Know more

Our use of cookies

Cookies are a set of data stored on a user’s device when the user browses a web site. The data is in a file containing an ID number, the name of the server which deposited it and, in some cases, an expiry date. We use cookies to record information about your visit, language of preference, and other parameters on the site in order to optimise your next visit and make the site even more useful to you.

To improve your experience, we use cookies to store certain browsing information and provide secure navigation, and to collect statistics with a view to improve the site’s features. For a complete list of the cookies we use, download “Ghostery”, a free plug-in for browsers which can detect, and, in some cases, block cookies.

Ghostery is available here for free: https://www.ghostery.com/fr/products/

You can also visit the CNIL web site for instructions on how to configure your browser to manage cookie storage on your device.

In the case of third-party advertising cookies, you can also visit the following site: http://www.youronlinechoices.com/fr/controler-ses-cookies/, offered by digital advertising professionals within the European Digital Advertising Alliance (EDAA). From the site, you can deny or accept the cookies used by advertising professionals who are members.

It is also possible to block certain third-party cookies directly via publishers:

Cookie type

Means of blocking

Analytical and performance cookies

Realytics
Google Analytics
Spoteffects
Optimizely

Targeted advertising cookies

DoubleClick
Mediarithmics

The following types of cookies may be used on our websites:

Mandatory cookies

Functional cookies

Social media and advertising cookies

These cookies are needed to ensure the proper functioning of the site and cannot be disabled. They help ensure a secure connection and the basic availability of our website.

These cookies allow us to analyse site use in order to measure and optimise performance. They allow us to store your sign-in information and display the different components of our website in a more coherent way.

These cookies are used by advertising agencies such as Google and by social media sites such as LinkedIn and Facebook. Among other things, they allow pages to be shared on social media, the posting of comments, and the publication (on our site or elsewhere) of ads that reflect your centres of interest.

Our EZPublish content management system (CMS) uses CAS and PHP session cookies and the New Relic cookie for monitoring purposes (IP, response times).

These cookies are deleted at the end of the browsing session (when you log off or close your browser window)

Our EZPublish content management system (CMS) uses the XiTi cookie to measure traffic. Our service provider is AT Internet. This company stores data (IPs, date and time of access, length of the visit and pages viewed) for six months.

Our EZPublish content management system (CMS) does not use this type of cookie.

For more information about the cookies we use, contact INRA’s Data Protection Officer by email at cil-dpo@inra.fr or by post at:

INRA
24, chemin de Borde Rouge –Auzeville – CS52627
31326 Castanet Tolosan CEDEX - France

Dernière mise à jour : Mai 2018

Menu Logo Principal CBGP Cirad IRD SupAgro Muse

Home page

Simon Boitard

Boitard

I am interested in the development of inference methods for population genetics. The methods I develop aim at reconstructing the evolution history of species based on high-density genomic data observed in these species. They concern both neutral (population size history, population structure ...) and adaptive (detection of locus under selection, estimation of selection history ...) aspects of this evolution. These methods are generic and can be applied to a wide range of plant and animal species. Until 2019, I have mainly focused on farm animal species, studying both the domestication process and the recent period of intensive breeding. In 2020 I joined the CBGP and started to contribute to ongoing projects concerning the invasive species Drosophila suzukii and Harmonia axyridis.

Ongoing projects

Genomic prediction of the adaptive potentiel of populations. PhD position available from sptember 2021.

Genomics of the invasion of the ladybird Harmonia axyridis (ANR GANDHI, leader A. Estoup).

Software

Pool-HMM & Freq-HMM, https://forge-dga.jouy.inra.fr/projects/pool-hmm

PopSizeABC, https://forge-dga.jouy.inra.fr/projects/popsizeabc

Recent publications (2019-2021)

S. Boitard, A. Arredondo, C. Noûs, L. Chikhi, O. Mazet (2021). Heterogeneity in effective size across the genome: effects on the Inverse Instantaneous Coalescence Rate (IICR) and implications for demographic inference under linked selection. bioRxiv 2021.06.11.448122

Boitard, S., Paris, C., Sevane, N., Servin, B & Dunner, S. (2021). Gene banks as reservoirs to detect recent selection: the example of the Asturiana de los Valles bovine breed. Frontiers in Genetics, 12.

Soto, A. A., Mourato, B., Nguyen, K., Boitard, S., Valcarce, W. R. R., Noûs, C., ... & Chikhi, L. (2021). Inferring number of populations and changes in connectivity under the n-island model. Heredity, 1-17.

Morris, K. M., Hindle, M. M., Boitard, S., Burt, D. W., Danner, A. F., Eory, L., ... & Jaffredo, T. (2020). The quail genome: insights into social behaviour, seasonal biology and infectious disease response. BMC biology, 18(1), 1-18.

C. Paris, B. Servin & S. Boitard (2019). Inference of selection from genetic time series using various parametric approximations to the Wright-Fisher model. G3: Genes, Genomes, Genetics, 9(12), 4073-4086.

A. Vignal, S. Boitard, N. Thebault, G. K. Dayo, V. Yapi‐Gnaore, I. Youssao Abdou Karim, ... & W. C. Warren (2019). A guinea fowl genome assembly provides new evidence on evolution following domestication and selection in galliformes. Molecular ecology resources 19: 997– 1014.

F. Jay, S. Boitard, & F. Austerlitz (2019). An ABC method for whole-genome sequence data: inferring paleolithic and neolithic human expansions. Molecular biology and evolution, 36(7), 1565-1579.

Selection of more ancient publications

M.I. Fariello, S. Boitard, S. Mercier, D. Robelin, T. Faraut, C. Arnould, J. Recoquillay, O. Bouchez, G. Salin, P. Dehais, D. Gourichon, S. Leroux, F. Pitel, C. Leterrier and M. SanCristobal (2017). Accounting for Linkage Disequilibrium in genome scans for selection without individual genotypes: the local score approach. Mol Ecol 26:3700–3714.

S. Boitard, W. Rodríguez, F. Jay, S. Mona and F. Austerlitz (2016). Inferring Population Size History from Large Samples of Genome-Wide Molecular Data - An Approximate Bayesian Computation Approach. PLoS Genet 12(3): e1005877.

S. Boitard, M. Boussaha, A. Capitan, D. Rocha and B. Servin (2016). Uncovering Adaptation from Sequence Data: Lessons from Genome Resequencing of Four Cattle Breeds. Genetics 203(1), 433-450.

O. Mazet, W. Rodríguez, S. Grusea, S. Boitard and L. Chikhi (2015). On the importance of being structured: instantaneous coalescence rates and human evolution-lessons for ancestral population size inference? Heredity116(4):362-71.

M. I. Fariello, S. Boitard, H. Naya, M. SanCristobal and B. Servin (2013). Detecting signatures of selection through haplotype differentiation among hierarchically structured populations. Genetics 193 (3), 929-941.

S. Boitard, C. Schltterer, V. Nolte, R. V. Pandey and A. Futschik (2012). Detecting selective sweeps from pooled next generation sequencing samples. Mol. Biol. Evol. 29(9): 2177-2186.