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Although our knowledge of human cells and tissues has steadily increased in recent decades, many things remain unknown. For example, cells exist in transient and dynamic states and their understanding is fundamental for deciphering diseases and finding remedies. Conventional laboratory techniques for studying cell types were limited and did not provide a finely detailed profile of cell function.
To overcome this obstacle, a group of scientists from the National Center for Genomic Regulation (CRG) of the National Center for Genomic Analysis (CNAG-CRG) in Barcelona (Spain), led by Holger Heyn, has developed a new tool computer science, based on the mathematical graph theory, to infer large-scale global regulatory networks, from healthy and pathological organs, such as those affected by diabetes or Alzheimer's disease. The researchers were able to identify genes relevant to the functioning of organs and potential disease factors. They publish their results in the last issue of Genome biology newspaper.
Our previously developed single-cell transcriptomic tools were very useful for discovering unknown cell types. These tools allowed us to describe new cell types and subtypes, with their unique biological roles and hierarchical relationships. "
Giovanni Iacono, senior postdoctoral researcher at CNAG-CRG and first author of the study
Until now, unicellular badysis had been used to understand cell types and their function in tissues. "Large-scale consortia such as the Human Cell Atlas Project generate whole-body single-cell maps, and sophisticated badysis strategies are needed to transform Big Data into biological and clinical disturbance data," he said. Holger Heyn, leader of the CNAG-CRG unicellular genomic research group and lead author of the article.
The tool that this scientific team has now developed will allow them to go further and understand how genes interact to form tissues. "Our tool attempts to accurately deal with the regulatory process that controls the morphology and functions of a cell," Iacono emphasizes.
The tool is based on graph theory, an abstract mathematical model in which there are nodes connected by edges. Once you have a graph, a structure, you can measure the importance of each node for the network. In this case, each node was a gene and its importance was defined as the function of this gene being essential for the biological system studied.
CNAG-CRG researchers have processed datasets from ten thousand cells in order to deduce the regulatory networks that govern cell phenotype formation and their respective functions. They applied their tool to the study of type 2 diabetes and Alzheimer's disease and were able to detect the relevant functional changes for these diseases. Importantly, this opens the door to new drug targets.
"The network badysis that we have developed goes beyond the approaches currently applied to provide in-depth information on how gene activities shape tissues and organs." This is essential for understanding the diseases in which these activities occur. Networks are disrupted and find their "Achilles' heels" for effective treatments. " Heyn said.
Potentially, the tool can be applied to any disease, from Alzheimer's disease to chronic lymphocytic leukemia. "We will use our tool to propose new target genes for many diseases, which can then be validated in further studies." Iacono declares.
Source:
Genome Regulatory Center (CRG)
Journal reference:
Heyn, H. et al. (2019) The monocellular transcriptomics unveils the plasticity of the gene regulation network. Genome biology. doi.org/10.1186/s13059-019-1713-4.
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