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Learning from the past: linking ancestral epigenetic states to current cellular fates with single-cell multi-omic approaches

Periodic Reporting for period 2 - FateID (Learning from the past: linking ancestral epigenetic states to current cellular fates with single-cell multi-omic approaches)

Okres sprawozdawczy: 2023-04-01 do 2024-09-30

Biological systems and pathologies like cancer are comrpised of a heterogeneous mixture of cells with diverse identities and functions. To understand the full functioning of such complex biological systems, new methods are required that have the cacacity to measure gene-regulation in single cells. To achieve this, we develop methods that have the sensitivity to measure nuclear processes in single cells. Previously, based on an ERC-StG, we have developed the first methods to profile one layer of epigenetics and transcriptomics in the same cell. Currently, for this proposal we plan to achieve mapping many layers of gene-regulation in single cells. This will provide us with information on the interdependencies and hierarchies of various components that coorinately regulate gene expression. We implement these technologies in preimplantation development to obtain insight into the epigenetic states that comprise totipotency. Such knowledge is indispensable to pave the way for the development of new tissue-regeneration approaches to more efficiently generate patient-derived tissues and organs.
For workpackage 1 we aimed to develop a new technology to map many epigentic profiles in the same single cell. We achieved this in the first period and we have submitted a manuscript for publication to the journal Nature Methods. This work is in revision currently.

For workpacge 2 we aim to develop a molecular timemachine to track a cells epigenetic history over prolonged periods of time in development. We are currently in the process of testing the different options outlined in workpackege 2 and with the finalization of the work for wp1 this aim will be a major focus for the next reporting period.

For workpackage 3, we have implemented our single-cell technologies in mouse preimplantation development and uncovered an interrelationship between large domains of H3K27me3 and atypical genome nuclear positioning at the totipotent 2-cell stage. Removal of these large H3K27me3 domains renders spatial genome positioing to a conventional state and also alleviates a stong bias in allelic genome organization normally seen. We are currently investingating the mechanistic underpinning and biological implications of these findings further. This work has been submitted for publication at Nature Genetics. We are currently working on a revised manuscript.

Finally, also for workpackage 3, we have further optimized and developed a method to profile two epigentic features from the same cell. A unique feature of this combination is that it introduces an epigentic time axis which was not possible before with excisting technologies. As a proof-of-concept we are currently implementing this technology to study X-chromosome inactivation and we plan to submit this work for publication in june 2023. Next, we plan to inplement this method in preimplantaion development to understand the epigenetic mechanisms that govern the first lineage decision in life (to become part of the embryo proper or the extra embryonic material).

In summary, we are well on schedule for completing the research project as it is described in the original research proposal.
-We have developed a novel technology to profile many epigenetic signatures (so far 6) in the same cell. This is unprecented and we will continue developing this technology further during the next period of the project. The objectives for the development will be to 1) increase the information content per epigenetic layer (more unique reads/cell), 2) profile more epigenetic features jointly in the same cell, 3) include transcriptomics. We have filed a patent for this method (PCT/NL2022/050635).

-We have developed a method to measure at high resolution two epigenetic profiles in the same cell. Unique about this combiunation of measurements is that it introduces a time axis. This allows making better preditions on cellular behaviour because this method provided information on the past state of a cell while knowinng its current identity. This is unprecedented and we plan to develop this further in the next period. The focus will be on combining this method with the development of the molecular timemachine described in workpackage 2 and to include transcriptomics.

-We have implemented our methods into preimplantation development. This resulted into the first single-cell epigenetic profiles, and at allelic resolution, of the epigenetic states that govern early development. Insight into the chromatin mechanisms that shape the totipotent epigenome are important because these cells can give rise to all cell types. Such knowledge could contribute to more efficient reprogramming of patient-derived cells to establish in vitro organs and tissues. We will continue working on this topic to further understand the epigenetic mechanisms that govern a totipotent state and that contribute to the regulation of the first lineage decision in life.
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