The document provides information about a short course on next generation sequencing and analysis of sequence variants. It includes an agenda with sessions on introduction to NGS applications in medical research, data analysis pipelines, interpretation of variants, and tools for predicting pathogenicity. It also provides background on the organizing institutions, the CNAG sequencing center and its projects, and an overview of bioinformatics analysis pipelines and resources.

1. presentation tilte
Text specific for subtitle
19.07.2010
Centro Nacional de Análisis Genómico
Introduction to Meeting
NGS and the molecular basis of
disease: a practical view.
Vall d’Hebron
Barcelona
Ivo Glynne Gut
11.02.2015

2. 11th and 18th February 2015
Identification and analysis of sequence variants in
sequencing projects: fundamentals and tools
Short Course organised by the CNAG and VHIR
Sessions:
- Introduction to applications of next generation
sequencing to medical research
- Data analysis pipelines for NGS applications
- Interpretation of sequence variants in the biomedical
environment: what should we take into account
- Variant calling and somatic mutation identification and
prioritization on NGS data: an advanced overview
- Using and combining the different tools for predicting
the pathogenicity of sequence variants (PolyPhen,
SIFT, etc)

3. Overview of the Series
NGS and the molecular
basis of disease: a
practical view.
Ivo Gut, CNAG
Data analysis pipelines
for NGS applications
Sergi Beltran, CNAG
Interpretation of
sequence variants in
the clinical setting.
Xavier de la Cruz, VHIR
SESSION 1 (2h): FUNDAMENTALS
11. February 2015, 15:00-17:00
Data analysis pipelines
for NGS applications
Sophia Derdak, CNAG
Interpretation:
processing the output
of bioinformatics tools.
Casandra Riera, VHIR
SESSION 2 (2h): TOOLS
18. February 2015, 15:00-17:00

4. CNAG
The CNAG is a non-profit organization created on 2010 and integrated in the
Barcelona Science Park. It is funded by the Spanish Ministry of Economy and
Competitiveness and the Catalan Government through the Economy and
Knowledge Department and the Health Department (30M € initial funding, 2010-
2012). Competitive grants and contractual research with the private sector
provide additional funds.
Our Mission
To carry out large-scale projects in genome analysis that will lead to significant
improvements in people’s health and quality of life, in collaboration with the Catalan,
Spanish, European and International research and clinical community.
Our Vision
To be a large-scale, high quality sequence analysis center and to be a world reference
center for genomic analysis.

5. Director
Ivo Gut
1
Sequencing Department
Marta Gut
1
Biorepository (1)
Sample Preparation
(9)
Sequencing
Production (4)
Laboratory Support (3)
Single Cell
Genomics(2)
Bioinformatics Analysis
Sergi Beltran
1
Production
Bioinformatics (3)
Data Analysis (7)
Bioinformatics
Support (2)
Bioinformatics Development
Simon Heath
1
Statistical Genomics
(7)
Algorithm
Development (4)
Genome Biology
Marc Marti-Renom
1
Structural
Genomics (9)
Comparative
Genomics (1)
Applied Genomics
Ivo Gut
Biomedical
Genomics (4)
Genome Assembly
and Annotation (3)
Population
Genomics (1)
Programme
Manager
Mònica Bayés
2
Administrative
Support
3
Production Teams
ResearchTeams
CNAG Organigram
64 people 1 ICREA Research Professor
28 people funded or co-funded with personnel
grants or competitive projects

6. ICTS
The CNAG becomes part of the National Scientific and Technological Infrastructure Map (ICTS):
- Integrated Infrastructure for OMICS :
- Plataforma de Metabolómica del Centro de Ciencias Ómicas (COS, Lluis Arola).
- Centro Nacional de Análisis Genómico (CNAG, Ivo Gut)
- Requires >20% of competitive access. Since 2014 researchers with large scale projects are
required to submit an application that is reviewed by the Access Committee (constituted by CNAG
director, Elías Campo, Pere Puigdoménech and Ángel Carracedo).

7. The genomehenge
Sequencing capacity
• >1000 Gbases/day = 9-10 human genomes per day
at 30x coverage
Equipment
• 11 Illumina HiSeq2000/2500/1T
• 1 Illumina MiSeq
• 4 Illumina cBots
• 2 Oxford Nanopore Minions
• Caliper/Eppendorf liquid handling robotics
• Bull 1200 core cluster super computer
• Maxeler Data Flow Engine
• 25 Tflops
• 2.7 petabyte disc space
• Barcelona Supercomputing Center (10 x 10 Gb/s)

8. How we work – Our process
Biological
Resources
Sequencing Informatics
- Reception
- Quality control
- Conditioning
- Storage
- Sample Preparation
- Sequencing Production
- Methods Development
o Bioinformatic Analysis
o Bioinformatic Development
o Genome Biology
o Applied Genomics
LIMS + QC

