Annotation of the zebrafish genome through an integrated transcriptomic and proteomic analysis

The posterity of Zebrafish in paradigm of in vivo molecular toxicological profiling

The aggrandised advancement in utility of advanced day-to-day materials and nanomaterials has raised serious concern on their biocompatibility with human and other biotic members. In last few decades, understanding of toxicity of these materials has been given the centre stage of research using many in vitro and in vivo models. Zebrafish (Danio rerio), a freshwater fish and a member of the minnow family has garnered much attention due to its distinct features, which make it an important and frequently used animal model in various fields of embryology and toxicological studies. Given that fertilization and development of zebrafish eggs take place externally, they serve as an excellent model organism for studying early developmental stages. Moreover, zebrafish possess a comparable genetic composition to humans and share almost 70% of their genes with mammals. This particular model organism has become increasingly popular, especially for developmental research. Moreover, it serves as a link between in vitro studies and in vivo analysis in mammals. It is an appealing choice for vertebrate research, when employing high-throughput methods, due to their small size, swift development, and relatively affordable laboratory setup. This small vertebrate has enhanced comprehension of pathobiology and drug toxicity. This review emphasizes on the recent developments in toxicity screening and assays, and the new insights gained about the toxicity of drugs through these assays. Specifically, the cardio, neural, and, hepatic toxicology studies inferred by applications of nanoparticles have been highlighted.

Multi-tissue proteogenomic analysis for mechanistic toxicology studies in non-model species

New approach methodologies (NAM), including omics and in vitro approaches, are contributing to the implementation of 3R (reduction, refinement and replacement) strategies in regulatory science and risk assessment. In this study, we present an integrative transcriptomics and proteomics analysis workflow for the validation and revision of complex fish genomes and demonstrate how proteogenomics expression matrices can be used to support multi-level omics data integration in non-model species in vivo and in vitro. Using Atlantic salmon as an example, we constructed proteogenomic databases from publicly available transcriptomic data and in-house generated RNA-Seq and LC-MS/MS data. Our analysis identified ∼80,000 peptides, providing direct evidence of translation for over 40,000 RefSeq structures. The data also highlighted 183 co-located peptide groups that supported a single transcript each, and in each case, either corrected a previous annotation, supported Ensembl annotations not present in RefSeq, or identified novel previously unannotated genes. Proteogenomics data-derived expression matrices revealed distinct profiles for the different tissue types analyzed. Focusing on proteins involved in defense against xenobiotics, we detected distinct expression patterns across different salmon tissues and observed homology in the expression of chemical defense proteins between in vivo and in vitro liver systems. Our study demonstrates the potential of proteogenomic analyses in extending our understanding of complex fish genomes and provides an advanced bioinformatic toolkit to support the further development of NAMs and their application in regulatory science and (eco)toxicological studies of non-model species.

Multi-omics analysis of zebrafish response to tick saliva reveals biological processes associated with alpha-Gal syndrome

The alpha-Gal syndrome (AGS) is a tick-borne allergy. A multi-omics approach was used to determine the effect of tick saliva and mammalian meat consumption on zebrafish gut transcriptome and proteome. Bioinformatics analysis using R software was focused on significant biological and metabolic pathway changes associated with AGS. Ortholog mapping identified highly concordant human ortholog genes for the detection of disease-enriched pathways. Tick saliva treatment increased zebrafish mortality, incidence of hemorrhagic type allergic reactions and changes in behavior and feeding patterns. Transcriptomics analysis showed downregulation of biological and metabolic pathways correlated with anti-alpha-Gal IgE and allergic reactions to tick saliva affecting blood circulation, cardiac and vascular smooth muscle contraction, behavior and sensory perception. Disease enrichment analysis revealed downregulated orthologous genes associated with human disorders affecting nervous, musculoskeletal, and cardiovascular systems. Proteomics analysis revealed suppression of pathways associated with immune system production of reactive oxygen species and cardiac muscle contraction. Underrepresented proteins were mainly linked to nervous and metabolic human disorders. Multi-omics data revealed inhibition of pathways associated with adrenergic signaling in cardiomyocytes, and heart and muscle contraction. Results identify tick saliva-related biological pathways supporting multisystemic organ involvement and linking α-Gal sensitization with other illnesses for the identification of potential disease biomarkers.

Manual correction of genome annotation improved alternative splicing identification of Artemisia annua

Gene annotation is essential for genome-based studies. However, algorithm-based genome annotation is difficult to fully and correctly reveal genomic information, especially for species with complex genomes. Artemisia annua L. is the only commercial resource of artemisinin production though the content of artemisinin is still to be improved. Genome-based genetic modification and breeding are useful strategies to boost artemisinin content and therefore, ensure the supply of artemisinin and reduce costs, but better gene annotation is urgently needed. In this study, we manually corrected the newly released genome annotation of A. annua using second- and third-generation transcriptome data. We found that incorrect gene information may lead to differences in structural, functional, and expression levels compared to the original expectations. We also identified alternative splicing events and found that genome annotation information impacted identifying alternative splicing genes. We further demonstrated that genome annotation information and alternative splicing could affect gene expression estimation and gene function prediction. Finally, we provided a valuable version of A. annua genome annotation and demonstrated the importance of gene annotation in future research.

