KeyGenes, a Tool to Probe Tissue Differentiation Using a Human Fetal Transcriptional Atlas

• Published in: Stem cell reports Vol. 4; no. 6; pp. 1112 - 1124
• Main Authors: Roost, Matthias S., van Iperen, Liesbeth, Ariyurek, Yavuz, Buermans, Henk P., Arindrarto, Wibowo, Devalla, Harsha D., Passier, Robert, Mummery, Christine L., Carlotti, Françoise, de Koning, Eelco J.P., van Zwet, Erik W., Goeman, Jelle J., Chuva de Sousa Lopes, Susana M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 09.06.2015; Elsevier
• Subjects: Algorithms; Cell Differentiation; Databases, Factual; Female; Fetus - cytology; Fetus - metabolism; High-Throughput Nucleotide Sequencing; Humans; Oligonucleotide Array Sequence Analysis; Pluripotent Stem Cells - cytology; Pluripotent Stem Cells - metabolism; Pregnancy; Pregnancy Trimester, First - genetics; Pregnancy Trimester, First - metabolism; Pregnancy Trimester, Second - genetics; Pregnancy Trimester, Second - metabolism; Resource; Sequence Analysis, DNA; Transcriptome
• ISSN: 2213-6711; 2213-6711
• DOI: 10.1016/j.stemcr.2015.05.002

Differentiated derivatives of human pluripotent stem cells in culture are generally phenotypically immature compared to their adult counterparts. Their identity is often difficult to determine with certainty because little is known about their human fetal equivalents in vivo. Cellular identity and signaling pathways directing differentiation are usually determined by extrapolating information from either human adult tissue or model organisms, assuming conservation with humans. To resolve this, we generated a collection of human fetal transcriptional profiles at different developmental stages. Moreover, we developed an algorithm, KeyGenes, which uses this dataset to quantify the extent to which next-generation sequencing or microarray data resemble specific cell or tissue types in the human fetus. Using KeyGenes combined with the human fetal atlas, we identified multiple cell and tissue samples unambiguously on a limited set of features. We thus provide a flexible and expandable platform to monitor and evaluate the efficiency of differentiation in vitro. [Display omitted] •NGS-derived transcriptional profiles of human fetal tissues/organs are generated•Algorithm called KeyGenes uses a training set to predict the identity of a test set•KeyGenes using the fetal atlas identifies NGS- and microarray-derived data•KeyGenes is a flexible and expandable platform to monitor stem cell differentiations In this article, Lopes and colleagues introduce a platform called KeyGenes, which uses a collection of human fetal transcriptional profiles to assign identity and developmental stages to NGS- and microarray-derived data. Furthermore, they show that KeyGenes is flexible and expandable to get the most meaningful output for a given experiment.