9. BIOREPOSITORY LABORATORY SEQUENCING
QCANALYSISTRANSFER
LIMS
CNAG Workflow ISO9001

10. Sample preparation pipeline
Whole genome shotgun sequencing
no PCR, low input, FFPE, single cell
Whole exome capture sequencing
low input, FFPE
Custom capture sequencing
Amplicon sequencing
Genotyping-by-sequencing
RNA sequencing
polyA selection, Ribo Zero selection, directional,
low input, single cell
Whole genome bisulphite sequencing
regular and low input

14. Informatics Resources
Production Bioinformatics
• Primary run analysis and verification
• QC systems and LIMS
Analysis Production
• Alignment, variant calling and annotation
• Analysis and interpretation
Statistical Genomics
• DNA methylation pipeline
• RNA analysis pipeline
de novo Assembly and Annotation
• Pipeline for de novo assembly
• Pipeline for genome annotation
Algorithm Development
• Development and improvement of alignment and assembly methods - GEM
• Data compression
Structural Genomics
• Modelling of 3-d structure of genomes - HiC analysis
Comparative Genomics
Biomedical Genomics
• Advanced data mining
Population Genomics
Databases
• Storage and distribution of data

15. Variant Calling
Identification of genetic differences in comparison to a reference
(strict definition)
- Designs: Pedigree, trio, group, somatic

16. Variant analysis example: stepwise filtering
VCF
Filtering parameters
dbSNP
dbCNAG
Inheritance model
Functional annotation
Pedigree Multiple samples Somatic detection
Shared vs non-shared Fisher test allele counts

17. Variant analysis example: stepwise filtering
VCF
Filtering parameters
dbSNP
dbCNAG
Inheritance model
Functional annotation
Pedigree Multiple samples Somatic detection
Shared vs non-shared Fisher test allele counts

18. CNAG is a major contributor and driver in three large International Initiatives:
1.- International Cancer Genome Consortium (ICGC)
Spanish Project on Chronic Lymphocytic Leukaemia
French Project on Prostate Cancer
French Project on Ewing’s Sarcoma
2.- International Human Epigenome Consortium (IHEC)
EU-funded Project Blueprint
3.- International Rare Disorders Research Consortium (IRDiRC)
Spanish Project on Charcot-Marie-Tooth Disease
EU-funded C-Project on data analysis and coordination
What are our major projects?

19. 83 Projects/18 Countries

20. Nature 464, 993-998 (15.04.2010)

21. Tumoral
Non-Tumoral
RNADNA methylationDNA
peripheral peritumoral
Whole-genome
bisulphite seq
Exome seq RNA seq
Whole-genome seq
short insert PE
Sampling structure

22. International Cancer Genome Consortium
The International Cancer Genome Consortium
is an international effort to establish a
comprehensive description of genomic,
transcriptomic and epigenomic changes in
50 different tumor types and/or subtypes
which are of clinical and societal importance
across the globe.
Spain’s contribution to the ICGC is on chronic
lymphocytic leukaemia (CLL).
FUNDING SOURCE: Ministerio de Ciencia e Innovación
COORDINATOR: Prof. Elias Campo, Hospital Clínic
Barcelona
DURATION: May 2009 – May 2014
PROJECT FUNDING: €10 million

23. XS Puente et al. Nature 000, 1-5 (2011) doi:10.1038/nature10113
Mutational and functional analysis of NOTCH1 in CLL
5. June 2011

24. • Sequencing of 105 CLL tumours
• Identification of 1246 somatic mutations in 1.100 genes
• 78 genes with mutations in more than one patient
• Mutated genes cluster in pathways
• Distinct mutations are associated with clinical classifications
• Mutations in the SF3B1 gene identifies a group of patients with more aggressive
disease
• SF3B1 encodes a subunit of the spliceosomal U2 small nuclear ribonucleoprotein
(snRNP)
V Quesada et al. Nature Genetics 44, 47-52 (2011) doi:10.1038/ng1032

26. Epigenetics

27. Sample Prep
Add unmethylated
lambda DNA
Bisulfite
conversion
qPCR check of
conversion
Sequencing
Fully convert
reads
Alignment
(GEM)
QC (mapping,
conversion)
Select uniquely mapping
read pairs
Make genotype and
methylation calls
Select sites with
genotype p.p. >=0.99
Select CpGs and non-
CpGs
Select homozygous CC
or GG sites
Region detection
and annotation
BS-Seq oxBS-Seq
Merge to obtain
estimates of mC and
hmC levels
BS-Sequencing Pipeline
Statistical Genomics Team (S. Heath)

28. • Distinct DNA methylomes of newborns and centenarians. Heyn
et al. 2012 (PNAS)
• Epigenomic analysis detects widespread gene-body DNA
hypomethylation in chronic lymphocytic leukemia. Kulis et al.
2012 (Nat. Genetics)
• Blueprint EU-FP7 project
BS-Sequencing applications - Statistical Genomics Team (S. Heath)

