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Identification of key regulators of lipid plasticity in two major livestock species (pig and chicken) by combined high-throughput technologies, statistics, bioinformatics and phylogenics approaches – FatInteger

Lipid metabolism flexibility: a levier by which animal may adapt to prospective changes in the availability and fluctuating costs of feed resources

To better understand lipid metabolism taking into account genotypes and diets as sources of variation. <br />To decipher the cellular actors and master elements acting together in regulating body fat content and partition.<br />To develop software tools for gathering and mining transcriptomics datasets

To reveal the main molecular actors controlling lipid metabolism in pig and chicken by the association of experimental studies and bioinformatics.

Modern farm animal production has to cope with numerous economic, environmental and social concerns. Both the efficiency of feed conversion into meat, egg or milk products, the composition of animal products themselves, and the environmental wastes associated to these productions are important to consider. Fatty animals are generally less feed efficient. Moreover, producer is paid on a carcass weight and grade based on fat thickness or percent fat, and lean meat content. However, fat content in meat products may be associated to better eating quality. This justifies considering body fat content and its distribution as important issues for animal production. A recurrent question in animal production concerns the interaction between genetics and the environmental pressure. Diets are often formulated at the least costs and may include many energy sources, but the way animals valorize these diets depends likely of their genotypes. The FATINTEGER project was proposed to add scientific knowledge in lipid metabolism that regulates fat storage and its partition between animal tissues, considering genotypes and diets as sources of flexibility.

Physiological, phylogenetics, statistics and bio-informatics skills are gathered together. Transcriptional and biochemical data relevant to tissue functions are acquired in key tissues serving as energy reserve (adipose tissues) or using energy (liver and muscle), and in the blood that summarizes the way they communicate to orchestrate the answers. Statistical methods are used to analyze the differences induced by experimental conditions and find the genes that work together (networks). The upstream regulators of these networks are proposed by searching common motifs of response on the promoters of the genes and analyzing the influences between genes by automatic reasoning informatics. Some actors are observed by gene evolution between mammals and other vertebrates.

The responses to diets rich in cereals or diets rich in lipids and by-products, each providing a same level of metabolizable energy and proteins to growing animals, are clearly different between species. For chicken, we do not observe any variations of growth performance and fat contents as induced by the diets, which means that animals are able to synthetize a same amount of lipids beside differences in dietary fat content. For pigs, the diets markedly alter animal growth and body composition. According to lipidomics and transcriptional data, not only lipid metabolism but also protein metabolism is affected in the two species, which underscores interconnections between the two in the use of feed energy and control of body composition

This project addresses the physiological bases of feed efficiency, body composition and growth, which are pillars of agricultural productivity. It is clearly connected to nutrigenomics, the branch of research describing the influence of food constituents on gene expression and considering body responses via system biology. It will contribute to develop rational means to optimize nutrition with respect to the subject's genotype, such as refining the nutritional recommendations or finding biomarkers to be used in animals monitoring. It could suggest agonists of particular metabolic pathways such as micronutrients to be added in diets. Beside nutrition, the targets will also enrich the traits to be recorded in support to on-going genomic selection.

Preliminary results of the project are going to be disseminated through professional congress talks on poultry (JRA-JRPFG, la Rochelle, 2013) and pigs ((JRP, Paris, 2014),
Beside, because the project also aims to provide application tools in bioinformatics, interventions in congress on bioinformatics (JOBIM, Rennes, 2012) and metabolomics (RFMF à Amiens; Metabolomics society à Glasgow, 2013) have been done. Academic and vocational training sessions dedicated to data integration will be also realized (AgroCampus-Ouest, France), and a statistics forum will be organized by one of the partners in the project.

Body fat content and the partition of lipid stores in the different tissues of the carcasses are important phenotypic traits to be considered for the sustainability of farm animal production. Indeed, fatty animals are generally less efficient in the conversion of feed during rearing period, and detrimental costs are associated to trimming of visible fats when butchering the carcasses. However, the fat content of meat and meat-processed products is generally linked to better scores of sensory quality traits. Both genetics and non-genetic factors are able to modify body fatness of animals, through their actions on lipid metabolism that occurs in key tissues. Energy input from nutrients is indeed partly stored in various organs and tissues into lipids that will be re-mobilized to cope with low energy intake periods, physiological transitions or stress situations. Thus, flexibility of lipid metabolism may influence the adaptation of animals to cope with various environments, including the distribution of diets formulated under the optimal requirements.
To answer the question of elucidating key regulators of lipid metabolism associated to variations in body fat content and partition, we propose a systemic approach to unravel the flexibility of lipid metabolism into a generic frame. This systemic approach is based on acquisition of transcriptomics and lipidomics data in key tissues and the whole blood from genetic lines divergent for body fatness, and on statistical, bioinformatics and phylogenetics approaches to analyse the tissues- and species-specificities of the key actors.
Complementary skills of teams gathering physiologists, (phylo)-geneticians, statisticians and bioinformaticians are mobilized. A coordinated diet (isoenergetic low vs high fat diets) x genotype (lines with divergence in body fatness) will be performed in growing animals of two phylogenetically-distant farm species (pigs and chickens). The FatInteger project proposes first to acquire new transcriptional data in 4 tissues (the liver, two fat pads, and one skeletal muscle) playing key roles in various aspects of lipid metabolism and in the whole blood integrating organs communication. Second, sets of differentially-expressed genes will be provided. Each gene-set will be analyzed more deeply by gene-network statistical approaches to identify modules in which genes are likely co-regulated by a same mechanism. Third, the key regulators in these gene-modules will be proposed by bioinformatics and promotology. To identify tissues- or species- specificities versus genericities, some of these genes and regulators will be compared between tissues and species, respectively, and the differences will be analyzed by the gene evolution of corresponding paralog (for tissue differences) and ortholog (for species-differences) genes. Fourth, phenotypic changes in pathways that are suggested to be correlated to the gene-sets, and having or not a priori links to lipid metabolism, will be checked in experimental animals or cell line cultures.
Taken together, the FatInteger project will provide relevant answers and novel hypotheses related to the plasticity of body fatness and lipid metabolism in pigs and chickens, to offer clues for next feeding or genetic schemes. It will participate in developing statistical, bioinformatical and phylogenetical tools that could serve a wide community interested in analyzing transcriptomic data from various experimental settings.

Project coordination

Florence GONDRET (INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE - CENTRE DE RECHERCHE DE RENNES) – florence.gondret@rennes.inra.fr

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

CNRS-IRISA CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE BRETAGNE ET PAYS- DE-LA-LOIRE
URA INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE - CENTRE DE RECHERCHE DE TOURS
LMA-IRMAR INSTITUT SUPERIEUR DES SCIENCES AGRONOMIQUES, AGROALIMENTAIRES, HORTICOLES ET DU PAYSAGE (AGRO CAMPUS OUEST)
SENAH INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE - CENTRE DE RECHERCHE DE RENNES
GARen INSTITUT NATIONAL DE LA RECHERCHE AGRONOMIQUE - CENTRE DE RECHERCHE DE RENNES

Help of the ANR 384,957 euros
Beginning and duration of the scientific project: February 2012 - 36 Months

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