中国畜牧杂志

深度学习模型提高猪繁殖性状基因组选择准确性的研究

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中国畜牧杂志 | 遗传育种 2026,62(2): 191-197

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中国畜牧杂志 |遗传育种 2026 , 62 (2) : 191 -197

深度学习模型提高猪繁殖性状基因组选择准确性的研究

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韦佳霖¹, 刘炎², 印遇龙¹, 孙敬春¹, 徐康¹

作者信息

通讯作者:

孙敬春

作者简介:

韦佳霖（1999-），男，广西河池人，硕士研究生，主要从事动物遗传育种与繁殖方向研究，E-mail:w18178889075@163.com;

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出版时间: 2025-12-04 doi: 10.19556/j.0258-7033.20250802-04

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为了探究深度学习模型在猪繁殖性状中的基因组选择效果，本研究以唐人神集团大白猪种猪群体的繁殖表型和芯片分型数据为研究对象，采用基因型填充的策略增加遗传数据标记密度，并评估填充前后数据集，使用GBLUP、RF、LightGBM和深度学习模型DNNGP进行基因组选择的准确性。结果显示，深度学习模型在芯片数据基因组选择中准确性比其他3款模型高0.032～0.155，并且在基因型填充数据集中准确性比其他3款模型最高提升了0.248。结果表明深度学习模型在低遗传力性状和基因型填充数据集中均能够保持较好的基因组选择准确性，并在猪智能化精准育种中具有较好的应用前景。

关键词

大白猪 / 深度学习 / 基因组选择 / 繁殖性状

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韦佳霖, 刘炎, 印遇龙, 孙敬春, 徐康. 深度学习模型提高猪繁殖性状基因组选择准确性的研究. 中国畜牧杂志, 2026 , 62 (2) : 191 -197 . DOI: 10.19556/j.0258-7033.20250802-04

基金

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农业生物育种国家科技重大专项（2023ZD04046）;中国博士后科学基金面上资助（2024M753485）;

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2026年第62卷第2期

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doi: 10.19556/j.0258-7033.20250802-04

首发时间：2026-07-01
出版时间：2025-12-04

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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