Développement d'une application de lecture de profil génétique microsatellite

Description

STAGE DE 2 MOIS

Mission

Development of an Open-Source Application for Microsatellite Data Analysis on R Shiny

Internship Context

A reduction in organism size has been proposed as a third universal response to climate change (Daufresne et al., 2009; Gardner et al., 2011), alongside species’ geographic distribution shifts (Parmesan, 2006) and phenological changes (Charmantier et al., 2008). Unlike the latter two responses, patterns of body size reduction remain unclear, particularly regarding their adaptive nature and the mechanisms behind these morphological changes—whether they arise from environmental and/or genetic effects (Gienapp et al., 2008). Body size is a key life-history trait in most organisms, especially in mammals, where it is closely linked to survival and reproductive success (Blueweiss et al., 1978). Understanding the implications of such morphological variations is therefore crucial to assessing the demographic and evolutionary impacts of this response (Ozgul et al., 2010).

Climate change is particularly pronounced in high-altitude environments (Beniston, 2006), and hibernating species may be especially sensitive to these changes given the importance of body size during hibernation (Wells et al., 2022). As part of a PhD project on the evolutionary responses of the Alpine marmot (Marmota marmota) to climate change, we aim to establish a genetic pedigree (i.e., genealogy) for a population of marmots that has been monitored for 34 years in the Grande Sassière Nature Reserve in the French Alps. This genetic pedigree will refine the current social pedigree, which assumes that the dominant individuals in a territory are the parents of that year's offspring. While this assumption is largely valid for this socially monogamous species, where only dominant individuals reproduce (Allainé, 2000), it does not account for frequent extra-pair parentage (Cohas et al., 2006). Ultimately, this pedigree will enable quantitative genetic analyses (Lynch & Walsh, 1996) to study the evolutionary dynamics of body size in this Alpine marmot population in response to climate change.

Internship Objectives

Genetic data from 16 microsatellites have been collected for individuals in this population from 1990 to 2023. Until 2015, individual genetic profiles were determined using the proprietary software GenMapper. The objective of this internship is to develop an open-source application that will automate the determination of marmot genetic profiles based on sequencer output files (.fsa).

A preliminary version of this application has been developed using R Shiny and is available on GitHub (link to be provided). The intern will be responsible for improving this existing application. Specific tasks include:

• Automating the calibration function to convert fluorescence data into base pair lengths (to determine individual alleles for each microsatellite marker).
• Implementing a feature to remove erroneous fluorescence peaks.

The application will use the Fragman and seqinr R packages. A literature review will also be necessary to identify the most suitable algorithms for automation.

This internship is an excellent opportunity to develop advanced programming skills, application development expertise (useful for data sharing and science communication), and experience in open science practices.

Desired Profile

We are looking for a student with strong programming skills in R. Experience with the Shiny package for application development would be a plus but is not mandatory. Ideally, the candidate should be:

• Motivated and passionate about programming.
• Interested in reproducibility in science (GitHub, open-source applications, etc.).
• Familiar with basic genetics concepts.

The internship is expected to last approximately two months. Students from various academic backgrounds may be suitable, provided they meet the criteria above. However, students in bioinformatics, engineering, or biomathematics may be particularly well-suited for this project. This internship is unpaid.

Hosting & Supervision

The internship will take place at the Centre d’Écologie Fonctionnelle et Évolutive (CEFE) in Montpellier, within the Ecology team, and will be co-supervised by the Laboratoire de Biométrie Évolutive (LBBE) in Lyon. Weekly meetings will be held to discuss the project’s progress and address any issues. Visits to LBBE may also be organized.

The intern will be primarily supervised by Pierre-Alexandre QUITTET (PhD student, CEFE) and his two PhD advisors:

• Christophe BONENFANT (Researcher, LBBE)

Application & Contact

To apply, please send your CV and a recommendation letter to:

Candidature

Contacts