Efficient inference of recombination hot regions in bacterial genomes.
Efficient inference of recombination hot regions in bacterial genomes.
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DOI：
10.1093/molbev/msu082
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发表时间：
2014-06
影响因子：
10.7
通讯作者：
Falush D
中科院分区：
文献类型：
--
作者：
Yahara K;Didelot X;Ansari MA;Sheppard SK;Falush D
在真核生物中，对重组率的详细调查已经显示了多个基因组尺度上的变异和高度升高的重组的“热点”的存在。在细菌中，重组率变化的研究较少，部分原因是很少有分析方法考虑到细菌进化发生的克隆背景。在这里，我们特别关注识别基因组的“热点区域”，其中DNA在分离株之间频繁转移。我们提出了一个计算效率高的算法的基础上，最近开发的“染色体绘画”算法，其特征在于模式的单倍型共享整个基因组。我们比较了平均基因组范围的绘画，这主要反映了克隆下降，与绘画的每个网站，另外反映了特定的偏差，在网站由于重组。使用模拟数据，我们表明，热点地区有一贯更高的偏离基因组范围内的平均比正常地区。我们将我们的方法应用于先前分析的大肠杆菌基因组，并发现新方法与影响ClonalOrigin推断的每个位点的重组事件数量高度相关，ClonalOrigin是一种仅适用于少量基因组的方法。此外，我们分析了重组热区空肠弯曲菌使用200个基因组。我们确定了三个重组热点区域，这是丰富的膜蛋白相关基因。我们的方法及其实现，可从https：//github.com/bioprojects/orderedPainting下载，将有助于开发原核生物重组的群体基因组研究的新阶段。
In eukaryotes, detailed surveys of recombination rates have shown variation at multiple genomic scales and the presence of “hotspots” of highly elevated recombination. In bacteria, studies of recombination rate variation are less developed, in part because there are few analysis methods that take into account the clonal context within which bacterial evolution occurs. Here, we focus in particular on identifying “hot regions” of the genome where DNA is transferred frequently between isolates. We present a computationally efficient algorithm based on the recently developed “chromosome painting” algorithm, which characterizes patterns of haplotype sharing across a genome. We compare the average genome wide painting, which principally reflects clonal descent, with the painting for each site which additionally reflects the specific deviations at the site due to recombination. Using simulated data, we show that hot regions have consistently higher deviations from the genome wide average than normal regions. We applied our approach to previously analyzed Escherichia coli genomes and revealed that the new method is highly correlated with the number of recombination events affecting each site inferred by ClonalOrigin, a method that is only applicable to small numbers of genomes. Furthermore, we analyzed recombination hot regions in Campylobacter jejuni by using 200 genomes. We identified three recombination hot regions, which are enriched for genes related to membrane proteins. Our approach and its implementation, which is downloadable from https://github.com/bioprojects/orderedPainting, will help to develop a new phase of population genomic studies of recombination in prokaryotes.
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