Suárez-Vega Aroa, Frutos Pilar, Gutiérrez-Gil Beatriz, Esteban-Blanco Cristina, Toral Pablo G, Arranz Juan-José, Hervás Gonzalo
Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, León, Spain.
Instituto de Ganadería de Montaña (CSIC-Universidad de León), Grulleros, León, Spain.
Front Vet Sci. 2023 Apr 3;10:1122953. doi: 10.3389/fvets.2023.1122953. eCollection 2023.
As higher feed efficiency in dairy ruminants means a higher capability to transform feed nutrients into milk and milk components, differences in feed efficiency are expected to be partly linked to changes in the physiology of the mammary glands. Therefore, this study aimed to determine the biological functions and key regulatory genes associated with feed efficiency in dairy sheep using the milk somatic cell transcriptome.
RNA-Seq data from high (H-FE, = 8) and low (L-FE, = 8) feed efficiency ewes were compared through differential expression analysis (DEA) and sparse Partial Least Square-Discriminant analysis (sPLS-DA).
In the DEA, 79 genes were identified as differentially expressed between both conditions, while the sPLS-DA identified 261 predictive genes [variable importance in projection (VIP) > 2] that discriminated H-FE and L-FE sheep.
The DEA between sheep with divergent feed efficiency allowed the identification of genes associated with the immune system and stress in L-FE animals. In addition, the sPLS-DA approach revealed the importance of genes involved in cell division (e.g., and ) and cellular lipid metabolic process (e.g., , and ) for the H-FE sheep in the lactating mammary gland transcriptome. A set of discriminant genes, commonly identified by the two statistical approaches, was also detected, including some involved in cell proliferation (e.g., , or ) or encoding heat-shock proteins (). These results provide novel insights into the biological basis of feed efficiency in dairy sheep, highlighting the informative potential of the mammary gland transcriptome as a target tissue and revealing the usefulness of combining univariate and multivariate analysis approaches to elucidate the molecular mechanisms controlling complex traits.
由于反刍动物的饲料效率更高意味着将饲料营养转化为牛奶和牛奶成分的能力更强,因此预计饲料效率的差异部分与乳腺生理变化有关。因此,本研究旨在利用乳体细胞转录组确定与奶山羊饲料效率相关的生物学功能和关键调控基因。
通过差异表达分析(DEA)和稀疏偏最小二乘判别分析(sPLS-DA)比较了高(H-FE,n = 8)和低(L-FE,n = 8)饲料效率母羊的RNA测序数据。
在DEA中,有79个基因被鉴定为在两种情况下差异表达,而sPLS-DA鉴定出261个预测基因[投影变量重要性(VIP)>2],这些基因可区分H-FE和L-FE绵羊。
对饲料效率不同的绵羊进行DEA,能够鉴定出与L-FE动物免疫系统和应激相关的基因。此外,sPLS-DA方法揭示了参与细胞分裂(如MCM3和MCM7)和细胞脂质代谢过程(如FABP3、FABP4和PLIN2)的基因对泌乳期乳腺转录组中H-FE绵羊的重要性。还检测到一组通过两种统计方法共同鉴定的判别基因,包括一些参与细胞增殖(如MKI67、TOP2A或CCNE1)或编码热休克蛋白(HSPA1A)的基因。这些结果为奶山羊饲料效率的生物学基础提供了新的见解,突出了乳腺转录组作为靶组织的信息潜力,并揭示了结合单变量和多变量分析方法来阐明控制复杂性状分子机制的有用性。