Rfam: The community resource for RNA families

Rfam：RNA 家族的社区资源

• 批准号: BB/S020462/1
• 负责人: Alex Bateman
• 金额: $ 64.88万
• 依托单位: European Bioinformatics Institute
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FS020462%2F1
• 关键词: Rfam; community; resource; RNA; families

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.

DNA 编码从父母传递给后代的遗传信息。当需要时，DNA 首先被转录成 RNA，然后翻译成在细胞内发挥有用作用的蛋白质。但许多 RNA 的作用不仅仅是充当基因和蛋白质之间的信使。这些非编码 RNA（ncRNA；因为它们不“编码”蛋白质）存在于所有生物中，其中许多对于生存至关重要。 ncRNA 有多种类型，例如 ncRNA 是核糖体的核心，核糖体是合成我们体内所有蛋白质的分子机器。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该 RNA 及其功能。此外，每当对新的基因组进行测序时，都必须找到组成RNA的部分。 Rfam 数据库由此创建，这是一个在线资源，将相关的 ncRNA 分组到各个家族中，每个家族都由一个统计模型表示，允许检测同一家族的其他成员。自 2002 年成立以来，Rfam 已从约 100 个家族扩展到如今的近 3,000 个家族，反映了 ncRNA 领域的发展。 Rfam 已在世界各地的数千项研究中得到应用，涉及许多生物学学科，例如生物学。当水稻和甜菜等重要作物的基因组首次被测序时，Rfam 被用来寻找 ncRNA。然而，保持 Rfam 的最新状态非常重要，因为新的 RNA 不断被发现，并且有关已知 ncRNA 的更多信息也被收集。我们将与 RNA 界合作实现以下目标：（1）我们将重点更新一些至少已发现 3D 结构的最重要的 RNA 家族。 3D 结构可以向我们展示长 RNA 序列的哪些部分在 3D 空间中彼此靠近。有了这些知识，我们就可以预测序列如何改变，同时形成相同的 3D 形状。虽然 Rfam 拥有一些此类信息，但它不如从 3D 结构中获知的信息准确。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，根据序列预测 RNA 3D 结构。 (2) 我们将创建一个完整的 ncRNA 类型集合，称为 microRNA，它们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相关是很重要的。我们将与曼彻斯特大学的 miRBase 开发人员合作，同步两个数据库中包含的 microRNA 家族。尽管 miRBase 很完整，但它没有维护家族的工具，而 Rfam 则相反。通过共同努力，我们将创建一个单一、完整的 microRNA 家族集合，以促进使用 Rfam 在新基因组中发现 microRNA。(3) 我们将基于病毒中发现的 RNA 创建更多家族。许多病毒利用 RNA 结构来感染、繁殖或避免宿主免疫反应。 Rfam 有少数病毒家族，大部分可以追溯到十年前。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，他们编制了一套保守的病毒 RNA 结构。科学家随后将能够使用 Rfam 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，回复用户查询，并参加会议与同事见面并共享资源开发。总的来说，这项工作将进一步增强强大资源的功能和实用性，并巩固 Rfam 在全球 RNA 研究领域的中心地位。

项目成果

Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research.

• DOI: 10.1093/bib/bbaa232
• 发表时间: 2021-03-22
• 期刊: Briefings in bioinformatics
• 影响因子: 9.5
• 作者: Hufsky F;Lamkiewicz K;Almeida A;Aouacheria A;Arighi C;Bateman A;Baumbach J;Beerenwinkel N;Brandt C;Cacciabue M;Chuguransky S;Drechsel O;Finn RD;Fritz A;Fuchs S;Hattab G;Hauschild AC;Heider D;Hoffmann M;Hölzer M;Hoops S;Kaderali L;Kalvari I;von Kleist M;Kmiecinski R;Kühnert D;Lasso G;Libin P;List M;Löchel HF;Martin MJ;Martin R;Matschinske J;McHardy AC;Mendes P;Mistry J;Navratil V;Nawrocki EP;O'Toole ÁN;Ontiveros-Palacios N;Petrov AI;Rangel-Pineros G;Redaschi N;Reimering S;Reinert K;Reyes A;Richardson L;Robertson DL;Sadegh S;Singer JB;Theys K;Upton C;Welzel M;Williams L;Marz M
• 通讯作者: Marz M

Rfam 14: expanded coverage of metagenomic, viral and microRNA families.

• DOI: 10.1093/nar/gkaa1047
• 发表时间: 2021-01-08
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Kalvari I;Nawrocki EP;Ontiveros-Palacios N;Argasinska J;Lamkiewicz K;Marz M;Griffiths-Jones S;Toffano-Nioche C;Gautheret D;Weinberg Z;Rivas E;Eddy SR;Finn RD;Bateman A;Petrov AI
• 通讯作者: Petrov AI