Abstract
The important role of non coding RNAs (ncRNAs) in the cell has made their identification a critical issue in the biological research. However, traditional approaches such as PT-PCR and Northern Blot are costly. With recent progress in bioinformatics and computational prediction technology, the discovery of ncRNAs has become realistically possible. This paper aims to introduce major computational approaches in the identification of ncRNAs, including homologous search, de novo prediction and mining in deep sequencing data. Furthermore, related software tools have been compared and reviewed along with a discussion on future improvements.
Highlights
In the early biological researches, scientists mainly focused on the prokaryotes, which are dominated (85%90%) by protein-coding genes [1] and it is publicly considered that the cellular activities are implemented by the proteins which are transcribed from those coding genes
It is estimated that 98% of mammalian genomic output may be non-coding RNAs, while the remaining 2% encodes the proteins [2]
Non-coding RNAs are involved in translation, splicing, gene regulation, chromatin remodeling, gene modification, degradation and other functions [61]
Summary
In the early biological researches, scientists mainly focused on the prokaryotes, which are dominated (85%90%) by protein-coding genes [1] and it is publicly considered that the cellular activities are implemented by the proteins which are transcribed from those coding genes. Non-coding RNAs are involved in translation, splicing, gene regulation, chromatin remodeling, gene modification, degradation and other functions [61] They are closely associated with cancer and other complex diseases [4]. Non-coding RNAs are recognized only in biological experiments with technologies such as full-length complementary DNA cloning and genomic tiling arrays in the transcriptomes of organisms These technologies can suit long ncRNA (lncRNA) genes in an efficient way, they are costly always requiring enough RNA samples, and are limited. Different functions are induced by diverse ncRNA structures and there are variations in ncRNA length They are different from protein-coding genes which have a lot of common conserved features of primary sequence, including splice cites, promoters, terminator and binding motifs etc. We try to introduce most currently existing approaches about the identification of ncRNAs
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