Computer model IDs roles of individual genes in early embryonic
development
May provide insight into birth defects, miscarriage, cancer

Date:
February 10, 2023
Source:
Washington University School of Medicine
Summary:
Computer software can predict what happens to complex gene
networks when individual genes are missing or dialed up more than
usual. Mapping the roles of single genes in these networks is key
to understanding healthy development and finding ways to regrow
damaged cells and tissues.

Understanding genetic errors could provide insight into birth
defects, miscarriage or even cancer.


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FULL STORY ========================================================================== 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 genes that play important roles in development but that may have been missed by older,
slower techniques.

CellOracle is open source, with the code and information about the
software available at thislink.

"The scientific community has collected enough data from animal
experiments 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, PhD, 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.

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, PhD, 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 online 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
cells 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 stem cells 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."
* RELATED_TOPICS
o Health_&_Medicine
# Stem_Cells # Genes # Brain_Tumor
o Plants_&_Animals
# Developmental_Biology # Genetics # Biotechnology
o Computers_&_Math
# Computer_Modeling # Software # Computer_Programming
* RELATED_TERMS
o BRCA1 o BRCA2 o Cancer o Gene_therapy o Gene o
Introduction_to_genetics o Genetic_code o Human_genome

========================================================================== Story Source: Materials provided by
Washington_University_School_of_Medicine. Original written by Julia
Evangelou Strait. Note: Content may be edited for style and length.


========================================================================== Journal References:
1. Kenji Kamimoto, Blerta Stringa, Christy M. Hoffmann, Kunal Jindal,
Lilianna Solnica-Krezel, Samantha A. Morris. Dissecting
cell identity via network inference and in silico gene
perturbation. Nature, 2023; DOI: 10.1038/s41586-022-05688-9
2. Kenji Kamimoto, Mohd Tayyab Adil, Kunal Jindal, Christy M. Hoffmann,
Wenjun Kong, Xue Yang, Samantha A. Morris. Gene regulatory network
reconfiguration in direct lineage reprogramming. Stem Cell Reports,
2023; 18 (1): 97 DOI: 10.1016/j.stemcr.2022.11.010 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2023/02/230210185147.htm

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