Rfam: The community resource for RNA families

DNA对从父母传给后代的遗传信息进行编码。当需要时，DNA首先被转录成RNA，然后RNA被翻译成在细胞内进行有用工作的蛋白质。但许多RNA不仅仅是基因和蛋白质之间的信使。这些非编码的RNA(ncRNAs；因为它们不是蛋白质的“编码”)可以在所有生物中找到，其中许多是生存所必需的。核糖体是合成人体所有蛋白质的分子机器，核糖体是核糖体的核心。重要的是，当科学家遇到RNA序列时，他们需要一个可靠的工具来识别这种RNA及其功能。此外，每当对新的基因组进行测序时，都有必要找到组成RNA的部分。因此创建了Rfam数据库，这是一种在线资源，将相关的ncRNA组合成家庭，每个家庭由一个统计模型表示，该统计模型允许检测同一家庭的其他成员。自2002年成立以来，Rfam已经从大约100个家庭扩大到今天的近3000个家庭，反映了ncRNA领域的增长。Rfam已被用于世界各地跨越许多生物学学科的数千项研究，例如，当首次对水稻和甜菜等重要作物的基因组进行测序时，Rfam被用于在这些重要作物中寻找ncRNA。然而，让Rfam保持最新是很重要的，因为新的RNA正在不断被发现，并且关于已知的ncRNA的额外信息被收集。我们将与RNA社区合作，以实现以下目标：(1)我们将专注于更新一些最重要的RNA家族，这些家族至少有一个三维结构。3D结构可以向我们展示一个长RNA序列的哪些部分在3D空间中彼此接近。有了这些知识，我们可以预测序列可能如何变化，但形成相同的3D形状。虽然Rfam有一些这样的信息，但它并不像从3D结构中所知的那样准确。通过将3D数据集成到Rfam中，科学家将能够编写新的计算机程序，可以根据序列预测RNA3D结构。(2)我们将创建一个ncRNA类型的完整集合，称为microRNAs，它是控制体内不同蛋白质数量的短RNA序列。由于microRNA的问题与癌症有关，因此能够在基因组中发现这些问题并确定哪些是相关的是很重要的。我们将与曼彻斯特大学的miRBase开发人员合作，使两个数据库中包含的microRNA家族同步。虽然miRBase是完整的，但它没有工具来维护族，而Rfam的情况正好相反。通过合作，我们将创建一个单一的、完整的microRNA家族集合，以便使用Rfam在新的基因组中发现microRNAs。(3)我们将根据病毒中的RNA创建更多的家族。许多病毒使用RNA结构来感染、繁殖或避免宿主免疫反应。Rfam有少量的病毒式家庭，大多数可以追溯到十年前。我们将通过与欧洲病毒生物信息学中心的病毒学家合作来更新它们，他们已经汇编了一套保守的病毒RNA结构。然后，科学家将能够使用Rfam来检测序列中的病毒并研究其RNA结构。我们还将定期更新Rfam网站，回答用户的问题，并出席会议，与同事会面，分享资源开发。总的来说，这项工作将进一步增强这一强大资源的功能性和实用性，并巩固Rfam在全球RNA研究领域的中心地位。

DNA encodes the genetic information that is transferred from parents to their offspring. When required, DNA is first transcribed into RNA, which is then translated into proteins that do useful work inside the cells. But many RNAs do much more than merely act as messengers between genes and proteins. These non-coding RNAs (ncRNAs; because they do not "code" for proteins) can be found in all living things, many of which are essential for survival. There are many types of ncRNAs, for example ncRNA is at the heart of a ribosome, the molecular machine that synthesises all proteins in our bodies.Importantly, when scientists encounter an RNA sequence, they need a reliable tool to identify this RNA and its function. Moreover, it is necessary to find the constituent RNA parts whenever a new genome is sequenced. The Rfam database was thus created, which is an online resource that groups together related ncRNAs into families, each represented by a statistical model that allows the detection of other members of the same family. Since its inception in 2002, Rfam has expanded from ~100 families to nearly 3,000 families today, reflecting the growth of the ncRNA field. Rfam has been used world over in thousands of studies spanning many biology disciplines, e.g. Rfam was used to find ncRNAs in important crops like rice and sugar beet when their genomes were first sequenced. However, it is important to keep Rfam up-to-date because new RNAs are being constantly discovered and additional information is gleaned about already known ncRNAs. We will collaborate with the RNA community to accomplish the following objectives:(1) We will focus on updating some of the most important RNA families for which at least one 3D structure has been found. The 3D structure can show us which parts of a long RNA sequence are close to each other in 3D space. With this knowledge, we can predict how the sequence may change, yet forming the same 3D shape. While Rfam has some of this information, it is not as accurate as what is known from 3D structures. By integrating 3D data into Rfam, scientists will be able to write new computer programs that can predict RNA 3D structure from sequence. (2) We will create a complete collection of ncRNA type called microRNAs, which are short RNA sequences that control the amounts of different proteins in the body. Since problems with microRNAs are linked to cancer, it is important to be able to discover these in genomes and identify which ones are related. We will collaborate with the miRBase developers at the University of Manchester to synchonise microRNA families contained within the two databases. Although miRBase is complete, it does not have the tools to maintain the families while the opposite holds true for Rfam. By working together, we will create a single, complete collection of microRNA families so as to facilitate the discovery of microRNAs in new genomes using Rfam.(3) We will create more families based on RNAs found in viruses. Many viruses use RNA structures to infect, reproduce, or avoid the host immune response. Rfam has a small number of viral families, mostly dating from a decade ago. We will update them by working with the virologists from the European Viral Bioinformatics Center who have compiled a set of conserved viral RNA structures. Scientists will then be able to use Rfam to detect viruses in sequences and study their RNA structures.We will also regularly update the Rfam website, respond to user queries, and attend conferences to meet colleagues and share resource developments. Collectively, this work will further enhance the functionality and utility of a powerful resource and cement Rfam's central status in the field of RNA research worldwide.