Back to Search Start Over

Delineating Rearrangements in Single Yeast Artificial Chromosomes by Quantitative DNA Fiber Mapping.

Authors :
Weier HU
Greulich-Bode KM
Wu J
Duell T
Source :
The open genomics journal [Open Genomics J] 2009 Oct 09; Vol. 2, pp. 15-23.
Publication Year :
2009

Abstract

Cloning of large chunks of human genomic DNA in recombinant systems such as yeast or bacterial artificial chromosomes has greatly facilitated the construction of physical maps, the positional cloning of disease genes or the preparation of patient-specific DNA probes for diagnostic purposes. For this process to work efficiently, the DNA cloning process and subsequent clone propagation need to maintain stable inserts that are neither deleted nor otherwise rearranged. Some regions of the human genome; however, appear to have a higher propensity than others to rearrange in any host system. Thus, techniques to detect and accurately characterize such rearrangements need to be developed. We developed a technique termed 'Quantitative DNA Fiber Mapping (QDFM)' that allows accurate tagging of sequence elements of interest with near kilobase accuracy and optimized it for delineation of rearrangements in recombinant DNA clones. This paper demonstrates the power of this microscopic approach by investigating YAC rearrangements. In our examples, high-resolution physical maps for regions within the immunoglobulin lambda variant gene cluster were constructed for three different YAC clones carrying deletions of 95 kb and more. Rearrangements within YACs could be demonstrated unambiguously by pairwise mapping of cosmids along YAC DNA molecules. When coverage by YAC clones was not available, distances between cosmid clones were estimated by hybridization of cosmids onto DNA fibers prepared from human genomic DNA. In addition, the QDFM technology provides essential information about clone stability facilitating closure of the maps of the human genome as well as those of model organisms.

Details

Language :
English
ISSN :
1875-693X
Volume :
2
Database :
MEDLINE
Journal :
The open genomics journal
Publication Type :
Academic Journal
Accession number :
20502619
Full Text :
https://doi.org/10.2174/1875693X00902010015