In recent years, there have been increasing numbers of transcripts identified that do not encode proteins, many of which are developmentally regulated and appear to have regulatory functions. Here, we describe the construction of a comprehensive mammalian noncoding RNA database (RNAdb) which contains over 800 unique experimentally studied non-coding RNAs (ncRNAs), including many associated with diseases and/or developmental processes.
Piwi-interacting RNAs (piRNAs) are expressed in mammalian germline cells and have been identified as key players in germline development. These molecules, typically of length 25-33 nt, associate with Piwi proteins of the Argonaute family to form the Piwi-interacting RNA complex. These small regulatory RNAs have been implicated in spermatogenesis, repression of retrotransposon transposition in germline cells, epigenetic regulation and positive regulation of translation and mRNA stability.
Recent interests, such as RNA interference and antisense RNA regulation, strongly motivate the problem of predicting whether two nucleic acid strands interact.
Imprinted noncoding RNAs (ncRNAs) are expressed mono-allelically in a parent-of-origin-dependent manner, which is mainly evident in mammals. Lying at a crossroad between imprinted genes and ncRNAs, imprinted ncRNAs show distinct features. They are likely to function in nontraditional ways compared to non-imprinted ncRNAs, and are much more responsible for the mechanism of genomic imprinting compared to imprinted protein-coding genes. An increasing number of human diseases have been shown to be related to abnormalities in imprinted ncRNAs.
Recent advances in RNA sequencing technology (RNA-Seq) enables comprehensive profiling of RNAs by producing millions of short sequence reads from size-fractionated RNA libraries. Although conventional tools for detecting and distinguishing non-coding RNAs (ncRNAs) from reference-genome data can be applied to sequence data, ncRNA detection can be improved by harnessing the full information content provided by this new technology. Here we present NorahDesk, the first unbiased and universally applicable method for small ncRNAs detection from RNA-Seq data.
Piwi proteins and their guiding small RNAs, termed Piwi-interacting (pi-) RNAs, are essential for silencing of transposons in the germline of animals. A substantial fraction of piRNAs originates from genomic loci termed piRNA clusters and sequences encoded in these piRNA clusters determine putative targets for the Piwi/piRNA system. In the past decade, studies of piRNA transcriptomes in different species revealed additional roles for piRNAs beyond transposon silencing, reflecting the astonishing plasticity of the Piwi/piRNA system along different phylogenetic branches.
Endogenous small non-coding RNAs (sRNAs), including microRNAs, PIWI-interacting RNAs and small interfering RNAs, play important gene regulatory roles in animals and plants by pairing to the protein-coding and non-coding transcripts. However, computationally assigning these various sRNAs to their regulatory target genes remains technically challenging. Recently, a high-throughput degradome sequencing method was applied to identify biologically relevant sRNA cleavage sites.
Small silencing RNAs, including microRNAs, endogenous small interfering RNAs (endo-siRNAs) and Piwi-interacting RNAs (piRNAs), have been shown to play important roles in fine-tuning gene expression, defending virus and controlling transposons. Loss of small silencing RNAs or components in their pathways often leads to severe developmental defects, including lethality and sterility. Recently, non-templated addition of nucleotides to the 3' end, namely tailing, was found to associate with the processing and stability of small silencing RNAs.
Next generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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