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Publikationstyp: Zeitschriftenaufsatz
Dokumentart: Originalarbeit

Publikationsjahr: 1999

AutorInnen: Bachtrog, D; Weiss, S; Zangerl, B; Brem, G; Schlötterer, C

Titel: Distribution of dinucleotide microsatellites in the Drosophila melanogaster genome.

Quelle: Mol Biol Evol (16), 5 602-610.

Autor/innen der Vetmeduni Vienna:

Brem Gottfried
Schlötterer Christian

Beteiligte Vetmed-Organisationseinheiten
Institut für Tierzucht und Genetik

Microsatellites, a special class of repetitive DNA, have become one of the most popular genetic markers. The progress of various genome projects has made it possible to study the genomic distribution of microsatellites and to evaluate the potential influence of several parameters on their genesis. We report the distribution of dinucleotide microsatellites in the genome of Drosophila melanogaster. When considering only microsatellites with five or mure repeat units, the average length of dinucleotide repeats in D. melanogaster is 6.7 repeats. We tested a wide range of parameters which could potentially influence microsatellite density, and we did not detect a significant influence of recombination rate, number of exons, or total length of coding sequence. In concordance with the neutral expectation for the origin of microsatellites. a significant positive correlation between AT content and (AT/TA)(n) microsatellite density was detected. While this pattern may indicate that microsatellite genesis is a random process, we also found evidence for a nonrandom distribution of microsatellites. Average microsatellite density was higher on the X chromosome, but extreme heterogeneity was observed between different genomic regions. Such a clumping of microsatellites was also evident on a more local scale, as 38.9% of the contiguous sequences analyzed showed a deviation from a random distribution of microsatellites.

Keywords Pubmed: Animals - : Dinucleotide Repeats - genetics : Drosophila melanogaster - genetics : Genetic Variation - genetics : Genome - genetics : Models, Genetic - genetics : Regression Analysis - genetics

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