Mots-Clés

cancer, epigenomic, genomics, genetics, bio-informatics

Description

Titre

ATAC-seq as a versatile tool to probe cancer-driving mutations, chromosomal rearrangements, and genetic instability

Description de l’offre

First introduced in 2013, the assay for transposase-accessible chromatin with sequencing (ATAC-seq) is a popular method routinely used as a cost-effective and easy-to-set-up technic to identify regulatory elements throughout the epigenome and quantify their activity. With recent advances in bio-informatic and machine learning, it is nowadays commonplace to extract additional invaluable additional information from ATAC-seq data, enabling nucleosome mapping, transcription factor digital footprinting or to predict chromatin topologically associating (TADs) and lamina-associated domains (LADs). Nevertheless, most of these advances does not take advantage of the DNA sequence information contained in ATAC-seq data. In modern medical oncology, the precise characterization of the tumor genetic landscape, chromosomal abnormalities and genetic instability is emerging as the gold standard to adapt the therapeutic protocols and move towards personalized medicine. However, this in-depth genetic characterization relies on the combination of expensive molecular assays such as whole genome / exome sequencing, comparative genomic hybridization arrays, spectral karyotyping, or multicolor fluorescence in situ hybridization. Carrying both structural and DNA sequence information at the base-pair resolution, ATAC-seq might therefore stand as an all-in-one substitute to these tests. Relying on the massive data compendium collected in the scope of The Cancer Genome Atlas (TCGA), the intern will used matched bulk paired-end ATAC-seq data, whole genome / exome sequencing data and whole-genome genotyping array data to 1) evaluate the sensitivity and specificity of ATAC-seq in defining the mutational landscape at known and relevant cancer-driving loci using standard SNPs and CNVs calling algorithms, 2) develop a strategy to precisely identify large-scale karyotypic abnormalities and chromosomal rearrangements using paired-end ATAC-seq data, and 3) adapt algorithms used so far on whole-genome / exome sequencing data to quantify genetic instability and loci amplification and depletion. These approaches will finally be applied on in-house ATAC-seq data to characterize human tumors.

A background in genomics and sequence bio-informatics are required.

Secteurs d’activité

cancer, epigenomic, genomics, genetics, bio-informatics

Compétences à acquérir ou à développer

The successful candidate will acquire skills in cancer genetics, bio-informatics, bio-statistics and machine learning, and will benefits from the expertise of his supervisor in sequence bio-informatics, big data analysis and integration, R & UNIX programming and super-computing.

Activités du stagiaire

The successful candidate will be involved in the laboratory research program, aiming at characterizing the molecular mechanisms underpinning aging and oncogenesis, and will join a cohesive team with transversal skills. The candidate will benefit from technical and scientific support in a stimulating environment ideal to develop her/his scientific mindset.

Contact

Pierre-François ROUX, PhD

pierre-francois.roux@inserm.fr

Équipe de Laurent Le Cam - Oncogenèse moléculaire

Institut de Recherche en Cancérologie de Montpellier

https://pierre-francois-roux.com