Seo Minseok, Lee Hyun-Jeong, Kim Kwondo, Caetano-Anolles Kelsey, Jeong Jin Young, Park Sungkwon, Oh Young Kyun, Cho Seoae, Kim Heebal
Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-741, Korea ; CHO&KIM genomics, Seoul 151-919, Korea .
Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-741, Korea ; Animal Nutritional & Physiology Team, National Institute of Animal Science, Jeonju 565-851, Korea .
Asian-Australas J Anim Sci. 2016 Mar;29(3):343-51. doi: 10.5713/ajas.15.0525. Epub 2016 Mar 1.
Although the chemical, physical, and nutritional properties of bovine milk have been extensively studied, only a few studies have attempted to characterize milk-synthesizing genes using RNA-seq data. RNA-seq data was collected from 21 Holstein samples, along with group information about milk production ability; milk yield; and protein, fat, and solid contents. Meta-analysis was employed in order to generally characterize genes related to milk production. In addition, we attempted to investigate the relationship between milk related traits, parity, and lactation period. We observed that milk fat is highly correlated with lactation period; this result indicates that this effect should be considered in the model in order to accurately detect milk production related genes. By employing our developed model, 271 genes were significantly (false discovery rate [FDR] adjusted p-value<0.1) detected as milk production related differentially expressed genes. Of these genes, five (albumin, nitric oxide synthase 3, RNA-binding region (RNP1, RRM) containing 3, secreted and transmembrane 1, and serine palmitoyltransferase, small subunit B) were technically validated using quantitative real-time polymerase chain reaction (qRT-PCR) in order to check the accuracy of RNA-seq analysis. Finally, 83 gene ontology biological processes including several blood vessel and mammary gland development related terms, were significantly detected using DAVID gene-set enrichment analysis. From these results, we observed that detected milk production related genes are highly enriched in the circulation system process and mammary gland related biological functions. In addition, we observed that detected genes including caveolin 1, mammary serum amyloid A3.2, lingual antimicrobial peptide, cathelicidin 4 (CATHL4), cathelicidin 6 (CATHL6) have been reported in other species as milk production related gene. For this reason, we concluded that our detected 271 genes would be strong candidates for determining milk production.
尽管牛乳的化学、物理和营养特性已得到广泛研究,但仅有少数研究尝试利用RNA测序(RNA-seq)数据对乳汁合成基因进行表征。从21份荷斯坦奶牛样本中收集了RNA-seq数据,以及关于产奶能力、产奶量、蛋白质、脂肪和固体含量的分组信息。采用荟萃分析以全面表征与产奶相关的基因。此外,我们试图研究与乳汁相关性状、胎次和泌乳期之间的关系。我们观察到乳脂肪与泌乳期高度相关;这一结果表明,为了准确检测与产奶相关的基因,在模型中应考虑这种影响。通过应用我们开发的模型,271个基因被显著(错误发现率[FDR]调整后p值<0.1)检测为与产奶相关的差异表达基因。在这些基因中,有五个(白蛋白、一氧化氮合酶3、含RNA结合区域(RNP1、RRM)的3、分泌和跨膜蛋白1以及丝氨酸棕榈酰转移酶小亚基B)通过定量实时聚合酶链反应(qRT-PCR)进行了技术验证,以检验RNA-seq分析的准确性。最后,使用DAVID基因集富集分析显著检测到83个基因本体生物学过程,包括几个与血管和乳腺发育相关的术语。从这些结果中,我们观察到检测到的与产奶相关的基因在循环系统过程和乳腺相关生物学功能中高度富集。此外,我们观察到检测到的基因包括小窝蛋白1、乳腺血清淀粉样蛋白A3.2、舌抗菌肽、cathelicidin 4(CATHL4)、cathelicidin 6(CATHL6),在其他物种中已被报道为与产奶相关的基因。因此,我们得出结论,我们检测到的271个基因将是确定产奶量的有力候选基因。