Know more

About cookies

What is a "cookie"?

A "cookie" is a piece of information, usually small and identified by a name, which may be sent to your browser by a website you are visiting. Your web browser will store it for a period of time, and send it back to the web server each time you log on again.

Different types of cookies are placed on the sites:

  • Cookies strictly necessary for the proper functioning of the site
  • Cookies deposited by third party sites to improve the interactivity of the site, to collect statistics

Learn more about cookies and how they work

The different types of cookies used on this site

Cookies strictly necessary for the site to function

These cookies allow the main services of the site to function optimally. You can technically block them using your browser settings but your experience on the site may be degraded.

Furthermore, you have the possibility of opposing the use of audience measurement tracers strictly necessary for the functioning and current administration of the website in the cookie management window accessible via the link located in the footer of the site.

Technical cookies

Name of the cookie


Shelf life

CAS and PHP session cookies

Login credentials, session security



Saving your cookie consent choices

12 months

Audience measurement cookies (AT Internet)

Name of the cookie


Shelf life


Trace the visitor's route in order to establish visit statistics.

13 months


Store the anonymous ID of the visitor who starts the first time he visits the site

13 months


Identify the numbers (unique identifiers of a site) seen by the visitor and store the visitor's identifiers.

13 months

About the AT Internet audience measurement tool :

AT Internet's audience measurement tool Analytics is deployed on this site in order to obtain information on visitors' navigation and to improve its use.

The French data protection authority (CNIL) has granted an exemption to AT Internet's Web Analytics cookie. This tool is thus exempt from the collection of the Internet user's consent with regard to the deposit of analytics cookies. However, you can refuse the deposit of these cookies via the cookie management panel.

Good to know:

  • The data collected are not cross-checked with other processing operations
  • The deposited cookie is only used to produce anonymous statistics
  • The cookie does not allow the user's navigation on other sites to be tracked.

Third party cookies to improve the interactivity of the site

This site relies on certain services provided by third parties which allow :

  • to offer interactive content;
  • improve usability and facilitate the sharing of content on social networks;
  • view videos and animated presentations directly on our website;
  • protect form entries from robots;
  • monitor the performance of the site.

These third parties will collect and use your browsing data for their own purposes.

How to accept or reject cookies

When you start browsing an eZpublish site, the appearance of the "cookies" banner allows you to accept or refuse all the cookies we use. This banner will be displayed as long as you have not made a choice, even if you are browsing on another page of the site.

You can change your choices at any time by clicking on the "Cookie Management" link.

You can manage these cookies in your browser. Here are the procedures to follow: Firefox; Chrome; Explorer; Safari; Opera

For more information about the cookies we use, you can contact INRAE's Data Protection Officer by email at or by post at :


24, chemin de Borde Rouge -Auzeville - CS52627 31326 Castanet Tolosan cedex - France

Last update: May 2021

Menu Logo Principal AgroParisTech Université Paris-Saclay SAPS - Sciences Animales Paris-Saclay


GABI : Génétique Animale et Biologie IntégrativeUnité Mixte de Recherche INRA - AgroParisTech

Denis LALOE, Senior Research Engineer

ORCID id : 0000-0001-8359-0760

My work with the GiBBS team is focused on the analysis of data concerning different fields (x-omics, Biodiversity and Genetic Structure of Populations, Animal Production). I am specialized in Factorial Analysis (principal components analysis, analysis of correspondence, multiple factorial analysis, coinertia, ....).

INRA UMR 1313 Génétique Animale et Biologie Intégrative

Domaine de Vilvert, Bat 211, 78352 Jouy en Josas
Tel : +33 (0) 1 34 65 22 00 Fax : +33 (0) 1 34 65 22 10

Email : denis.laloe(at)

Research Team : GenomIcs, Biodiversity, Bioinformatics and Statistics (GiBBS)

CV :

1980 : Agronomic Engineering Degree from ENSA at Rennes
1983 : DEA in Quantitative Genetics (Paris XI)
Head of the Informatics Unit of the Porcine UPRA
1987 : Senior Research Engineer at INRA
1993 : DEA in Stochastical and Statistical Modeling ( Paris XI)

2015 : HDR (Habilitation à diriger des recherches), INP Toulouse

Fields of Research:

Population Genetics, Analysis of Genetic Structure of Livestock, Analysis of x-omics data, Quantitative Genetics.

