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Center for Clinical Genomics and
Personalized Medicine

2014

Bálint L. Bálint MD, PhD
Head of Laboratory
Center for Clinical Genomics and Personalized Medicine
IVDI Building 3-d floor
http://genomics.med.unideb.hu
Our Team
Our Infrastructure
Biobanking

Microarays

NG-Sequencing

Bioinformatics
Students coming from
Medical Centre service area

1.45 hours
Facts about the University of
Debrecen
 33000

students

 Teaching
 More

in Hungarian and English

than 1500 faculty members

 15

branches

 21

Doctoral Schools

 15%

of Hungarian RnD is located here
Brief overview of the region:
Underdeveloped region with large Regional Developmental Funds
University City with long history
Medical Centre that serves 2 mil people
Pharmapolis Cluster:
TEVA (Biogal)
Richter Gedeon new Pharma Plant for Biological drugs (recombinant proteins and
antibodies)
Cell Therapy Unit (already performing clinical studies)
Stem Cell Research Unit (starts 2010)
RCMM twinning with EMBL
Several EMBO members locally
Personalized Health Care Unit (from 2011)
Well organized Medical Centre open to patients from foreign countries
SAP and ISO implementation at the Medical Centre level
Our vision is to channel the advances in
genomics towards medical research for the
benefit of the patients in the form of
Personalized Medicine
Goals:
 Leader

in the Personalized Medicine in the region

 Implementation

of novel research tools for the benefit
of the patients through clinical research

 Take

the opportunity of the regional grants and use
them to develop tools that can be used on a global
scale

 Taking

care of every spent pence in a very
conservative way
Activities to implement our Goals:
 Activities


in two directions:

Clinical Research





Common projects with clinicians
Infrastructure for clinical research

Regional training


From PCR oligo design through Study design till Data analysis



Global gene expression and functional genomics, Epigenetics

01/22/14

11
Activities in the field of Clinical Research:
 Genomics
 National

Genomics Technological Platform

 Biomarker

discovery and Biobanking



Partners: Pfizer, Astra Zeneca, Richter Gedeon, Biosystems International,
Roche Hungary



Biobanking: COPD, Schizophrenia, Lung cancer, Leukemias
Tools for Biomarker discovery: UPL based miRNA measurement
(Roche Hungary and Astrid Research)



 Epigenetics



Partners: Diagenode Belgium and Millipore USA
Areas: developing of standards for epigenetic studies and protocols for
HTS and clinical research in the field of epigenetics

01/22/14

12
Coordinated from the University of Debrecen:
1. Genomic Research for Human Health Consortium
(GRHH) 2002-2008- FP6 (www.humangenom.hu)
2. National Genomic Technological Platform (NGTP) 2009-2011National Grant

www.genomika.net
Core facility:
 Implementation

of novel technologies require expensive infrastructure

 Expensive

infrastructure can be best used if shared by several
research groups and operated by dedicated staff

 Without

streets

knowledge dissemination core facilities are like dead end
Detailed Infrastructure
 Laboratories
 Biobank

depositories

 Offices
 QPCR

Instruments

 QPCR

assays (hundreds)

 Capillary
 Deep

sequencer (4 chanell ABI)

Sequencing System (Illumina HiScan SQ)

 Pipetting

robots (4)

 Microarray
 DNA/RNA

systems (1)

QC instruments (Agilent Bioanalyzer, Nanodrop, Qubit)
Relevant output

Lifecycles of technologies
Additional
developments

Original
innovation

Distinctive technology / development phase/
time
Both instrument and reagent costs are high
Peak technology / penetretion phase/
Instrument price is high, reagent price is decreasing
Basic technology / spreading phase/
Both instrument and reagent costs are rapidly decreasing
Based on: „Pataki Béla: Technológia menedzsment”
Relevant output

Lifecycles of technologies

Distinctive technology / development phase/
time
Both instrument and reagent costs are high
Peak technology / penetretion phase/
Instrument price is high, reagent price is decreasing
Basic technology / spreading phase/
Both instrument and reagent costs are rapidly decreasing
Based on: „Pataki Béla: Technológia menedzsment”
L ab
RE
CO

Sequencing and
genomics unit

Epigenetic unit
b
D La
Rn

Se

b
e La
rvic

Biobanking unit

Protein and cell
engeneereing unit
b
D La
Rn
Sequencing and genomics unit

Instruments:
•Capillary sequencer
•Affymetrix
•Illumina NGS
•Server system

La b
RE
CO

Wet lab people:
Post docs:

•Beata Scholtz
•Szilárd Póliska

Technicians:

•Sipos Lilla
•Erzsébet Mátyás

Bioinformatics support team:
Endre Barta (leader)
Attila Horvath (system administrator)
Laszlo Steiner (biomathematics and bio statistics)
Gergely Nagy (bioinformatics)
NGS Sequencing
Illumina Sequencing System HiScan SQ-

