Denoeud France, Vergnaud Gilles, Benson Gary
Laboratoire GPMS, Institut de Génétique et Microbiologie, Université Paris-Sud, 91405 Orsay cedex, France.
Genome Res. 2003 May;13(5):856-67. doi: 10.1101/gr.574403. Epub 2003 Apr 14.
We seek to define sequence-based predictive criteria to identify polymorphic and hypermutable minisatellites in the human genome. Polymorphism of a representative pool of minisatellites, selected from human chromosomes 21 and 22, was experimentally measured by PCR typing in a population of unrelated individuals. Two predictive approaches were tested. One uses simple repeat characteristics (e.g., unit length, copy number, nucleotide bias) and a more complex measure, termed HistoryR, based on the presence of variant motifs in the tandem array. We find that HistoryR and percentage of GC are strongly correlated with polymorphism and, as predictive criteria, reduce by half the number of repeats to type while enriching the proportion with heterozygosity >/=0.5, from a background level of 43% to 59%. The second approach uses length differences between minisatellites in the two releases of the human genome sequence (from the public consortium and Celera). As a predictor, this similarly enriches the number of polymorphic minisatellites, but fails to identify an unexpectedly large number of these. Finally, typing of the highly polymorphic minisatellites in large families identified one new hypermutable minisatellite, located in a predicted coding sequence. This may represent the first coding human hypermutable minisatellite.
我们试图定义基于序列的预测标准,以识别人类基因组中的多态性和高变微卫星。从人类21号和22号染色体中选取一组具有代表性的微卫星,通过PCR分型在无关个体群体中对其多态性进行实验测量。测试了两种预测方法。一种方法使用简单重复特征(如单元长度、拷贝数、核苷酸偏差)以及一种基于串联阵列中变异基序存在情况的更复杂测量方法,称为HistoryR。我们发现HistoryR和GC百分比与多态性密切相关,作为预测标准,在对重复序列进行分型时,可将分型数量减少一半,同时将杂合度≥0.5的比例从背景水平的43%提高到59%。第二种方法利用人类基因组序列两个版本(公共联盟和赛雷拉公司)中微卫星之间的长度差异。作为一种预测指标,这同样能富集多态性微卫星的数量,但未能识别出数量意外之多的此类微卫星。最后,对大家族中高度多态性微卫星进行分型时,发现了一个新的高变微卫星,位于一个预测的编码序列中。这可能代表首个编码人类高变微卫星。