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BENZER: An Interval Graph Tool for Deletion Mapping, Restriction Mapping, Complementation Mapping, Sequencing, and Food Web Analysis

John R. Jungck (Beloit College),
Vince Streif (University of Wisconsin-Madison),
Ivica Ceraj (University of Zagreb), and
Stephen J. Everse (University of California - San Diego)
Screen Shots | System Requirements

In 1962, Seymour Benzer presented a method for the rapid mapping of point mutations, without resorting to numerous three point crosses (the classical method), by employing overlapping deletions. The construction of topological maps of deletion mutants has become a common exercise in genetics problem books and genetics laboratory manuals. The “Benzer problem” as it has been discussed in some general texts on graph theory is a mathematical generalization of this approach that has broad applicability to contemporary problems such as the “middle level” problem of genome projects which orders restriction fragments that have individually been sequenced. Graph theory has broad educational utility because of the diversity of applications which can be learned without concomitantly learning a tremendous amount of sophisticated computational procedures.

BENZER has been used for restriction mapping, sequencing proteins and nucleic acids, deletion mapping, complementation mapping, seriating archeological artifacts and fossils in sedimentary layers, and food web analysis.

In 1965, Shkurba developed a matrix manipulation that allowed an analysis of Gershenzon’s hypothesis “that supplementary nutrition of Drosophila larvae with preparations of DNA caused mutations which affect whole sections of the chromosome.” Shkurba employed partially linearly ordered set theory to describe this matrix manipulation approach to the Benzer problem which is implemented in this software. Most students find Shkurba’s approach easier to use than the graph theoretical approach.

BENZER can be used to generate problem sets, to interactively solve problems from actual biological experiments by heuristic matrix manipulation, and to automatically solve problems with a built-in algorithm that recognizes incompatibilities in datasets. Illustrated below is a solution to a “food web” problem as described in Joel E. Cohen’s (1978) Food Webs and Niche Space, Princeton University Press, Princeton, New Jersey.

This program offers opportunities for students to develop analytical skills beyond those typically found in textbook problems. The conditions stated explicitly in an algorithm can be used to discuss what happens when they are violated. Thus, circular genetic maps, overlapping genes , when one gene’s intron is another gene’s exon, and “boxity” in food webs all violate the assumptions of the algorithm presented here. Students can see that such violations are illustrative of new genetic or ecological phenomena and are not simply the fault of poor experimental or field collection techniques.

 

Screen Shots

 

System Requirements

Windows 3.1, Windows 95, or Windows NT

  • Windows 3.1 or later and DOS 5.0 or later , or Windows 95, or Windows NT 3.5 or later.


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