molecular biology

• Product and vendor• Robust products minimize need

• Vendor support reduces lab requirements

• NGS eliminates need for expertise to resolve ambiguities

• New challenges (optional?)• Non-coding polymorphism

• Predicting impact of novel sequences• Hands on time

• NGS can be less labor intensive than Sanger seq + ambiguity resolution

IT and bioinformatics support•System set-up

• Server

•Data

• Storage•Management

• Bioinformatics• Predominantly commercial products

Advantages to attract institutional support

• Cost effectiveness

• Importance for• Patient care

• Research• Educational environment

• Compatibility with other areas of laboratory medicine

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NGS is becoming mainstream

•Cancer diagnostics

•Infectious disease

•Genetic diseases

Is NGS for my lab?• Typing indications

• Typing volume and turn-around-time

• Local environment

• Cost

Factors to consider in vendor selection

• Lab’s resources

• Platform

• Performance characteristics

• Practical

• Support

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Factors to consider in evaluating products

Lab’s resources for evaluating products

• Conferences (e.g., ASHI meetings)

• Evaluation options

•On-site vs off-site • Lab’s cost for evaluation of product

•How many vendor evaluations can be supported by lab?

Factors to consider in typing approach

Platform beyond performance

• Institutional availability • Institutional compatibility (backup)• Capacity/cost of the chip/flow cell

• Flexibility (reagent alternatives for platform)

• If purchasing • Cost of purchase/lease and maintenance

• Reagents

Factors to consider in vendor selection

Performance characteristics

•Accuracy

•Failure rate

•Ambiguities

•Gene coverage

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What is an acceptable failure rate?

Run Frequency

AcceptableFailure rate

TAT

2/week Highest 3-5 working days

Weekly Low 3-10 working days

Every 2 weeks

0 17-20 working days

Gene coverage

Gene coverage

Whole Gene Coverage

Exon 1 + Exon 2 to Intron 5

Exon 2 to Exon 4

HLA-A (3.1 kb)1 8765432UTR

UTR

1 65432

UTR

UTR

1 65432UTR

UTR

1 65432UTR

UTR

1 65432UTR

UTR

1 432UTR

UTR

1 65432

UTR

UTR

1 432UTR

UTR

1 5432

UTR

UTR

1 765432UTR

UTR

1 8765432UTR

UTR

HLA-B (3.4 kb)

HLA-C (3.4 kb)

HLA-DRB1 (3.7-4.8 kb)

HLA-DQB1 (3.7-4.1 kb)

HLA-DPB1 (5.0 & 5.7 kb)

HLA-DPA1 (4.7 kb)

HLA-DQA1 (5.4-5.8 kb)

HLA-DRB3 (3.8 kb)

HLA-DRB4 (0.4 & 1.3 kb)

HLA-DRB5 (4.0 kb)

NGSgo-AmpX amplification primer

Amplified exon

GENDX

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Gene coverage

Phasing best with long amplicons

Allele 1Allele 2

AT

GC

Allele 3Allele 4

TA

GC

No phasing with short amplicons if intervening sequence is the identical in both alleles

Phasing possible with long ampliconsA G

Every approach has advantages

Amplicon Length

Long Short

Phasing Best

Base call accuracy Best

PCR efficiency Best

Fragmented DNA Best

Long Short

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Practical factors to consider

• Packaging • Amenable to lab’s run volume• Flexibility for selecting loci

• Cost/sample• Software

• User friendliness• Features • Quality metrics

• Ease of use/robust

• Time/run• Platform constraints• Automation

Factors to consider in vendor selection

Support

•Technical

•Bioinformatics

•Validation

•Sales

The bells and whistles….

• Packaging • Amenable to lab’s run volume• Flexibility for selecting loci

• Cost/sample• Software

• User friendliness• Features • Quality metrics

• Ease of use/robust• Time/run• Platform constraints• Automation

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Fundamental NGS metrics

• Coverage• Depth (number of times a base call is made at a

given position)• Uniformity

• Quality Scores• Phred-like quality scores for each base call• Generated by platform-specific algorithms

Assuring the quality of next-generation sequencing in clinical laboratory practiceGargis et al Nature Biotech 2013

Quality Statistics: Depth of Coverage

EU: RUO, ROW: RUO NGSengine

Quality values (Phred-like scores)

