Missions

All marine ecosystems are supported by a diverse range of eukaryotic algae, essential to their food chains. Amongst these, several groups (diatoms, haptophytes, dinoflagellates, pelagophytes) stand out, from their abundance and their importance to global primary production. These highly abundant algal groups possess chloroplasts derived from the secondary or higher endosymbiosis of a eukaryotic red alga, which themselves are strikingly rare in the contemporary ocean. In contrast, green algae, particularly the diverse groups that form the Prasinophyta, are important players in marine ecosystems, but their evolutionary, genetic and functional diversity remain poorly understood.

Recent genomic studies have shown that diatoms, and other abundant algae with secondary red chloroplasts, also contain large numbers of genes derived from green algae. These genes seem to be important for supporting their chloroplast biology, and contributing to their biology in the wild. The timing, extent and functional consequences of these cryptic green signals remains poorly understood, however, particularly due to the absence until recently of detailed genetic information for many taxonomically important Prasinophyta groups. In parallel, the expansion of both cultured and meta-genomic data for many secondary red algal species, particularly the model diatom Phaeodactylum, offers new windows for understanding the function of these green genes at a purely computational level.

References :

Dorrell and Smith, Do red and green make brown? Perspectives on plastid acquisitions within chromalveolates, Euk Cell (2011) https://journals.asm.org/doi/10.1128/EC.00326-10

Dorrell et al, Chimeric origins of ochrophytes and haptophytes revealed through an ancient plastid proteome, eLife (2017) https://elifesciences.org/articles/23717

Villar et al, DiatOmicBase: a versatile gene‐centered platform for mining functional omics data in diatom research, Plant J (2025) https://onlinelibrary.wiley.com/doi/10.1111/tpj.70061

Activités

This project will aim to create a census of green genes associated with secondary red chloroplast groups, availing of the expanded repertoire of primary and secondary red and green algal genomes that have become available in the last five years. Particular interest will be to integrate metagenome-assembled genomes (MAGs) from Tara Oceans, which include multiple deep-branching and as yet uncultured Prasinophyta groups, into our understanding of the time and extent of these signals. A second question may involve tracing the extent of gene transfer from primary red algae into secondary red algal groups, to ascertain why this signal is functionally supplemented by genes of green algal origin. In both cases, gene signals will be evaluated by orthology searches and high-throughput phylogenetic (supertree) approaches, and plastid-associated proteins will be assessed by in silico localization.

The functions of validated green genes will be assessed, with a particular focus on mature genetic resources for Phaeodactylum and other diatoms. These may include extablishing gene expression trends in response to different physiological conditions in published Phaeodactylum RNA data, and expression in wild diatoms using meta-genomic information from Tara Oceans. If desired, the candidate can also establish collaborations with other groups at the CQSB, working variously on computational models of domain evolution, protein structural interactions, and protein mutational landscapes, to predict probable functions of each green protein in silico.

Compétences

- A prior knowledge of algal taxonomy and evolution is essential
- Prior experience of bioinformatics, including multiple scripting and programming tools (bash, python, R) is essential
- Prior experience of high-throughput phylogenetic analysis, including automated tree sorting and supertree approaches, is essential
- Willingness to exchange oral and written English and French are strongly desired, to allow collaborations both internationally and within the host institution
- Prior experience in the application of AI techniques to specific bioinformatic questions, e.g. in silico protein localization, is strongly desired
- Prior experience of meta-genomics, transcriptomics, or computational structural biology analyses, are all welcomed but not essential

Contexte de travail

CQSB - UMR 7238 CNRS- Sorbonne University

The CQSB is an interdisciplinary laboratory working at the interface between biology and quantitative sciences. It is built to promote a balanced interaction of theoretical and experimental approaches in biology, and to foster the definition of new experimental questions, data analysis and modeling of biological phenomena. Our projects address questions about biological structures and processes through the collection of experimental measurements, the in silico generation of new biological data that today remain inaccessible to experiments (modeling of biological systems), the development of statistical methods for data analysis, and the design of original algorithms for prediction. The laboratory is supported by the CNRS and Sorbonne University.

The CQSB is one of the laboratories of the Institut de Biologie Paris-Seine (IBPS).

Location (Management/Department) :
UMR 7238 CNRS - Sorbonne Université Campus Jussieu
Bât. C - 4th floor
4, place Jussieu
75005 Paris, France

Contraintes et risques

This post can be partly performed via homeworking.