RNA takes center stage

Todd, Gabrielle C.; Karbstein, Katrin

doi:10.1002/bip.20824

Cited by 6 publications

(5 citation statements)

References 43 publications

(39 reference statements)

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“…The past 20 years have witnessed much progress in the study of RNAs [ 1 , 2 ]. A large proportion of known RNAs were proved to undertake diverse important biological functions.…”

Section: Introductionmentioning

confidence: 99%

CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

2015

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Recent studies reveal that circular RNAs (circRNAs) are a novel class of abundant, stable and ubiquitous noncoding RNA molecules in animals. Comprehensive detection of circRNAs from high-throughput transcriptome data is an initial and crucial step to study their biogenesis and function. Here, we present a novel chiastic clipping signal-based algorithm, CIRI, to unbiasedly and accurately detect circRNAs from transcriptome data by employing multiple filtration strategies. By applying CIRI to ENCODE RNA-seq data, we for the first time identify and experimentally validate the prevalence of intronic/intergenic circRNAs as well as fragments specific to them in the human transcriptome.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-014-0571-3) contains supplementary material, which is available to authorized users.

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“…The past 20 years have witnessed much progress in the study of RNAs [ 1 , 2 ]. A large proportion of known RNAs were proved to undertake diverse important biological functions.…”

Section: Introductionmentioning

confidence: 99%

CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

2015

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“…This has brought about the emergence of microRNAs (miRNAs) and important biological processes such as RNA interference [Lee et al., ; Fire et al., ], greatly expanding the view of how gene regulation works [Pasquinelli et al., ; Lau et al., ] and thus showing that ncRNAs have a much richer functional spectrum than anticipated [Amaral et al., ]. All of this has contributed to one of the most significant biological discoveries of the last decade: the uncovering of the existence of several types of RNAs, each with their specific functions [Eddy, ; Todd and Karbstein, ]. Thus, as recent transcriptomic analyses have confirmed, over 90% of the human genome is in fact transcribed, but only a very small fraction of it encodes for proteins [Birney et al., ; Elgar and Vavouri, ].…”

Section: Introductionmentioning

confidence: 99%

Noncoding RNA: Current Deep Sequencing Data Analysis Approaches and Challenges

et al. 2016

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One of the most significant biological discoveries of the last decade is represented by the reality that the vast majority of the transcribed genomic output comprises diverse classes of noncoding RNAs (ncRNAs) that may play key roles and/or be affected by many biochemical cellular processes (i.e., RNA editing), with implications in human health and disease. With 90% of the human genome being transcribed and novel classes of ncRNA emerging (tRNA-derived small RNAs and circular RNAs among others), the great majority of the human transcriptome suggests that many important ncRNA functions/processes are yet to be discovered. An approach to filling such vast void of knowledge has been recently provided by the increasing application of next-generation sequencing (NGS), offering the unprecedented opportunity to obtain a more accurate profiling with higher resolution, increased throughput, sequencing depth, and low experimental complexity, concurrently posing an increasing challenge in terms of efficiency, accuracy, and usability of data analysis software. This review provides an overview of ncRNAs, NGS technology, and the most recent/popular computational approaches and the challenges they attempt to solve, which are essential to a more sensitive and comprehensive ncRNA annotation capable of furthering our understanding of this still vastly uncharted genomic territory.

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“…As interest on the hypothesized “RNA world” grew, subsequent studies allowed to explore the potential of such new vision (Lee et al, 1993 ; Fire et al, 1998 ), eventually leading to one of the most significant biological discoveries of the past decade: the existence of several types of RNAs, each with their specific functions in eukaryotic cells (Eddy, 2001 ; Todd and Karbstein, 2007 ). As the ENCODE project has confirmed, most of the human genome is in fact transcribed, but only a very small fraction of it encodes for proteins (Birney et al, 2007 ; Elgar and Vavouri, 2008 ).…”

Section: Introductionmentioning

confidence: 99%

Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques

Veneziano

Nigita

Ferro

2015

Front. Bioeng. Biotechnol.

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The majority of the human transcriptome is defined as non-coding RNA (ncRNA), since only a small fraction of human DNA encodes for proteins, as reported by the ENCODE project. Several distinct classes of ncRNAs, such as transfer RNA, microRNA, and long non-coding RNA, have been classified, each with its own three-dimensional folding and specific function. As ncRNAs are highly abundant in living organisms and have been discovered to play important roles in many biological processes, there has been an ever increasing need to investigate the entire ncRNAome in further unbiased detail. Recently, the advent of next-generation sequencing (NGS) technologies has substantially increased the throughput of transcriptome studies, allowing an unprecedented investigation of ncRNAs, as regulatory pathways and novel functions involving ncRNAs are now also emerging. The huge amount of transcript data produced by NGS has progressively required the development and implementation of suitable bioinformatics workflows, complemented by knowledge-based approaches, to identify, classify, and evaluate the expression of hundreds of ncRNAs in normal and pathological conditions, such as cancer. In this mini-review, we present and discuss current bioinformatics advances in the development of such computational approaches to analyze and classify the ncRNA component of human transcriptome sequence data obtained from NGS technologies.

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RNA takes center stage

Cited by 6 publications

References 43 publications

CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

CIRI: an efficient and unbiased algorithm for de novo circular RNA identification

Noncoding RNA: Current Deep Sequencing Data Analysis Approaches and Challenges

Computational Approaches for the Analysis of ncRNA through Deep Sequencing Techniques

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