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4D-OMICS

Construire un instrument numérique régional pour la biologie quantitative multi-échelle
Pascal Barbry

Omics Data Integration Network

Fédérer un réseau de bio-informaticiens en appui à la recherche des équipes d’Université Côte d’Azur
Kevin Lebrigand

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High throughput error corrected Nanopore single cell transcriptome sequencing

Droplet-based high throughput single cell sequencing techniques tremendously advanced our insight into cell-to-cell heterogeneity. However, those approaches only allow analysis of one extremity of the transcript after short read sequencing. In consequence, information on splicing and sequence heterogeneity is lost. To overcome this limitation …

Citation: Lebrigand K. et al (2020) "High throughput error corrected Nanopore single cell transcriptome sequencing" Nature Communications https://www.nature.com/articles/s41467-020-17800-6

The spatial landscape of gene expression isoforms in tissue sections

In situ capturing technologies add tissue context to gene expression data, with the potential of providing a greater understanding of complex biological systems. However, splicing variants and full-length sequence heterogeneity cannot be characterized at spatial resolution with current transcriptome profiling methods. To that end, we introduce spatial isoform transcriptomics (SiT)…

Citation: Lebrigand K. et al (2023) "The spatial landscape of gene expression isoforms in tissue sections" Nucleic Acids Research https://academic.oup.com/nar/article/51/8/e47/7079641

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