Mathematical ‘Gingko trees’ reveal Mutations in single cells that characterize diseases Credit http://dx.doi.org/10.1038/nmeth.3578
A new interactive analysis program called Gingko has been released that reduces the uncertainty of single-cell analysis and provides a simple way to visualize patterns in copy number mutations across populations of cells. Detailed knowledge of CNVs can point to specific treatment regimens.
The free software will improve scientists’ ability to study this important type of genetic anomaly and could help clinicians better target medications based on cells’ specific mutation profiles.
In copy number variations (CNV), large chunks of DNA are either deleted from or added to the genome. When there are too many or too few copies of a given gene or genes, due to CNVs, disease can occur. Such mutations have been linked not only with cancer but a host of other illnesses, including autism and schizophrenia. Researchers can learn a lot by analyzing CNVs in bulk samples -from a tumor biopsy etc -but they can learn more by investigating CNVs in individual cells. “You may think that every cell in a tumor would be the same, but that’s actually not the case,” says CSHL Associate Professor Michael Schatz. Simultaneously employing different drugs to target different cancer subclasses could prevent remission, scientists have proposed.
One powerful single-cell analytic technique for exploring CNV is whole genome sequencing. The challenge is that, before sequencing can be done, the cell’s DNA has to be amplified many times over. This process is rife with errors, with some arbitrary chunks of DNA being amplified more than others. In addition, because many labs use their own software to examine CNVs, there is little consistency in how researchers analyze their results.
The interactive, web-based program automatically processes sequence data, maps the sequences to a reference genome, and creates CNV profiles for every cell that can then be viewed with a user-friendly graphical interface. In addition, Gingko constructs phylogenetic trees based on the profiles, allowing cells with similar copy number mutations to be grouped together. It also analyzes patterns in the sequence reads in order to recognize, and greatly reduce, amplification errors. http://www.cshl.edu/news-and-features/mathematical-gingko-trees-reveal-mutations-in-single-cells-that-characterize-diseases.html
Recent Comments