A Random Regression Model Based on a Single-Step Method for Improving the Genomic Prediction Accuracy of Residual Feed Intake in Pigs.

Ye Wang,Wenjie Hao,Raphael Mrode,Junhai Chen,Jianfeng Liu,Lei Zhou,Huimin Kang,Chenguang Diao

doi:10.3389/fgene.2021.769849

Abstract

Residual feed intake (RFI) is considered as a measurement of feed efficiency, which is greatly related to the growth performance in pigs. Daily feeding records can be obtained from automatic feeders. In general, RFI is usually calculated from the total measurement records during the whole test period. This measurement cannot reflect genetic changes in different growth periods during the test. A random regression model (RRM) provides a method to model such type of longitudinal data. To improve the accuracy of genetic prediction for RFI, the RRM and regular animal models were applied in this study, and their prediction performances were compared. Both traditional pedigree-based relationship matrix (A matrix) and pedigree and genomic information-based relationship matrix (H matrix) were applied for these two models. The results showed that, the prediction accuracy of the RRM was higher than that of the animal model, increasing 24.2% with A matrix and 40.9% with H matrix. Furthermore, genomic information constantly improved the accuracy of evaluation under each evaluation model. In conclusion, longitudinal traits such as RFI can describe feed efficiency better, and the RRM with both pedigree and genetic information was superior to the animal model. These results provide a feasible method of genomic prediction using longitudinal data in animal breeding.

Highlights

As feeding production cost is the highest among all production costs of pig farming, feed efficiency has great importance for the swine industry efficiency (Patience et al, 2015)
Total feed intake was the sum of feed intake of one pig during the whole test period, and total weight gain was the difference of the initial body weight and final body weight of the test for that pig
Longitudinal data and cumulative data of feed intake for the whole test periods of a Yorkshire boars’ population were used, the prediction performance of the random regression model (RRM) based on pedigree and genomic information for Residual feed intake (RFI) prediction was compared with a regular animal model

Summary

Introduction

As feeding production cost is the highest among all production costs of pig farming, feed efficiency has great importance for the swine industry efficiency (Patience et al, 2015). Improving feed efficiency is vital for the whole swine industry. It reduces feed consumption, breeding cost, and energy consumption, but is helpful in reducing fecal and greenhouse gas emissions (Shirali et al, 2012). The ratio of feed intake to body weight gain, which is defined as feed conversion ratio (FCR), is commonly regarded as a measure of feed efficiency.

Methods

Results

Conclusion