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Background: The crisis of Misidentified and contaminated cell lines have plagued the biological research community for decades. Some repositories and journals have heeded calls for mandatory authentication of human cell lines, yet misidentification of mouse cell lines has received little publicity despite their importance in sponsored research. Short tandem repeat (STR) profiling is the standard authentication method, but it may fail to distinguish cell lines derived from the same inbred strain of mice. Additionally, STR profiling does not reveal karyotypic changes that occur in some high-passage lines and may have functional consequences. Single nucleotide polymorphism (SNP) profiling has been suggested as a more accurate and versatile alternative to STR profiling; however, a high-throughput method for SNP-based authentication of mouse cell lines has not been described., Results: We have developed computational methods (Cell Line Authentication by SNP Profiling, CLASP) for cell line authentication and copy number analysis based on a cost-efficient SNP array, and we provide a reference database of commonly used mouse strains and cell lines. We show that CLASP readily discriminates among cell lines of diverse taxonomic origins, including multiple cell lines derived from a single inbred strain, intercross or wild caught mouse. CLASP is also capable of detecting contaminants present at concentrations as low as 5%. Of the 99 cell lines we tested, 15 exhibited substantial divergence from the reported genetic background. In all cases, we were able to distinguish whether the authentication failure was due to misidentification (one cell line, Ba/F3), the presence of multiple strain backgrounds (five cell lines), contamination by other cells and/or the presence of aneuploid chromosomes (nine cell lines)., Conclusions: Misidentification and contamination of mouse cell lines is potentially as widespread as it is in human cell culture. This may have substantial implications for studies that are dependent on the expected background of their cell cultures. Laboratories can mitigate these risks by regular authentication of their cell cultures. Our results demonstrate that SNP array profiling is an effective method to combat cell line misidentification.

Replicated artificial selection for high levels of voluntary wheel running in an outbred strain of mice favored an autosomal recessive allele whose primary phenotypic effect is a 50% reduction in hind-limb muscle mass. Within the High Runner (HR) lines of mice, the numerous pleiotropic effects (e.g., larger hearts, reduced total body mass and fat mass, longer hind-limb bones) of this hypothesized adaptive allele include functional characteristics that facilitate high levels of voluntary wheel running (e.g., doubling of mass-specific muscle aerobic capacity, increased fatigue resistance of isolated muscles, longer hind-limb bones). Previously, we created a backcross population suitable for mapping the responsible locus. We phenotypically characterized the population and mapped the Minimsc locus to a 2.6-Mb interval on MMU11, a region containing ∼100 known or predicted genes. Here, we present a novel strategy to identify the genetic variant causing the mini-muscle phenotype. Using high-density genotyping and whole-genome sequencing of key backcross individuals and HR mice with and without the mini-muscle mutation, from both recent and historical generations of the HR lines, we show that a SNP representing a C-to-T transition located in a 709-bp intron between exons 11 and 12 of the Myosin heavy polypeptide 4 (Myh4) skeletal muscle gene (position 67,244,850 on MMU11; assembly, December 2011, GRCm38/mm10; ENSMUSG00000057003) is responsible for the mini-muscle phenotype, Myh4(Minimsc). Using next-generation sequencing, our approach can be extended to identify causative mutations arising in mouse inbred lines and thus offers a great avenue to overcome one of the most challenging steps in quantitative genetics.