Random subcloning.

Abstract

Random subcloning strategies are commonly employed for analyzing pieces of DNA that are too large for direct analysis. Such strategies are applicable to gene finding, physical mapping, and DNA sequencing. Random subcloning refers to the generation of many small, directly analyzable fragments of DNA that represent random fragments of a larger whole, such as a genome. Following analysis of these fragments, a map or sequence of the original target may be reconstructed. Mathematical modeling is useful in planning such strategies and in providing a reference for their evaluation, both during execution and following completion. The statistical theory necessary for constructing these models has been developed independently over the last century. This paper brings this theory together into a statistical model for random subcloning strategies. This mathematical model retains its utility even at high subclone redundancies, which are necessary for project completion. The discussion here centers on shotgun sequencing, a random subcloning strategy envisioned as the method of choice for sequencing the human genome.