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Theoretical basis of one‐dimensional genome scanning: A direct method to identify the site of a mutation
Author(s) -
Gondo Yoichi,
Brilliant Murray H.
Publication year - 1995
Publication title -
electrophoresis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 158
eISSN - 1522-2683
pISSN - 0173-0835
DOI - 10.1002/elps.1150160131
Subject(s) - genome , genetics , locus (genetics) , human genome , positional cloning , computational biology , biology , gene , mutation , gene duplication
Genome scanning is a technique designed to uncover a net genetic difference between otherwise identical DNA samples. As such, it can be used to directly identify the site of a gene mutation, facilitating the cloning of DNA fragments from that site. Unlike other conventional positional cloning methods, one‐dimensional genome scanning does not require prior knowledge of the location of the gene or mutation nor does it require closely linked markers. Rather, this method can directly identify the site of a net genomic change, such as a deletion or duplication caused by a mutation. Thus, the genome scanning method can be used in place of classic positional cloning strategies because prior positioning or mapping of the objective gene is unnecessary. By using this approach, we have identified and cloned a DNA fragment duplicated in the p un mutation of the mouse pink‐eyed dilution locus (Brilliant et al., Science 1991, 252 , 566–569). However, no other similar attempt using one‐dimensional genome scanning has been reported so far, in spite of the simplicity of the procedure and its success in identifying and ultimately characterizing the pink‐eyed dilution gene of the mouse. The lack of other reports of its success are perhaps not because of the practical difficulties of this method, but may be due to the false presumption that the probability for directly identifying the mutation site using genome scanning is extremely low. The theoretical probability was calculated and is presented here. We calculate that there is about a 50% chance in identifying a 200 kbp net genomic change (due to a mutation) by scanning 10 000 random sites in the mammalian genome. The practical key elements for calculating the probability of success are also discussed.