Gene Ontology-based function prediction of long non-coding RNAs using bi-random walk

Background

With the development of sequencing technology, more and more long non-coding RNAs (lncRNAs) have been identified. Some lncRNAs have been confirmed that they play an important role in the process of development through the dosage compensation effect, epigenetic regulation, cell differentiation regulation and other aspects. However, the majority of the lncRNAs have not been functionally characterized. Explore the function of lncRNAs and the regulatory network has become a hot research topic currently.

Methods

In the work, a network-based model named BiRWLGO is developed. The ultimate goal is to predict the probable functions for lncRNAs at large scale. The new model starts with building a global network composed of three networks: lncRNA similarity network, lncRNA-protein association network and protein-protein interaction (PPI) network. After that, it utilizes bi-random walk algorithm to explore the similarities between lncRNAs and proteins. Finally, we can annotate an lncRNA with the Gene Ontology (GO) terms according to its neighboring proteins.

Results

We compare the performance of BiRWLGO with the state-of-the-art models on a manually annotated lncRNA benchmark with known GO terms. The experimental results assert that BiRWLGO outperforms other methods in terms of both maximum F-measure (F_max) and coverage.

Conclusions

BiRWLGO is a relatively efficient method to predict the functions of lncRNA. When protein interaction data is integrated, the predictive performance of BiRWLGO gains a great improvement.

     

长链非编码RNA研究进展

基因组计划研究表明, 在组成人类基因组的30亿个碱基对中, 仅有1.5%的核酸序列用于蛋白质编码, 其余98.5%的基因组为非蛋白质编码序列。这些序列曾被认为是在进化过程中累积的“垃圾序列”而未予以关注, 但在随后启动的ENCODE研究计划中却发现, 75%的基因组序列能够被转录成RNA, 其中近74%的转录产物为非编码RNA(Non-coding RNA, ncRNA)。在非编码RNA中, 绝大多数转录本的长度大于200个碱基, 这些“长链非编码RNA(Long non-coding RNA, lncRNA)”能够在转录及转录后水平上调节蛋白编码基因的表达, 从而广泛地参与包括细胞分化、个体发育在内的重要生命过程, 其异常表达还与多种人类重大疾病的发生密切相关。文章综述了长链非编码RNA的发现、分类、表达、作用机制以及其在个体发育和人类疾病中的作用。     

长链非编码RNA生物学功能及其意义研究进展

人类基因组DNA核苷酸序列中约93%能被转录为RNA,其中仅2%的转录产物被翻译为蛋白质,余下98%属于非编码RNA（non-coding RNA,ncRNA）。ncRNA中长度超过200 nt的称为长链非编码RNA（long non-coding RNA,LncRNA）,长期以来LncRNA被认为是转录过程中的副产物而不具有生物学功能。近年随着微小RNA（microRNA,miRNA）的研究进展,揭示了ncRNA在人类基因转录后调节、细胞生长、分化、增殖中起着相当重要的作用。同时也提示,相比miRNA,在细胞内转录比例更高的LncRNA具有极其复杂而重要的生物学功能,并与人类疾病密切相关。结合LncRNA的表观遗传学功能及其病理生理意义作一简述。     

动物长链非编码RNA研究进展

长链非编码RNA(long non-coding RNA,lncRNA)是一类广泛存在于动植物体内、长度大于200nt、基本不编码蛋白质的转录本。研究表明,lncRNA能够协助蛋白质复合体转运、参与基因和染色体的激活与失活调控等,在胚胎发育、肌肉生长、脂肪沉积以及免疫应答等过程中发挥重要作用。近年来,在人类基因组计划和ENCODE(The Encyclopedia of DNA Elements)计划推动下,在动物中不仅鉴定出数量众多的lncRNA,而且在lncRNA调控脂肪代谢、肌肉发育以及免疫抗病等重要生物学过程的机理研究方面也取得了突破性的进展。这些研究结果颠覆了lncRNA不编码蛋白的传统观念,提出了lncRNA编码功能性小肽调控生物学过程的新模型。本文主要介绍了动物lncRNA的特征与类型、常用数据库、生物学功能、分子调控模型以及未来lncRNA的研究方向,以期为动物lncRNA功能研究提供参考信息。     

Conservation analysis of long non-coding RNAs in plants

Long non-coding RNAs (lncRNAs) are gene regulators that have vital roles in development and adaptation to the environment in eukaryotes. However, the structural and evolutionary analyses of plant lncRNAs are limited. In this study, we performed an analysis of lncRNAs in five monocot and five dicot species. Our results showed that plant lncRNA genes were generally shorter and had fewer exons than protein-coding genes. The numbers of lncRNAs were positively correlated with the numbers of protein-coding genes in different plant species, despite a high range of variation. Sequence conservation analysis showed that the majority of lncRNAs had high sequence conservation at the intra-species and sub-species levels, reminiscent of protein-coding genes. At the inter-species level, a subset of lncRNAs were highly diverged at the nucleotide level, but conserved by position. Interestingly, we found that plant lncRNAs have identical splicing signals, and those which can form precursors or targets of miRNAs have a conservative identity in different species. We also revealed that most of the lowly expressed lncRNAs were tissue-specific, while those highly conserved were constitutively transcribed. Meanwhile, we characterized a subset of rice lncRNAs that were co-expressed with their adjacent protein-coding genes, suggesting they may play cis-regulatory roles. These results will contribute to understanding the biological significance and evolution of lncRNAs in plants.     

Role of long non-coding RNAs in metabolic control

Long non-coding RNAs (lncRNAs) have emerged as pivotal regulators of gene expression by influencing various biological processes including proliferation, apoptosis, differentiation, and senescence. Accumulating evidence implicates lncRNAs in the maintenance of metabolic homeostasis; dysregulation of certain lncRNAs promotes the progression of metabolic disorders such as diabetes, obesity, and cardiovascular diseases. In this review, we discuss our understanding of lncRNAs implicated in metabolic control, focusing on in particular diseases arising from chronic inflammation, insulin resistance, and lipid homeostasis. We have analyzed lncRNAs and their molecular targets involved in the pathogenesis of chronic liver disease, diabetes, and obesity, and have discussed the rising interest in lncRNAs as diagnostic and therapeutic targets improving metabolic homeostasis. This article is part of a Special Issue entitled: ncRNA in control of gene expression edited by Kotb Abdelmohsen.     

From structure prediction to genomic screens for novel non-coding RNAs

Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.