Discovering Putative Peptides Encoded from Noncoding RNAs in Ribosome Profiling Data of Arabidopsis thaliana

NCPbook: A comprehensive database of noncanonical peptides

Noncanonical peptides (NCPs) are a class of peptides generated from regions previously thought of as noncoding, such as introns, 5' UTRs, 3' UTRs, and intergenic regions. In recent years, the significance and diverse functions of NCPs have come to light, yet a systematic and comprehensive NCP database remains absent. Here, we developed NCPbook (https://ncp.wiki/ncpbook/), a database of evidence-supported NCPs, which aims to provide a resource for efficient exploration, analysis, and manipulation of NCPs. NCPbook incorporates data from diverse public databases and scientific literature. The current version of NCPbook includes 180,676 NCPs across 29 different species, evidenced by MS, ribosome profiling, or molecular experiments. These NCPs are distributed across kingdoms, comprising 123,408 from 14 plant species, 56,999 from 7 animal species, and 269 from 8 microbial species. Furthermore, NCPbook encompasses 9,166 functionally characterized NCPs playing important roles in immunity, stress resistance, growth, and development. Equipped with a user-friendly interface, NCPbook allows users to search, browse, visualize, and retrieve data, making it an indispensable platform for researching NCPs in various plant, animal, and microbial species.

Understanding small ORF diversity through a comprehensive transcription feature classification

Small open reading frames (small ORFs/sORFs/smORFs) are potentially coding sequences smaller than 100 codons that have historically been considered junk DNA by gene prediction software and in annotation screening; however, the advent of next-generation sequencing has contributed to the deeper investigation of junk DNA regions and their transcription products, resulting in the emergence of smORFs as a new focus of interest in systems biology. Several smORF peptides were recently reported in noncanonical mRNAs as new players in numerous biological contexts; however, their relevance is still overlooked in coding potential analysis. Hence, this review proposes a smORF classification based on transcriptional features, discussing the most promising approaches to investigate smORFs based on their different characteristics. First, smORFs were divided into nonexpressed (intergenic) and expressed (genic) smORFs. Second, genic smORFs were classified as smORFs located in noncoding RNAs (ncRNAs) or canonical mRNAs. Finally, smORFs in ncRNAs were further subdivided into sequences located in small or long RNAs, whereas smORFs located in canonical mRNAs were subdivided into several specific classes depending on their localization along the gene. We hope that this review provides new insights into large-scale annotations and reinforces the role of smORFs as essential components of a hidden coding DNA world.

The role of long noncoding RNA SNHG7 in human cancers (Review)

Long non-coding RNAs (lncRNAs) have been demonstrated to serve important roles in a variety of human tumor types. The lncRNA small nucleolar RNA host gene 7 (SNHG7) is associated with a variety of cancer types, such as esophageal cancer, breast cancer and gastric neoplasia. Based on previous studies that examined SNHG7 expression in tumors, it has become clear that SNHG7 modulates tumorigenesis and cancer progression by acting as a competing endogenous RNA. SNHG7 can sponge tumor-suppressive microRNAs and regulate downstream signaling pathways. In addition, overexpression of SNHG7 is associated with the clinical characteristics of patients with cancer by regulating cellular proliferation, invasion and metastasis and by inhibiting apoptosis via a variety of mechanisms of action. The function of SNHG7 in tumorigenesis and cancer progression indicates that it can potentially act as a novel therapeutic target or a diagnostic biomarker for cancer therapy or detection, respectively.

Emerging role of tumor-related functional peptides encoded by lncRNA and circRNA

Non-coding RNAs do not encode proteins and regulate various oncological processes. They are also important potential cancer diagnostic and prognostic biomarkers. Bioinformatics and translation omics have begun to elucidate the roles and modes of action of the functional peptides encoded by ncRNA. Here, recent advances in long non-coding RNA (lncRNA) and circular RNA (circRNA)-encoded small peptides are compiled and synthesized. We introduce both the computational and analytical methods used to forecast prospective ncRNAs encoding oncologically functional oligopeptides. We also present numerous specific lncRNA and circRNA-encoded proteins and their cancer-promoting or cancer-inhibiting molecular mechanisms. This information may expedite the discovery, development, and optimization of novel and efficacious cancer diagnostic, therapeutic, and prognostic protein-based tools derived from non-coding RNAs. The role of ncRNA-encoding functional peptides has promising application perspectives and potential challenges in cancer research. The aim of this review is to provide a theoretical basis and relevant references, which may promote the discovery of more functional peptides encoded by ncRNAs, and further develop novel anticancer therapeutic targets, as well as diagnostic and prognostic cancer markers.

