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DOE Human Genome Program Contractor-Grantee Workshop IV

Santa Fe, New Mexico, November 13-17, 1994

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Introduction to the Workshop
URLs Provided by Attendees

Abstracts
Mapping
Informatics
Sequencing
Instrumentation
Ethical, Legal, and Social Issues
Infrastructure
 

The electronic form of this document may be cited in the following style:
Human Genome Program, U.S. Department of Energy, DOE Human Genome Program Contractor-Grantee Workshop IV, 1994.

Abstracts scanned from text submitted for November 1994 DOE Human Genome Program Contractor-Grantee Workshop. Inaccuracies have not been corrected.

Automated Methods for Large-Scale Physical Mapping and Sequencing

Patricia A. Medvick[1], Tony J. Beugelsdijk, Jerome T. Chen, Bobi K. Den Hartog
Systems and Robotics Group, ESA-6, MS J580, and Center for Human Genome Studies; Los Alamos National Laboratory, Los Alamos, NM 87545. [1]Corresponding author.

As a major contribution to the Los Alamos mapping and library distribution effort, we have successfully created a prototype gridding system. This system reduces user interaction to initial setup, is flexible, and can produce 8 duplicate membrane arrays from 16 microtiter plates in two hours [1,2]. System development provided insight into the requirements of molecular biologists in the laboratory. With prolonged use of the prototype gridding system, analysis of the probed membranes was rate limiting. Our software for automating this analysis procedure addressed the data glut and data-tracking problems that result from isolated automation of individual steps in a process. These problems are a familiar occurrence in analytical chemistry labs. To combat the analytical-chemistry throughput problem for the Department of Energy cleanup effort, the Robotic Technology Development Program has supported the Contaminant Analysis Automation (CAA) project, an integrated effort involving five national laboratories [3]. The CAA concept, in which samples are directed through intelligent submodules by a central controller, consisting of a user interface, task sequence controller, database and expert system, has been developed and implemented. This paradigm is directly applicable to the molecular biology laboratory, particularly to a high-throughput effort such as the mapping and sequencing of the human genome.

Our next generation gridding system conforms to this model. The software interfaces and controller are directly applicable to our next task of constructing a high-throughput sequencer. The gridding system contains four hardware modules consisting of a robot, tool-washer, plate stacker/restacker, and barcode reader. Controllers for these modules include an Adept controller, two single-board IBM-type PCs and a Sun workstation that contains the central control software. The central control software consists of a user interface, database, task sequencer, and communication interface to each of the hardware controllers. Configuration information for each hardware module is stored in the database and provides a list of tasks performed by each module. Scripts provide the pattern of tasks for the system and can be modified by the biologist. This model for hardware control provides the flexibility to incorporate changes to the process and to upgrade hardware as new equipment becomes available. The control software is directly applicable to the integration of a high-throughput sequencing system and is suitable for facilitating cooperation between centers of automation development.

This work was funded by the DOE Genome Program (ERW-F142, P. Medvick, P.I.).

[1] Medvick, P. A., R. M. Hollen, R. S. Roberts, D. Trimmer, and T. J. Beugelsdijk. (1992) Automated DNA Hybridization Array Construction and Database Design for Robotic Control and for Source Determination of Hybridization Responses. International Journal of Genome Research 1, 1, 17-23.
[2] Medvick, P. A., R. M. Hollen, and R. S. Roberts. (1991) Development of an Automated Workcell for DNA Hybridization Array Construction, Journal of Laboratory Robotics and Automation, 3, 4/5, 169-173.
[3] Whole issue of Laboratory Robotics and Automation, 6, 2, 55-104.


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