Why Multi-omic Analysis is Crucial for Reproducibility

by Hardik Jeena

Reproducibility is one of the most important aspects of research and a great deal of effort is taken to ensure that the findings of a study can be reproduced as otherwise, the conclusions lose credibility. This crucial reproductivity can be compromised by technical as well as biological variations. This blog emphasises the importance of the latter.

There are thousands of studies that relay on cell line, particularly cancer and immortalized cell lines in their research, acquired and cultured from other laboratories. This together with genomic instability, allows for clonal selection and diversification between different laboratories and a gradual change of a cell line in the same laboratory as these cells are cultured over and over again. Consequently, this poses a major challenge as the variability and render reproducibility on only a subset of cells. Figure 1 below demonstrates how profound these variations are as two Hela cell lines (Kyoto – blue and CCL2- green) are as different as cell lines from various tissues.

Figure 1: Degree of variation between cell lines

Figure 2: Heterogeneity in CNV, mRNA and Protein



A different layer is the proteome of a cell, which is tightly corelated with the phenotype but cannot be necessarily corelated with the genome. Variation analysis in kypto Hela cell line shows that there is a poor correlation between protein and mRNA levels (p = 0.04). Figure 2 below further emphasizes this as the variation in CNV translates to variation in mRNA but not to the protein levels. This Means that cell cannot be authenticated solely on the basis of the genome and a proteomic analysis is also necessary for an acceptable cell line authentication.

In conclusion, the conclusion of a study using cell lines is not transparent if only one layer is analysed. To understand and account for the heterogeneity, a multi-omic analysis is crucial.


1. Liu, Y., Mi, Y., Mueller, T., Kreibich, S., Williams, E.G., Van Drogen, A., Borel, C., Frank, M., Germain, P.L., Bludau, I. and Mehnert, M., 2019. Multi-omic measurements of heterogeneity in HeLa cells across laboratories. Nature biotechnology, 37(3), pp.314-322.

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