PhD position OT-11672

Analysis of the genetic determinism of milk characteristics, as determined by mid-infrared spectrometry, and use for characterization of animal adaptability.


Back to jobs listing

INRAE presentation

The French National Research Institute for Agriculture, Food, and the Environment (INRAE) is a public research establishment. It is a community of 12,000 people with more than 200 research units and 42 experimental units located throughout France. The institute is among the world leaders in agricultural and food sciences, in plant and animal sciences, and is 11th in the world in ecology and environment. INRAE’s main goal is to be a key player in the transitions necessary to address major global challenges. In the face of the increase in population, climate change, scarcity of resources and decline in biodiversity, the institute develops solutions for multiperformance agriculture, high quality food and sustainable management of resources and ecosystems.

Work environment, missions and activities

You will be integrated in two research teams of the GenPhySE unit (Genetics, Physiology and Livestock Systems) near Toulouse: GeSPR (Genetics and Selection of Small Ruminants), and MG² (Genetic and Genomic Modeling). These teams are specialized in the development of models and methods for the study of genetic determinism of traits and genetic and genomic evaluations.

You will receive scientific support from the unit's researchers with expertise in genetic modeling, trait determinism and methodology, as well as from academic (other INRAE units) and professional (Institut de l'élevage, CNBL) partners necessary for the successful completion your research topic. You will benefit from the rich and numerous national and international collaborations established by GenPhySE scientists.

Socio-economic and scientific context:

In the current context of increased food autonomy of dairy sheep farms, having animals capable of using their feed as efficiently as possible, of mobilizing their body reserves at key moments of the production cycle while maintaining a quality milk production, becomes an important issue for ewe breeders. For this purpose, the use of high throughput, non-invasive, inexpensive and fast phenotyping methods is an important element for the incorporation of these traits in future breeding goals. The analysis of milk by mid-infrared spectrometry, traditionally performed during milk recording, could be such a tool. The objective of this thesis project is to study the genetic determinism of traits related to feed efficiency and milk composition in dairy sheep, determined (in large part) by mid-infrared spectrometry (MIR). It also aims to determine a typology of ewe profiles according to these criteria and to explore the potential of direct analysis of mid-infrared spectra for this same purpose. In addition, it will include a comparison of genomic and spectra-based parentage matrices.

The main research questions asked in this work are: what are the heritabilities of traits that predict energy balance or metabolic status in ewes?  What are the genetic correlations of these traits with each other and with milk production traits throughout lactation in dairy ewes? How can these criteria be used to characterize ewe adaptability? How can milk MIR spectra be used for this characterization?

This work is based on the hypothesis that the MIR spectra are a function of the chemical composition of the milk, and therefore reflect what can impact it directly (the feed) or more indirectly such as the health status of the animal.

Main steps of the thesis:

The thesis will be based on milk recording data collected on farms and in particular on MIR spectra collected since 2019. It will also include data from an experimental protocol, carried out in the framework of the European H2020 SMARTER project, which includes a finer phenotyping of ewes (doubling of the number of milk tests, recovery of the MIR spectra, scoring of body condition). Predictive equations for blood and milk metabolites and milk fatty acids will be applied to MIR spectra.

This thesis will included 3 main steps:

- Analysis of the genetic determinism of the measured traits: body condition score, milk quantity, fat and protein contents, and predicted by MIR spectra (fatty acid profile, beta hydroxybutyrate, and other metabolites)

- Typology of animals: based on the predicted genetic values (or observed phenotypes) for each individual along the production cycle, a classification of the individuals by taking into account the evolutions of several traits will be performed.

- Exploration of the MIR spectra: this part will included an analysis of the intra-individual spectra at different measurement points, as well as a comparison between different measurement points of the spectral matrices between individuals, and the genomic and spectral matrices at each measurement point. A classification of individuals will be performed from the spectral base and this typology will be compared to the first one.


Training and skills

Master's degree/Engineering degree

Recommended training:

- Engineer or master’s degree in animal breeding / genetics / applied mathematics

Abilities required:

- data analysis (R/SAS), programming (awk/Fortran/Python)

- knowledge in quantitative genetics, zootechnics

Skills sought:

- strong interest in data analysis

- autonomy, rigor, ability to work in a team

- ability to communicate in French and English (written and oral)

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
parenting support: CESU childcare, leisure services;
- skills development systems: trainingcareer advise;
social support: advice and listening, social assistance and loans;
holiday and leisure services: holiday vouchers, accommodation at preferential rates;
sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter
Sujet de thèse_2021_2024_HLarroque.pdfpdf - 1.73 MB

Offer reference

  • Contract: PhD position
  • Duration: 36 mois
  • Beginning: 01/10/2021
  • Remuneration: 1874.41 €
  • Reference: OT-11672
  • Dealine: 12/06/2021