The Role of Reverse Transcriptase in Intron Gain and Loss Mechanisms
The Role of Reverse Transcriptase in Intron Gain and Loss Mechanisms
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DOI：
10.1093/molbev/msr192
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发表时间：
2012-01-01
影响因子：
10.7
通讯作者：
Carmel, Liran
中科院分区：
文献类型：
--
作者：
Cohen, Noa E.;Shen, Roy;Carmel, Liran
内含子密度在真核生物物种中是高度可变的。似乎不同的谱系经历了相当不同水平的内含子获得和丢失事件，但其原因尚不清楚。已经提出了大量的内含子丢失和获得的机制，其中大多数至少有一定程度的间接支持。因此，我们发现内含子密度的变化可能反映了不同的机制在不同的谱系中是活跃的。相当多的这些推定的机制，无论是内含子丢失和内含子的增益，假定酶逆转录酶（RT）在这个过程中有一个关键的作用。在本文中，我们列出了三个预测，其批准或证伪表明RT参与内含子的获得和损失过程。测试这些预测需要真核生物系统发育树上沿着不同分支的单个基因的内含子增加和丢失率的数据。到目前为止，这种比率还无法计算，因此，这些预测无法得到严格的评估。在这里，我们使用的最大似然算法，我们在过去设计的，进化重建的期望最大化，它允许估计这样的利率。利用该算法计算了19种真核生物系统发育树各分支中300多个基因的内含子丢失率和增加率。在此基础上，我们发现只有很少的支持RT活动的内含子增益。相反，我们认为RT介导的内含子丢失是一种非常有效的去除内含子的机制，因此，其活性水平可能是内含子数量的主要决定因素。此外，我们发现，内含子的增益和损失率是负相关的内含子穷人的物种，但正相关的内含子丰富的物种。对此的一种解释是，富含内含子的物种（如后生动物）中的内含子获得和丢失机制共享一个共同的机制组件，尽管不是RT。
Intron density is highly variable across eukaryotic species. It seems that different lineages have experienced considerably different levels of intron gain and loss events, but the reasons for this are not well known. A large number of mechanisms for intron loss and gain have been suggested, and most of them have at least some level of indirect support. We therefore figured out that the variability in intron density can be a reflection of the fact that different mechanisms are active in different lineages. Quite a number of these putative mechanisms, both for intron loss and for intron gain, postulate that the enzyme reverse transcriptase (RT) has a key role in the process. In this paper, we lay out three predictions whose approval or falsification gives indication for the involvement of RT in intron gain and loss processes. Testing these predictions requires data on the intron gain and loss rates of individual genes along different branches of the eukaryotic phylogenetic tree. So far, such rates could not be computed, and hence, these predictions could not be rigorously evaluated. Here, we use a maximum likelihood algorithm that we have devised in the past, Evolutionary Reconstruction by Expectation Maximization, which allows the estimation of such rates. Using this algorithm, we computed the intron loss and gain rates of more than 300 genes in each branch of the phylogenetic tree of 19 eukaryotic species. Based on that we found only little support for RT activity in intron gain. In contrast, we suggest that RT-mediated intron loss is a mechanism that is very efficient in removing introns, and thus, its levels of activity may be a major determinant of intron number. Moreover, we found that intron gain and loss rates are negatively correlated in intron-poor species but are positively correlated for intron-rich species. One explanation to this is that intron gain and loss mechanisms in intron-rich species (like metazoans) share a common mechanistic component, albeit not a RT.