Use of SNPs to determine the breakpoints of complex deficiencies, facilitating gene mapping in Caenorhabditis elegans

Author:

Kadandale Pavan,Geldziler Brian,Hoffmann Melissa,Singson Andrew

Abstract

Abstract Background Genetic deletions or deficiencies have been used for gene mapping and discovery in various organisms, ranging from the nematode Caenorhabditis elegans all the way to humans. One problem with large deletions is the determination of the location of their breakpoints. This is exacerbated in the case of complex deficiencies that delete a region of the genome, while retaining some of the intervening sequence. Previous methods, using genetic complementation or cytology were hampered by low marker density and were consequently not very precise at positioning the breakpoints of complex deficiencies. The identification of increasing numbers of Single Nucleotide Polymorphisms (SNPs) has resulted in the use of these as genetic markers, and consequently in their utilization for defining the breakpoints of deletions using molecular biology methods. Results Here, we show that SNPs can be used to help position the breakpoints of a complex deficiency in C. elegans. The technique uses a combination of genetic crosses and molecular biology to generate robust and highly reproducible results with strong internal controls when trying to determine the breakpoints of deficiencies. The combined use of this technique and standard genetic mapping allowed us to rapidly narrow down the region of interest in our attempts to clone a gene. Conclusion Unlike previous methods used to locate deficiency breakpoints, our technique has the advantage of not being limited by the amount of starting material. It also incorporates internal controls to eliminate false positives and negatives. The technique can also easily be adapted for use in other organisms in which both genetic deficiencies and SNPs are available, thereby aiding gene discovery in these other models.

Publisher

Springer Science and Business Media LLC

Subject

Genetics(clinical),Genetics

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