The mseqdr consortium is a collaborative global effort to create a resource for genomic studies focused on mitochondrial diseases, involving over 100 international experts. It aims to systematically analyze patient data through web-based tools to prioritize sequence variants and support better diagnosis and research in mitochondrial conditions. The consortium has established a prototype resource that integrates various genomic databases and tools for capturing and annotating data related to mitochondrial diseases.

1. MseqDR consortium: a grass-roots
effort to establish a global resource
aimed to empower genomic studies
of mitochondrion diseases
Marcella Attimonelli
Dept. of Biosciences, Biotechnology
and Biopharmaceutics, University of Bari – IT

2. NGS and Mitochondrial diseases
A worldwide call for a great bioinformatics effort
to correctly identify and prioritize the extensive
number of sequence variants present in each
patient affected by a suspected mitochondrial
disease.

3. NGS, Mitochondrial diseases
and bioinformatics
The likelihood of success of the effort can be
greatly improved if the large cohort of patient
data is organized in a structured resource in
which sequence variants can be systematically
analysed, annotated and interpreted relatively
to known phenotype.

4. The establishement of the
MSeqDR consortium
To carry out this effort more than 100
international mitochondrial clinicians,
researchers and bioinformaticians get engaged
and united in the Mitochondrial Disease
Sequence Data Resource (MSeqDR) consortium.

5. Through regular web-based meetings, we have
familiarized ourselves with existing strengths and
gaps facing
• integration of MSeqDR with public resources
• the major practical, technical, and ethical
challenges that must be overcome to create a
sustainable data resource

6. Thanks to this effort a prototype of the MSeqDR
central resource has been established
http://mseqdr.org/
The resource offers both public access and secure but
web-based features allowing the analysis, annotation
and organization of WES (Whole Exome Sequencing)
and mtDNA datasets of suspected mt disease patients
generated in both clinical- and research-based
settings.

7. MSeqDR consortium structure
• WG1 – Technology and Bioinformatics
CoChair: Marni Falk (CHOP/Upenn), Xiaowu Gai PhD (MEEI) and Curt Sharfe (MD, PhD Stanford)
Advisors: Lisa Brooks, Phd (NHGRI), Dehanna Church PhD (NCBI, NIH)
• WG2 – Phenotyping, Databases, IRB concerns and Access
CoChair: Patrick Chinnery MD, PhD (NewCastle), Lee-Jun Wong PhD (Baylor) and Peter White,
PhD (CHOP/Pen)
Advisors: Donna Maglott PhD (NCBI,NIH) and Yaffa Rubinstein PhD (NCATS, ORDR)
• WG3 – Mitochondrial DNA Specific concerns
CoChair: Vincent Procaccio PhD (Angers) and Douiglas Wallace PhD (CHOP/Upenn)
Advisors : Marie Lott PhD (CHOP), Marcella Attimonelli (DBBB)

8. MSeqDR major software components are:
o Data Capture software allowing capturing, annotation and
integration of data derived from external resources.
o Gbrowse software allowing graphical display of the captured data
o MSeqDR-LSDB, the MSeQDR locus specific database designed by
using LOVD
o MITO-BOX : a compendium of software allowing variants
annotation and prioritization
o Account & Access Management.

9. MSeqDR LSDB
Data are organised according to the following classes:
• Genes
• Transcripts
• Variants
• Diseases
• Individuals
• Screenings
New data can be submitted by registered users

10. General
Genomic
Platform Data
Backend
• Ensembl Genes, UCSC
Genes, NCBI Genes, HUGO
genes nomenclature (HGNC)
• EVS, 1000 Genomes
MSeqDR
Community
Genomic
Resources
• Proprietary Exome (3500+)
Data
• Mitomap: Expert Curation,
10K mitochondrial variants
• HmtDB: annotated complete
mitochondrial genomes
• PhyloTree: Human mt
Haplogroups classification
• Community data:
Transgenomics Inc., POLG DB,
Mito-Phenome
Resources
•OMIM, ClinVar, MedGen
•Ensembl Phenotype
•Mitomap disease names,
HmtDB pathogenicity database,
HPO: the human Phenotype
Ontology
•Mito Dictionaries from NAMDC
and UMDF

