高通量非靶向代谢组学揭示了两种不同猪品种的代谢物和代谢途径。

IF 4 2区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE Animal Pub Date : 2025-01-01 DOI:10.1016/j.animal.2024.101393
S. Bovo , M. Bolner , G. Schiavo , G. Galimberti , F. Bertolini , S. Dall’Olio , A. Ribani , P. Zambonelli , M. Gallo , L. Fontanesi
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引用次数: 0

摘要

代谢组学可以描述分子表型,并可能有助于剖析家畜物种中与经济相关性状相关的生物过程。纯种猪代谢组学特征的比较分析可以为解释生产性能差异的基本生物学机制提供见解。根据这一概念,本研究旨在大规模比较两个意大利重猪品种(意大利杜洛克猪和意大利大白猪)的血浆代谢组学特征,以间接评估其不同遗传背景对品种代谢组学的影响。我们在总共962头猪中使用了一种高通量非靶向代谢组学方法,使我们能够检测和相对量化来自不同生物类别的722种代谢物。分子数据分析使用生物信息学管道,包括Boruta算法(一种随机森林包装算法)和稀疏偏最小二乘判别分析(sPLS-DA)进行特征选择,该管道专为识别两个品种之间差异丰富的代谢物而设计,具有鲁棒性和统计显著性。在充分评估随机成分对缺失值imputation的影响后,Boruta选择了100个鉴别代谢物,并使用sPLS-DA鉴定了17个鉴别代谢物(均在前面的列表中)。100种区别代谢物中约有一半在一个或另一个品种中具有较高的浓度(48种在意大利大白猪中,以氨基酸和肽为主;在意大利杜洛克猪中有52个,具有脂质患病率)。这些代谢物来自7个不同的超级途径,两个品种之间的绝对平均百分比差异(|Δ|%)为39.2±32.4。这些代谢物中有6种|Δ|% |00。基于boruta鉴定的代谢物的一般相关网络分析包括31个单子和69个连接141条边的代谢物,其中2个大簇(> 15个节点),3个中等簇(3-6个节点)和8对额外的代谢物,大多数代谢物属于同一个超级通路。代表脂质超通路的主要簇包括24种代谢物,主要是鞘磷脂。总的来说,本研究确定了意大利杜洛克猪和意大利大白猪之间的代谢组学差异,这两个品种的特定遗传背景解释了这一差异。这些生物标志物可以解释这两个品种之间的生物学差异,并在养猪和畜牧业中具有潜在的实际应用价值。
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High-throughput untargeted metabolomics reveals metabolites and metabolic pathways that differentiate two divergent pig breeds
Metabolomics can describe the molecular phenome and may contribute to dissecting the biological processes linked to economically relevant traits in livestock species. Comparative analyses of metabolomic profiles in purebred pigs can provide insights into the basic biological mechanisms that may explain differences in production performances. Following this concept, this study was designed to compare, on a large scale, the plasma metabolomic profiles of two Italian heavy pig breeds (Italian Duroc and Italian Large White) to indirectly evaluate the impact of their different genetic backgrounds on the breed metabolomes. We utilised a high-throughput untargeted metabolomics approach in a total of 962 pigs that allowed us to detect and relatively quantify 722 metabolites from various biological classes. The molecular data were analysed using a bioinformatics pipeline specifically designed for identifying differentially abundant metabolites between the two breeds in a robust and statistically significant manner, including the Boruta algorithm, which is a Random Forest wrapper, and sparse Partial Least Squares Discriminant Analysis (sPLS-DA) for feature selection. After thoroughly evaluating the impact of random components on missing value imputation, 100 discriminant metabolites were selected by Boruta and 17 discriminant metabolites (all included within the previous list) were identified with sPLS-DA. About half of the 100 discriminant metabolites had a higher concentration in one or the other breed (48 in Italian Large White pigs, with a prevalence of amino acids and peptides; 52 in Italian Duroc pigs, with a prevalence of lipids). These metabolites were from seven distinct super pathways and had an absolute mean value of percentage difference between the two breeds (|Δ|%) of 39.2 ± 32.4. Six of these metabolites had |Δ|%> 100. A general correlation network analysis based on Boruta−identified metabolites consisted of 31 singletons and 69 metabolites connected by 141 edges, with two large clusters (> 15 nodes), three medium clusters (3–6 nodes) and eight additional pairs, with most metabolites belonging to the same super pathway. The major cluster representing the lipids super-pathway included 24 metabolites, primarily sphingomyelins. Overall, this study identified metabolomic differences between Italian Duroc and Italian Large White pigs explained by the specific genetic background of the two breeds. These biomarkers can explain the biological differences between these two breeds and can have potential practical applications in pig breeding and husbandry.
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来源期刊
Animal
Animal 农林科学-奶制品与动物科学
CiteScore
7.50
自引率
2.80%
发文量
246
审稿时长
3 months
期刊介绍: Editorial board animal attracts the best research in animal biology and animal systems from across the spectrum of the agricultural, biomedical, and environmental sciences. It is the central element in an exciting collaboration between the British Society of Animal Science (BSAS), Institut National de la Recherche Agronomique (INRA) and the European Federation of Animal Science (EAAP) and represents a merging of three scientific journals: Animal Science; Animal Research; Reproduction, Nutrition, Development. animal publishes original cutting-edge research, ''hot'' topics and horizon-scanning reviews on animal-related aspects of the life sciences at the molecular, cellular, organ, whole animal and production system levels. The main subject areas include: breeding and genetics; nutrition; physiology and functional biology of systems; behaviour, health and welfare; farming systems, environmental impact and climate change; product quality, human health and well-being. Animal models and papers dealing with the integration of research between these topics and their impact on the environment and people are particularly welcome.
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