A chromosome-scale genome and proteome draft of Tremella fuciformis

In this study, we first reported a high-quality chromosome-scale genome of Tremella fuciformis using Pacbio HiFi sequencing combining Hi-C technology. According to 21.6 Gb PacBio HiFi reads and 18.1 Gb Hi-C valid reads, we drafted a T. fuciformis genome of 27.38 Mb assigned to 10 chromosomes, with the contig N50 of 2.28 Mb, GC content of 56.51 %, BUSCOs completeness of 93.1 % and consensus quality value of 33.7. The following annotation of genomic components predicted 5,171 repeat sequences, 283 RNAs, and 10,150 protein-coding genes. Next, the intracellular proteins at three differential life stages of T. fuciformis (conidium, hyphal and fruiting body) were identified by the shot-gun proteomics. 6,823 canonical proteins (68.1 % of predicted proteome) have been identified with protein FDR cut-off of 0.01, establishing the first proteome draft of predicted protein-coding genes of T. fuciformis. Finally, 24 T. fuciformis polysaccharides (TPS) biosynthesis-related genes in mycelia were identified by comparative transcriptomics and proteomics, which may be more active than in conidium and revealed the TPS biosynthesis process in mycelia. This present study elucidated T. fuciformis genome composition and organization, drafted its associated proteome, and provided a genome-view of TPS biosynthesis, which will be a powerful platform for biological and genetic studies in T. fuciformis.

3' RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism

Introduction: The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Methods and results: Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. Conclusions: These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

The PeptideAtlas of a widely cultivated fish Labeo rohita: A resource for the Aquaculture Community

Labeo rohita (Rohu) is one of the most important fish species produced in world aquaculture. Integrative omics research provides a strong platform to understand the basic biology and translate this knowledge into sustainable solutions in tackling disease outbreak, increasing productivity and ensuring food security. Mass spectrometry-based proteomics has provided insights to understand the biology in a new direction. Very little proteomics work has been done on 'Rohu' limiting such resources for the aquaculture community. Here, we utilised an extensive mass spectrometry based proteomic profiling data of 17 histologically normal tissues, plasma and embryo of Rohu to develop an open source PeptideAtlas. The current build of "Rohu PeptideAtlas" has mass-spectrometric evidence for 6015 high confidence canonical proteins at 1% false discovery rate, 2.9 million PSMs and ~150 thousand peptides. This is the first open-source proteomics repository for an aquaculture species. The 'Rohu PeptideAtlas' would promote basic and applied aquaculture research to address the most critical challenge of ensuring nutritional security for a growing population.

Organ-Based Proteome and Post-Translational Modification Profiling of a Widely Cultivated Tropical Water Fish, Labeo rohita

Proteomics has enormous applications in human and animal research. However, proteomic studies in fisheries science are quite scanty particularly for economically important species. Few proteomic studies have been carried out in model fish species, but comprehensive proteomics of aquaculture species are still scarce. This study aimed to perform a comprehensive organ-based protein profiling of important tissue samples for one of the most important aquaculture species,Labeo rohita.Deep proteomic profiling of 17 histologically normal tissues, blood plasma, and embryo provided mass-spectrometric evidence for 8498 proteins at 1% false discovery rate that make up about 26% of the total annotated protein-coding sequences in Rohu. Tissue-wise expression analysis was performed, and the presence of several biologically important proteins was also verified using a targeted proteomic approach. We identified the global post-translational modifications (PTMs) in terms of acetylation (N-terminus and lysine), methylation (N-terminus, lysine, and arginine), and phosphorylation (serine, threonine, and tyrosine) to present a comprehensive proteome resource. An interactive web-based portal has been developed for an overall landscape of protein expression across the studied tissues of Labeo rohita (www.fishprot.org). This draft proteome map of Labeo rohita would advance basic and applied research in aquaculture to meet the most critical challenge of providing food and nutritional security to an increasing world population.

Novel Technologies in Studying Brain Immune Response

Over the past few decades, the immune system, including both the adaptive and innate immune systems, proved to be essential and critical to brain damage and recovery in the pathogenesis of several diseases, opening a new avenue for developing new immunomodulatory therapies and novel treatments for many neurological diseases. However, due to the specificity and structural complexity of the central nervous system (CNS), and the limit of the related technologies, the biology of the immune response in the brain is still poorly understood. Here, we discuss the application of novel technologies in studying the brain immune response, including single-cell RNA analysis, cytometry by time-of-flight, and whole-genome transcriptomic and proteomic analysis. We believe that advancements in technology related to immune research will provide an optimistic future for brain repair.

Transcriptome assisted label free proteomics of hepatic tissue in response to both dietary restriction and compensatory growth in cattle

Compensatory growth (CG) is a naturally occurring phenomenon where, following a period of under nutrition, an animal exhibits accelerated growth upon re-alimentation. The objective was to identify and quantify hepatic proteins involved in the regulation of CG in cattle. Forty Holstein Friesian bulls were equally assigned to one of four groups. Groups; A1 and A2 had ad libitum access to feed for 125 days, groups R1 and R2 were feed restricted. Following this, R1 and A1 animals were slaughtered. Remaining animals (R2 and A2) were slaughtered following ad libitum feeding for a successive 55 days. At slaughter hepatic tissue samples were collected and label-free quantitative proteomics undertaken with spectra searched against a custom built transcriptome database specific to the animals in this study. 24 differentially abundant proteins were identified during CG (R2 vs. R1) including; PSPH, ASNS and GSTM1, which are involved in nutrient metabolism, immune response and cellular growth. Proteins involved in biochemical pathways related to nutrient metabolism were down-regulated during CG, indicating a possible adaptive response by the liver to a period of fluctuating nutrient availability. The livers ability to regulate its metabolic activity may have profound effects on the efficiency of whole body energy utilization during CG. SIGNIFICANCE: This study is the first to unravel the effect of compensatory growth on the hepatic proteome of cattle using transcriptome-assisted shot gun proteomics. Proteins identified as being affected by dietary restriction and subsequent expression of compensatory growth in this study may, following appropriate validation, contribute to the identification of functional genetic variants. Such information could be harnessed within the context of genomic selection in cattle breeding programs to identify animals with a greater genetic potential to undergo compensatory growth, thus increasing the profitability of the beef sector and accelerating genetic gain.