Oral communications and other productions

  • D. Laloë , F. Jehl , C. Desert , M. Boutin , S. Leroux , D. Esquerre , C. Klopp , D. Gourichon , F. Pitel , S. Lagarrigue , and T. Zerjal (2019).Integrated metabolomic and transcriptomic analysis evaluating heat and feed stress in layer chickens. ISAG, 7-12 July, Lleida, Spain
  • D Laloë, 2019. Challenges in big data integration. Multivariate approaches. Presented at the Micobion Workshop, Praha, 3-5 June 2019
  • Laloë, D., Le Bourhis, D., Brochard, V., Fernandez-Gonzalez, A., Dube, D., Trigal, B., ... & Duranthon, V. (2015). Metabolomic analysis revealed differences between bovine cloned embryos with contrasting development abilities. Anim. Reprod, 12(3), 818.
  • D Laloë, T Zerjal, 2013. Landscape Genomics and Multivariate Analyses. Examples and prospects for poultry. WPSA, 8th European Genetics Symposium, Venice Italy, 25-27 september 2013 [Landscapenomix_2013]
  • Zerjal, T., Lagarrigue, S., Jaffrezic, F., Moroldo, M., Laloë, D., Rau, A., 2013. Genome-wide transcriptomic analysis of liver from chicken lines selected for residual feed consumption. Presented at the 8. European Symposium on Poultry Genetics (ESPG)
  • D Laloë, 2010. Evaluation génétique. Les fondements.Séminaire du département de Génétique Animale, 18-21 octobre 2010. [Fondements_evalgenet.2010]
  • D Laloë, B Salmi, 2012. Analyse factorielle multiple et intégration de données. Application à la variabilité de la qualité de viande de porc.Réunion du réseau "Statomique", 15 mai 2012.[AFM_2012]
  • D Laloë, M Gautier, 2012. Interprétation génétique des ACP entre groupes appliquées aux SNP. Séminaire du laboratoire TIMC-IMAG, université Joseph Fourier, Grenoble, 14 juin 2012. [ACP_SNP_2012]
  • D Laloë, T Zerjal,  2013. Diversita genetica degli animali domestici. Qualche esempio e un po’ di teoria.Università di Pisa, 24 maggio 2013. [diversitagenetica_2013]

Publications  :

x-omics data analysis (Genomic evaluation, transcriptomics, etc.) and other applications

Rau, A., Manansala, R., Flister, M. J., Rui, H., Jaffrézic, F., Laloë, D., & Auer, P. L. (2020). Individualized multi-omic pathway deviation scores using multiple factor analysis. Biostatistics, kxaa029. Rau, A., Manansala, R., Flister, M. J., Rui, H., Jaffrézic, F., Laloë, D., & Auer, P. L. (2019). DOI: 10.1093/biostatistics/kxaa029

Doublet, A. C., Restoux, G., Fritz, S., Balberini, L., Fayolle, G., Hozé, C., ... & Croiseau, P. (2020). Intensified Use of Reproductive Technologies and Reduced Dimensions of Breeding Schemes Put Genetic Diversity at Risk in Dairy Cattle Breeds. Animals, 10(10), 1903. 10.3390/ani10101903

Lévy, E., Jaffrézic, F., Laloë, D., Rezaei, H., Huang, M. E., Béringue, V., ... & Vernis, L. (2020). PiQSARS: A pipeline for quantitative and statistical analyses of ratiometric fluorescent biosensors. MethodsX, 7, 101034.