Szilárd Póliska
Automatic Chromatin IP for maximal
reproducibility

Diagenode IP-Star Magnetic ChIP
Affymetrix Systems
GeneChip® 3000 platform

•

•

Hybridisation Oven

Delivers precise
temperature control
during hybridization

• Fluidics stations
• Washing and staining
of hybridized target
probe complexes

• Scanner
• High resolution
scanner for fast
image acquisition
• Autoloader
including barcode
reader for sample
tracking
Bioinformatics

Endre Barta
NGS software installed on ngsdeb
Programs used for ChIP-seq,
GRO-seq and RNA-seq analysis
•

HOMER

•

SAMTOOLS

•

BOWTIE

•

ChIPSEEQER

•

BEDTOOLS

•

BAMTOOLS

•

TOPHAT

•

TRINITYRNASEQ

•

BWA

•

MEME

•

MACS

•

FASTX-TOOLKIT

•

PICARD

25

Head Node: 2x6 core, 144GB RAM, 20 Tbyte disk
6x computing nodes: 2x6 core, 48GB RAM 600GB
disk
2012.05.16.
ChIP-seq analyze script
•

Aim: To have a simple script that can be used either to analyze local
ChIP-seq sequencing data or to do meta-analysis of ChIP-seq
experiments stored on the NCBI SRA database

•

Command line tool

•

Input: SRA (NCBI reads), fastq (reads), bam (alignments)
•
•
•
•
•
•
•

Downloads SRA format files NCBI
Maps fastq format reads
Peak calling by HOMER and MACS
Peak annotation by HOMER
Known and denovo motif finding by HOMER
GO enrichment analysis by HOMER
Generates bedgraph and bed files for visualization

Barta E
Command line analysis of ChIP-seq results.
EMBNET JOURNAL 17:(1) pp. 13-17. (2011)
UPL based miRNS detection system

Czimmerer Zsolt

Astrid
Research

http://genomics.dote.hu:8080/mirnadesigntool/
High sensitivity e.g on hsa-mir-181 miRNA gen
family
Hsa-mir-181a:
AACAUUCAACGCUGUCGGUGAGU

Hsa-mir-181b:
AACAUUCAUUGCUGUCGGUGGGU

Hsa-mir-181c:
AACAUUCAAC*CUGUCGGUGAGU

http://genomics.dote.hu:8080/mirnadesigntool/
More info:
Balint L. Balint , Head of
Laboratory

Lbalint@med.unideb.hu
http://genomics.med.unideb.hu

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Center for Clinical Genomics and Personalized Medicine, Hungary

