Journal Article

Estimation of the RNU2 macrosatellite mutation rate by BRCA1 mutation tracing

Chloé Tessereau, Yann Lesecque, Nastasia Monnet, Monique Buisson, Laure Barjhoux, Mélanie Léoné, Bingjian Feng, David E. Goldgar, Olga M. Sinilnikova, Sylvain Mousset, Laurent Duret and Sylvie Mazoyer

in Nucleic Acids Research

Volume 42, issue 14, pages 9121-9130
Published in print August 2014 | ISSN: 0305-1048
Published online July 2014 | e-ISSN: 1362-4962 | DOI: https://dx.doi.org/10.1093/nar/gku639

More Like This

Show all results sharing these subjects:

  • Chemistry
  • Biochemistry
  • Bioinformatics and Computational Biology
  • Genetics and Genomics
  • Molecular and Cell Biology

GO

Show Summary Details

Preview

Large tandem repeat sequences have been poorly investigated as severe technical limitations and their frequent absence from the genome reference hinder their analysis. Extensive allelotyping of this class of variation has not been possible until now and their mutational dynamics are still poorly known. In order to estimate the mutation rate of a macrosatellite, we analysed in detail the RNU2 locus, which displays at least 50 different alleles containing 5-82 copies of a 6.1 kb repeat unit. Mining data from the 1000 Genomes Project allowed us to precisely estimate copy numbers of the RNU2 repeat unit using read depth of coverage. This further revealed significantly different mean values in various recent modern human populations, favoring a scenario of fast evolution of this locus. Its proximity to a disease gene with numerous founder mutations, BRCA1, within the same linkage disequilibrium block, offered the unique opportunity to trace RNU2 arrays over a large timescale. Analysis of the transmission of RNU2 arrays associated with one ‘private’ mutation in an extended kindred and four founder mutations in multiple kindreds gave an estimation by maximum likelihood of 5 × 10−3 mutations per generation, which is close to that of microsatellites.

Journal Article.  6928 words.  Illustrated.

Subjects: Chemistry ; Biochemistry ; Bioinformatics and Computational Biology ; Genetics and Genomics ; Molecular and Cell Biology

Users without a subscription are not able to see the full content. Please, subscribe or login to access all content. subscribe or login to access all content.