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Prospective Estimation of Recombination Signal Efficiency and Identification of Functional Cryptic Signals in the Genome by Statistical Modeling

机译:通过统计建模对重组信号效率进行前瞻性估计和基因组中功能性密码信号的鉴定

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摘要

The recombination signals (RS) that guide V(D)J recombination are phylogenetically conserved but retain a surprising degree of sequence variability, especially in the nonamer and spacer. To characterize RS variability, we computed the position-wise information, a measure correlated with sequence conservation, for each nucleotide position in an RS alignment and demonstrate that most position-wise information is present in the RS heptamers and nonamers. We have previously demonstrated significant correlations between RS positions and here show that statistical models of the correlation structure that underlies RS variability efficiently identify physiologic and cryptic RS and accurately predict the recombination efficiencies of natural and synthetic RS. In scans of mouse and human genomes, these models identify a highly conserved family of repetitive DNA as an unexpected source of frequent, cryptic RS that rearrange both in extrachromosomal substrates and in their genomic context.
机译:引导V(D)J重组的重组信号(RS)在系统发育上是保守的,但保留了令人惊讶的序列变异性,尤其是在九聚体和间隔区中。为了表征RS变异性,我们计算了RS比对中每个核苷酸位置的位置信息,这是一种与序列保守性相关的度量,并证明RS七聚体和九聚体中存在大多数位置信息。我们以前已经证明了RS位置之间的显着相关性,并且在这里表明,作为RS变异性基础的相关结构的统计模型可以有效地识别生理和隐性RS,并准确预测天然和合成RS的重组效率。在对小鼠和人类基因组进行扫描时,这些模型将高度保守的重复DNA家族鉴定为频繁的,隐秘的RS的意外来源,该RS在染色体外底物及其基因组环境中均发生了重排。

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