In silico detection of control signals:: mRNA 3′-end-processing sequences in diverse species
In silico detection of control signals:: mRNA 3′-end-processing sequences in diverse species
复制标题
DOI：
10.1073/pnas.96.24.14055
复制
发表时间：
1999-11-23
影响因子：
11.1
通讯作者：
Smith, TF
中科院分区：
文献类型：
--
作者：
Graber, JH;Cantor, CR;Smith, TF
我们通过分析超过20，000个3 '端表达的序列标签，研究了6种真核生物（酵母、水稻、拟南芥、果蝇、小鼠和人类）的mRNA 3'端加工信号。典型的AAUAAA元件的使用和保存在六个物种中差异很大，在植物和酵母中尤其薄弱。即使在动物物种中，AAUAAA信号似乎也不像以前的研究所表明的那样普遍。AAUAAA的单碱基变体的丰度与其测量的加工效率相关。如前所述，植物多聚腺苷酸化信号与酵母的信号比与动物的信号更相似，具有共同的信号元件的内容和排列。在所有物种的检查，完整的多聚腺苷酸化信号似乎是由多个元素的聚集。根据这些和以前的结果，我们提出了一个扩大的概念，3 '端处理信号，其中没有一个确切的序列元素是普遍需要的处理。更确切地说，总效率是所有元素的函数，重要的是，一个元素中的低效词可以通过其他元素中的强词来补偿。这些复杂的模式表明，有效的工具，以确定3 '-末端加工信号将需要更多的共识序列鉴定。
We have investigated mRNA 3'-end-processing signals in each of six eukaryotic species (yeast, rice, arabidopsis, fruitfly, mouse, and human) through the analysis of more than 20,000 3'-expressed sequence tags. The use and conservation of the canonical AAUAAA element vary widely among the six species and are especially weak in plants and yeast. Even in the animal species, the AAUAAA signal does not appear to be as universal as indicated by previous studies. The abundance of single-base variants of AAUAAA correlates with their measured processing efficiencies. As found previously, the plant polyadenylation signals are more similar to those of yeast than to those of animals, with both common content and arrangement of the signal elements. In all species examined, the complete polyadenylation signal appears to consist of an aggregate of multiple elements. In light of these and previous results, we present a broadened concept of 3'-end-processing signals in which no single exact sequence element is universally required for processing. Rather, the total efficiency is a function of all elements and, importantly, an inefficient word in one element can be compensated for by strong words in other elements. These complex patterns indicate that effective tools to identify 3'-end-processing signals will require more than consensus sequence identification.