Genomic ‘Hotspots’ Drive Pluripotent Stem Cell Variability

What are Pluripotent Stem Cells?

Stem cells are the foundation of the body’s ability to regenerate different cell types. Bone marrow stem cells, for example, are the essential precursor cells for most of the major cell types in the immune system. A “pluripotent” stem cell is a stem cell that can differentiate into many different types of mature cells, and differs from a normal dividing cell which is typically terminally differentiated into a single type.

When you hear “pluripotent stem cells,” however, your mind may jump to the 2012 Nobel Prize in Physiology or Medicine awarded to Shinya Yamanaka and John Gurdon. Their work was on the discovery of how to use transcription factors in vitro to create induced pluripotent stem cells. That is to say, they discovered how to reprogram fully differentiated, mature cells back into pluripotent cells that could be used to generate a different cell type.

Variability in Pluripotent Stem Cells

The discovery of the ability to grow pluripotent stem cells for research, e.g. deriving them from mouse embryonic stem cells, or the ability to reprogram human cells into a pluripotent state has obvious and exciting applications for regenerative medicine and research. However, it became immediately apparent that most cells retain some form of genetic “memory” from their differentiated state, even when reprogrammed, and would preferentially differentiate into certain cell types.

Similarly, there is significant variability among mouse embryonic stem cell lines in their derivation, stability, and tendencies towards differentiation into different cell types that makes research and modeling disease challenging.

Multi-Omics Integration Identifies Genomic “Hotspots” that Drive PSC Variability

Existing studies examining the variability between pluripotent stem cell lines have focused primarily on transcriptomics and chromatin states using methods like RNA-seq and ATAC-seq. However, these studies alone have not sufficiently explained observed variability, and conflict with proteomic studies on the same cell lines, suggesting that post-translational activities are also playing a significant role.

In a recent paper published in Cell Genomics, Aydin et. al. performed a comprehensive proteogenomics analysis of 190 genetically diverse mouse embryonic stem cell (mESC) lines. The authors identified activated pathways for cellular differentiation using the proteomic data that were not apparent in transcriptomic data alone. By integrating transcriptomic, proteomic and chromatin accessibility data, the authors honed in on the shared drivers of variation in pluripotency-related pathways. These markers could then be mapped back to the genome and were clustered in genomic “hotspots,” clearly identifying signatures of the moderators of pluripotency and variation in pluripotent cells.

By understanding the multi-omic causes of the variation between pluripotent cell lines, researchers can account for those variables in disease research and regenerative medicine, isolating more stable cell lines and predicting propensities for differentiation.

Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help

Understanding and integrating multi-omic datasets requires comprehensive data storage and pipeline development expertise. As experts across data types from cutting-edge sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data
Bridge Informatics’ bioinformaticians have a strong background in bench research, so they understand the biological questions driving your analysis needs. From pipeline development and software engineering to deploying existing bioinformatic tools, Bridge Informatics can help you at every step of your research journey. Click here to schedule a free introductory call with a member of our team.



Jane Cook, Biochemist & Content Writer, Bridge Informatics

Jane Cook, leading Content Writer for Bridge Informatics, has written over 100 articles on the latest topics and trends for the bioinformatics community. Jane’s broad and deep interdisciplinary molecular biology experience spans developing biochemistry assays to genomics. Prior to joining Bridge, Jane held research assistant roles in biochemistry research labs across a variety of therapeutic areas. While obtaining her B.A. in Biochemistry from Trinity College in Dublin, Ireland, Jane also studied journalism at New York University’s Arthur L. Carter Journalism Institute. As a native Texan, she embraces any challenge that comes her way. Jane hails from Dallas but returns to Ireland any and every chance she gets. If you’re interested in reaching out, please email jennifer.martinez@old.bridgeinformatics.com or dan.ryder@old.bridgeinformatics.com.

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