Mots-Clés
microproteins, aging, molecular innovation, noncoding genome, OMICS analyses
Description
Context: Genomes are traditionally divided into coding and noncoding regions, yet recent discoveries reveal that noncoding regions can also give rise to small proteins, called microproteins, produced from short open reading frames (sORFs)[1-3]. Although they were overlooked for a long time because they are tiny and expressed at low levels, recent OMICS technologies have uncovered thousands of these new microproteins in organisms ranging from bacteria to mammals. Some are functional, contributing to cell signaling, stress response, or antibiotic resistance, while others are linked to human diseases such as cancer and neurodegeneration [3-4]. In some cases, these microproteins even become established as new genes (de novo), illustrating how noncoding regions can serve as a source of biological innovation [5-7].
Despite growing interest, the conditions and mechanisms driving microprotein expression remain poorly understood, especially under physiological transitions such as aging. Aging provides an ideal framework to explore this question, as it is accompanied by transcriptional and translational dysregulation, a decline in RNA surveillance and protein quality control, and an increased incidence of neurodegenerative diseases [8-9]. Such changes could favor the translation of cryptic or noncanonical sequences, potentially revealing new, age-related microproteins whose functions remain unexplored.
Objectives: In this project, conducted within a collaborative consortium at I2BC that combines experimental and computational teams, we will investigate how aging reshapes the microproteome of C. elegans. The nematode provides an ideal model for studying the impact of aging on the microproteome, since both RNA and protein quality control have been shown to decline with age [10]. The candidate will analyze Ribo-seq datasets generated by our collaborators from young (day 1 adults) and old (day 9 adults) worms to detect novel translated microproteins and analyze how noncanonical translation changes during aging. The project will rely on an original combination of two in-house developments from the team: (i) a k-mer-based computational approach that infers translated ORFs directly from sequencing data, independently of genome annotation [11], and (ii) a Ribo-seq protocol optimized for short and noncanonical ORFs [1].
The intern will apply and refine these methods to uncover microproteins arising from RNA rearrangements such as trans-splicing or mis-splicing events, assess their sequence features, and compare their occurrence and translation signatures across age groups. Depending on progress and interest, selected candidates may then be analyzed for structural properties using our deep-learning prediction methods and experimentally characterized by our collaborators.
This project offers a unique opportunity to explore how aging and RNA dysregulation contribute to proteome diversification, at the crossroads of genomics, evolution, and molecular biology, within a stimulating and complementary research environment.
Environnement: The internship will take at the Institute for Integrative Biology of the Cell (I2BC). Our team brings together a wide range of complementary bioinformatics expertise and includes many young researchers (PhD students, engineers), providing an ideal and dynamic environment for early-career researchers. We are located in the new buildings of the I2BC, south of Paris, on the historic and green campus of the CNRS. The I2BC is a recent and highly dynamic institute with around 700 people, including about 150 PhD students and postdoctoral researchers. The project will benefit from the broad range of expertise and techniques already available at the I2BC, as well as from the strong network of collaborations we have developed with experimentalists specialized in transcriptomics, Ribosome Profiling, mass spectrometry and structural characterization.
Required Technical Skills: Programming (mandatory). Skills in OMICS, genomics, statistics, and artificial intelligence are a plus.
References:
[1] Papadopoulos C, Arbes H, Cornu D, Chevrollier N, Blanchet S, Roginski P, Rabier C, Atia S, Lespinet O, Namy O, Lopes A. The Ribosome Profiling landscape of yeast reveals a high diversity in pervasive translation. Genome Biology, 2024, 25, 268
[2] Patraquim P, Magny EG, Pueyo JI, Platero AI, Couso JP. Translation and natural selection of micropeptides from long non-canonical RNAs. Nature Communications. 2022; 13:6515
[3] Wacholder A, Parikh SB, Coelho NC, Acar O, Houghton C, Chou L, et al. A vast evolutionarily transient translatome contributes to phenotype and fitness. Cell Systems. 2023; 14:363-381.e8
[4] Chen J et al. Pervasive functional translation of noncanonical human open reading frames. Science. 2020; 367, 1140–1146
[5] Carvunis A.-R. et al. Proto-genes and de novo gene birth. Nature. 2012; 487, 370–374
[6] Roginski P, Granchamp A, Quignot C, Lopes A. De Novo Emerged Gene Search in Eukaryotes with DENSE. Genome Biology and Evolution, 2024, 16, 8, evae159
[7] Papadopoulos C, Callebaut I, Gelly JC, Hatin I, Namy O, Renard M, Lespinet O, Lopes A. Intergenic ORFs as Elementary Structural Modules of de Novo Gene Birth and Protein Evolution. Genome Research. 2021; 2303–2315
[8] Arif M et al. Global and tissue-specific transcriptomic dysregulation in human aging: Pathways and predictive biomarkers. GeroScience (2025) doi:10.1007/s11357-025-01672-z
[9] Bartz J, Jung H, Wasiluk K, Zhang L & Dong X. Progress in Discovering Transcriptional Noise in Aging. Int. J. Mol. Sci. 2023; 24, 3701
[10] Kwon HC, Bae Y, Lee SV. The Role of mRNA Quality Control in the Aging of Caenorhabditis elegans. Mol Cells. 2023; 46(11):664-671
[11] Xue H, Gallopin M, Marchet C, Nguyen HN, Wang Y, Lainé A, Bessiere C, Gautheret. DKaMRaT: a C++ toolkit for k-mer count matrix dimension reduction. Bioinformatics. 2024; 40, btae090