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

TY - JOUR

T1 - KeyGenes, a Tool to Probe Tissue Differentiation Using a Human Fetal Transcriptional Atlas

AU - Roost, Matthias S

AU - van Iperen, Liesbeth

AU - Ariyurek, Yavuz

AU - Buermans, Henk P

AU - Arindrarto, Wibowo

AU - Devalla, Harsha D

AU - Passier, Robert

AU - Mummery, Christine L

AU - Carlotti, Françoise

AU - de Koning, Eelco J P

AU - van Zwet, Erik W

AU - Goeman, Jelle J

AU - Chuva de Sousa Lopes, Susana M

N1 - Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

PY - 2015/6/9

Y1 - 2015/6/9

N2 - 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.

AB - 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.

U2 - 10.1016/j.stemcr.2015.05.002

DO - 10.1016/j.stemcr.2015.05.002

M3 - Article

C2 - 26028532

SN - 2213-6711

VL - 4

SP - 1112

EP - 1124

JO - Stem Cell Reports

JF - Stem Cell Reports

IS - 6

ER -