MseqDR consortium: a grass-roots
effort to establish a global resource
aimed to empower genomic studies
of mitochondrion d...
NGS and Mitochondrial diseases
A worldwide call for a great bioinformatics effort
to correctly identify and prioritize the...
NGS, Mitochondrial diseases
and bioinformatics
The likelihood of success of the effort can be
greatly improved if the larg...
The establishement of the
MSeqDR consortium
To carry out this effort more than 100
international mitochondrial clinicians,...
Through regular web-based meetings, we have
familiarized ourselves with existing strengths and
gaps facing
• integration o...
Thanks to this effort a prototype of the MSeqDR
central resource has been established
http://mseqdr.org/
The resource offe...
MSeqDR consortium structure
• WG1 – Technology and Bioinformatics
CoChair: Marni Falk (CHOP/Upenn), Xiaowu Gai PhD (MEEI) ...
MSeqDR major software components are:
o Data Capture software allowing capturing, annotation and
integration of data deriv...
MSeqDR LSDB
Data are organised according to the following classes:
• Genes
• Transcripts
• Variants
• Diseases
• Individua...
General
Genomic
Platform Data
Backend
• Ensembl Genes, UCSC
Genes, NCBI Genes, HUGO
genes nomenclature (HGNC)
• EVS, 1000 ...
MSeqDR Gbrowse
Once selected a human genomic region and chosen
the classes of data of interest, the user is allowed
to bro...
Mitochondrial Disease Tools
MSeqDR is collaborating with the community to bring
together various available and published t...
The MSeqDR Prototype Development
Site 1.
Xiaowu Gai , PhD , Lishuang Shen , PhD https://MSeqDR.org MEEI
Common data upload...
MSeqDR will improve the prioritization of mitochondrial disease
causing variants thanks to a self-training mechanism that ...
MSeqDR Participation
Interested in joining MSeqDR consortium?
If you are interested in joining the MSeqDR consortium, plea...
Mitochondrial Disease Sequence Data
Resource (MSeqDR) Consortium
MSeqDR Consortium is supported by United
Mitochondrial Di...
M.Attimonelli1, L.Shen11, M.Gonzalez2, D.C.Wallace3, M.Lott3, J.Leipzig3, F.Stassen4,
M.Tarnopolsky5, R.Boles6,7, J.DaRe8,...
Acknowledgements to my coworkers
• Giuseppe Gasparre, Researcher at the Dept. of Medical and Surgical Sciences,
University...
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MseqDR consortium: a grass-roots effort to establish a global resource aimed to empower genomic studies of mitochondrion diseases - Marcella Attimonelli

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The success of whole exome sequencing (WES) for highly heterogeneous disorders, such as mitochondrial disease, is limited by substantial technical and bioinformatics challenges to correctly identify and prioritize the extensive number of sequence variants present in each patient. The likelihood of success can be greatly improved if a large cohort of patient data is assembled in which sequence variants can be systematically analysed, annotated, and interpreted relative to known phenotype. This effort has engaged and united more than 100 international mitochondrial clinicians, researchers, and bioinformaticians in the Mitochondrial Disease Sequence Data Resource (MSeqDR) consortium that formed in June 2012 to identify and prioritize the specific WES data analysis needs of the global mitochondrial disease community. Through regular web-based meetings, we have familiarized ourselves with existing strengths and gaps facing integration of MSeqDR with public resources, as well as the major practical, technical, and ethical challenges that must be overcome to create a sustainable data resource. We have now moved forward toward our common goal by establishing a central data resource (http://mseqdr.org/) that has both public access and secure web-based features that allow the coherent compilation, organization, annotation, and analysis of WES and mtDNA genome data sets generated in both clinical- and research-based settings of suspected mitochondrial disease patients. The most important aims of the MSeqDR consortium are summarized in the MSeqDR portal within the Consortium overview sections. Consortium participants are organized in 3 working groups that include (1) Technology and Bioinformatics; (2) Phenotyping, databasing, IRB concerns and access; and (3) Mitochondrial DNA specific concerns. The online MSeqDR resource is organized into discrete sections to facilitate data deposition and common reannotation, data visualization, data set mining, and access management. With the support of the United Mitochondrial Disease Foundation (UMDF) and the NINDS/NICHD U54 supported North American Mitochondrial Disease Consortium (NAMDC), the MSeqDR prototype has been built. Current major components include common data upload and reannotation using a novel HBCR based annotation tool that has also been made publicly available through the website, MSeqDR GBrowse that allows ready visualization of all public and MSeqDR specific data including labspecific aggregate data visualization tracks, MSeqDR-LSDB instance of nearly 1250 mitochondrial disease and mitochodnrial localized genes that is based on the Locus Specific Database model, exome data set mining in individuals or families using the GEM.app tool, and Account & Access Management. Within MSeqDR GBrowse it is now possible to explore data derived from MitoMap, HmtDB, ClinVar, UCSC-NumtS, ENCODE, 1000 genomes, and many other resources that bioinformaticians recruited to the project are organizing.

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  • Thanks to the organizers and the scientific committee that have allowed me to introduce the MSeqDR consortium, a grass effort to establish a global resource aimed to empower genomic studies related to mitochondrial diseases, born here in Paris during the previous "Human Variome" meeting held in the June 2012.
    The starting idea to establish the MSeqDR consortium was born from the advent of New Generation Sequencing approaches and the repercussion of this technology on mitochondrial disease studies.
  • Infact the heterogeneity of mitochondrial diseases requires a scouting expedition along the whole genome, exome and/or trascriptome of more patients in order to recognize the onsetting loci as well as the loci where the primary events act and hence produce a cascade of effects.
    The opportunity offered from NGS technology to sequence in a short time with not a great financial and human effort
    the whole mtDNA with a high coverage and hence allowing to recognize very low heteroplasmic percentages,
    the whole genome/exome or transcriptome by including or excluding mtDNA
     
    allows in any case to have a complete view of the mutational spectrum of the two human genomic compartments in a large cohort of patients.
    Hence a worldwide call of 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.
  • We have now moved forward toward our common goal by establishing a central data resource (http://mseqdr.org/) that has both public access and secure web-based features that allow the coherent compilation, organization, annotation, and analysis of WES and mtDNA genome data sets of suspected mitochondrial disease patients generated in both clinical- and research-based settings.

  • The MSeqDR resource has been designed considering the following components:
    software allowing capturing and annotation of data derived from external resources,
    Gbrowse, a combination of database and interactive web pages for manipulating and displaying annotations on genomes.
    Features
  • MseqDR consortium: a grass-roots effort to establish a global resource aimed to empower genomic studies of mitochondrion diseases - Marcella Attimonelli

    1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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)

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