Comparative developmental toxicity of iron oxide nanoparticles and ferric chloride to zebrafish (Danio rerio) after static and semi-static exposure

Iron oxide nanoparticles (IONPs) are used in several medical and environmental applications, but their mechanism of action and hazardous effects to early developmental stages of fish remain unknown. Thus, the present study aimed to assess the developmental toxicity of citrate-functionalized IONPs (γ-Fe₂O₃ NPs), in comparison with its dissolved counterpart, in zebrafish (Danio rerio) after static and semi-static exposure. Embryos were exposed to environmental concentrations of both iron forms (0.3, 0.6, 1.25, 2.5, 5 and 10 mg L^-1) during 144 h, jointly with negative control group. The interaction and distribution of both Fe forms on the external chorion and larvae surface were measured, following by multiple biomarker assessment (mortality, hatching rate, neurotoxicity, cardiotoxicity, morphological alterations and 12 morphometrics parameters). Results showed that IONPs were mainly accumulated on the zebrafish chorion, and in the digestive system and liver of the larvae. Although the IONPs induced low embryotoxicity compared to iron ions in both exposure conditions, these nanomaterials induced sublethal effects, mainly cardiotoxic effects (reduced heartbeat, blood accumulation in the heart and pericardial edema). The semi-static exposure to both iron forms induced high embryotoxicity compared to static exposure, indicating that the nanotoxicity to early developmental stages of fish depends on the exposure system. This is the first study concerning the role of the exposure condition on the developmental toxicity of IONPs on fish species.

CCPRD: A Novel Analytical Framework for the Comprehensive Proteomic Reference Database Construction of NonModel Organisms

Protein reference databases are a critical part of producing efficient proteomic analyses. However, the method for constructing clean, efficient, and comprehensive protein reference databases of nonmodel organisms is lacking. Existing methods either do not have contamination control procedures, or these methods rely on a three-frame and/or six-frame translation that sharply increases the search space and the need for computational resources. Herein, we propose a framework for constructing a customized comprehensive proteomic reference database (CCPRD) from draft genomes and deep sequencing transcriptomes. Its effectiveness is demonstrated by incorporating the proteomes of nematocysts from endoparasitic cnidarian: myxozoans. By applying customized contamination removal procedures, contaminations in omic data were successfully identified and removed. This is an effective method that does not result in overdecontamination. This can be shown by comparing the CCPRD MS results with an artificially contaminated database and another database with removed contaminations in genomes and transcriptomes added back. CCPRD outperformed traditional frame-based methods by identifying 35.2-50.7% more peptides and 35.8-43.8% more proteins, with a maximum of 84.6% in size reduction. A BUSCO analysis showed that the CCPRD maintained a relatively high level of completeness compared to traditional methods. These results confirm the superiority of the CCPRD over existing methods in peptide and protein identification numbers, database size, and completeness. By providing a general framework for generating the reference database, the CCPRD, which does not need a high-quality genome, can potentially be applied to nonmodel organisms and significantly contribute to proteomic research.

CusVarDB: A tool for building customized sample-specific variant protein database from next-generation sequencing datasets

Cancer genome sequencing studies have revealed a number of variants in coding regions of several genes. Some of these coding variants play an important role in activating specific pathways that drive proliferation. Coding variants present on cancer cell surfaces by the major histocompatibility complex serve as neo-antigens and result in immune activation. The success of immune therapy in patients is attributed to neo-antigen load on cancer cell surfaces. However, which coding variants are expressed at the protein level can't be predicted based on genomic data. Complementing genomic data with proteomic data can potentially reveal coding variants that are expressed at the protein level. However, identification of variant peptides using mass spectrometry data is still a challenging task due to the lack of an appropriate tool that integrates genomic and proteomic data analysis pipelines. To overcome this problem, and for the ease of the biologists, we have developed a graphical user interface (GUI)-based tool called CusVarDB. We integrated variant calling pipeline to generate sample-specific variant protein database from next-generation sequencing datasets. We validated the tool with triple negative breast cancer cell line datasets and identified 423, 408, 386 and 361 variant peptides from BT474, MDMAB157, MFM223 and HCC38 datasets, respectively.

CusVarDB: A tool for building customized sample-specific variant protein database from next-generation sequencing datasets

Cancer genome sequencing studies have revealed a number of variants in coding regions of several genes. Some of these coding variants play an important role in activating specific pathways that drive proliferation. Coding variants present on cancer cell surfaces by the major histocompatibility complex serve as neo-antigens and result in immune activation. The success of immune therapy in patients is attributed to neo-antigen load on cancer cell surfaces. However, which coding variants are expressed at the protein level can't be predicted based on genomic data. Complementing genomic data with proteomic data can potentially reveal coding variants that are expressed at the protein level. However, identification of variant peptides using mass spectrometry data is still a challenging task due to the lack of an appropriate tool that integrates genomic and proteomic data analysis pipelines. To overcome this problem, and for the ease of the biologists, we have developed a graphical user interface (GUI)-based tool called CusVarDB. We integrated variant calling pipeline to generate sample-specific variant protein database from next-generation sequencing datasets. We validated the tool with triple negative breast cancer cell line datasets and identified 423, 408, 386 and 361 variant peptides from BT474, MDMAB157, MFM223 and HCC38 datasets, respectively.

