Charles Plessy, open-source biologist

My training as a researcher started with developmental genetics in drosophila and zebrafish, where I studied the activity of transcription enhancers (Blader and coll., 2003) and their evolutionary conservation (Plessy and coll., 2005). This gave me a strong interest for whole-transcriptome analysis and technology. For that purpose, I have worked at RIKEN in 2004–18 on high-throughput methods for profiling promoters and inferring gene networks, and in particular on CAGE (Cap Analysis Gene Expression).

I have developed a miniaturized version of CAGE, termed nanoCAGE, to analyse small samples yielding only nanograms of RNA (Plessy and coll., 2010). In the same manuscript, we also introduced its paired-end variant, CAGEscan, which we use to associate novel promoters with annotations. Since then, we have kept improving or expanding these techniques, by updating the protocol (Salimullah and coll., 2011), reducing the sequence bias introduced by the molecular barcodes (Tang and coll., 2013), combining multiple cap-enrichment steps (Batut and coll., 2013), benchmarking the use of locked nucleic acids for template switching (Harbers and coll., 2013), reducing the number of primer artefacts and unwanted sequences generated by ribosomal RNAs using low-complexity “pseudo-random” reverse-transcription primers (Arnaud and coll., 2016), and screening for optimal parameters of the template-switching reaction (Poulain and coll., 2020).

In 2013–8, I lead a new development cycle at the Genomics Miniaturization Technology Unit in RIKEN's Center for Life Sciences, Division of Genomics Technology, to expand this work on single cells following a population transcriptomics approach (Plessy and coll., 2013) focused on sampling the largest possible number of cells. In our ongoing developments, we have reached single-cell and single molecule resolution through the introduction of transposase fragmentation and unique molecular identifiers (Poulain and coll., 2017). The protocol exists in two versions, one for FACS-isolated cells, and one for the Fluidigm C1 platform (Kouno and coll., 2019).

I have complemented my work on CAGE with the development of a gene-centred technique for detecting promoters, termed Deep-RACE (Olivarius and coll., 2009, Plessy and coll., 2012), which we used to validate our discovery of the pervasive expression of retrotransposons detected by CAGE (Faulkner and coll., 2009). To study transcription start activity at nucleotide resolution in zebrafish transfected with chimeric transgenes containing a copy of an endogenous promoter, I combined Deep-RACE, CAGE and paired-end sequencing in a technology that we called “Single-Locus CAGE” (Haberle and coll., 2014). With my contributions related to CAGE development and analysis, I have been a member of the FANTOM consortium since FANTOM3.

Together with my colleagues at RIKEN and collaborators in the field of neuroscience, I have applied nanoCAGE to the study of single neuron cell types, for instance the olfactory neurons (Plessy and coll., 2012), or in dopaminergic cells, where we could demonstrate the expression of haemoglobin in the midbrain (Biagioli and coll., 2009). We are also exploring the sub-cellular localisation of RNA in Purkinje neurons (Kratz and coll., 2014), and neurogenesis in the mouse olfactory epithelium using single-cell CAGE and ATAC-seq techniques. In parallel with this promoter-centric work, I have also explored the huge repertoire of the T cell antigen receptors. I also applied the nanoCAGE technology to patient samples infected with the human papillomavirus (HPV) (Taguchi and coll., 2020).

I joined OIST in 2018, to study the genetic structure and population variations of an animal plankton, Oikopleura dioica, that has a genome 50 time more compact than the human one, which empowers us to sequence at chromosomal resolution many individual sampled from all over the World. Its mitochondria use a different genetic code than ours (Pichon and coll., 2019). We assembled whole-chromosome sequences for the Okinawan O. dioica population (Bliznina and coll., 2020), which has 3 pairs of chromosomes (Liu and coll, 2020) like the other dioceous species.

I am also a Free Software enthusiast, and contribute to the Debian Med project, by packaging bioinformatics tools, which are redistributed in Debian (Möller and coll., 2010) and its derivatives such as Ubuntu and (cloud)Bio-Linux. For digital signature of my contributions and other activities as a OIST researcher, I use the GPG key number AE57EADA9D77898C5B064F15A59E8B5A44E7EABC. My ORCID ID is 0000-0001-7410-6295.