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Computer model IDs roles of individual genes in early embryonic development

Computer model IDs roles of individual genes in early embryonic development
CellOracle KO simulation with zebrafish embryogenesis data. a, Two-dimensional force-directed graph of the axial mesoderm (AM) sub-branch (n = 1,669 cells) in a published zebrafish embryogenesis atlas (Farrell et al). Arrows indicate notochord cell differentiation (top) and prechordal plate differentiation (bottom). b, Conversion of URD-calculated pseudotime (left) into a 2D pseudotime gradient vector field (right). c, Degree centrality scores were used to rank the top 30 TFs in notochord (left) and prechordal plate (right). Black text denotes TFs. Gray text denotes non-TFs. d, Expression of noto projected onto the axial mesoderm sub-branch. e, Noto KO simulation vector and perturbation scores. f, Markov simulation to estimate cell density in the noto KO sample. The simulation predicted inhibited early notochord differentiation and promotion of prechordal plate differentiation, indicating a potential lineage switch. Credit: Nature (2023). DOI: 10.1038/s41586-022-05688-9

Computer software developed at Washington University School of Medicine in St. Louis can predict what happens to complex gene networks when individual genes are missing or dialed up more than usual. Such genetic networks play key roles in early embryonic development, guiding stem cells to form specific cell types that then build tissues and organs. Mapping the roles of single genes in these networks is key to understanding healthy development and finding ways to regrow damaged cells and tissues. Likewise, understanding genetic errors could provide insight into birth defects, miscarriage or even cancer.

Such genetic experiments—typically conducted in the laboratory in animal models such as mice and zebrafish—have been a mainstay of developmental biology research for decades. Much can be learned about a gene's function in animal studies in which a gene is missing or overexpressed, but these experiments are also expensive and time-consuming.

In contrast, the newly developed software called CellOracle—described Feb. 8 in the journal Nature—can model hundreds of genetic experiments in a matter of minutes, helping scientists identify key that play important roles in development but that may have been missed by older, slower techniques. CellOracle is , with the code and information about the software available here.

"The has collected enough data from that we now can do more than observe biology happening—we can build computer models of how genes interact with each other and predict what will happen when one gene is missing," said senior author Samantha A. Morris, Ph.D., an associate professor of developmental biology and of genetics. "And we can do this without any experimental intervention. Once we identify an important gene, we still need to do the lab experiments to verify the finding. But this computational method helps scientists narrow down which genes are most important."

CellOracle, which was included in a recent technology feature in the journal Nature, is one of a number of relatively new software systems designed to model insights into cellular gene regulation. Rather than simply identify the networks, CellOracle is unique in its ability to let researchers test out what happens when a network is disrupted in a specific way.

Software developed at Washington University School of Medicine in St. Louis can predict what happens to complex gene networks when individual genes are disrupted in specific ways. Shown on the left is a representation of the development of normal zebrafish axial-mesoderm cells, which form a precursor to the spine. The right animation shows what happens when a single key gene in this development pathway is disrupted. Credit: Washington University School of Medicine in St. Louis

Morris and her team harnessed the well-known developmental processes of blood cell formation in mice and humans and embryonic development in zebrafish to validate that CellOracle works properly. Their studies, in collaboration with the lab of co-author and zebrafish development expert Lilianna Solnica-Krezel, Ph.D., the Alan A. and Edith L. Wolff Distinguished Professor and head of the Department of Developmental Biology, also uncovered new roles for certain genes in zebrafish development that had not previously been identified.

And in a related paper published in the journal Stem Cell Reports, Morris and her colleagues used CellOracle to predict what happens when certain genes are dialed up beyond their usual expression levels.

"We found that if we dialed up two specific genes, we can transform skin into a type of cell that can repair damaged intestine and liver," Morris said. "In terms of regenerative medicine, these predictive tools are valuable in modeling how we can reprogram cells into becoming the types of cells that can promote healing after injury or disease."

According to Morris, most laboratory methods for converting into different cell types, such as blood cells or liver cells, are inefficient. Maybe 2% of the cells arrive at the desired destination. Tools like CellOracle can help scientist identify what factors should be added to the cocktail to guide more cells into the desired cell type, such as those capable repairing the gut and liver.

At present, CellOracle can model cell identity in more than 10 different species, including humans, mice, zebrafish, yeast, chickens, Guinea pigs, rats, fruit flies, roundworms, the Arabidopsis plant and two species of frog.

"We get a lot of requests to add different species," Morris said. "We're working on adding axolotl, which is a type of salamander. They are cool animals for studying regeneration because of their ability to regrow entire limbs and other complex organs and tissues."

More information: Kenji Kamimoto et al, Dissecting cell identity via network inference and in silico gene perturbation, Nature (2023). DOI: 10.1038/s41586-022-05688-9

Kenji Kamimoto et al, Gene regulatory network reconfiguration in direct lineage reprogramming, Stem Cell Reports (2022). DOI: 10.1016/j.stemcr.2022.11.010

Journal information: Stem Cell Reports , Nature

Citation: Computer model IDs roles of individual genes in early embryonic development (2023, February 10) retrieved 18 July 2024 from
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