Skin metabolome reveals immune responses in yellow drum Nibea albiflora to Cryptocaryon irritans infection

The yellow drum Nibea albiflora is less susceptible to Cryptocaryon irritans infection than is the case with other marine fishes such as Larimichthys crocea, Lateolabrax japonicus, and Pagrus major. To investigate further their resistance mechanism, we infected the N. albiflora with the C. irritans at a median lethal concentration of 2050 theronts/g fish. The skins of the infected and the uninfected fishes were sampled at 24 h and 72 h followed by an extensive analysis of metabolism. The study results revealed that there were 2694 potential metabolites. At 24 h post-infection, 12 metabolites were up-regulated and 17 were down-regulated whereas at 72 h post-infection, 22 metabolites were up-regulated and 26 were down-regulated. Pathway enrichment analysis shows that the differential enriched pathways were higher at 24 h with 22 categories and 58 subcategories (49 up, 9 down) than at 72 h whereby the differential enriched pathways were 6 categories and 8 subcategories (4 up, 4 down). In addition, the principal component analysis (PCA) plot shows that at 24 h the metabolites composition of infected group were separately clustered to uninfected group while at 72 h the metabolites composition in infected group were much closer to uninfected group. This indicated that C. irritans caused strong metabolic stress on the N. albiflora at 24 h and restoration of the dysregulated metabolic state took place at 72 h of infection. Also, at 72 h post infection a total of 17 compounds were identified as potential biomarkers. Furthermore, out of 2694 primary metabolites detected, 23 metabolites could be clearly identified and semi quantified with a known identification number and assigned into 66 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Most of the enriched KEGG pathways were mainly from metabolic pathway classes, including the metabolic pathway, biosynthesis of secondary metabolites, taurine and hypotaurine metabolism, purine metabolism, linoleic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis. Others were glyoxylate and dicarboxylate metabolism, glutathione metabolism, and alanine, aspartate, and glutamate metabolism. Moreover, out of the identified metabolites, only 6 metabolites were statistically differentially expressed, namely, L -glutamate (up-regulated) at 24 h was important for energy and precursor for other glutathiones and instruments of preventing oxidative injury; 15-hydroxy- eicosatetraenoic acid (15-HETE), (S)-(-)-2-Hydroxyisocaproic acid, and adenine (up-regulated) at 72 h were important for anti-inflammatory and immune responses during infection; others were delta-valerolactam and betaine which were down-regulated compared to uninfected group at 72 h, might be related to immure responses including stimulation of immune system such as production of antibodies. Our results therefore further advance our understanding on the immunological regulation of N. albiflora during immune response against infections as they indicated a strong relationship between skin metabolome and C. irritans infection.

The zebrafish embryotoxicity test (ZET) for nanotoxicity assessment: from morphological to molecular approach

Nanotechnology and use of nanomaterials (NMs) improve life quality, economic growth and environmental health. However, the increasing production and use of NMs in commercial products has led to concerns about their potential toxicity on human and environment health, as well as its toxicological classification and regulation. In this context, there is an urgent need to standardize and validate procedures for nanotoxicity testing. Since the zebrafish embryotoxicity test (ZET) has been indicated as a suitable approach for the toxicity assessment of traditional and emergent pollutants, the aim of this review is to summarize the existing literature on embryotoxic and teratogenic effects of NMs on zebrafish. In addition, morphological changes in zebrafish embryos induced by NMs were classified in four reaction models, allowing classification of the mode of action and toxicity of different types of NM. Revised data showed that the interaction and bioaccumulation of NMs on zebrafish embryos were associated to several toxic effects, while the detoxification process was limited. In general, NMs induced delayed hatching, circulatory changes, pigmentation and tegumentary alterations, musculoskeletal disorders and yolk sac alterations on zebrafish embryos. Recommendations for nanotoxicological tests are given, including guidance for future research. This review reinforces the use of the ZET as a suitable approach to assess the health risks of NM exposure.

Integrated Transcriptomic and Proteomic Analysis of Primary Human Umbilical Vein Endothelial Cells

Understanding the molecular profile of every human cell type is essential for understanding its role in normal physiology and disease. Technological advancements in DNA sequencing, mass spectrometry, and computational methods allow us to carry out multiomics analyses although such approaches are not routine yet. Human umbilical vein endothelial cells (HUVECs) are a widely used model system to study pathological and physiological processes associated with the cardiovascular system. In this study, next-generation sequencing and high-resolution mass spectrometry to profile the transcriptome and proteome of primary HUVECs is employed. Analysis of 145 million paired-end reads from next-generation sequencing confirmed expression of 12 186 protein-coding genes (FPKM ≥0.1), 439 novel long non-coding RNAs, and revealed 6089 novel isoforms that were not annotated in GENCODE. Proteomics analysis identifies 6477 proteins including confirmation of N-termini for 1091 proteins, isoforms for 149 proteins, and 1034 phosphosites. A database search to specifically identify other post-translational modifications provide evidence for a number of modification sites on 117 proteins which include ubiquitylation, lysine acetylation, and mono-, di- and tri-methylation events. Evidence for 11 "missing proteins," which are proteins for which there was insufficient or no protein level evidence, is provided. Peptides supporting missing protein and novel events are validated by comparison of MS/MS fragmentation patterns with synthetic peptides. Finally, 245 variant peptides derived from 207 expressed proteins in addition to alternate translational start sites for seven proteins and evidence for novel proteoforms for five proteins resulting from alternative splicing are identified. Overall, it is believed that the integrated approach employed in this study is widely applicable to study any primary cell type for deeper molecular characterization.