• Historically developed to assess Sanger sequencing accuracy • Used multivariate lookup tables• Accurate across sequencing chemistires and instruments

• Algorithm for QV for NGS are system-specific• All QV scores logarithmically related to probability of base calling error

Q = -10 log10 P

Q Value Probability of Error

Accuracy

10 1 in 10 90%

20 1 in 100 99%

30 1 in 1,000 99.9%

40 1 in 10,000 99.99%

50 1 in 100,000 99.999%

SangerNGS

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Duke et al International Journal of Immunogenetics, 42:346-358, 27 JUN 2015Towards allele‐‐‐‐level human leucocyte antigens genotyping – assessing two next‐‐‐‐generation sequencing platforms: Ion Torrent Personal Genome Machine and Illumina MiSeq

Quality score diminishes with read length

PCR Artifact (PCR crossover, chimeric PCR)

Primer extension, but partial length

DenatureAnneal

Partial length product becomes primer for another allele or locus

Extension

Hybrid molecule

Allele imbalance

• PCR efficiency is influenced by DNA sequence

• Numerous factors can contribute to differences in amplification efficiency– Primer mismatch–Denaturation efficiency• GC content• GC clamp

–Sequences that can disrupt polymerase binding

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Noise

Homozygous2 alleles ~50%

Quality Statistics:

Percentage most frequent base call versus rest

Phasing

Allele 1Allele 2

AT

GC

Allele 3Allele 4

TA

GC

Phased A G

Reads

Not Phased

A

Long readsAccuracy

If exceeds length of all reads, phasing will not

be possible

Duke et al International Journal of Immunogenetics, 42:346-358, 27 JUN 2015Towards allele‐‐‐‐level human leucocyte antigens genotyping – assessing two next‐‐‐‐generation sequencing platforms: Ion Torrent Personal Genome Machine and Illumina MiSeq

Fragment length

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Software filters reads, criteria vary

• Low quality value

•Short reads

• PCR crossover

•No alignment

•Multiple possible alignments

Read usage

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The Traffic Light System

Example of metrics for HLA typing

• Fragment size• Read length• Read quality• Read count• Noise ratio• Exon spot noise ratio• Non-exon spot noise ratio• Exon allele imbalance• Non-exon allele imbalance• PCR crossover artifact ratio• Crossmapping (intergenic ambiguity)• Ambiguous layout (intragenic ambiguity)• Continuous consensus• Fully phased consensus• Consensus coverage exon minimum depth• Consensus coverage non-exon minimum depth• Genotype available• Exon mismatch count• Non-exon mismatch count

Quality Control

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Mappability

Read length

Read depth

Mismatches

Phasing regions# possible genotypesand typing result

EU: RUO, ROW: RUO

Data analysis with NGSengine

50 All content © 2016 Immucor, Inc.

Review WindowData Review

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2

51 All content © 2016 Immucor, Inc.

Review Window 2Identification of Correct Allele

Overall Coverage Plot Correct vs. Incorrect Alleles

Central Coverage Plot Correct vs. Incorrect Alleles

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52 Proprietary & ConfidentialProprietary & ConfidentialProprietary & ConfidentialProprietary & Confidential

Genotype Summary

53 Proprietary & ConfidentialProprietary & ConfidentialProprietary & ConfidentialProprietary & Confidential Health (Quality) Metrics:• Uniformity of Coverage• Allele Balance• Full Key Exon Coverage (<20X)• Exon Mismatches (>0)

Genotype Summary

54 Proprietary & ConfidentialProprietary & ConfidentialProprietary & ConfidentialProprietary & ConfidentialMax Read Depth | Coverage Plot

Genotype Summary

(Min Read Depth >200)

Allele 1Allele 2

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Assign 2.0 Coverage View

Research Use Only. Not for use in diagnostic procedures.

Scisco Genetics GeMS-HLA Software

Summary• All systems automate assignments and allow user to drill down.

• Quality metrics are important for

• Acceptance of automated assignment

• Identify typings for manual interpretation

• Trouble shooting

• Criteria for acceptance should be validated by the laboratory

• Many programs available

• Most quality metrics determined by every program

• Presentation variable

• Important to be knowledgeable about software

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Next Generation Sequencing WorkshopNovember 10-11, 2016

Embassy Suites DFW Airport South