11. MSeqDR Gbrowse
Once selected a human genomic region and chosen
the classes of data of interest, the user is allowed
to browse among the available tracks and to move
to metadata and related tables
Example of a mtDNA region tracks
M:10,000-11,000

12. Mitochondrial Disease Tools
MSeqDR is collaborating with the community to bring
together various available and published tools.
Currently the following tools are fully implemented
HBPCR, GEM.APP, MITOMASTER
On the way: MT.AT, MToolBox*, The Phenom Portal
* See Poster 21

13. The MSeqDR Prototype Development
Site 1.
Xiaowu Gai , PhD , Lishuang Shen , PhD https://MSeqDR.org MEEI
Common data upload and reannotation
MSeqDR GBrowse
MSeqDR-LSDB
Phenome data
Site 2
Stephan Züchner, MD, PhD
University of Miami Miller School of Medicine
Exome data set mining in individuals or families using the GEM.App
tool
International group members of the consortium are contributing with
software and databases.

14. MSeqDR will improve the prioritization of mitochondrial disease
causing variants thanks to a self-training mechanism that will allow
the identification of
• rare cases whose genetic diagnosis may not have been known
• genetic links to "secondary" mitochondrial conditions

15. MSeqDR Participation
Interested in joining MSeqDR consortium?
If you are interested in joining the MSeqDR consortium, please contact
Dr. Marni Falk at falkm@email.chop.edu.
Discussion about this MSeqDR Prototype Website and Development
Effort?
Please contact Dr. Xiaowu Gai at Xiaowu_Gai@meei.harvard.edu, or
comment at our online Feedback below.
.

16. Mitochondrial Disease Sequence Data
Resource (MSeqDR) Consortium
MSeqDR Consortium is supported by United
Mitochondrial Disease Foundation (UMDF) and
extramural program officers at NICHD, NIH and
other institutions where the consortium
participants are affiliated.

17. M.Attimonelli1, L.Shen11, M.Gonzalez2, D.C.Wallace3, M.Lott3, J.Leipzig3, F.Stassen4,
M.Tarnopolsky5, R.Boles6,7, J.DaRe8, R.Bai9, M.Parisi10, D.Krotoski10, S.Zuchner2,
X.Gai11, M.J.Falk12
• 1Department of Biosciences Biotechnology and Biopharmaceutics, IT
• 2 Human-Genetics Department, Miami
• 3 Children’s Hospital Philadelphia, USA
• 4Maastricht University, NL
• 5 McMaster University, Canada
• 6California University, USA
• 8Transgenomic, USA
• 9GeneDx, Gaithersburg, USA
• 10 NICHD-NIH, Bethesda, USA
• 11 Massachusetts-Eye-and-Ear-Infirmary, Harvard.Univ USA;
• 12 University of Pennsylvania, USA

18. Acknowledgements to my coworkers
• Giuseppe Gasparre, Researcher at the Dept. of Medical and Surgical Sciences,
University of Bologna , Italy
• Domenico Simone, Post-doctoral fellow at the Dept. of Biosciences, University of
Milan, Italy (and now guest in my lab)
• Claudia Calabrese, Post-doctoral fellow at the Dept. of Medical and Surgical Sciences,
University of Bologna , Italy (and now guest in my lab)
• Maria Angela Diroma, PhD student at the Dept. of Biosciences, Biotechnologies and
Biopharmaceutics , University of Bari, Italy (and now guest at MEEI, Harvard
University, Cambridge MA, USA)
• Mariangela Santorsola, PhD student at the Dept. of Sciences and Technologies,
University of Sannio, Italy (and now guest in my lab)
• Rosanna Clima, PhD student at the Dept. of Medical and Surgical Sciences, University
of Bologna , Italy (and now guest in my lab)