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Discovering putative peptides encoded from non-coding RNAs in ribosome profiling data of Arabidopsis thaliana Qilin Li, Md. Asif Ahsan, Hongjun Chen, Jitong Xue, and Ming Chen ACS Synth. Biol., Just Accepted Manuscript • DOI: 10.1021/acssynbio.7b00386 • Publication Date (Web): 27 Jan 2018 Downloaded from http://pubs.acs.org on January 28, 2018
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ACS Synthetic Biology
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Discovering putative peptides encoded from non-coding RNAs in ribosome profiling data of Arabidopsis thaliana
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Qilin Li , Md. Asif Ahsan , Hongjun Chen , Jitong Xue and Ming Chen 1 Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, China 2 James D. Watson Institute of Genome Sciences, Zhejiang University, Hangzhou 310058, China
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* To whom correspondence should be addressed. Tel: +86-571-88206612; Fax: +86-571-88206612; Email:
[email protected] 9
Abstract
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Most of non-coding RNAs are considered as their expression at low levels and having a limited
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phylogenetic distribution in the cytoplasm, indicating that they may be only involved in specific
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biological processes. However, recent studies showed the protein-coding potential of ncRNAs,
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indicating that they might be source of some special proteins. Although there are increasing non-
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coding RNAs identified to be able to code proteins, it is challenging to distinguish coding RNAs from
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previously annotated ncRNAs, and to detect the proteins from their translation. In this article, we
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designed a pipeline to identify these non-coding RNAs in Arabidopsis thaliana from three NCBI GEO
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datasets with coding potential and predict their translation products. 31,311 non-coding RNAs were
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predicted to be translated into peptides, and they showed lower conservation rate than common
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proteins. In addition, we built an interaction network between these peptides and annotated
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Arabidopsis proteins using BIPS, which included 69 peptides from non-coding RNAs. Peptides in the
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interaction network showed different characteristics from other non-coding RNA-derived peptides, and
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they participated in several crucial biological processes, such as photorespiration and stress-
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responses. All the Information of putative ncPEPs and their interaction with proteins predicted above
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are finally integrated in a database, PncPEPDB (http://bis.zju.edu.cn/PncPEPDB). These results
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showed that peptides derived from non-coding RNAs may play important roles in non-coding RNA
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regulation, which provided another hypothesis that non-coding RNA may regulate the metabolism via
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their translation products.
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Keywords: ribosome profiling, ncRNA-encoded peptides, peptide-protein interaction network,
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database and visualization
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Introduction
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As transcriptomic research develops rapidly, nucleic acid sequences which were considered weakly
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expressed into proteins have become a hotspot
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RNAs (ncRNAs) such as micro RNA (miRNA), long non-coding RNA (lncRNA), circular RNA
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(circRNA), and competing endogenous RNA (ceRNA), were discovered to play crucial roles in gene
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regulatory networks, leading to a trend of studying them and their interactions
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expressed at low levels and have a limited phylogenetic distribution in the cytoplasm12, meaning that
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they may be only involved in specific biological processes.
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. During the decades of research, non-coding
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ACS Paragon Plus Environment
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. Most of them are
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Whether translation exists in these weakly expressed transcripts remains controversial. However
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recent studies showed the protein-coding potential of ncRNAs. lncRNAs were found to lodged into
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ribosome, indicating that they might be source of some special proteins
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open reading frames that encode small peptides. The regulatory roles of some miRNA-encoded
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peptides (miPEPs) have been investigated
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able to code proteins, it is challenging to distinguish coding RNAs from previously annotated ncRNAs,
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and to detect the proteins from ncRNAs translation.
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. microRNAs also contain
. Although there are increasing ncRNAs identified to be
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In 2009, ribosome profiling sequencing (Ribo-Seq), a new technique developed by N. Ingolia et al.
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made detection of small proteins with low abundance possible (Fig 1A) 15. Up to date, This technology
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had been chosen as a tool in various investigations, for instance, in order to prolong heat stress
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scientists globally profile the adaptive response of Arabidopsis thaliana by Ribo-Seq
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the three-nucleotide periodicity of the reads, resulting from the movement of the ribosome along the
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coding sequence, differentiates translated sequences from other possible RNA protein complexes. A
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growing number of studies based on this technique have reported that a significant proportion of
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ncRNAs are translated
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small proteins or peptides are not yet clear. Some of them may either be involved in their
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corresponding ncRNA expression events, or form an interaction network with other proteins. On a
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contrast, a substantial number of small proteins detected in Ribo-Seq may be encoded from
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misannotated protein coding genes, which have not been correctly predicted by bioinformatics
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algorithms because of their short size. This present study takes advantage of the existed Ribo-Seq
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and RNA-Seq data for Arabidopsis thaliana to investigate the putative ncRNAs and their expression
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products, providing evidence that ncRNAs may have more possible functions with the peptides.
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Material and Methods
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1 Detection of translated ORFs from Ribo-Seq data and related analysis
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Ribo-Seq and RNA-Seq data of leaf, root, shoot and flower bud in Arabidopsis thaliana were obtained
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from NCBI GEO Datasets (GSE40209
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. In addition,
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. However, the functions and regulation mechanisms of detected
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, GSE69802 22
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, GSE81332
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). After removal of adapters and
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processed with TopHat
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differed into coding and putative non-coding RNAs using CuffCompare. Transcripts with Cuffcompare
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class code of i (novel intronic), u (novel intergenic) and x (novel antisense) are recognized as putative
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non-coding RNAs, and they were later aligned to TAIR10 in order to filter coding sequences (Fig 2).
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and Cufflinks
with TAIR10 genome, all the assembled transcripts were
These transcripts were processed with TransDecoder
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and CIPHER
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to get their RNA
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sequences, peptide sequences and coding scores. Sequences of non-coding RNAs were processed
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by BLASTN with reference sequence of annotated ncRNAs in Ensembl24 (tRNA, rRNA, snRNA,
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snoRNA and miRNA), annotated and predicted ncRNAs in GreeNC
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(ceRNA). For peptide sequence conservation analysis, homologues of the Arabidopsis ORFs in
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transcript assemblies of Oryza sativa (e-value
