Prof. Dr. Walther Parson1,21Institute of Legal Medicine, Innsbruck Medical University, Innsbruck, Austria

2Forensic Science Program, The Pennsylvania State University, PA, USA

Recent Initiatives in Forensic Massively Parallel Sequencing in Europe

7th Investigator Forum • San Antonio, TX, USA • May 03 2018

CSI laboratory (ISO17025)Austrian Central DNA laboratoryEDNAP, ENFSI, Interpol

DVI laboratory (ISO17025)Tsunami (Sri Lanka, 2004), Chile (1973 regime victims)Missing Mexican students (2014)

Forensic molecular research laboratoryMitochondrial DNA QC and databasing (EMPOP)STR QC (STRidER)Population genetics (mito, Y)Predictive Forensic Markers (AIMs, phenotypic)New technologies (MS, RAPID, MPS)

Institute of Legal MedicineMedical University of Innsbruck

Short Tandem Repeats

DNASeqEx - DNA-STR Massive Sequencing & International Information Exchange

2 years (2016-2018)

Beneficiaries:The Biology Service of the National Institute of Toxicology and Forensic Science, Madrid, Spain

Antonio Alonso, Pablo Martin, Pedro Caballero

Department of Forensic Genetics of the Institute of Legal Medicine and Forensics Science, Berlin, GermanyLutz Roewer, Sascha Willuweit, Steffi Köcher

Institute of Legal Medicine, Medical University of Innsbruck, AustriaWalther Parson, Petra Müller, Burkhard Berger, Martin Bodner

Non-Beneficiary:Institute of Applied Genetics at the University of North Texas Health Science Center, Texas, USA

Bruce Budowle

Promote the implementation of MPS technology for improved STR profiling and international data exchange

→ Inter-laboratory evaluation studies

Evaluate the impact of STR sequencing on National DNA databases (EU Prüm) → Alonso et al. 2017 FSIG

Facilitate and standardize forensic STR sequence allele nomenclature → NOMAUT - lead Berlin (pending)

Objectives

Alonso et al. 2017 FSIG

Alonso et al. 2017 FSIG

Kit Supplier LaboratoryEarly Access Applied Biosystems Precision ID Globalfiler Mixture ID™ Panel TFS Madrid, Innsbruck

Early Access Applied Biosystems Precision ID Globalfiler NGS STR Panel for the Ion S5™

TFS Madrid, Innsbruck

PowerSeq aSTR/mito Kit Promega InnsbruckPowerSeq 46GY Kit Promega Innsbruck, BerlinForenSeq DNA Signature Prep Kit Verogen Innsbruck, BerlinNGS Prototype Qiagen Innsbruck, Berlin

Inter-laboratory studies

SEQforSTRsAdditional TestingQiagenPromega aSTR/mitoPromega aSTR/Y-STRs

Concordance ConcordanceSensitivity Sensitivity

Reproducibility ReproducibilityMixturesCasework

BerlinMadrid

Innsbruck

Interlaboratory studies

Köcher, Müller et al, under review

Allele coverage differences (ACD) over all markers with heterozygote alleles and different DNA inputs. Each rectangle represents the average ACD over three replicates for a particular marker.

Globalfiler NGS STR Panel

Müller et al, manuscriptin submission

Interlocus balance varies from 22.3% (D22S1045) to 182.7% (TH01) compared to the expected value (100%)

GMIINTCF

Interlocus BalanceD

2 2S1

0 45

FGA

D1 8

S51

DY S

3 91

AM

E LY

vWA

D1 9

S43 3

D4 S

2 40 8

D2 1

S 11

D3 S

4 52 9

D1 3

S31 7

D2 S

1 33 8

D1 0

S12 4

8D

7 S8 2

0

D1 2

AT A

6 3D

5 S2 8

0 0D

1 S1 6

7 7D

6 S4 7

4D

5 S8 1

8D

1 4S1

4 34

C SF 1

POD

1 S1 6

5 6D

1 2S3

9 1D

6 S1 0

4 3D

2 S4 4

1D

3 S1 3

5 8T P

OX

D8 S

1 17 9

D1 6

S53 9

AM

E LX

TH0 1

0

5 0

1 5 0

2 0 0

2 5 0

e x p e c te d v a lu e

% h

igh

er

% lo

we

r

Re

lati

ve m

ark

er

cove

rag

e (

%)

1 0 0

Globalfiler NGS STR Panel Stutter ratios range from 5.6 % (TH01) to 18.9 % (D12ATA63)

Dataset includes single person samples (1 ng DNA input), homo- and heterozygous genotypes as well as isometric allele calls.

