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UK funding (£128,215): Using planarians and single cell transcriptomics to study cell type evolution Ukri1 Mar 2024 UK Research and Innovation, United Kingdom

Overview

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Using planarians and single cell transcriptomics to study cell type evolution

Abstract Animals and other multicellular organisms are made of cells that can be classified into different "cell types". Often cell types are deeply conserved in evolution: for instance, all bilaterian animals seem to have muscle cells. These seem to have evolved from a cell type present in their last common ancestor. This is supported by the resemblance between their structural components but also their common gene regulation. Not only muscle, but also neurons, epidermis and other cell types seem to be conserved in most animals. However, we also know that there are cell types in some groups with no obvious equivalent in others. For instance, homologues of vertebrate immune cells (e.g. B cells or T cells) are difficult to identify in non-vertebrate types. How did this diversity of cell types emerge across evolution? Do all animals have the same cell types? Alternatively, do new cell types arise frequently in evolution? Do cell types vary only across phyla, or also within the same phylum? Several models of cell type evolution have been proposed. For instance, cell types could arise due to duplication of an original cell type. Then, one of the duplicated types specialises in a different function, while the other keeps the original function. A described example of this are a type of electroreceptor cells in fish that has diversified from hair cells. Other authors propose that novel expression of a new group of genes can lead to the creation of novel cell types. For instance, cells could express some genes under stress to enable new functions, but then if this expression becomes independent of stress it gives rise to a new cell type. Ultimately, the mechanisms by which cell types evolve and new cell types emerge are largely unknown. This is primarily due to a lack of techniques to profile them. Cell types are typically identified by markers (protein or RNA), but these are unknown in many species. Thus, cell type comparisons have been extremely challenging. In recent years, however, a novel technique called single cell transcriptomics (scRNA-seq) has allowed us to study the gene expression profiles of cells, enabling their classification in cell types by unbiased mathematical approaches. Using scRNA-seq we can sequence individual mRNAs, for thousands of individual cells. This allows us to classify them in types, since they express different mRNAs. Single-cell transcriptomics has already been applied to a broad range of animals and will therefore revolutionise our understanding of cell type evolution. Even harnessing single-cell transcriptomics methods, comparing highly divergent species (i.e. from different animal groups) is challenging, due to the sheer phylogenetic distance that hinders the identification of genes that are equivalent across species. To begin to address the mystery of cell type evolution, I propose to compare closely related species. This is a promising way to first develop the computational comparison of cell types to then understand differences from species to species. We expect that they will share a large set of cell types, and this will allow us to fine tune the mathematical algorithms used for comparison. Planarians are an exceptional model to perform this research since they can constantly generate all adult cell types. Thus, here I propose to study by scRNA-seq a collection of planarian species, to then identify their shared cell types, as well as any lineage specific cell type, and analyse their differences by functional studies. We will then study the similarities and dissect the differences by inhibiting the genes that underlie them. This will light the way of studying cell type evolution in other animal groups and lead to an understanding of cell types, the building blocks of all multicellular organisms.
Category Research Grant
Reference BB/V014447/2
Status Closed
Funded period start 01/03/2024
Funded period end 22/05/2025
Funded value £128,215.00
Source https://gtr.ukri.org/projects?ref=BB%2FV014447%2F2

Participating Organisations

UNIVERSITY OF EXETER

The filing refers to a past date, and does not necessarily reflect the current state. The current state is available on the following page: University OF Exeter, Exeter.