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Join the Fruit Biology and Pathology unit (UMR 1332 BFP)! The UMR BFP is a major actor in plant biology research in the Nouvelle-Aquitaine region, in partnership between the Biology and Plant Improvement (BAP) and Plant Health and Environment (SPE) departments of INRAE and the Environmental Sciences department of the University of Bordeaux.

As part of the Bordeaux Plant Sciences Major Research Program (GPR BPS), we are recruiting a Post-Doctoral Researcher whose work will focus on the fitness of woody plants in the face of global change: using genomic resources to increase productivity and resilience.

Main activities:

The Bordeaux Plant Sciences programme is a unique consortium of 11 laboratories of excellence on the Bordeaux campus specialized in plant studies.

Your mission fits into the PERFIT research axis “Perennial woody plant fitness in a changing world: making use of genomic resources to increase productivity and resilience”.

Your work will assess genomic diversity and genetic load from available genomic data for various woody species. For this, you will use the available pipelines from phase 1 of the project and apply machine learning-based methods, taking into account single nucleotide polymorphisms (SNPs) and structural variants (SVs).

You will build a searchable variant database for the implementation of genomically-assisted selection of alleles that are favourable or unfavourable to the improvement of perennial woody species.

# Domesticated woody plants

• You will perform a functional annotation of SNPs and SVs in almond (Prunus dulcis Batsch and related species) and cherry (Prunus avium L.), through the construction of pangenomes that will provide information on their impact on the coding regions of the genes, the regulatory elements and the genetic dosage
• You will make predictions of deleterious mutations using methods based on evolutionary conservation and machine learning
• You will evaluate the impact of domestication and selection on genetic load and genomic architecture using a comparative genomics approach, comparing the results obtained for these species with those already available for apricot, P. armeniaca, and for the phylogenetically more distant grapevine, in collaboration with two ongoing Horizon Europe projects

# Wild woody plants

• You will predict deleterious mutations using methods based on evolutionary conservation and machine learning in the tropical tree Dicorynia guianensis
• You will characterize genotype-environment (GEA) and genotype-phenotype (GWAS) associations to identify beneficial mutations related to climate adaptation and/or underlying fitness and performance traits (GWAS)
• You will calculate "positive effective alleles" (PEAs) statistics by counting at individual and at population levels. These statistics are similar to the statistics used to characterize the genetic load in the approaches developed during phase 1

You will have access to the INRAE Genotoul computing cluster. You will be supervised by Véronique Decroocq (BFP) and Myriam Heuertz (BIOGECO), in connection with the project coordinator Santiago González-Martínez (BIOGECO). Regular meetings will be organised with the whole consortium to discuss the analyses to be carried out and to exchange on the interpretation of the results.