31. Proposed model for a different cell of origin of CLL subtypes
(U-CLL from naive-like B cells and M-CLL from memory-like B cells)
Naive
B cell
Leukemictransformation
Activation Proliferation Differentiation
Normal B cell differentiation
66%
CpGs in
common
Memory
B cell
Plasma
cell23,052 hypoM / 3,231 hyperM
U-CLL
M-CLL
4,607 hypoM
1,246 hyperM
3,265
diffM
M Kulis et al. Nature Genetics 44, 1236-1242 (2012) doi:10.1038/ng2443

32. Single-cell RNA-seq
Cell isolation
Library preparation
Sequencing
Data analysis

33. Single-cell isolation methods
• Laser capture micro-dissection (LCM)
• Manual micro-pipetting (ICSI-like)
• Fluorescent-activated cell sorting (FACS)
• Microfluidic methods
– C1 Single-cell AutoPrep System (Fluidigm)
– Droplet-based microfluidics
• Single-cell RNA-seq in context (in situ), no need for single-cell isolation

34. • C1 Single-cell AutoPrep System (Fluidigm)
Continuous-flow microfluidics
Small cells: 5-10µm
Medium cells: 10-17µm
Large cells: 17-25µm
www.fluidigm.com

35. Library preparation
Cell lysis
Reverse transcription:
1st strand synthesis
2nd strand synthesis
cDNA amplification
Addition of
adapters for
sequencing
Library amplification

36. SMART-seq
Image from www.clontech.com Ramsköld et al, Nature Biotech, 2012
Switching
Mechanism
At 5’ end of
RNA
Template
Based on MMLV RTase properties:
1- Terminal transferase activity
Adds non-templated Cs
2- Template switching activity
(improves full-length capture)
MMLV RT: Moloney murine leukemia
virus reverse transcriptase
(Oligo dT)
1
2

37. Scatter plots (pairwise comparisons)
Correlation is better for highly
expressed genes
Single cell 750 a,b,c excellent correlation
although different libraries
Worst correlation with
debris

38. Principal component analysis

39. Principal component analysis (- pool and debris)

40. MARS-seq
Jaitin et al, Science, 2014

41. Collaborators
27
93 94
116
2
10 11
3
0
20
40
60
80
100
120
140
2011 2012 2013 2014
Collaborators by sector
Public Private
3
20
31 2626
83
74
93
0
20
40
60
80
100
120
140
2011 2012 2013 2014
Collaborators by origin
International National

42. Sequencing applications and research area
2014 activity by sequencing application 2014 activity by research area
51,12%
21,75%
0,95%
26,19%
Cancer Genomics
Disease Gene Identification
Infectious Disease Genomics
Model-and Agro-Genomics
41,60%
25,08%
21,29%
9,13%
1,49% 0,84% 0,57%
WG-Seq Exome-Seq
RNA-Seq BS-Seq
Custom Capture-Seq ChIP-Seq
Genotyping by Seq

43. 1st CNAG Call for Exome Sequencing in rare disorders – 2013/2014
The program has provided free-of-
charge Whole Exome Sequencing
and Bioinformatic analysis to the
selected projects.
 44 Applications received (941
exomes)
 23 Projects selected by an
External Selection Committee
(345 exomes)
 Confirmed causal variants in 3
families
 Putative causal variants in 19
families

44. How do we work with our collaborators?
• Collaboration from study design to paper writing
• Contact through the CNAG Project Manager (projectmanager-cnag@pcb.ub.es)
or Fatima Nuñez
• First point of discussion – advice on project
• Agreement on project
• Sample transfer using a standardized procedure (Lidia Agueda)
• Sample preparation and sequencing (Marta Gut)
• Data analysis (Sergi Beltran)

45. It is like Ballet, - because it looks easy,
everyone thinks it is easy.

46. 26th February 2015
Auditori Antoni Caparrós
Parc Científic de Barcelona
Free online registration at:
www.pcb.ub.edu/cnagevents

48. Acknowledgements
Ivo Gut
Mònica Bayés
Berta Fusté
Diego Ravenda
Katia López
Anna Borrell
Marta Gut
Julie Blanc
Katja Kahlem
María Méndez-Lago
Lidia Agueda
Lidia Sevilla
Javier Gutiérrez
Aurora Padrón
Gloria Plaja
Marta López
Pili Herruzo
Bea Fontal
Ana González
Laetitia Casano
Amaya Alzu
Maite Rico
Caterina Mata
Amy Guillaumet
Nicolas Boulanger
Esther Lizano
Simon Heath
Sergi Beltran
Marc A. Marti-Renom
Tomas Marques
Jordi Camps
Jean-Rémi Trotta
Emanuele Raineri
Ron Schuyler
Angelika Merkel
Marc Dabad
Justin Whalley
Paolo Ribeca
Tyler Alioto
Leonor Frías
Santiago Marco
Lukasz Roguski
Marcos Fernández
Fernando Cruz
Anna Esteve
Davide Baú
François Serra
Sophia Derdak
Steven Laurie
Raul Tonda
Enric Serra
Francisco Martínez
Mike Goodstadt
Matt Ingham
Colin Kingswood
Raul Alcántara
Meritxell Oliva
Gian Andri Thun
Gustavo Rodriguez-Esteban
Miranda Stobbe

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