Proteomic Investigation of a Diseased Gorgonian Coral Indicates Disruption of Essential Cell Function and Investment in Inflammatory and Other Immune Processes

As scleractinian coral cover declines in the face of increased frequency in disease outbreaks, future reefs may become dominated by octocorals. Understanding octocoral disease responses and consequences is therefore necessary if we are to gain insight into the future of ecosystem services provided by coral reefs. In Florida, populations of the octocoral Eunicea calyculata infected with Eunicea black disease (EBD) were observed in the field in the fall of 2011. This disease was recognized by a stark, black pigmentation caused by heavy melanization. Histological preparations of E. calyculata infected with EBD demonstrated granular amoebocyte (GA) mobilization, melanin granules in much of the GA population, and the presence of fungal hyphae penetrating coral tissue. Previous transcriptomic analysis also identified immune trade-offs evidenced by increased immune investment at the expense of growth. Our investigation utilized proteogenomic techniques to reveal decreased investment in general cell signaling while increasing energy production for immune responses. Inflammation was also prominent in diseased E. calyculata and sheds light on factors driving the extreme phenotype observed with EBD. With disease outbreaks continuing to increase in frequency, our results highlight new targets within the cnidarian immune system and provide a framework for understanding transcriptomics in the context of an organismal disease phenotype and its protein expression.

A protein identification algorithm for tandem mass spectrometry by incorporating the abundance of mRNA into a binomial probability scoring model

Peptide-spectrum matches (PSM) scoring between the experimental and theoretical spectrum is a key step in the identification of proteins using mass spectrometry (MS)-based proteomics analyses. Efficient protein identification using MS/MS data remains a challenge. The strategy of using RNA-seq data increases the number of proteins identified by re-constructing the custom search database and integrating mRNA abundance into the false discovery rate of post-PSM. However, this process lacks an algorithm that can allow the incorporation of mRNA abundance into the key scoring model of PSM. Therefore, we developed a novel PSM scoring model, which incorporates mRNA abundance for improved peptide and protein identification. In the new algorithm, abundance information of mRNA was transformed to the prior probability of protein identification and integrated to re-score in PSM using the binomial probability distribution model. Compared with other algorithms using five MS/MS datasets, the results showed that the least improvement ratios of peptide and protein groups were 3.39%-9.79% and 0.48%-8.16% in different datasets (human, rat, zebrafish, yeast, and Arabidopsis thaliana). The new strategy offers an effective solution for MS-based identification of peptides and proteins. SIGNIFICANCE: The new algorithm identifies proteins by quantifying mRNA abundance (FPKM) and incorporating it into a scoring model for peptide-spectrum matches. It is important to improve peptide and protein identification from MS/MS datasets in proteomics research.

Proteome data of Anopheles stephensi salivary glands using high-resolution mass spectrometry analysis

The data article reports data of the proteins expressed in female Anopheles stephensi salivary glands. Proteomic data were acquired using high-resolution mass spectrometers - Orbitrap-Velos and Orbitrap-Elite. Samples derived from adult female A. stephensi salivary glands led to the identification of 4390 proteins. Mass spectrometry data were analyzed on Proteome Discoverer (Version 2.1) platform with Sequest and Mascot search engines. The identified proteins were analyzed for their Gene Ontology annotation, interaction network and their possible roles in vector-parasite interaction. The data provided here are related to our published article "Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes" (Prasad et al., 2017) [1].

Proteome data of Anopheles stephensi ovary using high-resolution mass spectrometry

This article contains data on the proteins expressed in the ovaries of Anopheles stephensi, a major vector of malaria in India. Data acquisition was performed using a high-resolution Orbitrap-Velos mass spectrometer. The acquired MS/MS data was searched against An. stephensi protein database comprising of 11,789 sequences. Overall, 4407 proteins were identified, functional analysis was performed for the identified proteins and a protein-protein interaction map predicted. The data provided here is also related to a published article - “Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes” (Prasad et al., 2017) [1].

Mapping Anopheles stephensi midgut proteome using high-resolution mass spectrometry

Anopheles stephensi Liston is one of the major vectors of malaria in urban areas of India. Midgut plays a central role in the vector life cycle and transmission of malaria. Because gene expression of An. stephensi midgut has not been investigated at protein level, an unbiased mass spectrometry-based proteomic analysis of midgut tissue was carried out. Midgut tissue proteins from female An. stephensi mosquitoes were extracted using 0.5% SDS and digested with trypsin using two complementary approaches, in-gel and in-solution digestion. Fractions were analysed on high-resolution mass spectrometer, which resulted in acquisition of 494,960 MS/MS spectra. The MS/MS spectra were searched against protein database comprising of known and predicted proteins reported in An. stephensi using Sequest and Mascot software. In all, 47,438 peptides were identified corresponding to 5,709 An. stephensi proteins. The identified proteins were functionally categorized based on their cellular localization, biological processes and molecular functions using Gene Ontology (GO) annotation. Several proteins identified in this data are known to mediate the interaction of the Plasmodium with vector midgut and also regulate parasite maturation inside the vector host. This study provides information about the protein composition in midgut tissue of female An. stephensi, which would be useful in understanding vector parasite interaction at molecular level and besides being useful in devising malaria transmission blocking strategies. The data of this study is related to the research article “Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes”.

