Mots-Clés

Quantitative genomics QTL GWAS Insect

Description

The global population is estimated to reach approximately nine billion people by 2050, thus the demand for animal protein is expected to increase by 76% [1]. Such an increase questions the sustainability of our conventional food and feed production systems. At the same time, we also need to reduce the impact of agriculture on our environment [2]. Today, insect production is considered a sustainable alternative for food and feed production for several reasons. First, the suitable nutritional composition of edible insects [3] and second, the relatively low environmental impact its production involves compared to other conventional livestock production systems. 

The computational biology team led by Dr. Amin Madoui (https://madoui.github.io/) in the CEA François Jacob Institute of Biology in Fontenay-aux-Roses, France, is located 5 km from Paris and develops new research programs for human health and nutrition using high-throughput sequencing data and computational approaches to face new scientific challenges.

In the framework of the YnFabre project http://www.ynsect.com/en/ynsect-launches-ynfabre-the-worlds-first-industrial-programme-dedicated-to-beetle-genetics/, and in collaboration with private breeders, we offer a 2 years post-doctoral position to perform QTLs and GWAS analyses of complex traits in Tenebrio molitor to help our collaborators to better manage and improve the quality, environmental impact and yields of their production.

Mission and activity:

1. Analyze Illumina data to detect SNP, Indels and structural variants
2. Perform QTL, GWAS analyses and result interpretations
3. Lead the scientific article production and communication

Profile:

1. Programming in R and Python (or Perl)
2. Programming in Bash/Unix/Linux
3. Applied statistics
4. PhD in Quantitative genetics or/and genomics

[1] Alexandratos N, Bruinsma J: World agriculture towards 2030/2050: the 2012 revision. 2012

[2] Steinfeld H, Gerber P, Wassenaar T, et al.: Livestock’s long shadow. 2006.  

[3] Nowak V, Persijn D, Rittenschober D, et al.: Review of food composition data for edible insects. Food Chem. 2016; 193: 39–46.