StemCellDB: the human pluripotent stem cell database at the National Institutes of Health.

Much of the excitement generated by induced pluripotent stem cell technology is concerned with the possibility of disease modeling as well as the potential for personalized cell therapy. However, to pursue this it is important to understand the 'normal' pluripotent state including its inherent variability. We have performed various molecular profiling assays for 21 hESC lines and 8 hiPSC lines to generate a comprehensive snapshot of the undifferentiated state of pluripotent stem cells. Analysis of the gene expression data revealed no iPSC-specific gene expression pattern in accordance with previous reports. We further compared cells, differentiated as embryoid bodies in 2 media proposed to initiate differentiation towards separate cell fates, as well as 20 adult tissues. From this analysis we have generated a gene list which defines pluripotency and establishes a baseline for the pluripotent state. Finally, we provide lists of genes enriched under both differentiation conditions which show the proposed bias toward independent cell fates.

Use of a Drosophila genome-wide conserved sequence database to identify functionally related cis-regulatory enhancers.

BACKGROUND: Phylogenetic footprinting has revealed that cis-regulatory enhancers consist of conserved DNA sequence clusters (CSCs). Currently, there is no systematic approach for enhancer discovery and analysis that takes full-advantage of the sequence information within enhancer CSCs. RESULTS: We have generated a Drosophila genome-wide database of conserved DNA consisting of >100,000 CSCs derived from EvoPrints spanning over 90% of the genome. cis-Decoder database search and alignment algorithms enable the discovery of functionally related enhancers. The program first identifies conserved repeat elements within an input enhancer and then searches the database for CSCs that score highly against the input CSC. Scoring is based on shared repeats as well as uniquely shared matches, and includes measures of the balance of shared elements, a diagnostic that has proven to be useful in predicting cis-regulatory function. To demonstrate the utility of these tools, a temporally-restricted CNS neuroblast enhancer was used to identify other functionally related enhancers and analyze their structural organization. CONCLUSIONS: cis-Decoder reveals that co-regulating enhancers consist of combinations of overlapping shared sequence elements, providing insights into the mode of integration of multiple regulating transcription factors. The database and accompanying algorithms should prove useful in the discovery and analysis of enhancers involved in any developmental process.