The Long Non-Coding RNA Transcriptome Landscape in CHO Cells Under Batch and Fed-Batch Conditions.
The Long Non-Coding RNA Transcriptome Landscape in CHO Cells Under Batch and Fed-Batch Conditions.
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DOI：
10.1002/biot.201800122
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发表时间：
2018-06
影响因子：
4.7
通讯作者：
Davide Vito;C. Smales
中科院分区：
文献类型：
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作者：
Davide Vito;C. Smales
近年来，非编码 RNA 在决定中国仓鼠卵巢 (CHO) 细胞生长、生产力和重组产品质量属性方面的作用受到广泛关注，特别是对 microRNA 的研究。然而，其他类别的非编码 RNA 受到的关注较少。其中一类非编码 RNA 统称为长非编码 RNA (lncRNA)。作者使用基于小鼠的微阵列对 CHO 中的 lncRNA 转录组进行了首次景观分析，该微阵列也可用于编码转录组的监测。作者报告了在不同天的分批和补料分批条件下模型宿主 CHO 细胞系中存在的那些 lncRNA，并将不同 lncRNA 的表达相互关联。作者证明，小鼠微阵列适用于检测和分析数千种 CHO lncRNA，并通过 qRT-PCR 验证了其中的一些。然后，作者进一步分析了数据，以确定那些在培养的生长期和静止期之间或分批培养和补料培养之间表达变化最大的 lncRNA，从而确定潜在的 lncRNA 靶点，以进一步研究它们在控制 CHO 细胞生长中的作用。作者讨论了这个丰富数据集的发布的影响以及社区如何使用它。
The role of non-coding RNAs in determining growth, productivity, and recombinant product quality attributes in Chinese hamster ovary (CHO) cells has received much attention in recent years, exemplified by studies into microRNAs in particular. However, other classes of non-coding RNAs have received less attention. One such class are the non-coding RNAs known collectively as long non-coding RNAs (lncRNAs). The authors have undertaken the first landscape analysis of the lncRNA transcriptome in CHO using a mouse based microarray that also provided for the surveillance of the coding transcriptome. The authors report on those lncRNAs present in a model host CHO cell line under batch and fed-batch conditions on two different days and relate the expression of different lncRNAs to each other. The authors demonstrate that the mouse microarray is suitable for the detection and analysis of thousands of CHO lncRNAs and validated a number of these by qRT-PCR. The authors then further analyzed the data to identify those lncRNAs whose expression changed the most between growth and stationary phases of culture or between batch and fed-batch culture to identify potential lncRNA targets for further functional studies with regard to their role in controlling growth of CHO cells. The authors discuss the implications for the publication of this rich dataset and how this may be used by the community.