Adapting the feed, the animal and the feeding techniques to improve the efficiency and sustainability of monogastric livestock production systems
Adapting the feed, the animal and the feeding techniques to improve the efficiency and sustainability of monogastric livestock production systems

Molecular indicators of feed efficiency as proposed by a meta-analysis of transcriptomics data

Authors: 
F. Gondret, B. Koffi, J. van Milgen, I. Louveau
Publication date: 
28 August 2017
Full title: 
Molecular indicators of feed efficiency as proposed by a meta-analysis of transcriptomics data
Publishing information: 
68th EAAP Annual meeting, 28 August - 1 September 2017, Tallinn, Estonia
Abstract: 

Improving feed efficiency is an import challenge for pig production. This study aimed at proposing molecular traits able to predict feed conversion ratio (FCR) in growing pigs. A total of 71 pigs from two divergent lines selected for residual feed intake (RFI) and fed under different conditions (ad libitum or restricted) and different diets (low fat high starch or high fat high fiber) were considered, so that a broad range of FCR data was obtained. Transcriptomics data from the loin muscle and blood were obtained using porcine microarrays. The dataset (22 288 molecular probes per tissue and pig) was split into 70% for machine learning methods and 30% for cross-validation. Random forests were used to propose a reasonable set of 359 genes identified as very important predictors (VIP) of FCR. The FCR was well predicted (RMSE = 0.16; R² = 0.63) by a model combining the expression levels of 50 genes in muscle (out of the 359 VIP). These genes were involved in various biological pathways, including the response to insulin, homeostatic processes, signal transduction, regulation of cell proliferation, apoptosis, protein metabolism, and inflammatory responses. About 82% of the muscle VIP were also expressed in the blood. The FCR was also predicted correctly (RMSE = 0.21; R² = 0.52) by using the same model of genes expressed in blood. Technical validation is in progress to evaluate the predictive potential of the model when expression levels of these genes are measured by target methodology (qPCR) in blood of the same pigs. Further tests will be performed on blood samples taken at earlier growth stages to obtain early predictors and by using different pig populations to obtain generic predictors. In conclusion, identifying molecular traits related to feed efficiency could be helpful to identify important genomic regions and new biomarkers for genetic selection. This project has received funding from EU H2020 research and innovation program under grant agreement No 633531 Feed-a-Gene

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