Introduction Methods Results

Translocation detection in lung cancerusing mate-pair sequencing and iVIGS

Richard Meier & Stefan Graw

University of Kansas Medical Center

February 3, 2014

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Content

Introduction

Methods

Results

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Introduction

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Structural variations

No variation

Deletion

Insertion

Translocation

Chromosome 1 Chromosome 17

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Structural variations in mate pair mapping

reference genome

cancer genome

Insertion Deletion

reads map closer than expected reads map farther away than expected

reference genome

cancer genome

reference genome

cancer genome

Translocation

reads map to different chromosomes

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Breakpoint resolution with split reads

Where are the breakpoints ?

known referencecluster cluster

known reference

unknown sample

cluster cluster

reads

Looking at soft clipping reads

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Methods

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Data

A set of mate-pair sequencing data from lung cancer patients was analysed.

35 samples were processed with the sv tool iVIGS

32 samples were processed with the sv tool delly

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Mate-pair preprocessing

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Translocation analysis: general strategy

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Translocation analysis: tools and workflow

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Comparison of the toolsBoth tools

• cluster paired reads to find potential translocation regions• use split reads to find potential breakpoint positions

delly

• re-assembles split reads• re-maps the assembly to the cluster region

iVIGS (tool for identification of variations in genomic structure)

• is developed in our lab and currently still a work in progress• performs Kernel Density Estimation on split read mapping positions• estimates propability distribution of breakpoint positions

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Results

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Effect of iVIGS quality control filteringThe separation distance distribution was similar for all samples

Molina−Dataset

distance between mate−reads

cou

nts

0 1000 2000 3000 4000 5000 6000

0e

+0

01

e+

06

2e

+0

63

e+

06

4e

+0

6 unfilteredfiltered

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Problems with delly

• Applying iVIGS filter resulted in delly not reporting any translocations

• Taking all reads and applying delly internal filtering resulted in findingtranslocations

• Coverage for reads after strict iVIGS filtering was probably tooinconsistent for assembly.The type of used assembly is also important. (see next slides)

• Thus the following results for delly are refering to a workflow that usesthe internal filtering method.

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Selection of breakpoint distributions calculated by iVIGS

27730000 27735000 27740000

0e+0

01e

−04

2e−0

43e

−04

4e−0

4

Kernel Density Estimation

base position

brea

kpoi

ntde

nsity

|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| |||||||||||||||||||||||||||||||||||||||||||||||||||||||| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| |||||||||||||||||||||||||||||| | |||||

135496000 135500000 135504000 135508000

0.00

000.

0005

0.00

100.

0015

Kernel Density Estimation

base positionbr

eakp

oint

dens

ity

| |||||| || | |

33970000 33975000 33980000

0.00

000

0.00

005

0.00

010

0.00

015

Kernel Density Estimation

base position

brea

kpoi

ntde

nsity

| | | || ||| || || | | |||| || | | | || | || || | ||||

121480000 121482000 121484000 121486000 121488000

0e+0

02e

−04

4e−0

46e

−04

8e−0

41e

−03

Kernel Density Estimation

base position

brea

kpoi

ntde

nsity

|||||||||||||||||||| ||||| |||||||||||||||||||||||||||

190194000 190198000 190202000

0.00

000.

0005

0.00

100.

0015

0.00

20

Kernel Density Estimation

base position

brea

kpoi

ntde

nsity

| || | |||||||||| ||||

61792000 61794000 61796000 61798000

0.00

00.

005

0.01

00.

015

0.02

00.

025

0.03

0

Kernel Density Estimation

base position

brea

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nsity

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Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Model of translocation divergence due to cancer proliferation

density

position

active regionschromosomes with highly

breaking and translocation

daughter cellssubsequent variations in

breakpoint and clusterdistribution

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Error sources

• Adapter contamination(before filtering approximately 15% of all reads are contaminated.)

• Ligation errors

• PCR bias

• Sequencing errors

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

General information• Estimated breakpoint positions were highly variable (spanning up toseveral thousand base positions in difference)

• Translocations were found to almost always overlap with potentialdeletion or insertion cluster regions (estimated by iVIGS).

• In most cases around 35 translocations per sample were estimated

20 30 40 50 60 70 80

0.00

0.01

0.02

0.03

0.04

translocation discovery of iVIGS

number of estimated translocations per sample

Den

sity

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Typical translocation distribution observed in samplesCHR1

CHR2

CHR3

CHR4

CHR5

CHR6

CHR7

CHR8

CHR9

CHR10

CHR11

CHR12

CHR13

CHR14

CHR15

CHR16

CHR17

CHR18

CHR19

CHR20

CHR21

CHR22

CHRX

CHRY

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Occuring genes altered by a translocation

Genes used for the diagram were altered in one or more samples

108 15841

delly

iVIGS

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Potential gene fusions

Genes used for the diagram were altered in one or more samples

32 7311

delly

iVIGS

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Potential gene to intergenic fusions

Genes used for the diagram were altered in one or more samples

106 10927

delly

iVIGS

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Reproducibility: delly

Gene alterations

13 21

sample_A1

sample_A2

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Reproducibility: iVIGS

Gene alterations

11 1015

sample_A1

sample_A2

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Conclusion

• Results varied significantly between delly and iVIGS

• Reproducibility of iVIGS seems promising

• It is still unclear how strong the influences of diversity in close relatedcancer cells and library preparation errors are in respect to the results.

• It is thus still difficult to determine whether predictions are FP or TP.

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw

Introduction Methods Results

Plans for the future

• Apply adapter removal in preprocessing to improve mapping yield

• Pick a subset of potential gene fusions and validate them

• Examine other structural variation types (insertions, deletions,inversions)

• Find and use additional sv tools

Translocation detection in lung cancer using mate-pair sequencing and iVIGS Richard Meier & Stefan Graw