T H0 1

D 4S 2

4 08

D 5S 2

8 00

D 3S 4

5 29

T PO

X

D 2S 4

4 1

D 6S 4

7 4

D YS 3

9 1

D 13 S

3 17

C SF 1

P O

D 7S 8

2 0

D 6S 1

0 43

D 16 S

5 39

D 8S 1

1 79

D 14 S

1 43 4

D 21 S

1 1

D 1S 1

6 77

D 5S 8

1 8

D 3S 1

3 58

D 10 S

1 24 8

vWA

D 19 S

4 33

D 2S 1

3 38

D 1S 1

6 56

D 12 S

3 91

D 18 S

5 1

D 22 S

1 04 5

D 12 A

T A6 3FG

A

0

2 0

4 0

6 0

8 0

1 0 0

Re

lati

ve s

tutt

er

he

igh

t (%

)

GMIINTCF

Stutter Analysis

Müller et al, manuscriptin submission

Sensitivity Study24 PCR cycles, NIST 2372A run in duplicate using Globalfiler NGS STR Panel

Standard PCR conditions display the expected decrease in reads/marker relative to DNA input

Müller et al, manuscriptin submission

5 0 0 p g 2 5 0 p g 1 2 5 p g 6 2 p g

0

2 0 ,0 0 0

4 0 ,0 0 0

6 0 ,0 0 0

G e n o m ic D N A in p u t / a s s a y (p g )

To

tal N

um

be

r o

f R

ea

ds

*

Innsbruck BerlinMadridEA Applied Biosystems Precision

ID Globalfiler NGS STR (Thermo Fisher Sientific)

Ongoing task: population studies

PowerSeq GY46 Kit (Promega) PowerSeq GY46 Kit (Promega)

500 anonymous donors from Spain

250 anonymous donors from Austria

150 anonymous donors from Germany

Alonso et al 2017 FSIG (published)Alonso et al 2018 Electrophoresis(under revision)Köcher, Müller et al 2018 FSIG (under review)Müller et al 2018 FSIG (in submission)

Poster Presentations:

Müller et al ISFG Seoul 2017

Barrio et al ISFG Seoul 2017

former

2001 Collaborative ENFSI DNA WG population study SGMplus (ABI)24 populations, 5700 samples

2003 QC-checked - Gill et al (2003) FSI2004 STRbase V1 (GMI funded)2016 STRidER (EU-funded)

History

https://strider.online/

+ STR Sequence Guide as static ESM with alignment examples

+ revised STR Sequence Guide as dynamic document at STRidER

Audit of GRCh38 reference genome builds released between 2013 - 2017Revised repeat region sequence structure summariesInverted multiple allele Y-STRs, mobility shift SNPs, flank indels, …+ 34 aSTRs (total of 71 aSTRs)+ 22 Y-STRs (total of 47 Y-STRs)

NCBI BioProject—STRseq and STRidERCollaboration in QC and exchange of data

https://strider.online/

52,982 CE profilessubmitted to STRidER for QCsince Aug 2017 + 398 MPS

profiles

2/3 from China

48 datasets submitted for QC

• 10 datasets passed• 4 datasets were retracted by submitter• 2 datasets were rejected by STRidER• remaining datasets in various stages of progress

a single CE dataset without errors detected by STRidER

extreme example: CE dataset (n = 628) containing 40 identical pairs and 4 identical trios

MONOPOLY 2016 - STEFA - WP G7Empowering forensic genetic DNA databases for the interpretation of

next generation sequencing profiles (dna.bases)

STRidER & EmPOP

Jan 2018 - Dec 2019

Sequence alignmentsIncrease sample sizeIncrease markers/regionsFurther develop QC toolsUser-friendly access