Proteomic Analysis of the Human Olfactory Bulb

The importance of olfaction to human health and disease is often underappreciated. Olfactory dysfunction has been reported in association with a host of common complex diseases, including neurological diseases such as Alzheimer's disease and Parkinson's disease. For health, olfaction or the sense of smell is also important for most mammals, for optimal engagement with their environment. Indeed, animals have developed sophisticated olfactory systems to detect and interpret the rich information presented to them to assist in day-to-day activities such as locating food sources, differentiating food from poisons, identifying mates, promoting reproduction, avoiding predators, and averting death. In this context, the olfactory bulb is a vital component of the olfactory system receiving sensory information from the axons of the olfactory receptor neurons located in the nasal cavity and the first place that processes the olfactory information. We report in this study original observations on the human olfactory bulb proteome in healthy subjects, using a high-resolution mass spectrometry-based proteomic approach. We identified 7750 nonredundant proteins from human olfactory bulbs. Bioinformatics analysis of these proteins showed their involvement in biological processes associated with signal transduction, metabolism, transport, and olfaction. These new observations provide a crucial baseline molecular profile of the human olfactory bulb proteome, and should assist the future discovery of biomarker proteins and novel diagnostics associated with diseases characterized by olfactory dysfunction.

Proteome data of Anopheles stephensi hemolymph using high resolution mass spectrometry

The article provides insights into the protein expression in Anopheles stephensi hemolymph. We carried out data acquisition using a high-resolution LTQ-Orbitrap Velos mass spectrometer to identify the hemolymph proteins of An. stephensi. Experimentally derived mass spectrometry data was analyzed using Proteome Discoverer 2.1 software using two different search algorithms SEQUEST and MASCOT. A total of 1091 proteins were identified from the hemolymph. The identified proteins were categorized for their role in biological processes and molecular functions. The interactions between these proteins were predicted using STRING online tool. Relation can be drawn between the data provided in this study to the already published article “Integrating transcriptomics and proteomics data for accurate assembly and annotation of genomes” (Prasad et al., 2017) [1].

Chemical and genetic rescue of an ep300 knockdown model for Rubinstein Taybi Syndrome in zebrafish

EP300 is a member of the EP300/CBP family of lysine acetyltransferases (KATs) with multiple roles in development and physiology. Loss of EP300/CBP activity in humans causes a very rare congenital disorder called Rubinstein Taybi Syndrome (RSTS). The zebrafish genome has two co-orthologs of lysine acetyltransferase EP300 (KAT3B) in zebrafish viz. ep300a and ep300b. Chemical inhibition of Ep300 with C646, a competitive inhibitor and morpholino-based genetic knockdown of ep300a and ep300b cause defects in embryonic development reminiscent of the human RSTS syndrome. Remarkably, overexpression of Ep300a KAT domain results in near complete rescue of the jaw development defects, a characteristic feature of RSTS in human suggesting the dispensability of the protein-interaction and DNA-binding domains for at least some developmental roles of Ep300. We also perform a chemical screen and identify two inhibitors of deacetylases, CHIC35 and HDACi III, that can partially rescue the RSTS-like phenotypes. Thus, modeling rare human genetic disorders in zebrafish allows for functional understanding of the genes involved and can also yield small molecule candidates towards therapeutic goals.

Mosquito-Borne Diseases and Omics: Tissue-Restricted Expression and Alternative Splicing Revealed by Transcriptome Profiling of Anopheles stephensi

Malaria is one of the most debilitating mosquito-borne diseases with high global health burdens. While much of the research on malaria and mosquito-borne diseases is focused on Africa, Southeast Asia accounts for a sizable portion of the global burden of malaria. Moreover, about 50% of the Asian malaria incidence and deaths have been from India. A promising development in this context is that the completion of genome sequence of Anopheles stephensi, a major malaria vector in Asia, offers new opportunities for global health innovation, including the progress in deciphering the vectorial ability of this mosquito species at a molecular level. Moving forward, tissue-based expression profiling would be the next obvious step in understanding gene functions of An. stephensi. We report in this article, to the best of our knowledge, the first in-depth study on tissue-based transcriptomic profile of four important organs (midgut, Malpighian tubules, fat body, and ovary) of adult female An. stephensi mosquitoes. In all, we identified over 20,000 transcripts corresponding to more than 12,000 gene loci from these four tissues. We present and discuss the tissue-based expression profiles of majority of annotated transcripts in An. stephensi genome, and the dynamics of their alternative splicing in these tissues, in this study. The domain-based Gene Ontology analysis of the differentially expressed transcripts in each of the mosquito tissue indicated enrichment of transcripts with proteolytic activity in midgut; transporter activity in Malpighian tubules; cell cycle, DNA replication, and repair activities in ovaries; and oxidoreductase activities in fat body. Tissue-based study of transcript expression and gene functions markedly enhances our understanding of this important malaria vector, and in turn, offers rationales for further studies on vectorial ability and identification of novel molecular targets to intercept malaria transmission.

Evolution of complexity in the zebrafish synapse proteome

The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ∼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases.

