Integration and Fixation Preferences of Human and Mouse Endogenous Retroviruses Uncovered with Functional Data Analysis.
Integration and Fixation Preferences of Human and Mouse Endogenous Retroviruses Uncovered with Functional Data Analysis.
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DOI：
10.1371/journal.pcbi.1004956
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发表时间：
2016-06
影响因子：
4.3
通讯作者：
Makova KD
中科院分区：
文献类型：
--
作者：
Campos-Sánchez R;Cremona MA;Pini A;Chiaromonte F;Makova KD
内源性逆转录病毒（erv）是种系中逆转录病毒感染的残余，分别占人类和小鼠基因组的8%和10%，并影响其结构、进化和功能。然而，我们对基因组景观如何影响erv的整合和固定的理解仍然有限。在这里，我们对人类和小鼠基因组中最近活跃的erv进行了全基因组研究。我们在人体内研究了826个固定型和1065个体外HERV-Ks，在小鼠体内研究了1624个固定型和242个多态性etn，以及3964个固定型和1986个多态性iap。我们在这些erv的±32 kb的整合位点和对照区定量分析了人类和小鼠的基因组特征（例如，非b DNA结构、重组率和组蛋白修饰），并使用功能数据分析（FDA）方法对其进行了分析。在FDA在基因组学中的第一个应用中，我们确定了这些特征显示其影响的基因组规模和位置，以及它们如何协同工作，为erv的整合和固定提供必要的信号。对不同进化年龄的erv的研究（年轻的体外erv和多态erv，较老的固定erv）使我们能够解开整合与固定偏好的纠缠。作为这些分析的结果，我们建立了一个全面的模型来解释erv在基因组中的不均匀分布。我们发现erv整合在具有丰富微卫星、镜像重复和抑制性组蛋白标记的晚期复制的富含at的区域。有利于固定的区域缺乏基因和进化上保守的元件，重组率低，反映了纯化选择和异位重组将erv从基因组中去除的影响。除了提供这些生物学见解外，我们的研究还展示了利用FDA的多尺度和本地化的力量。这些强大的技术有望应用于许多其他基因组研究。大约一半的人类基因组是由重复元素组成的。然而，我们还不能完全理解为什么某些元素会插入特定的基因组位置，以及是什么决定了哪些元素被保留，哪些元素被从基因组中删除。为了解决这些问题，我们研究了内源性逆转录病毒，一种占据人类和小鼠基因组约10%的重复元件，以及表征这些元件附近各种生物过程（例如重组和转录）的基因组特征。利用统计技术，我们在不同进化年龄的内源性逆转录病毒附近发现了基因组特征的富集。与年轻内源性逆转录病毒相邻的特征被认为促进了它们在基因组中的插入。与较老的内源性逆转录病毒相邻的特征被认为促进了它们的插入和在基因组中维持的机会。我们的分析使我们能够解释内源性逆转录病毒在基因组中的不均匀分布，从而更好地理解不同生物过程在塑造基因组结构进化中的相互作用。
Endogenous retroviruses (ERVs), the remnants of retroviral infections in the germ line, occupy ~8% and ~10% of the human and mouse genomes, respectively, and affect their structure, evolution, and function. Yet we still have a limited understanding of how the genomic landscape influences integration and fixation of ERVs. Here we conducted a genome-wide study of the most recently active ERVs in the human and mouse genome. We investigated 826 fixed and 1,065 in vitro HERV-Ks in human, and 1,624 fixed and 242 polymorphic ETns, as well as 3,964 fixed and 1,986 polymorphic IAPs, in mouse. We quantitated >40 human and mouse genomic features (e.g., non-B DNA structure, recombination rates, and histone modifications) in ±32 kb of these ERVs’ integration sites and in control regions, and analyzed them using Functional Data Analysis (FDA) methodology. In one of the first applications of FDA in genomics, we identified genomic scales and locations at which these features display their influence, and how they work in concert, to provide signals essential for integration and fixation of ERVs. The investigation of ERVs of different evolutionary ages (young in vitro and polymorphic ERVs, older fixed ERVs) allowed us to disentangle integration vs. fixation preferences. As a result of these analyses, we built a comprehensive model explaining the uneven distribution of ERVs along the genome. We found that ERVs integrate in late-replicating AT-rich regions with abundant microsatellites, mirror repeats, and repressive histone marks. Regions favoring fixation are depleted of genes and evolutionarily conserved elements, and have low recombination rates, reflecting the effects of purifying selection and ectopic recombination removing ERVs from the genome. In addition to providing these biological insights, our study demonstrates the power of exploiting multiple scales and localization with FDA. These powerful techniques are expected to be applicable to many other genomic investigations. Approximately half of the human genome is composed of repetitive elements. Yet we do not completely understand why certain elements insert in particular genomic locations, and what determines which elements are retained and which are eliminated from the genome. To address these questions we studied endogenous retroviruses, one type of repetitive elements which occupy ~10% of the human and mouse genomes, together with genomic features characterizing various biological processes (e.g., recombination and transcription) in the neighborhoods of these elements. Using statistical techniques, we identified enrichment of genomic features in the vicinity of endogenous retroviruses of different evolutionary ages. Features overrepresented adjacent to young endogenous retroviruses are expected to have facilitated their insertion in the genome. Features overrepresented adjacent to older endogenous retroviruses are expected to have facilitated both their insertion and their chances of being sustained in the genome. Our analyses allowed us to explain the uneven distribution of endogenous retroviruses along the genome, and thus to better understand the interaction of different biological processes in shaping the evolution of genome architecture.