Automating DNA processing

Abstract

Technology is currently available to identify the genetic codes responsible for physical traits and genetic diseases in both plants and animals. Regardless of whether the final goal is medical diagnosis or breeder selection, extensive time and resources must be spent in laboratory research to determine the genetic structure of the relevant organisms. DNA processing is riddled with time intensive laboratory techniques that must be improved or replaced if genotyping large numbers of samples is to be accomplished. This thesis identifies and explains modules in DNA processing and how they can be improved by automation. modules associated with genome mapping are the focus of most of the discussion. A functional biochemistry background is provided so that researchers in automation can be efficiently assimilated to future biochen-fistry/automation projects. The needs of biochemistry researchers at Texas A&M University are specifically addressed. Herein, DNA processing has been defined as a series of discrete sub-processes or process modules in order to aid scheduling of future automation projects. Target process modules (sub-processes with a high probability of automation success) have been identified. In addition, possible automation solutions have been proposed for each target module along with a characterization of fundamental design parameters. Concluding this text is a discussion of procedures in genome mapping that have not been sufficiently automated. The initial focus of this thesis is on short term solutions. However, attention is given to more conceptual solutions accompanied by the biochemistry background necessary to begin developing them. Though systems are proposed to improve the efficiency of many processes, no implementation has been attempted. Design specifications are based on observation of current laboratory techniques and the variance that is typically allowed in relevant process parameters in TAMU laboratories.