Proteomics informed by transcriptomics for characterising active transposable elements and genome annotation in Aedes aegypti

BACKGROUND

Aedes aegypti is a vector for the (re-)emerging human pathogens dengue, chikungunya, yellow fever and Zika viruses. Almost half of the Ae. aegypti genome is comprised of transposable elements (TEs). Transposons have been linked to diverse cellular processes, including the establishment of viral persistence in insects, an essential step in the transmission of vector-borne viruses. However, up until now it has not been possible to study the overall proteome derived from an organism's mobile genetic elements, partly due to the highly divergent nature of TEs. Furthermore, as for many non-model organisms, incomplete genome annotation has hampered proteomic studies on Ae. aegypti.

RESULTS

We analysed the Ae. aegypti proteome using our new proteomics informed by transcriptomics (PIT) technique, which bypasses the need for genome annotation by identifying proteins through matched transcriptomic (rather than genomic) data. Our data vastly increase the number of experimentally confirmed Ae. aegypti proteins. The PIT analysis also identified hotspots of incomplete genome annotation, and showed that poor sequence and assembly quality do not explain all annotation gaps. Finally, in a proof-of-principle study, we developed criteria for the characterisation of proteomically active TEs. Protein expression did not correlate with a TE's genomic abundance at different levels of classification. Most notably, long terminal repeat (LTR) retrotransposons were markedly enriched compared to other elements. PIT was superior to 'conventional' proteomic approaches in both our transposon and genome annotation analyses.

CONCLUSIONS

We present the first proteomic characterisation of an organism's repertoire of mobile genetic elements, which will open new avenues of research into the function of transposon proteins in health and disease. Furthermore, our study provides a proof-of-concept that PIT can be used to evaluate a genome's annotation to guide annotation efforts which has the potential to improve the efficiency of annotation projects in non-model organisms. PIT therefore represents a valuable new tool to study the biology of the important vector species Ae. aegypti, including its role in transmitting emerging viruses of global public health concern.

Proteomics informed by transcriptomics for characterising active transposable elements and genome annotation in Aedes aegypti

BACKGROUND

Aedes aegypti is a vector for the (re-)emerging human pathogens dengue, chikungunya, yellow fever and Zika viruses. Almost half of the Ae. aegypti genome is comprised of transposable elements (TEs). Transposons have been linked to diverse cellular processes, including the establishment of viral persistence in insects, an essential step in the transmission of vector-borne viruses. However, up until now it has not been possible to study the overall proteome derived from an organism's mobile genetic elements, partly due to the highly divergent nature of TEs. Furthermore, as for many non-model organisms, incomplete genome annotation has hampered proteomic studies on Ae. aegypti.

RESULTS

We analysed the Ae. aegypti proteome using our new proteomics informed by transcriptomics (PIT) technique, which bypasses the need for genome annotation by identifying proteins through matched transcriptomic (rather than genomic) data. Our data vastly increase the number of experimentally confirmed Ae. aegypti proteins. The PIT analysis also identified hotspots of incomplete genome annotation, and showed that poor sequence and assembly quality do not explain all annotation gaps. Finally, in a proof-of-principle study, we developed criteria for the characterisation of proteomically active TEs. Protein expression did not correlate with a TE's genomic abundance at different levels of classification. Most notably, long terminal repeat (LTR) retrotransposons were markedly enriched compared to other elements. PIT was superior to 'conventional' proteomic approaches in both our transposon and genome annotation analyses.

CONCLUSIONS

We present the first proteomic characterisation of an organism's repertoire of mobile genetic elements, which will open new avenues of research into the function of transposon proteins in health and disease. Furthermore, our study provides a proof-of-concept that PIT can be used to evaluate a genome's annotation to guide annotation efforts which has the potential to improve the efficiency of annotation projects in non-model organisms. PIT therefore represents a valuable new tool to study the biology of the important vector species Ae. aegypti, including its role in transmitting emerging viruses of global public health concern.

Proteomics informed by transcriptomics for characterising active transposable elements and genome annotation in Aedes aegypti

BACKGROUND

Aedes aegypti is a vector for the (re-)emerging human pathogens dengue, chikungunya, yellow fever and Zika viruses. Almost half of the Ae. aegypti genome is comprised of transposable elements (TEs). Transposons have been linked to diverse cellular processes, including the establishment of viral persistence in insects, an essential step in the transmission of vector-borne viruses. However, up until now it has not been possible to study the overall proteome derived from an organism's mobile genetic elements, partly due to the highly divergent nature of TEs. Furthermore, as for many non-model organisms, incomplete genome annotation has hampered proteomic studies on Ae. aegypti.

RESULTS

We analysed the Ae. aegypti proteome using our new proteomics informed by transcriptomics (PIT) technique, which bypasses the need for genome annotation by identifying proteins through matched transcriptomic (rather than genomic) data. Our data vastly increase the number of experimentally confirmed Ae. aegypti proteins. The PIT analysis also identified hotspots of incomplete genome annotation, and showed that poor sequence and assembly quality do not explain all annotation gaps. Finally, in a proof-of-principle study, we developed criteria for the characterisation of proteomically active TEs. Protein expression did not correlate with a TE's genomic abundance at different levels of classification. Most notably, long terminal repeat (LTR) retrotransposons were markedly enriched compared to other elements. PIT was superior to 'conventional' proteomic approaches in both our transposon and genome annotation analyses.

CONCLUSIONS

We present the first proteomic characterisation of an organism's repertoire of mobile genetic elements, which will open new avenues of research into the function of transposon proteins in health and disease. Furthermore, our study provides a proof-of-concept that PIT can be used to evaluate a genome's annotation to guide annotation efforts which has the potential to improve the efficiency of annotation projects in non-model organisms. PIT therefore represents a valuable new tool to study the biology of the important vector species Ae. aegypti, including its role in transmitting emerging viruses of global public health concern.