Mitochondrial DNA

History1999 Idea and concept for a centrally curated mtDNA database

Inspection of published data - high error rates

2004 Collaborative EDNAP study on quality of mtDNA sequencingParson et al 2004 FSI - 10% error rate - corrective actions

2006 EMPOP V1 (GMI funded) Development of software tools for QC (e.g. QMN, Parson and Dür 2007 FSIG)

2010 EMPOP V2 (GMI funded)Introduction of alignment-free sequence searches (SAM, Röck et al 2011 FSIG)

2015 EMPOP V3 (GMI funded)Haplogrouping, programming update, new features

2018 EMPOP V4 (EU-funded)Updated search engine, alignment tool (SAM2, Huber et al in prep)

New developments

SAM 2Development of software for

automated phylogenetic alignment and consistent nomenclature of mitochondrial DNA sequences

Different mtDNA nomenclature between forensic laboratories (and betweenscientific disciplines)

False exclusions in forensic practice

Mitotypes not directly comparable

Need software to harmonize alignment and nomenclature

SAM2 - Motivation

Alignment can be ambiguous

WAC091

rCRS

16189

16188T 16189Cphylogenetic alignment (Bandelt & Parson 2008)

16188- 16193+CFormal alignment rules (Wilson et al 2002)=Apply Max ParsimonyIndels > Transversions > Transitions3’ Alignment

Phylogenetic ruleAnchor 16189 and 310

3’ Alignment

123

16189x

Consequences of alignment ambiguity

1. Forensic interpretation2. Database searches

Effect of alignment on forensic interpretation*

Exclusion Inconclusive Inclusiontwo or more differences one difference identical (+Het)

16188T 16189Cphylogenetic alignment (Bandelt & Parson 2008)

16188- 16193+CFormal alignment rules (Wilson et al 2002)

3 differences between both haplotypes* Carracedo et al FSI 2000, SWGDAM 2013, Parson et al FSIG 2014

Effect of alignment on database searches

Search method 16188T 16189C 16188- 16193+CrCRS-coded 28 matches 0 matches

EMPOP V3 R11; N = 34,617

Alignment-free searches in EMPOP

Alignment-free sequence queries guarantee that a haplotype is not missed in a database search

SAM on EMPOP since V2.0 (04/2010)

Solving the database issue

SAM on EMPOP since V2.0 (04/2010)

Search method 16188T 16189C 16188- 16193+CrCRS-coded 28 matches 0 matches

EMPOP V3 R11; N = 34,617

Search method 16188T 16189C 16188- 16193+CSAM 28 matches 28 matches

EMPOP V3 R11; N = 34,617

But …..

alignment problem not yet addressed

we need softwareto solve the issue

AlignmentTTCTTTCATGGGGAAGCAGATTTGGGTACCACCCAAGTATTGACTCACCCATCAACAACCGCTATGTATTTCGTACATTACTGCCAGCCACCATGAATATTGTACGGTACCATAAATACTTGACCACCTGTAGTACATAAAAACCCAATCCACATCAAAACCCCCCCCCCCATGCTTACAAGCAAGTACAGCAATCAACCCTCAACTATCACACATCAACTGCAACTCCAAAGCCACCCCTCACCCACTAGGATACCAACAAACCTACCCACCCTTAACAGTACATAGTACATAAAGCCATTTACCGTACATAGCACATTACAGTCAAATCCCCTCTCGCCCCCATGGATGACCCCCCTCAGATAGGGGTCCCTTGACCACCATCCTCCGTGAAATCAATATCCCGCACAAGAGTGCTACTCTCCTCGCTCCGGGCCCATAACACTTGGGGGTAGCTAAAGTGAACTGTATCCGACATCTGGTTCCTACTTCAGGGCCATAAAGCCTAAATAGCCCACACGTTCCCCTTAAATAAGACATCACGATGGATCACAGGTCTATCACCCTATTAACCACTCACGGGAGCTCTCCATGCATTTGGTATTTTCGTCTGGGGGGTATGCACGCGATAGCATTGCGAGACGCTGGAGCCGGAGCACCCTATGTCGCAGTATCTGTCTTTGATTCCTGCCTCATCCTATTATTTATCGCACCTACGTTCAATATTACAGGCGAACATACTTACTAAAGTGTGTTAATTAATTAATGCTTGTAGGACATRATAATAACAATTGAATGTCTGCACAGCCGCTTTCCACACAGACATCATAACAAAAAATTTCCACCAAACCCCCCCTCCCCCCGCTTCTGGCCACAGCACTTAAACACATCTCTGCCAAACCCCAAAAACAAAGAACCCTAACACCAGCCTAACCAGATTTCAAATTTTATCTTTTGGCGGTATGCACTTTTAACAGTCACCCCCCAACTAACACATTATTTTCCCCTCCCACTCCCATACTACTAATCTCATCAATACAACCCCCGCCCATCCTACCCAGCACACACNN--CGCTGCTAACCCCATACCCCGAACCAACCAAACCCCAAAGACACCCCCCCCACA

