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"Key Genes" predicts identity of stem cells in fetus

Now, a snapshot of gene activity is all that is needed to determine what organ or tissue type a cluster of fetal stem cells will ultimately become. Such information is vital when planning stem cell transplants.

An algorithm developed by a team of Dutch scientists, makes it possible to match an immature stem cell to a known human fetal cell in order to identify what that stem cell might become. Called "KeyGenes," the software and technology were published May 28 in Stem Cell Reports, and could also help in testing the quality of stem cells for transplants.

"One of the hardest things in stem cell biology is determining what you have turned cells into using a particular method of differentiation. We think "KeyGenes" can help us develop protocols for differentiation that lead to cells resembling their in-vivo counterparts much more closely."

Susana Chuva de Sousa Lopes PhD, Leiden University Medical Center in The Netherlands, and study senior author.

"CellNet", another platform for mapping stem cell fate, was published in the summer of 2014 by researchers from Harvard University. "CellNet" helps determine the quality of procedures used to differentiate adult human tissues by testing to find which genes are turned on or off in a tissue sample. "KeyGenes", is based primarily on gene expression from both fetal and adult human tissues.

"By collecting extensive data on gene expression during human fetal development (at different stages and from multiple organs), "KeyGenes" allows human stem cell derivatives to be identified and given a correct 'age' equivalent [to the patient receiving the tissue]."

Christine Mummery PhD, research co-author, and board member of the International Society for Stem Cell Research, Leiden University.

In the clinic, researchers feel "KeyGenes" will be helpful in cases where human development has gone wrong — to identify which tissues are present in excessive amounts, or specific tissues that didn't migrate to their intended location.

In the lab, "KeyGenes" has already helped identify which genes determine a cell's fate. Genes are always a mix of molecules that determine which is being turned on and those strictly related to cell adhesion and cell shape.

"... some "KeyGenes" identified are long non-coding RNAs, confirming the increasingly important role for this class of molecules."

Susana Chuva de Sousa Lopes PhD

Dr. Lopes has made "KeyGenes" openly available to the scientific community in order to expand its database. She wants "KeyGenes" to eventually include epigenetic data — external or environmental influences that turn genes on and off — to find out whether epigenetic memory exists within cells. If epigentic memory remains within specific organ cells, the next quesion is whether and how it influences that cell to differentiate into a new cell.

Abstract
Highlights
•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

Summary
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.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Stem Cell Reports, Roost et al.: "KeyGenes, a tool to probe tissue differentiation using a human fetal transcriptional atlas" http://dx.doi.org/10.1016/j.stemcr.2015.05.002

Stem Cell Reports, published by Cell Press for the International Society for Stem Cell Research, is a monthly open-access forum communicating basic discoveries in stem cell research, in addition to translational and clinical studies. The journal focuses on shorter, single-point manuscripts that report original research with conceptual or practical advances that are of broad interest to stem cell biologists and clinicians. For more information, please visit http://www.cell.com/stem-cell-reports. To receive media alerts for Stem Cell Reports or other Cell Press journals, please contact press@cell.com.

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