Computational Analysis Platform for Single Cells
Funded since 2018
Purpose
Our infrastructure offers a bioinformatics service that enables researchers to generate, analyze, and share genomic data from individual cells following their isolation and the sequencing of their transcriptomes. This approach, better known as “Single-cell RNA sequencing” (abbreviated as scRNAseq), is useful for evaluating the transcriptome (polyA mRNA) of each living cell previously dissociated from retinas (or other organs of interest) at various stages of development, both in physiological and pathological contexts, regardless of the species whose genome is available (to allow alignment of sequencing data). With the advent of spatial transcriptomics, we can also support researchers in this field.
Service description
Our infrastructure is managed collaboratively, involving Dr. Joyal’s laboratory and student members of the Single-Cell Academy. This service is available to all researchers who are members of the VSRN.
Four types of services are offered:
- We provide consulting services for the preparation of individual cell samples dissociated from retinas (animal or human), as well as their sequencing through the sequencing platform supported by Génome Québec at CHU Sainte-Justine. Over the past year, we transitioned from DROP-seq to state-of-the-art technology supported by 10X Genomics, which enables the analysis of various “OMICS” modalities such as transcriptomics (scRNAseq) and epigenomics (scATACseq). This transition offers greater flexibility in the minimum number of cells required and experimental design (“cell hashing”). We also offer new technological innovations such as “spatial transcriptomics” and “Nanopore long-read sequencing.”
- The infrastructure also enables, in a second phase, bioinformatics analysis and interpretation of the data, as well as the complementary integration of publicly available data (“single-cell atlas”). This service will also be offered to network members who have obtained sequencing data from another center but have limited access to the services of a bioinformatician specialized in retinal/vascular biology. The currently available “in-house” data come from analyses performed on retinas of mice aged 5 to 17 days, under normal conditions or with retinopathy (OIR). The analyzed mice come from different genetic lineages (C57B6 WT and S129 WT). Other analyses can be conducted on samples of different ages and origins, following targeted cell dissociation and enrichment protocols.
- In a third phase, our infrastructure allows researchers to access single-cell data through a web interface (genap.ca). This web interface enables effective “datamining” of these shared databases, initially limited to network members, to provide a competitive advantage in developing new research questions, enhancing a manuscript in preparation, or preparing funding applications. The integration of single-cell analysis functions into GenAP was launched in 2020 and includes scRNAseq data repositories. These data, stored on Compute Canada servers, are easily accessible to all network researchers via login and password.
- Finally, the platform, through the Single-Cell Academy, supports the training of the next generation of bioinformaticians interested in vision research through a consortium of experts at Sainte-Justine Research Center and its partners. The Single-Cell Academy also provides an interface with the Quebec bioinformatics community, notably through its contribution to single-cell online meetings held every three weeks, bringing together Montreal researchers interested in single-cell technology.
Impact
Compared to traditional RNAseq (“bulk” RNAseq), scRNAseq technology allows for the evaluation of transcriptomic variations within a sample, which are due to the inherent cellular heterogeneity of living tissues. This technology represents a significant advancement in transcriptomic analysis and interpretation of cellular variability within a sample and is rapidly becoming the predominant tool for studying tissue gene expression.
Accessibility
This infrastructure is available to all researchers who are members of the RRSV. It is crucial to promote access to and use of published or soon-to-be-published data to encourage collaborations within the network and allow several laboratories to benefit from scRNAseq technology. This competitive advantage enables researchers to test their hypotheses in silico for funding applications and to enhance their manuscripts by leveraging existing bioinformatics data. New models could be analyzed using scRNAseq for larger-scale collaborative projects.
We are establishing a website that will provide privileged access to network members for our published (public access) or soon-to-be-published (private access) scRNAseq data. Each principal investigator (PI) can choose to grant access to a data repository under publication in the context of a collaboration. We believe that better data sharing could foster closer collaborations within our network.
Infrastructure administrator
Jean-Sébastien Joyal, MD, FRCPC, PhD, Assistant Professor, Department of Pediatrics, Accredited Professor, Department of Pharmacology, University of Montreal; Associate Professor, Department of Pharmacology and Therapeutics, McGill University, Pediatric Intensivist, CHU Sainte-Justine
Contact information
Gael Cagnone – gael.cagnone.1@gmail.com
Funding
Vision Sciences Research Network (VSRN)