16024

576

16181C 16182C 16183C 16189C 16213A 16217C 16242T 16261T 16292T 16301T 16519C61A 62A 73G 183G 263G 309.1C 309.2C 309.3C 315.1C 323N 324N 523Del 524Del

953,110(24+1 mutations)

16181C 16182C 16183C 16189C 16213A 16217C 16242T 16261T 16292T 16301T 16519C61A 62A 73G 183G 263G 308.1C 309.1C 309.2C 315.1C 323N 324N 523Del 524Del

Code programming is accomplished

Internal and external testing is accomplished

Manuscript in preparation

Adaptation of EMPOP in preparation

SAM2 - Progress

SAM2 - Alignment changes

0.52%

Huber et al in prep

Meetings 2017/2018

SAM2 - SWGDAM Meeting, Fredericksburg, VA, Jan 2017EMPOP workshop - GEDNAP Meeting, Giessen, Germany, Feb 2017EMPOP-QC/SAM2 - mitoDB meeting, MPI Jena, Germany, Feb 2017EMPOP-Update - EDNAP, Vilnius, Lithuania, Apr 2017 EMPOP workshop - Rio de Janeiro, Brazil, May 2017EMPOP-QC/SAM2 - Genome Variants, Santiago de Compostela, Spain, Jun 2017 EMPOP workshop - ISFG World Conference, Seoul, South Korea, Aug 2017EMPOP training - NFI, The Hague, Netherlands, Sep 2017EMPOP-Update - EDNAP, Athens, Greece, Oct 2017

SAM2 - SWGDAM Meeting, Woodbridge, VA, Jan 2018EMPOP training - HSA, Singapore, Jan 2018EMPOP QC - Monopoly 16 project dna.bases, Innsbruck, Austria, Jan 2018EMPOP workshop - GEDNAP Meeting, Basel, Switzerland, Feb 201811th Haploid Marker Meeting, Bydgoszcz, Poland, May 2018

EMPOP training HSA Singapore

11th Haploid Markers Meeting, May 17-19 2018

‘Inferring Ancestry from DNA’Invited speakersChristopher PhillipsMark JoblingChris-Tyler Smith

44 oral presentations64 posters

Bydgoszcz [ˈbɨdgɔʃʧ] ‘bid’ ‘gosh’

https://de.wikipedia.org/wiki/Liste_der_IPA-Zeichen

Forensic DNA Phenotyping

STR typing

appearanceancestry

age

Phenotypic markers

Cases without database match

Composite Sketch

Kayser et al AJHG 2008

Forensic DNA Phenotyping

Kayser et al FSIG 2015

OCA2/HERC2

Slide kindly provided by C. Phillips, USC Spain

Ancestry Informative DNA Markers

Eduardoff et al FSIG (2015)

Ancestry Informative DNA Markers

Age estimation

2012

Forensic application of MethAge estimation

Zbiec-Piekarska et al FSIG 2015

Freire-Aradas et al FSR 2017 Vidaki and Kayser Gen Biol 2018

Manfred Kayser (Coordinator) Rotterdam, NEDWojciech Branicki Krakow, POLChris Phillips, Angel Carracedo S. de Compostela, ESPWalther Parson Innsbruck, AUTMichael Nothnagel Cologne, GERBarbara Prainsack Vienna, ATPeter M. Schneider Cologne, GERIngo Bastisch Wiesbaden, GERFrançois-Xavier Laurent Lyon, FRATitia Sijen The Hague, NEDJohannes Hedman Linkoping, SWEShazia Khan London, UKMagdalena Spólnicka Warsaw, POL

www.visage-h2020.eu

05/2017 - 04/2021

This project received funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 740580

