Estimating change rates of genetic markers using serial samples:: applications to the transposon IS6110 in Mycobacterium tuberculosis
Estimating change rates of genetic markers using serial samples:: applications to the transposon IS6110 in Mycobacterium tuberculosis
复制标题
DOI：
10.1016/s0040-5809(03)00010-8
复制
发表时间：
2003-06-01
影响因子：
1.4
通讯作者：
Tanaka, MM
中科院分区：
文献类型：
--
作者：
Rosenberg, NA;Tsolaki, AG;Tanaka, MM
在传染病流行病学中，了解病原体的遗传标记在宿主体内进化的速度是有用的。我们提出了一个可以估计这些基因型变化率的模块化框架。估计方案需要遗传变化的基本过程的模型、将该过程过滤为可观察量的检测方案以及描述观察时间的监测方案。我们研究了转座元件基因型变化的线性“出生-转变-死亡”模型，获得了用于各种检测和监测方案的最大似然估计。该方法适用于结核分枝杆菌转座子 IS6110 的系列基因型。估计的出生率 0.0161（每年每个转座子拷贝的事件数）和死亡率 0.0108 都显着大于估计的转移率 0.0018。这些估计的总和对应于具有 10 个该元素拷贝的典型菌株的 2.4 年“半衰期”，大大超过了之前估计的每年每个拷贝 0.0135 的总变化。我们考虑能够提高估计精度的实验设计问题。我们还讨论了其他标记的扩展以及对分子流行病学的影响。 (C) 2003 年爱思唯尔科学（美国）。版权所有。
In infectious disease epidemiology, it is useful to know how quickly genetic markers of pathogenic agents evolve while inside hosts. We propose a modular framework with which these genotype change rates can be estimated. The estimation scheme requires a model of the underlying process of genetic change, a detection scheme that filters this process into observable quantities, and a monitoring scheme that describes the timing of observations. We study a linear "birth-shift-death" model for change in transposable element genotypes, obtaining maximum-likelihood estimators for various detection and monitoring schemes. The method is applied to serial genotypes of the transposon IS6110 in Mycobacterium tuberculosis. The estimated birth rate of 0.0161 (events per copy of the transposon per year) and death rate of 0.0108 are both significantly larger than the estimated shift rate of 0.0018. The sum of these estimates, which corresponds to a "half-life" of 2.4 years for a typical strain that has 10 copies of the element, substantially exceeds a previous estimate of 0.0135 total changes per copy per year. We consider experimental design issues that enable the precision of estimates to be improved. We also discuss extensions to other markers and implications for molecular epidemiology. (C) 2003 Elsevier Science (USA). All rights reserved.