Neou, M., Villa, C., Armignacco, R., Jouinot, A., Raffin-Sanson, M. L., Septier, A., ... & Assié, G. (2020). Pangenomic classification of pituitary neuroendocrine tumors. Cancer Cell, 37(1), 123-134.

Bazile, J., Jaffrezic, F., Dehais, P., Reichstadt, M., Klopp, C., Laloë, D., & Bonnet, M. (2020). Molecular signatures of muscle growth and composition deciphered by the meta-analysis of age-related public transcriptomics data. Physiological Genomics, 52(8), 322-332.

Biase, F. H., Hue, I., Dickinson, S. E., Jaffrezic, F., Laloë, D., Lewin, H. A., & Sandra, O. (2019). Fine-tuned adaptation of embryo–endometrium pairs at implantation revealed by transcriptome analyses in Bos taurus. PLoS biology, 17(4), e3000046.

Hue, I., Dufort, I., Carvalho, A.V., Laloë, D., Peynot, N., Degrelle, S.A., Viebahn, C., Sirard, M.-A., 2018. Different pre-implantation phenotypes of bovine blastocysts produced in vitro. Reproduction 1.

Verrier, E. R., Genet, C., Laloë, D., Jaffrezic, F., Rau, A., Esquerre, D., ... & Jouneau, L. (2018). Genetic and transcriptomic analyses provide new insights on the early antiviral response to VHSV in resistant and susceptible rainbow trout. BMC genomics, 19(1), 482.

Mobuchon, L., Le Guillou, S., Marthey, S., Laubier, J., Laloë, D., Bes, S., ... & Leroux, C. (2017). Sunflower oil supplementation affects the expression of miR-20a-5p and miR-142-5p in the lactating bovine mammary gland. PloS one, 12(12), e0185511.

M Boerries, F Grahammer, S Eiselein, Moritz Buck, C Meyer, M Goedel, W Bechtel, S Zschiedrich, D Pfeifer, D Laloë, C Arrondel, S Gonçalves, M Krüger, S J. Harvey, H Busch, J Dengjel, T B. Huber, 2013. Molecular fingerprint of the podocyte reveals novel gene and protein regulatory networks.
Kidney International ; doi:10.1038/ki.2012.487

R Rincent, D Laloë, S Nicolas, T Altmann, D Brunel, P Revilla, V M. Rodriguez, J Moreno-Gonzales, A E. Melchinger, E Bauer, C-C Schön, N Meyer, C Giauffret, C Bauland, P Jamin, J Laborde, H Monod, P Flament, A Charcosset,  L Moreau, 2012. Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds (Zea mays L.) Genetics, 192:715-728.

S Le Guillou, N Sdassi, J Laubier, B Passet, M Vilotte, J Castille,D Laloë, J Polyte, S Bouet, F Jaffrézic, E Cribiu, J-L Vilotte, F Le Provost, 2012. Overexpression of miR-30b in the developing mouse mammary gland development causes a lactation defect and delays involution. Plos ONE 7-9:e45727

Genetic structuring of populations

Boushaba, N., Boujenane, I., Moazami-Goudarzi, K., Flori, L., Saïdi-Mehtar, N., Tabet-Aoul, N.,  Laloë, D. (2019). Genetic diversity and relationships among six local cattle populations in semi-arid areas assessed by a bovine medium-density single nucleotide polymorphism data. Animal, 13(1), 8-14.

Flori, L., Moazami‐Goudarzi, K., Alary, V., Araba, A., Boujenane, I., Boushaba, N., ... ,Laloë, D., Gautier,M  (2019). A genomic map of climate adaptation in Mediterranean cattle breeds. Molecular ecology, 28(5), 1009-1029.

Mir C, Zerjal T, Combes V, Dumas F, Madur D, Bedoya C, Dreisigacker S, Franco J, Grudloyma P, Hao PX, Hearne S, Jampatong C, Laloë D, Muthamia Z, Nguyen T, Prasanna BM, Taba S, Xie CX, Yunus M, Zhang S, Warburton ML, Charcosset A, 2013 . Out of America: tracing the genetic footprints of the global diffusion of maize.Theor Appl Genet, 2013  Aug 7. [ahead of print]; PMID 23921956 ; DOI 10.1007/s00122-013-2164-z

D Laloë, M Gautier, 2011. On the genetic interpretation of Between-Group PCA on SNP data.  HAL open archive n° hal-00661214.