MiTPeptideDB: a proteogenomic resource for the discovery of novel peptides

Motivation

The principal lines of research in MS/MS based Proteomics have been directed toward the molecular characterization of the proteins including their biological functions and their implications in human diseases. Recent advances in this field have also allowed the first attempts to apply these techniques to the clinical practice. Nowadays, the main progress in Computational Proteomics is based on the integration of genomic, transcriptomic and proteomic experimental data, what is known as Proteogenomics. This methodology is being especially useful for the discovery of new clinical biomarkers, small open reading frames and microproteins, although their validation is still challenging.

Results

We detected novel peptides following a proteogenomic workflow based on the MiTranscriptome human assembly and shotgun experiments. The annotation approach generated three custom databases with the corresponding peptides of known and novel transcripts of both protein coding genes and non-coding genes. In addition, we used a peptide detectability filter to improve the computational performance of the proteomic searches, the statistical analysis and the robustness of the results. These innovative additional filters are specially relevant when noisy next generation sequencing experiments are used to generate the databases. This resource, MiTPeptideDB, was validated using 43 cell lines for which RNA-Seq experiments and shotgun experiments were available.

Availability and implementation

MiTPeptideDB is available at http://bit.ly/MiTPeptideDB.

Supplementary information

Supplementary data are available at Bioinformatics online.

Proteogenomics in the context of the Human Proteome Project (HPP)

INTRODUCTION

The technological and scientific progress performed in the Human Proteome Project (HPP) has provided to the scientific community a new set of experimental and bioinformatic methods in the challenging field of shotgun and SRM/MRM-based Proteomics. The requirements for a protein to be considered experimentally validated are now well-established, and the information about the human proteome is available in the neXtProt database, while targeted proteomic assays are stored in SRMAtlas. However, the study of the missing proteins continues being an outstanding issue. Areas covered: This review is focused on the implementation of proteogenomic methods designed to improve the detection and validation of the missing proteins. The evolution of the methodological strategies based on the combination of different omic technologies and the use of huge publicly available datasets is shown taking the Chromosome 16 Consortium as reference. Expert commentary: Proteogenomics and other strategies of data analysis implemented within the C-HPP initiative could be used as guidance to complete in a near future the catalog of the human proteins. Besides, in the next years, we will probably witness their use in the B/D-HPP initiative to go a step forward on the implications of the proteins in the human biology and disease.

Translatomics: The Global View of Translation

In all kingdoms of life, proteins are synthesized by ribosomes in a process referred to as translation. The amplitude of translational regulation exceeds the sum of transcription, mRNA degradation and protein degradation. Therefore, it is essential to investigate translation in a global scale. Like the other “omics”-methods, translatomics investigates the totality of the components in the translation process, including but not limited to translating mRNAs, ribosomes, tRNAs, regulatory RNAs and nascent polypeptide chains. Technical advances in recent years have brought breakthroughs in the investigation of these components at global scale, both for their composition and dynamics. These methods have been applied in a rapidly increasing number of studies to reveal multifaceted aspects of translation control. The process of translation is not restricted to the conversion of mRNA coding sequences into polypeptide chains, it also controls the composition of the proteome in a delicate and responsive way. Therefore, translatomics has extended its unique and innovative power to many fields including proteomics, cancer research, bacterial stress response, biological rhythmicity and plant biology. Rational design in translation can enhance recombinant protein production for thousands of times. This brief review summarizes the main state-of-the-art methods of translatomics, highlights recent discoveries made in this field and introduces applications of translatomics on basic biological and biomedical research.