Developing Global Cellular Information Retrieval System with Minimum Reporting Guidelines on Cellular Data for Regenerative Medicine

A wide range of stem cell research towards regenerative medicine has been conducted in a large number of domains in the world over the years. However, those produced data and information are not fully utilized and sometimes causes failure to be reproduced among laboratories or cell banks due to a lack of standardization of cellular assay reporting formats. To maximize a value placed on the information in stem cell and derivative cell research, we have proposed reporting guidelines for describing cellular assay data to pursue the facilitation of practical regenerative medicine named ‘Minimum Information About a Cellular Assay for Regenerative Medicine (MIACARM)’. MIACARM has been developed based on the existing Minimum Information About a Cellular Assay (MIACA) with defined taxonomy of human cell types, which allows for the description of advanced cellular experiments. MIACARM is applicable for exchanging data from not only for basic cellular assay, but also stem cell assay data that are produced and provided by cell banks, registries, or other academic institutions all over the world. And here we would like to introduce our recent progress that is developing stem cell data retrieval system based on MIACARM.

[1]  Sean K. Simmons,et al.  Enabling Privacy-Preservi ng GWASs in Heterogeneous Human Populations Graphical Abstract Highlights , 2016 .

[2]  Shane J. Neph,et al.  Systematic Localization of Common Disease-Associated Variation in Regulatory DNA , 2012, Science.

[3]  D. Conrad,et al.  Global variation in copy number in the human genome , 2006, Nature.

[4]  Ituro Inoue,et al.  Phase-defined complete sequencing of the HLA genes by next-generation sequencing , 2013, BMC Genomics.

[5]  J. Thomson,et al.  Embryonic stem cell lines derived from human blastocysts. , 1998, Science.

[6]  Rachel G Liao,et al.  A federated ecosystem for sharing genomic, clinical data , 2016, Science.

[7]  Glyn Stacey,et al.  Banking stem cells for research and clinical applications. , 2012, Progress in brain research.

[8]  Kenneth K. Kidd,et al.  SNPs for a universal individual identification panel , 2010, Human Genetics.

[9]  W. Fujibuchi,et al.  First Proposal of Minimum Information About a Cellular Assay for Regenerative Medicine , 2016, Stem cells translational medicine.

[10]  Peggy J. Farnham,et al.  Functional annotation of colon cancer risk SNPs , 2014, Nature Communications.

[11]  K. Makova,et al.  A matter of life or death: how microsatellites emerge in and vanish from the human genome. , 2011, Genome research.

[12]  Ron Edgar,et al.  NCBI GEO standards and services for microarray data , 2006, Nature Biotechnology.

[13]  M. Daly,et al.  A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms , 2001, Nature.

[14]  W. Greenhalf,et al.  Single-nucleotide polymorphism (SNP) analysis to associate cancer risk. , 2010, Methods in molecular biology.

[15]  Zhen Lin,et al.  Genomic Research and Human Subject Privacy , 2004, Science.

[16]  C. Mummery,et al.  International Coordination of Large-Scale Human Induced Pluripotent Stem Cell Initiatives: Wellcome Trust and ISSCR Workshops White Paper , 2014, Stem cell reports.

[17]  T. Ichisaka,et al.  Induction of Pluripotent Stem Cells from Adult Human Fibroblasts by Defined Factors , 2007, Cell.