C Berthouly, J c Maillard, L Pham Doan, T Nhu Van  B Bed'Hom, G Leroy, H Hoang Thanh, D Laloë, N Bruneau, C Vu Chi, V Nguyen Dang, E Verrier and X Rognon, 2010. Revealing fine scale subpopulations structure in the Vietnamese H'mong cattle breed for conservation purposes. BMC Genetics 2010, 11:45

C. Berthouly, X. Rognon, T. Nhu Van, A. Berthouly, H. Thanh Hoang, B. Bed'Hom, D. Laloë, C. Vu Chi, E. Verrier, J.-C. Maillard, 2010. Genetic and morphometric characterization of a local Vietnamese Swamp Buffalo population . Journal of Animal Breeding and Genetics, 127:1,74-84

M Gautier, D Laloë, L Moazami-Goudarzi, 2010. Insights into the genetic history of French cattle from dense SNP data on 47 worlwide breeds. PLOS ONE, 5:9, e13038

Laloë, D.; Moazami-Goudarzi, K.; Lenstra, J.A.; Marsan, P.A.; Azor, P.; Baumung, R.; Bradley, D.G.; Bruford, M.W.; Cañón, J.; Dolf, G.; Dunner, S.; Erhardt, G.; Hewitt, G.; Kantanen, J.; Obexer-Ruff, G.; Olsaker, I.; Rodellar, C.; Valentini, A.; Wiener, P.; European Cattle Genetic Diversity Consortium and Econogene Consortium Spatial Trends of Genetic Variation of Domestic Ruminants in Europe. Diversity 2010, 2, 932-945.

Mathieu Gautier, Laurence Flori, Andrea Riebler, Florence Jaffrezic, Denis Laloë, Ivo Gut, Katayoun Moazami-Goudarzi and Jean-Louis Foulley, 2009.  A whole genome bayesian scan for adaptive genetic divergence in West African cattle BMC Genomics 2009, 10:550

P K Rout, M B Joshi, A Mandal, D Laloë, L Singh , K Thangaraj, 2008. Microsatellite-based phylogeny of Indian domestic goats. BMC Genetics 2008, 9:11

C. Berthouly, B. Bed’Hom, M.Tixier-Boichard, C.F. Chen, Y.P. Lee, D. Laloë, H. Legros, E. Verrier, X. Rognon, 2008. Using molecular markers and multivariate methods to study the genetic diversity on local european and asian chickens breeds,. Animal Genetics39(2):121-129

D. Laloë, T. Jombart, A.B. Dufour, K. Moazami-Goudarzi , 2007. Consensus genetic structuring and typological value of markers using Multiple Co-Inertia Analysis. Genet Sel Evol, 39 (2007) 545-567.

K. Moazami-Goudarzi , D. Laloë , 2002. Is a multivariate consensus representation of genetic relationships among populations always meaningful  (Genetics,162:473-484)

K Moazami-Goudarzi, D Laloë, JP Furet, F Grosclaude, 1997. Analysis of genetic relationships between 10 cattle breeds with 17 microsatellites. Animal Genetics, 1997,28,338-345

Quantitative genetics : Models of genetic evaluation; estimation of genetic parameters.

Ducrocq, V., Laloë, D., Swaminathan, M., Rognon, X., Tixier-Boichard, M., & Zerjal, T. (2018). Genomics for ruminants in developing countries: from principles to practice. Frontiers in genetics, 9.

Eynard, S. E., Croiseau, P., Laloë, D., Fritz, S., Calus, M. P., & Restoux, G. (2018). Which individuals to choose to update the reference population? Minimizing the loss of genetic diversity in animal genomic selection programs. G3: Genes, Genomes, Genetics, 8(1), 113-121.

