Counting individual DNA molecules by the stochastic attachment of diverse labels.

We implement a unique strategy for single molecule counting termed stochastic labeling, where random attachment of a diverse set of labels converts a population of identical DNA molecules into a population of distinct DNA molecules suitable for threshold detection. The conceptual framework for stochastic labeling is developed and experimentally demonstrated by determining the absolute and relative number of selected genes after stochastically labeling approximately 360,000 different fragments of the human genome. The approach does not require the physical separation of molecules and takes advantage of highly parallel methods such as microarray and sequencing technologies to simultaneously count absolute numbers of multiple targets. Stochastic labeling should be particularly useful for determining the absolute numbers of RNA or DNA molecules in single cells.