Job offer details
Postdoc position in human comparative genomics
Ancient and modern human comparative genomics to learn about
adaptation, genes, and culture
Are our genomes helping us to adapt better to climate and nutritional changes? In this project, we will analyse archaic genomes to extract genomic signals connected to climate adaptation and to nutrition, will analyze the same signals in genomes from modern populations, and will finally integrate these data into a comparative analysis. Within the large spectrum of structural variations in the human genome, we shall look at gene copy number variations (CNV) aiming to demonstrate that they are reference indicators of past and modern human dietary strategies.
The postdoctoral fellow will participate:
1. in the selection of available genomes from the specimens of Denisova, Neandertal, early and late Homo sapiens (HS) and of modern populations originating from different regions worldwide and based on available databases.
2. in the design and implementation of the pipeline that will prepare the genomic data. A number of technically important steps need to be realized to ensure statistically sound results.
3. in a large-scale CNV screening from which to extract all relevant genes showing a differential CNV in the genomes of Denisova, Neandertal, late and early HS and in the statistical (gene function enrichment) analysis of biological processes which are expected to differentiate ancient populations with respect to their gene CNV. Time, climate, geographic localization and functional classification will be parameters stratifying genome analysis used to emit hypotheses on the adaptation of these populations to the environment.
4. in a large-scale data analysis of differential gene CNV, similar to that realized for ancient populations, of genomes from modern populations living in different climatic conditions and geographic regions.
5. in the extraction of genetic information from these large-scale analysis leading to a comparative analysis among modern populations and early HS spanning chronologically the period from the Neolithic to modern populations living in comparable or different climatic conditions.
6. In the construction of a dedicated database made available to the international community and collecting the comparative analysis and the data gathered. These genomic data are expected to go far behind the interests of this project.
This project will provide a unique opportunity to do interdisciplinary work in genomics in tight interaction with archeologists and anthropologists. We confront Neandertals and Denisovans to late and early HS in (i) biology (anatomical variations and timing of growth and development, morphological variation in teeth, dental microwear and oral pathology, as well as body proportion changes), (ii) genomics (Copy Number Variations expressing enzymes for starch metabolization and others) and (iii) behaviour (emergence of grinding stones).
We look for a postdoctoral candidate from the field of bioinformatics or computer science with an experience in genomics, read mapping and NGS data analysis.
Sorbonne Université (SU, www.sorbonne-universite.fr) is a fully multidisciplinary research-intensive university, located in several campuses at the heart of Paris. Sorbonne Université covers all major disciplinary fields and offers transversal academic and research programs with three faculties: Humanities and Social Sciences, Medicine and Sciences & Engineering, bringing together the best talents in a wide array of these disciplines. With more than 55 600 students (among 10 200 international students), 4700 doctoral students and 6400 researchers, Sorbonne Université is one of the leading French universities.
The Computational and Quantitative Biology unit, SU-CNRS UMR7238, offers a multidisciplinary work environment made up of a part of experimenters (genetics and synthetic biology) and a part of theorists (computer science, mathematics, physics), around several themes: evolution, genome and population dynamics, regulatory networks, structural bioinformatics, environment, modeling of complex biological systems, synthetic biology and protein engineering. Further information can be found at www.lcqb.upmc.fr
The Analytical Genomics team at LCQB works on various problems connected with the functioning and evolution of biological systems. We use mathematical concepts, coming from statistics and combinatorics, algorithmic and molecular physics approaches to study basic principles of cellular functioning starting from genomic data. Our projects aim at understanding the basic principles of evolution and co-evolution of molecular structures in the cell. They are intimately linked to each other. Applications are in medicine and environment.
Position: 2 years postdoctoral position starting from January 2021 or later.
Contact: Alessandra Carbone, email@example.com