Wang, S., Laloë, D., Missant, F. M., Malm, S., Lewis, T., Verrier, E., ... & Leroy, G. (2018). Breeding policies and management of pedigree dogs in 15 national kennel clubs. The Veterinary Journal, 234, 130-135.

N.T. Pegolo, D. Laloë,  H.N. de Oliveira, R.B. Lobo,  M.-N. Fouilloux, 2012. Trends of the genetic connectedness measures among Nelore beef cattle herds. J. Anim. Breed. Genet. 129 :1, 20-29.

D. Laloë, 2011. La genèse et le développement des concepts de l'évaluation génétique classique. IN : Numéro spécial Amélioration génétique. Mulsan P., Bodin L., Coudurier B., Deretz S., Leroy P., Quillet E., Perez J.M. (Eds), INRA Prod. Anim. 24, 323-330

E. Venot,  M.N. Fouilloux, F. Forabosco, A. Fogh, T. Pabiou, M. Coffey,  J.Å. Eriksson,  D. Laloë, 2009. Beef without borders:  genetic parameters for Charolaise and Limousine Interbeef genetic evaluation of weaning weights. Proceedings of the 2009 Interbull meeting. Barcelone, Spain , August 21-24. Bulletin 40, 61-67

E. Venot,  M.N. Fouilloux, F. Forabosco, A. Fogh, T. Pabiou, M. Coffey,  J.E. Eriksson, D. Laloë, 2009. Interbeef genetic evaluation of weaning weights for Charolaise and Limousine breeds. Proceedings of the 2009 Interbull meeting. Barcelone, Spain , August 21-24. Bulletin 40, 55-60

M.N. Fouilloux, V Clément, D Laloë, 2008. Measuring connectedness among random effects in mixed linear models: from theory to practice in large-size genetic evaluations. Genet. Sel. Evol. 40 (2008) 145-159.

Jaffrézic F, Venot E, Laloë D, Vinet A, Renand G, 2004. Use of structured antedependence models for the genetic analysis of growth curves.J Anim Sci. 2004 Dec;82(12):3465-73.

Florence Phocas, D. Laloë, 2004. Genetic parameters for birth and weaning traits in French specialized beef cattle breeds. Livestock Production Science89) 121-128.

Florence Phocas, D. Laloë, 2004. Should genetic groups be fitted in BLUP evaluation ? Practical answer for the French AI beef sire evaluation. Genet. Sel. Evol. 36:325-345

D Laloë, Florence Phocas, 2003. A proposal of criteria of robustness in genetic evaluation. Livestock Production Science80(3) 241-256.

Florence Phocas,D Laloë, 2003. Evaluation models and genetic parameters for calving difficulty in beef cattle.Journal of Animal Science 81:933-938

M N Fouilloux, D Laloë, 2001. A sampling method for estimating the accuracy of predicted breeding values in genetic evaluation.Genet Sel Evol33, 473-486 10.1186/1297-9686-33-5-473

D Laloë, Florence Phocas, F Ménissier, 1996. Considerations about measures of precision and connectedness in mixed linear models of genetic evaluation. Genet Sel Evol28, 359-378.

D Laloë, 1993.  Precision and information in linear models of genetic evaluation. Genet Sel Evol, 25, 557-576

Multivariate analysis applied to animal production

B. Salmi, C. Larzul,, M. Damon, L. Lefaucheur, J. Mourot, E. Laville, P. Gatellier, K. Méteau,, D. Laloë, B. Lebret, 2010. Multivariate analysis to compare pig meat quality traits according to breed and rearing system . Proceedings of the 9th World congress on Genetics applied to Livestock Production. Leipzig, August 1-6, 2010, 442

L. Canario, Y. Billon, J.C. Caritez, J.P. Bidanel, D. Laloë, 2009. Comparison of sow farrowing characteristics between a Chinese breed and three French breeds. Livestock Science, 125, 132-140