Abstract
A clonally derived (or “monoclonal”) cell line is a cell population derived from a single progenitor cell. Clonally derived cell lines are required for many biotechnological applications. For instance, recombinant mammalian cells used to produce therapeutic proteins are expected by regulatory authorities to be clonally derived. Assurance of clonal derivation (or “clonality”) is usually obtained from the characterization of the procedure used for cell cloning, for instance by assessing the success rate of single‐cell sorting but not by assessing the cell line itself. We have developed a method to assess clonal derivation directly from the genetic makeup of cells. The genomic test of clonality is based on whole‐genome sequencing and statistical analysis of single nucleotide variants. This approach quantifies the clonal fractions present in nonclonal samples and it provides a measure of the probability that a cell line is derived from a single cell. Upon experimental validation of the test, we show that it is highly accurate and that it can robustly detect minor clonal fractions of as little as 1% of the cell population. Moreover, we find that it is applicable to various cell line development protocols. This approach can simplify development protocols and shorten timelines while ensuring clonal derivation with high confidence.
Highlights
Building on the statistical analysis of single nucleotide variants (SNVs), we developed an accurate measure of the clonal fractions present in a cell population and derived a measure of the probability that the cell line is clonally derived (i.e., p‐value for clonal derivation, or “monoclonality”)
This demonstrates that if single‐ cell cloning performed upon the second transfection had failed, each of the two cells would contain hundreds of SNVs that would be absent from the other progenitor cell and that would yield a strong signal for genomic test of clonality (GTC) to detect non‐clonality and provide a sensitive measure of clonal fractions
We report the development of a novel method to assess cell line clonality based on the genome‐wide analysis of SNVs
Summary
Genetically more homogeneous, which can improve the consistency and robustness of recombinant protein. From the classical limiting dilution method to the recent development of microfluidic chips to sort single cells individually, every new technology has improved the effectiveness of single‐cell cloning. Direct assessment of clonal derivation based on the analysis of the recombinant cell line itself has witnessed few improvements. The clonal derivation of a cell line can be established by verifying that the specific integration site is homogeneously present in the population. We show that non‐clonal cell lines can be efficiently detected based on the genome‐wide analysis of its single nucleotide variants (SNVs). Building on this principle, we developed and validated a formal statistical procedure for testing clonal derivation named genomic test of clonality (GTC). We demonstrate that it can be efficiently integrated in the context of commercial cell line development, even in the case of procedures involving multiple successive subcloning steps
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