VISAGE – Main Goals

1) Known markers + explore new markers on appearance, age and ancestry

2) Design, develop and validate prototype tools

3) Design interpretation software considering combined stats of all information

4) Identify ethical issues and make recommendations

5) Implement in routine casework

6) Training and dissemination

Tool development in VISAGETe

chni

cal R

eadi

ness

Leve

l Basic Research

Final Product

1

10

5

The VISAGE - Consortium is developing genotypingand statistical prototype tools, forensically validateand implement them into forensic practice forpredicting appearance, age, and ancestry from DNAtraces and study its ethical, societal & regulatorydimensions (period: 05/2017-04/2021).Tool 1: Appearance & Ancestry (SNP multiplex)Tool 2: Age (quantitative methylation)

Multiplex design/optimization Check with Final evaluationPrimer design

StructureDimer formationNo of primer poolsReaction conditionsEfficiencySensitivity

Primer design / PCR optimization

Multiplex PCR

target DNAgenomic DNA

Library Prep

Sequencing

libraries

Multiplex design/optimization

primer poolshow many reactions

optimize PCR

Adapt to different library

prep commercial products

How many samples per chipOverall performance

Coverage requirements

Ancestry & Appearance Tool

SNP multiplex optimization*Coverage

1 ng 2 ng

1 ng

2ng

* 217 gAIMs (C. Phillips, USC), 2800M (Promega), Ion S5, 530 V1, DL8 AmpliSeq (TFS)

norm

alize

d co

vera

ge

p < 0.001 D=0.13364, p < 0.05

SNP multiplex optimization*Strand bias

* 217 gAIMs (C. Phillips, USC), 1 ng 2800M (Promega), 16 replicates, Ion S5, 530 V1, DL8 AmpliSeq (TFS)

Mean = 0.497 SNPs > mean - 114 SNPs 0.55 – 26 (~12%)

SNP multiplex optimization*Base misincorporation

* 217 gAIMs (C. Phillips, USC), 1 ng 2800M (Promega), 16 replicates, Ion S5, 530 V1, DL8 AmpliSeq (TFS)

% Mean total misinc. = 0.175% SNPs > mean - 55 (~25.3%)31 alt. allele base8 random bases6 alt. and random bases

SNP multiplex optimization*Baseline noise

* 217 gAIMs (C. Phillips, USC), 14 neg cons, Ion S5, 530 V1, DL8 AmpliSeq (TFS)

Mean in all SNPs = 1.56 reads SNPs < mean - 178 (~82%)5 SNPs > 10 reads2 SNPs > 20 reads ratio described allele/random base = 0.99

SNP multiplex optimization*Sensitivity

* 217 gAIMs (C. Phillips, USC), 2800M (Promega), Ion S5, 530 V1, DL8 AmpliSeq (TFS)

50 p

g

Multiplex PCR

genomic DNA

target DNA

Library Prep Sequencing

Bissulfiteconversion

https://www.gatc-biotech.com

Age estimation by quantitative methylation

MethAge tool

Test different bisulfite conversion kitsTest primer pairs in singleplexOptimize PCR temperature conditions

Multiplex all primers and sequenceTest alternative primer pairsAdjust PCR protocolAdjust primer concentrationTest PCR enhancers

MethAge toolConversion time

5 bisulfite conversion kits

MethAge toolEfficiency of bisulfite conversion

Kit 1 Kit 2 Kit 3 Kit 4 Kit 5

PCR MM 1

PCR MM 2

Bisulfite conversion kits

200 ng input

MethAge toolEfficiency of bisulfite conversion

Kit 1

Bisulfite conversion kits

Kit 2 Kit 3 Kit 4 Kit 5

100 ng input

PCR MM 1PCR MM 2

Kit 1 Kit 2 Kit 3 Kit 4 Kit 5 Kit 1 Kit 2 Kit 3 Kit 4 Kit 5

50 ng input 10 ng input

MethAge toolMultiplex PCR - 5 amplicons

200 ng input DNA, ca. 15 ng bisulfite converted DNA for MP-PCR, sequence-verified

