基于多层感知机的绵羊限性性状基因组选择模拟研究

doi:10.11843/j.issn.0366-6964.2023.07.015

Abstract

Abstract: This study aimed to apply multilayer perceptron(MLP) to genome selection of sex-limited traits in sheep, and compare it with other classical genome selection methods in various situations. In this study, Qmsim software was used to simulate the phenotype data and genotype data of 2 sheep population(Popl and Pop2). Artificial neural network (ANN) was used in MLP, and residual maximum likelihood (REML) method was used in linear model to estimate genetic parameters of different populations. Using Python to write MLP model, using DMU software to achieve best linear unbiased prediction (BLUP), genomic BLUP (GBLUP) and single-step GBLUP (SSGBLUP). The differences in the estimation of heritability (h²) and breeding values under different conditions were evaluated. In all cases, MLP and SSGBLUP were significantly (P<0.05) better than GBLUP and BLUP. There is no significant difference between h² estimation of MLP and SSGBLUP in the 3 conditions:When h² was 0.05, the QTL number was 100 and the marker number was 10K in the Pop2 population; when h² was 0.2, the QTL number was 500 under the two marker number in Pop1, and the QTL number was 100 under the marker number of 50K in Pop2; when h² was 0.5 and QTL number was 100, the marker number of 10K in Pop1 and the marker number of 50K in Pop2. Except for the above, the h² estimates of MLP were significantly better (P<0.05) than SSGBLUP, GBLUP, and BLUP. Under different prior values of h², when QTL number, marker number changed, the difference between the estimated h² of MLP and that of contemporary population was smaller than that of SSGBLUP, GBLUP, and BLUP. The h² estimation results of SSGBLUP and GBLUP methods were very different under different marker number, and the MLP difference was small. In all cases, the prediction accuracy of GEBV by MLP was the highest. When the prior value of h² was 0.05, the GEBV accuracy of MLP at 10K was slightly higher than that of SSGBLUP at 50K. Under the same h², number of QTL and marker number, the EBV prediction accuracy of each method in the Pop2 population was improved compared with that in the Pop1 population. According to the above simulation results, MLP is superior to other classical genome selection methods in the genome selection of sex-limited traits in sheep.

Key words: multilayer perceptron, genomic selection, simulation, prediction, sex-limited trait

CLC Number:

S826.2

WANG Wannian, CHEN Sijia, GAO Jinrong, WEN Zhonghao, YUAN Mengjiao, ZHANG Hongzhi, PANG Zhixu, QIAO Liying, LIU Wenzhong. Simulation Study on Genomic Selection of Sex-limited Traits Using Multilayer Perceptron in Sheep[J]. Acta Veterinaria et Zootechnica Sinica, 2023, 54(7): 2824-2835.

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Simulation Study on Genomic Selection of Sex-limited Traits Using Multilayer Perceptron in Sheep

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