Discovering putative peptides encoded from non-coding RNAs in

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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]

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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