Searching the Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Diabetes affects millions of people worldwide, and β-cell replacement is one of the promising new strategies for treatment. Induced pluripotent stem cells (iPSCs) can differentiate into any cell type, including pancreatic β cells, providing a potential treatment for diabetes. However, the molecular mechanisms underlying the differentiation of iPSC-derived β cells have not yet been fully elucidated. Here, we generated pancreatic β-like cells from mouse iPSCs using a 3-step protocol and performed deep RNA sequencing to get a transcriptional landscape of iPSC-derived pancreatic β-like cells during the selective differentiation period. We then focused on the differentially expressed genes (DEGs) during the time course of the differentiation period, and these genes underwent Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway analysis. In addition, gene-act networks were constructed for these DEGs, and the expression of pivotal genes detected by quantitative real-time polymerase chain reaction was well correlated with RNA sequence (RNA-seq). Overall, our study provides valuable information regarding the transcriptome changes in β cells derived from iPSCs during differentiation, elucidates the biological process and pathways underlying β-cell differentiation, and promotes the identification and functional analysis of potential genes that could be used for improving functional β-cell generation from iPSCs.
Pubmed ID: 28901190
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.
View all literature mentionsCommercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)
View all literature mentionsCollection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
View all literature mentionsComputable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
View all literature mentionsA portal to biomedical and genomic information. NCBI creates public databases, conducts research in computational biology, develops software tools for analyzing genome data, and disseminates biomedical information for the better understanding of molecular processes affecting human health and disease.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. Accurate mapping of RNA-seq reads for splice junction discovery.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentions