Genetic bottlenecks and the hazardous game of population reduction in cell line based research

Exp Cell Res. 2010 Dec 10;316(20):3379-86. doi: 10.1016/j.yexcr.2010.07.010. Epub 2010 Jul 17.


Established tumour cell lines are ubiquitous tools in research, but their representativity is often debated. One possible caveat is that many cell lines are derived from cells with genomic instability, potentially leading to genotype changes in vitro. We applied SNP-array analysis to an established tumour cell line (WiT49). Even though WiT49 exhibited chromosome segregation errors in 30% of cell divisions, only a single chromosome segment exhibited a shift in copy number after 20 population doublings in culture. In contrast, sub-populations derived from single cells expanded for an equal number of population doublings showed on average 5.8 and 8.9 altered segments compared to the original culture and to each other, respectively. Most copy number variants differentiating these single cell clones corresponded to pre-existing variations in the original culture. Furthermore, no sub-clonal variation was detected in any of the populations derived from single cells. This indicates that genetic bottlenecks resulting from population reduction poses a higher threat to genetic representativity than prolonged culture per se, even in cell lines with a high rate of genomic instability. Genetic bottlenecks should therefore be considered a potential caveat in all studies involving sub-cloning, transfection and other conditions leading to a temporary reduction in cell number.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Culture Techniques
  • Cell Line, Tumor / metabolism*
  • Cell Line, Tumor / pathology*
  • Cell Proliferation
  • Chromosomal Instability / genetics
  • Chromosome Segregation / genetics
  • Clone Cells / cytology*
  • Clone Cells / metabolism*
  • DNA Copy Number Variations / genetics
  • Evolution, Molecular
  • Gene Frequency / genetics
  • Genomic Instability / genetics*
  • Genotype
  • Humans
  • Models, Genetic*
  • Oligonucleotide Array Sequence Analysis
  • Polymorphism, Single Nucleotide / genetics
  • Principal Component Analysis