The Genomic Unit of the Center for Genomic Science of IIT@SEMM processes thousands of samples on Next Generation Sequencing platforms. We will briefly present how we manage the experimental flow and data with our dedicated LIMS and facilitate primary and secondary analyses with HTS-flow, a workflow management system that has been standardized and made easily accessible to both dry and wet lab scientists. Finally, we will show how we are extending genome visualization tools to enable the integration of NGS data with molecular, network and structural biology. Presented at the "Giornata Milanese di NGS", 2016 Apr 8, University of Milan Bicocca

1. NGS Management And Analysis:
From Sample
To Molecular And Network Biology.
Computation Research Unit, iIT@SEMM http://cru.genomics.iit.it
@arnaudceolpro
Arnaud Ceol,
Center for Genomic Science of IIT@SEMM,
Fondazione Istituto Italiano di Tecnologia (IIT)

2. Sequencing Unit:
sequencing
Labs/Sequencing unit
Submit samples
(LIMS)
Data visualization/3ry analyses
Automatized
primary/secondary
analyses
Molecular (…) biology(epi)genomics

3. Venco,F. et al. (2014) SMITH: a LIMS for handling next-generation sequencing workflows. BMC Bioinformatics, 15
Suppl 1, S3.
Manage NGS data: SMITH
(Laboratory Information Management System)
Updated for a better management of meta-data
-> ready for GenoMetric Query Language

4. Labs/Sequencing unit
Submit samples
(LIMS)
Data visualization/3ry analyses
Automatized
primary/secondary
analyses
Molecular (…) biology(epi)genomics

5. Samples and metadata
• imported from the LIMS,
• From external files,
• Automatically imported from GEO
Bianchi, Ceol et al, under review

6. Primary analyses (alignment..)
• ChIP-seq, RNA-seq, DNaseI-seq, BS-seq
• Mostly automatize, with just enough
options
• Merging capability

7. Secondary analysis:
• Expression Quantification,
• Differential Genes Expression (DEG calling),
• Peak Calling,
• Footprint Calling,
• Methylation calling.,
• Analysis of 4sU-seq and RNA-seq time-course data (INSPEcT).

8. Labs/Sequencing unit
Submit samples
(LIMS)
Data visualization/3ry analyses
Automatized
primary/secondary
analyses
Molecular (…) biology(epi)genomics

9. Integrated Genome Browser (Ig-Bee)
http://bioviz.org
HTS-flow

10. Céol,A. and Müller,H. (2015) The MI bundle: enabling network and structural biology in genome visualization tools. Bioinformatics, btv431.

11. Mapping RUNX1 variations to molecular interactions. (a) Genomic variations for
RUNX1 are loaded from ClinVar (purple tracks). (b) Some variations are identified
at the interface with CBFB (yellow tracks), DNA (orange track) and RUNX1
(homodimer, blue track).
Ceol A. Muller M., Bioinformatics, 2015

12. Two mutations(positions K83 and R174)
are identified at the interface with DNA
only. Previous studies have shown that
in the presence of mutation at those sites
no DNA binding is observed while the
homodimerization capability is preserved
(Michaud et al., 2002).

13. Another mutation at position 107 is
mapped to the interface with CBFB and
may, as suggested by Walker et al. (2002),
impair this interaction, destabilizing the
binding of RUNX1 to DNA and leading to
RUNX1 degradation
Mutations from cBioPortal (Cerami et al., 2012):
Several of those where identified at the interface with
RUNX1 (14, of which 10 new), CBFB (10/9) and DNA
(5/4), suggesting how those variations may interfere with
the molecular network and cause or predispose to
disease.

14. PPI & drugs
Ceol,A et al.. Genome and network visualization facilitates the
analyses of the effects of drugs and mutations on protein-protein
and drug-protein networks.

15. MDM2
Nutlin
P5
3

16. Tacromilus interferes with ALK-1 / FKBP1A
interaction
• Hereditary hemorrhagic telangiectasia (HHT): is a genetic disorder that results
in abnormal blood vessel formation.
• It is caused by mutations in the ACVRL1, ENG, and SMAD4 genes.
• Both ENG and ACVRL1 mutations lead predominantly to underproduction of
the related proteins,

17. • This provides a structural bases for the observation from Albinana et al. [6]
that the amount of ACVRL1 pulled down by GST-FKBP1A was decreased
when cells were treated with Tacrolimus.
• By interfering with the binding of ACVRL1, Tacrolimus may increase ACVRL1
activity, and eventually improve the symptoms of HHT.

18. Mutations inducing drug-resistance:
the case of Imatinib
Gatekeeper mutations are defined as those that abrogate binding of drugs to their
targets, dramatically reducing the clinical efficacy of treatment.

19. Sequencing Unit:
sequencing
Labs/Sequencing unit
Submit samples
(LIMS)
Data visualization/3ry analyses
Automatized
primary/secondary
analyses
Molecular (…) biology(epi)genomics

20. thanks…
Computation Research Unit, iIT@SEMM http://cru.genomics.iit.it
SMITH (LIMS): Heiko Muller (IIT), Francesco Venco and Yuriy Vaskin (Politecnico di Milano)
HTS-flow: Valerio Bianchi, Marco Morelli and Mattia Pelizzola, Stefano De Pretis, Eugenia
Galeota, Kamal Kishore, Pranami Bora, Ottavio Croci, (IIT)
PPI-drug networks: Lisette Verhoef, Mark Wade, Heiko Muller (IIT)