The Cell Core C is the keystone of the FSHD-Wellstone research activities and will be responsible for thedevelopment and maintenance of reagents for its investigators and the FSHD research community at-large.Every project in this proposal will draw from its resources. A FSHD tissue bank (Aim 1) will be establishedfrom patients and first-degree family members specifically recruited, screened and enrolled to provide highquality and highly relevant biological specimens. Open muscle biopsies of FSHD muscle and control musclewill be obtained from 3 participating sites: Johns Hopkins, University of Utah and University of Sao Paulo,and distributed to multiple institutions for studies proposed. The Cell and Molecular Lab (Aim 2) of the Corewill be located at BBRI and will perform several functions including the establishment of primary andsecondary cultures and selected immortalized clonal lines from biopsy materials of FSHD subjects andprimary relatives. Additionally, evaluation of biochemical, cell biological, proteomic and molecular dataobtained from the relevant cell cultures and immortalized cell lines will be made available to the FSHDscientific community through the establishment of a national resource FSHD muscle cell repository. AnFSHD myoblast cell repository (Aim 3) will be established through collaboration with Genzyme/Myosix andan FSHD lymphocyte repository will be established with The Coriell Institute. Finally the BioinformaticsSupport Group (Aim 4) will have a large role in this Center, serving all projects as well as individual aspectsof the Cell Core. The Bioinformatics Support Group will set-up and maintain a portal for standardizing,managing and sharing data between collaborating laboratories in the Center, and for making data publiclyavailable as a companion to the public myoblast cell repository. It will also perform the computationalanalysis and modeling of the data produced by Cell Core C, including transcriptomic data, proteomics data,and data from cell-based assays. The Bioinformatics component will use both statistical and machinelearningapproaches to identify FSHD biomarkers from across the different data modalities, and will performintegrative analysis, with the goals of understanding the pathways that are disrupted in FSHD and identifyingand assessing potential therapeutic targets.
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