Robust measurement of telomere length in single cells.

Author: Wang F, Pan X, Kalmbach K, Seth-Smith ML, Ye X, Antumes DM, Yin Y, Liu L, Keefe DL, Weissman SM.
Affiliation: Department of Obstetrics and Gynecology, New York University Langone Medical Center, NY 10016.
Conference/Journal: Proc Natl Acad Sci U S A.
Date published: 2013 May 9
Other: Word Count: 262



Measurement of telomere length currently requires a large population of cells, which masks telomere length heterogeneity in single cells, or requires FISH in metaphase arrested cells, posing technical challenges. A practical method for measuring telomere length in single cells has been lacking. We established a simple and robust approach for single-cell telomere length measurement (SCT-pqPCR). We first optimized a multiplex preamplification specific for telomeres and reference genes from individual cells, such that the amplicon provides a consistent ratio (T/R) of telomeres (T) to the reference genes (R) by quantitative PCR (qPCR). The average T/R ratio of multiple single cells corresponded closely to that of a given cell population measured by regular qPCR, and correlated with those of telomere restriction fragments (TRF) and quantitative FISH measurements. Furthermore, SCT-pqPCR detected the telomere length for quiescent cells that are inaccessible by quantitative FISH. The reliability of SCT-pqPCR also was confirmed using sister cells from two cell embryos. Telomere length heterogeneity was identified by SCT-pqPCR among cells of various human and mouse cell types. We found that the T/R values of human fibroblasts at later passages and from old donors were lower and more heterogeneous than those of early passages and from young donors, that cancer cell lines show heterogeneous telomere lengths, that human oocytes and polar bodies have nearly identical telomere lengths, and that the telomere lengths progressively increase from the zygote, two-cell to four-cell embryo. This method will facilitate understanding of telomere heterogeneity and its role in tumorigenesis, aging, and associated diseases.
KEYWORDS:
cell senescence, single cell analysis, stem cell

PMID: 23661059