MethAge toolMultiplex PCR optimization - 4 amplicons

200 ng input DNA, ca. 15 ng bisulfite converted DNA for PCR, sequence-verified

MethAge toolMultiplex PCR optimization - 4 amplicons

200 ng input DNA, ca. 15 ng bisulfite converted DNA for PCR, sequence-verified

M 1 M 2 M 4 M 5

MethAge toolOptimized PCR multiplex - 4 amplicons

200 ng input DNA, ca. 15 ng bisulfite converted DNA for PCR, sequence-verified

M 1 M 2 M 4 M 5 M 1 M 3 M 4 M 5

MethAge toolEnhancer test - 4 amplicons

200 ng input DNA, ca. 15 ng bisulfite converted DNA for PCR, sequence-verified

M 1 M 2 M 4 M 5 M 1 M 3 M 4 M 5

Acknowledgements

FP7-SEC-2011-285487

Translational Research project L397 EMPOP–an innovative human mtDNA database

2011-MU-MU-K402

Maximizing mtDNA Testing Potential with the Generation of High-Quality mtGenome Reference Data

Richard ScheithauerBurkhard Berger Harald NiederstätterCordula Berger Lisa SchnallerMartin Bodner Christina StroblMayra Eduardoff Catarina XavierGabriela HuberNicole HuberPetra Müller

Research project P22880-B12Genetic discovery of an early medieval Alpine population

Home/2014/ISFP/AG/LAWX/4000007135

DNA-STR Massive Sequencing & International Information Exchange

740580Visual Attributes Through Genomics

Monopoly 2016, STEFA, 779485Steps Towards a European Forensic Science Area; WP7; Empowering Forensic Genetic DNA Databases for the Interpretation of Next Generation Sequencing Profiles (dna.bases)

ISFG Commission on MPS of STRsISFG Commission on STRidER

ENFSI laboratories

Peter Gill Christina StroblIngo Bastisch Nicole HuberDavid Ballard Arne DürChris Phillips Harald NiederstätterKatherine Gettings Burkhard BergerJonathan King Petra MüllerMartin Bodner Lisa SchnallerCatarina Xavier Mayra EduardoffAntonia HeideggerMaria de la Puente

Acknowledgements

THANK YOU!!!

Slide Number 1Slide Number 2Slide Number 3Slide Number 4Slide Number 5Slide Number 6Slide Number 7Slide Number 8Slide Number 9Slide Number 10Slide Number 11Slide Number 12Slide Number 13Slide Number 14Slide Number 15Slide Number 16Slide Number 17Slide Number 18Slide Number 19Slide Number 20Slide Number 21Slide Number 22Slide Number 23Slide Number 24NCBI BioProject—STRseq and STRidER�Collaboration in QC and exchange of dataSlide Number 26Slide Number 27Slide Number 28Slide Number 29Slide Number 30Slide Number 31MONOPOLY 2016 - STEFA - WP G7�Empowering forensic genetic DNA databases for the interpretation of �next generation sequencing profiles (dna.bases) Slide Number 33Slide Number 34Slide Number 35Slide Number 36Slide Number 37Slide Number 38Slide Number 39Slide Number 40Slide Number 41Slide Number 42Slide Number 43Slide Number 44Slide Number 45Slide Number 46Slide Number 47Slide Number 48Slide Number 49Slide Number 50Slide Number 51Cases without database matchForensic DNA PhenotypingAncestry Informative DNA MarkersAncestry Informative DNA MarkersAge estimationForensic application of MethAge estimationSlide Number 58Slide Number 59VISAGE – Main GoalsTool development in VISAGEPrimer design / PCR optimizationAncestry & Appearance ToolSNP multiplex optimization*�CoverageSNP multiplex optimization*�Strand biasSNP multiplex optimization*�Base misincorporationSNP multiplex optimization*�Baseline noiseSNP multiplex optimization*�SensitivityAge estimation by quantitative methylationMethAge toolMethAge tool�Conversion timeMethAge tool�Efficiency of bisulfite conversionMethAge tool�Efficiency of bisulfite conversionMethAge tool�Multiplex PCR - 5 ampliconsMethAge tool�Multiplex PCR optimization - 4 ampliconsMethAge tool�Multiplex PCR optimization - 4 ampliconsMethAge tool�Optimized PCR multiplex - 4 ampliconsMethAge tool�Enhancer test - 4 ampliconsSlide Number 79Slide Number 80Slide Number 81