Introduction
Whilst being mostly studied in the context of diseases, somatic mutations are fundamental to normal physiological function in plants and animals. Investigating the functional relevance of cellular heterogeneity in non-model systems requires adaptation of experimental and computational protocols and development of novel approaches for reusing and integrating existing data, but this is prevented by the current state of metadata annotations and high heterogeneity of public datasets. Our aims are to develop innovative single-cell approaches to address those needs.
Explaining the science
In multicellular organisms, transcriptional, epigenetic and even genetic heterogeneity emerges as a consequence of cell
division, differentiation and response to environmental stimuli. This cellular heterogeneity is fundamental to organism-level function and phenotype. CELLGEN aims to investigate the functional impact of cellular genomic and transcriptomic heterogeneity in healthy plants and animals
Project aims
We aim to:
- Develop a data science ecosystem to enable interpretation, sharing, reuse, and integration of single-cell datasets.
- Investigate the origin and functional consequences of somatic variation.
- Characterise cell expression heterogeneity during development and environmental response
Applications
WP1 will develop data science approaches to enable and deliver FAIR single-cell data. We will develop novel metadata
standards, automatically enrich, and annotate metadata, and extend our data brokering solutions to single-cell data. We will develop pipelines for reproducible handling of single-cell data, bias correction, and facilitate data integration.
WP2 will investigate the diversity and consequence of somatic variation in healthy systems. We will develop long read
sequencing methods to accurately genotype highly mutable repeats. We will use cell systems to test the impact of
polyploidization on the genome and repeat stability, and expression regulation. We will apply our developments to in vivo
highly polyploid plants and mammalian cells, and relate somatic variants to phenotypes in clonal crops.
WP3 will characterise cellular transcriptomic heterogeneity and its impact on cell and whole-organism response to
environment. We will apply single-cell multiomics developments in plant and animal to reconstruct single-cell gene and
transcript regulatory networks to investigate their rewiring during differentiation, and upon environmental variation.
CELLGEN will deliver novel approaches for cellular functional omics, linking advanced computational and experimental
analyses with metadata curation and data integration. This will improve our understanding of the regulation of gene
expression, and provide an understanding of the cellular mechanisms underpinning organismal adaptation to changing
environments in plants and animals during the healthy lifespan
Recent updates
This project is led by the Earlham Institute, with collaboration from The Alan Turing Institute, UK Health Security Agency, and the Sainsbury Laboratory at the University of Cambridge - bringing expertise in machine learning approaches, mathematical modelling, and bioinformatics - as well as breeding and technology leaders including WorldFish, PacBio, and Oxford Nanopore Technologies.
Recent press release from Earlham Institute: https://www.earlham.ac.uk/news/earlham-institute-BBSRC-funding-award-2023
Organisers