  • 1. Center for Clinical Genomics and Personalized Medicine 2014 Bálint L. Bálint MD, PhD Head of Laboratory
  • 2. Center for Clinical Genomics and Personalized Medicine IVDI Building 3-d floor
  • 6. Students coming from Medical Centre service area 1.45 hours
  • 7. Facts about the University of Debrecen  33000 students  Teaching  More in Hungarian and English than 1500 faculty members  15 branches  21 Doctoral Schools  15% of Hungarian RnD is located here
  • 8. Brief overview of the region: Underdeveloped region with large Regional Developmental Funds University City with long history Medical Centre that serves 2 mil people Pharmapolis Cluster: TEVA (Biogal) Richter Gedeon new Pharma Plant for Biological drugs (recombinant proteins and antibodies) Cell Therapy Unit (already performing clinical studies) Stem Cell Research Unit (starts 2010) RCMM twinning with EMBL Several EMBO members locally Personalized Health Care Unit (from 2011) Well organized Medical Centre open to patients from foreign countries SAP and ISO implementation at the Medical Centre level
  • 9. Our vision is to channel the advances in genomics towards medical research for the benefit of the patients in the form of Personalized Medicine
  • 10. Goals:  Leader in the Personalized Medicine in the region  Implementation of novel research tools for the benefit of the patients through clinical research  Take the opportunity of the regional grants and use them to develop tools that can be used on a global scale  Taking care of every spent pence in a very conservative way
  • 11. Activities to implement our Goals:  Activities  in two directions: Clinical Research    Common projects with clinicians Infrastructure for clinical research Regional training  From PCR oligo design through Study design till Data analysis  Global gene expression and functional genomics, Epigenetics 01/22/14 11
  • 12. Activities in the field of Clinical Research:  Genomics  National Genomics Technological Platform  Biomarker discovery and Biobanking  Partners: Pfizer, Astra Zeneca, Richter Gedeon, Biosystems International, Roche Hungary  Biobanking: COPD, Schizophrenia, Lung cancer, Leukemias Tools for Biomarker discovery: UPL based miRNA measurement (Roche Hungary and Astrid Research)   Epigenetics   Partners: Diagenode Belgium and Millipore USA Areas: developing of standards for epigenetic studies and protocols for HTS and clinical research in the field of epigenetics 01/22/14 12
  • 13. Coordinated from the University of Debrecen: 1. Genomic Research for Human Health Consortium (GRHH) 2002-2008- FP6 (www.humangenom.hu) 2. National Genomic Technological Platform (NGTP) 2009-2011National Grant www.genomika.net
  • 14. Core facility:  Implementation of novel technologies require expensive infrastructure  Expensive infrastructure can be best used if shared by several research groups and operated by dedicated staff  Without streets knowledge dissemination core facilities are like dead end
  • 15. Detailed Infrastructure  Laboratories  Biobank depositories  Offices  QPCR Instruments  QPCR assays (hundreds)  Capillary  Deep sequencer (4 chanell ABI) Sequencing System (Illumina HiScan SQ)  Pipetting robots (4)  Microarray  DNA/RNA systems (1) QC instruments (Agilent Bioanalyzer, Nanodrop, Qubit)
  • 16. Relevant output Lifecycles of technologies Additional developments Original innovation Distinctive technology / development phase/ time Both instrument and reagent costs are high Peak technology / penetretion phase/ Instrument price is high, reagent price is decreasing Basic technology / spreading phase/ Both instrument and reagent costs are rapidly decreasing Based on: „Pataki Béla: Technológia menedzsment”
  • 17. Relevant output Lifecycles of technologies Distinctive technology / development phase/ time Both instrument and reagent costs are high Peak technology / penetretion phase/ Instrument price is high, reagent price is decreasing Basic technology / spreading phase/ Both instrument and reagent costs are rapidly decreasing Based on: „Pataki Béla: Technológia menedzsment”
  • 18. L ab RE CO Sequencing and genomics unit Epigenetic unit b D La Rn Se b e La rvic Biobanking unit Protein and cell engeneereing unit b D La Rn
  • 19. Sequencing and genomics unit Instruments: •Capillary sequencer •Affymetrix •Illumina NGS •Server system La b RE CO Wet lab people: Post docs: •Beata Scholtz •Szilárd Póliska Technicians: •Sipos Lilla •Erzsébet Mátyás Bioinformatics support team: Endre Barta (leader) Attila Horvath (system administrator) Laszlo Steiner (biomathematics and bio statistics) Gergely Nagy (bioinformatics)
  • 20. NGS Sequencing Illumina Sequencing System HiScan SQ- Szilárd Póliska
  • 21. Automatic Chromatin IP for maximal reproducibility Diagenode IP-Star Magnetic ChIP
  • 23. GeneChip® 3000 platform • • Hybridisation Oven Delivers precise temperature control during hybridization • Fluidics stations • Washing and staining of hybridized target probe complexes • Scanner • High resolution scanner for fast image acquisition • Autoloader including barcode reader for sample tracking
  • 25. NGS software installed on ngsdeb Programs used for ChIP-seq, GRO-seq and RNA-seq analysis • HOMER • SAMTOOLS • BOWTIE • ChIPSEEQER • BEDTOOLS • BAMTOOLS • TOPHAT • TRINITYRNASEQ • BWA • MEME • MACS • FASTX-TOOLKIT • PICARD 25 Head Node: 2x6 core, 144GB RAM, 20 Tbyte disk 6x computing nodes: 2x6 core, 48GB RAM 600GB disk 2012.05.16.
  • 26. ChIP-seq analyze script • Aim: To have a simple script that can be used either to analyze local ChIP-seq sequencing data or to do meta-analysis of ChIP-seq experiments stored on the NCBI SRA database • Command line tool • Input: SRA (NCBI reads), fastq (reads), bam (alignments) • • • • • • • Downloads SRA format files NCBI Maps fastq format reads Peak calling by HOMER and MACS Peak annotation by HOMER Known and denovo motif finding by HOMER GO enrichment analysis by HOMER Generates bedgraph and bed files for visualization Barta E Command line analysis of ChIP-seq results. EMBNET JOURNAL 17:(1) pp. 13-17. (2011)
  • 27. UPL based miRNS detection system Czimmerer Zsolt Astrid Research http://genomics.dote.hu:8080/mirnadesigntool/
  • 28. High sensitivity e.g on hsa-mir-181 miRNA gen family Hsa-mir-181a: AACAUUCAACGCUGUCGGUGAGU Hsa-mir-181b: AACAUUCAUUGCUGUCGGUGGGU Hsa-mir-181c: AACAUUCAAC*CUGUCGGUGAGU http://genomics.dote.hu:8080/mirnadesigntool/
  • 29. More info: Balint L. Balint , Head of Laboratory Lbalint@med.unideb.hu http://genomics.med.unideb.hu

Notes de l'éditeur

  1. The „Standard“ System - every Affymetrix lab in the world uses the same instruments, with the same protocols => standardization of results, easy to compare - point out Fluidics Station is integral component: important for reduction of variability. Competitors dont have their own FS.