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利用短串联重复序列(STR)分析和数字PCR建立用于脊髓性肌萎缩症细胞系鉴定的参考数据集。

Establishing a reference dataset for the authentication of spinal muscular atrophy cell lines using STR profiling and digital PCR.

作者信息

Stabley Deborah L, Holbrook Jennifer, Harris Ashlee W, Swoboda Kathryn J, Crawford Thomas O, Sol-Church Katia, Butchbach Matthew E R

机构信息

Nemours Biomolecular Core Laboratory, Nemours Biomedical Research, Nemours Alfred I. duPont Hospital for Children, Wilmington, DE, USA.

Center for Applied Clinical Genomics, Nemours Biomedical Research, Nemours Alfred I. duPont Hospital for Children, Wilmington, DE, USA.

出版信息

Neuromuscul Disord. 2017 May;27(5):439-446. doi: 10.1016/j.nmd.2017.02.002. Epub 2017 Feb 6.

Abstract

Fibroblasts and lymphoblastoid cell lines (LCLs) derived from individuals with spinal muscular atrophy (SMA) have been and continue to be essential for translational SMA research. Authentication of cell lines helps ensure reproducibility and rigor in biomedical research. This quality control measure identifies mislabeling or cross-contamination of cell lines and prevents misinterpretation of data. Unfortunately, authentication of SMA cell lines used in various studies has not been possible because of a lack of a reference. In this study, we provide said reference so that SMA cell lines can be subsequently authenticated. We use short tandem repeat (STR) profiling and digital PCR (dPCR), which quantifies SMN1 and SMN2 copy numbers, to generate molecular identity codes for fibroblasts and LCLs that are commonly used in SMA research. Using these molecular identity codes, we clarify the familial relationships within a set of fibroblasts commonly used in SMA research. This study presents the first cell line reference set for the SMA research community and demonstrates its usefulness for re-identification and authentication of lines commonly used as in vitro models for future studies.

摘要

来自脊髓性肌萎缩症(SMA)患者的成纤维细胞和淋巴母细胞样细胞系(LCLs)一直并将继续对SMA的转化研究至关重要。细胞系的鉴定有助于确保生物医学研究的可重复性和严谨性。这种质量控制措施可识别细胞系的错误标记或交叉污染,并防止数据的错误解读。不幸的是,由于缺乏参考标准,各种研究中使用的SMA细胞系的鉴定一直无法实现。在本研究中,我们提供了所述参考标准,以便随后对SMA细胞系进行鉴定。我们使用短串联重复序列(STR)分析和数字PCR(dPCR)(其可定量SMN1和SMN2的拷贝数)来生成SMA研究中常用的成纤维细胞和LCLs的分子识别码。利用这些分子识别码,我们阐明了SMA研究中常用的一组成纤维细胞内的家族关系。本研究为SMA研究界提供了首个细胞系参考集,并证明了其对未来研究中常用作体外模型的细胞系进行重新识别和鉴定的有用性。

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