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

Matthias S. Roost, Liesbeth Van Iperen, Yavuz Ariyurek, Henk P. Buermans, Wibowo Arindrarto, Harsha D. Devalla, Robert Passier, Christine L. Mummery, Françoise Carlotti, Eelco J.P. De Koning, Erik W. Van Zwet, Jelle J. Goeman, Susana M. Chuva De Sousa Lopes*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

93 Citations (Scopus)
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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.

Original languageEnglish
Pages (from-to)1112-1124
Number of pages13
JournalStem cell reports
Issue number6
Publication statusPublished - 9 Jun 2015
Externally publishedYes


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