From: Charles Plessy Date: Mon, 15 Jun 2020 07:40:50 +0000 (+0900) Subject: CV en ligne. X-Git-Url: https://source.charles.plessy.org/?a=commitdiff_plain;h=f41a7b13d1c89d631f104bb785e302284a36d0fa;p=setup%2F.git CV en ligne. --- diff --git a/open-source-biologist.mdwn b/open-source-biologist.mdwn new file mode 100644 index 00000000..44cb7d05 --- /dev/null +++ b/open-source-biologist.mdwn @@ -0,0 +1,69 @@ +My training as a researcher started with developmental genetics in +drosophila and zebrafish, where I studied the activity of +transcription enhancers (Blader et al., 2003) and their evolutionary +conservation (Plessy et al., 2005). This gave me a strong interest for +whole-transcriptome analysis and technology. For that purpose, I have +joined RIKEN in 2004, where have worked 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 et al., +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 et al., 2011), +reducing the sequence bias introduced by the molecular barcodes (Tang +et al., 2013), combining multiple cap-enrichment steps (Batut et al., +2013), benchmarking the use of locked nucleic acids for template +switching (Harbers et al., 2013), and reducing the number of primer +artefacts and unwanted sequences generated by ribosomal RNAs using +low-complexity “pseudo-random” reverse-transcription primers (Arnaud +et al., 2016). + +On April 2013, I started a new development cycle as the leader of the +Genomics Miniaturization Technology Unit at RIKEN Center for Life +Sciences, Division of Genomics Technology, to expand this work on +single cells following a population transcriptomics approach (Plessy +et al., 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 et al., +2017). The protocol exists in two versions, one for FACS-isolated +cells, and one for the Fluidigm C1 platform (Kouno et al., 2019). + +I have complemented my work on CAGE with the development of a +gene-centred technique for detecting promoters, termed Deep-RACE +(Olivarius et al., 2009, Plessy et al., 2012), which we used to +validate our discovery of the pervasive expression of retrotransposons +detected by CAGE (Faulkner et al., 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 et al., 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 et al., 2012), +or in dopaminergic cells, where we could demonstrate the expression of +haemoglobin in the midbrain (Biagioli et al., 2009). We are also +exploring the sub-cellular localisation of RNA in Purkinje neurons +(Kratz et al., 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 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. + +I am also a Free Software enthusiast, and contribute to the Debian Med +project, by packaging bioinformatics tools, which are redistributed in +Debian (Möller et al., 2010) and its derivatives such as Ubuntu and +(cloud)Bio-Linux. For digital signature of my contributions and other +activities as a RIKEN researcher, I use the GPG key number +B3443334. My ORCID ID is 0000-0001-7410-6295.