Abstract
BACKGROUND: Karyotypic integrity is essential for the successful germline transmission of alleles mutated in embryonic stem (ES) cells. Classical methods for the identification of aneuploidy involve cytological analyses that are both time consuming and require rare expertise to identify mouse chromosomes. RESULTS: As part of the International Mouse Phenotyping Consortium, we gathered data from over 1,500 ES cell clones and found that the germline transmission (GLT) efficiency of clones is compromised when over 50 % of cells harbour chromosome number abnormalities. In JM8 cells, chromosomes 1, 8, 11 or Y displayed copy number variation most frequently, whilst the remainder generally remain unchanged. We developed protocols employing droplet digital polymerase chain reaction (ddPCR) to accurately quantify the copy number of these four chromosomes, allowing efficient triage of ES clones prior to microinjection. We verified that assessments of aneuploidy, and thus decisions regarding the suitability of clones for microinjection, were concordant between classical cytological and ddPCR-based methods. Finally, we improved the method to include assay multiplexing so that two unstable chromosomes are counted simultaneously (and independently) in one reaction, to enhance throughput and further reduce the cost. CONCLUSION: We validated a PCR-based method as an alternative to classical karyotype analysis. This technique enables laboratories that are non-specialist, or work with large numbers of clones, to precisely screen ES cells for the most common aneuploidies prior to microinjection to ensure the highest level of germline transmission potential. The application of this method allows early exclusion of aneuploid ES cell clones in the ES cell to mouse conversion process, thus improving the chances of obtaining germline transmission and reducing the number of animals used in failed microinjection attempts. This method can be applied to any other experiments that require accurate analysis of the genome for copy number variation (CNV).