Rfam: Towards a sustainable resource for understanding the genomic functional ncRNA repertoire

在分子生物学中，核心教条是说，在基因组中编码的基因编码RNA，然后RNA被翻译成执行细胞主要过程的蛋白质。但是，RNA不仅仅是基因和蛋白质之间的中间步骤。相反，RNA能够执行许多对生命至关重要的任务--例如，核糖体(负责从RNA合成蛋白质的机器)是一个基于RNA的机器，而RNA在调节其他基因的水平方面发挥着重要作用。这些涉及生物学的RNA被称为非编码RNA(NcRNA)。RNA研究一直落后于蛋白质，部分原因是在实验和计算方面对它们的研究存在困难。与蛋白质科学相比，RNA生物学领域提供的有助于研究的资源相对较少。RFAM是关于ncRNA信息的最大和最权威的来源之一，并提供了一个涵盖各种ncRNA类型的中央信息门户。我们使用统计模型将相关的非编码RNA分组为家族。然后，我们提供有关它们功能的信息，以及提供其他科学家可以用来在他们感兴趣的样本中发现相关非编码RNA的工具。我们数据库的一个主要用途是识别DNA序列中的ncRNAs。这使科学家能够绘制ncRNAs的位置图，并研究ncRNAs是如何在相关生物体之间进化的，从而为其功能提供线索。我们的目标是通过提供来自已完成全基因组测序的生物体的ncRNA家族来进一步促进这一点。这些生物通常是科学家感兴趣的生物，因为它们在疾病中的作用(例如，病原菌)，它们的经济重要性(例如，面包小麦，人类营养的主要来源)，或者因为它们占据了一个重要的生物学生态位(例如，人类)。我们还将为研究人员提供工具和培训，以建立他们自己的RNA家族，使他们能够研究他们特别感兴趣的RNA。重要的不仅是能够识别ncRNA，我们还必须告诉我们的用户ncRNA的功能是什么。为此，我们正在改进我们的RNA家族的功能注释，方法是使用人类和计算机都可以轻松解析的结构化语言术语。这意味着我们的大型数据集可以被快速挖掘，使研究人员能够建立起ncRNA如何与细胞其他组件相互作用的图景，并更多地了解ncRNA在生物系统中所扮演的角色。我们所有的信息都可以通过Rfam网站免费获得，也可以作为一个可下载的数据库。我们还将我们的数据输出到其他资源，例如与特定生物体有关的数据库，以及更通用的RNA数据库，如RNACentral。

In molecular biology, the central dogma says that genes encoded in a genome code for RNA, which is then translated into the proteins carrying out the main processes of the cell. But, RNA is not just an intermediate step between genes and protein. Instead, RNA is capable of performing a number of tasks that are essential for life - for example, the ribosome (the machine responsible for synthesizing proteins from RNA) is an RNA-based machine, and RNA plays important roles in regulating the levels of other genes. These RNAs involved in biology are known as non-coding RNAs (ncRNA).RNA research has lagged behind that of proteins, in part due to the difficulties in working with them experimentally and computationally. The field of RNA biology is comparatively poorly served with resources that can aid research when compared with protein science. Rfam is one of the largest and most authoritative sources on ncRNA information, and provides a central portal of information covering a wide variety of ncRNA types. We use statistical models to group related non-coding RNAs into families. We then provide information on their function, as well as providing tools which other scientists can use to discover related non-coding RNAs in their samples of interest. A primary use of our database is to identify ncRNAs in DNA sequences. This allows scientists to map the positions of ncRNAs and study how ncRNAs have evolved between related organisms giving clues to their function. We aim to facilitate this further by providing families of ncRNAs from organisms which have had their entire genome sequenced. These organisms are generally those which are of interest to scientists because of their role in disease (e.g. pathogenic bacteria), their economic importance (e.g bread wheat, a major source of human nutrition), or because they occupy an important biological niche (e.g, humans). We'll also provide researchers with tools and training to build their own RNA families, allowing them to study RNAs which are of particular interest to them. Not only is it important to be able to identify a ncRNA, it's also important for us to tell our users what the function of an ncRNA is. To this end, we are improving our functional annotation of our RNA families, by using structured language terms that are easily parseable by both humans and computers. This means that our large data sets can be mined quickly, allowing researchers to build up a picture of how ncRNAs interact with the rest of the cell's components and understand more about the roles ncRNA play in biological systems.All our information is freely available via the Rfam website and as a downloadable database. We also export our data to other resources, such as databases concerned with a specific organism, and more general RNA databases such as RNAcentral.