Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts
Liang Sun,Haitao Luo,Dechao Bu,Guoguang Zhao,Kuntao Yu,Changhai Zhang,Yuanning Liu,Runsheng Chen,Yi Zhao +8 more
TLDR
The implementation of CNCI offered highly accurate classification of transcripts assembled from whole-transcriptome sequencing data in a cross-species manner, that demonstrated gene evolutionary divergence between vertebrates, and invertebrates, or between plants, and provided a long non-coding RNA catalog of orangutan.Abstract:
It is a challenge to classify protein-coding or non-coding transcripts, especially those re-constructed from high-throughput sequencing data of poorly annotated species. This study developed and evaluated a powerful signature tool, Coding-Non-Coding Index (CNCI), by profiling adjoining nucleotide triplets to effectively distinguish protein-coding and non-coding sequences independent of known annotations. CNCI is effective for classifying incomplete transcripts and sense-antisense pairs. The implementation of CNCI offered highly accurate classification of transcripts assembled from whole-transcriptome sequencing data in a cross-species manner, that demonstrated gene evolutionary divergence between vertebrates, and invertebrates, or between plants, and provided a long non-coding RNA catalog of orangutan. CNCI software is available at http://www.bioinfo.org/software/cnci.read more
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CPC2: a fast and accurate coding potential calculator based on sequence intrinsic features.
TL;DR: The coding potential calculator CPC1 is upgraded to CPC2, which runs ∼1000 times faster than CPC1 and exhibits superior accuracy compared with CPC1, especially for long non-coding transcripts.
Journal ArticleDOI
NONCODE 2016: an informative and valuable data source of long non-coding RNAs
Yi Zhao,Hui Li,Shuangsang Fang,Yue Kang,Wei Wu,Yajing Hao,Ziyang Li,Dechao Bu,Ninghui Sun,Michael Q. Zhang,Runsheng Chen +10 more
TL;DR: In this update, NONCODE has added six new species, bringing the total to 16 species altogether and introduced three important new features: conservation annotation; the relationships between lncRNAs and diseases; and an interface to choose high-quality datasets through predicted scores, literature support and long-read sequencing method support.
Journal ArticleDOI
PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme
TL;DR: PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes and is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data.
Journal ArticleDOI
Long non-coding RNAs as a source of new peptides
TL;DR: It is found that a large fraction of the lncRNAs expressed in cells from six different species is associated with ribosomes, indicating that they play an important role in de novo protein evolution.
Journal ArticleDOI
NONCODEv4: exploring the world of long non-coding RNA genes
Chaoyong Xie,Jiao Yuan,Hui Li,Ming Li,Guoguang Zhao,Dechao Bu,Weimin Zhu,Wei Wu,Runsheng Chen,Yi Zhao +9 more
TL;DR: This update of NONCODE expands the ncRNA data set by collection of newly identified ncRNAs from literature published in the last 2 years and integration of the latest version of RefSeq and Ensembl.
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