Both Male-Biased and Female-Biased Genes Evolve Faster in Fish Genomes

Males and females often display extensive phenotypic differences, and many of these sexual dimorphisms are thought to result from differences between males and females in expression of genes present in both sexes. Sex-biased genes have been shown to exhibit accelerated rates of evolution in a wide array of species, however the cause of this remains enigmatic. In this study, we investigate the extent and evolutionary dynamics of sex-biased gene expression in zebrafish. Our results indicate that both male-biased genes and female-biased genes exhibit accelerated evolution at the protein level. In order to differentiate between adaptive and nonadaptive causes, we tested for codon usage bias and signatures of different selective regimes in our sequence data. Our results show that both male- and female-biased genes show signatures consistent with adaptive evolution. In order to test the generality of our findings across fish, we also analyzed publicly available data on sticklebacks, and found results consistent with our findings in zebrafish.

Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted “noncoding RNAs” to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes.

Pathway Analysis of Proteomics Profiles in Rabies Infection: Towards Future Biomarkers?

Rabies is a zoonotic viral disease that invariably leads to fatal encephalitis, which can be prevented provided post-exposure prophylaxis is initiated timely. Ante-mortem diagnostic tests are inconclusive, and rabies is nontreatable once the clinical signs appear. A large number of host factors are responsible for the altered neuronal functions observed in rabies; however their precise role remains uninvestigated. We therefore used two-dimensional electrophoresis and mass spectrometry analysis to identify differentially expressed host proteins in an experimental murine model of rabies. We identified 143 proteins corresponding to 45 differentially expressed spots (p < 0.05) in neuronal tissues of Swiss albino mice in response to infection with neurovirulent rabies strains. Time series analyses revealed that a majority of the alterations occur at 4 to 6 days post infection, in particular affecting the host's cytoskeletal architecture. Extensive pathway analysis and protein interaction studies using the bioinformatic tools such as Ingenuity Pathway Analysis and STRING revealed novel pathways and molecules (e.g., protein ubiquitination) unexplored hitherto. Further activation/inhibition studies of these pathway molecular leads would be relevant to identify novel biomarkers and mechanism-based therapeutics for rabies, a disease that continues to severely impact global health.

Integrating transcriptome and proteome profiling: Strategies and applications

Discovering the gene expression signature associated with a cellular state is one of the basic quests in majority of biological studies. For most of the clinical and cellular manifestations, these molecular differences may be exhibited across multiple layers of gene regulation like genomic variations, gene expression, protein translation and post-translational modifications. These system wide variations are dynamic in nature and their crosstalk is overwhelmingly complex, thus analyzing them separately may not be very informative. This necessitates the integrative analysis of such multiple layers of information to understand the interplay of the individual components of the biological system. Recent developments in high throughput RNA sequencing and mass spectrometric (MS) technologies to probe transcripts and proteins made these as preferred methods for understanding global gene regulation. Subsequently, improvements in "big-data" analysis techniques enable novel conclusions to be drawn from integrative transcriptomic-proteomic analysis. The unified analyses of both these data types have been rewarding for several biological objectives like improving genome annotation, predicting RNA-protein quantities, deciphering gene regulations, discovering disease markers and drug targets. There are different ways in which transcriptomics and proteomics data can be integrated; each aiming for different research objectives. Here, we review various studies, approaches and computational tools targeted for integrative analysis of these two high-throughput omics methods.

Rescue of neural crest-derived phenotypes in a zebrafish CHARGE model by Sox10 downregulation

CHD7 mutations are implicated in a majority of cases of the congenital disorder, CHARGE syndrome. CHARGE, an autosomal dominant syndrome, is known to affect multiple tissues including eye, heart, ear, craniofacial nerves and skeleton and genital organs. Using a morpholino-antisense-oligonucleotide-based zebrafish model for CHARGE syndrome, we uncover a complex spectrum of abnormalities in the neural crest and the crest-derived cell types. We report for the first time, defects in myelinating Schwann cells, enteric neurons and pigment cells in a CHARGE model. We also observe defects in the specification of peripheral neurons and the craniofacial skeleton as previously reported. Chd7 morphants have impaired migration of neural crest cells and deregulation of sox10 expression from the early stages. Knocking down Sox10 in the zebrafish CHARGE model rescued the defects in Schwann cells and craniofacial cartilage. Our zebrafish CHARGE model thus reveals important regulatory roles for Chd7 at multiple points of neural crest development viz., migration, fate choice and differentiation and we suggest that sox10 deregulation is an important driver of the neural crest-derived aspects of Chd7 dependent CHARGE syndrome.

A detailed proteomic profiling of plasma membrane from zebrafish brain

Zebrafish (Danio rerio) is a well-established model organism in developmental biology and disease modeling. In recent years, an increasing amount of studies used zebrafish to analyze the genetic changes underlying various neurological disorders. The brain plasma membrane proteome represents the major subsets of signaling proteins and promising drug targets, but is often understudied due to traditional experimental difficulties including problems with solubility, detergent removal, or low abundance. Here, we report a comprehensive dataset of the proteins identified in the enriched plasma membrane of the zebrafish brain by applying sequential trypsin/chymotrypsin digestion with multidimensional LC-MS/MS. A total number of 97 017 peptide groups corresponding to 9201 proteins were identified. These were annotated in various molecular functions or neurological disorders. The dataset of the current study provides a useful data source for further utilizing zebrafish in basic and clinical neuroscience.

Proteogenomic Methods to Improve Genome Annotation

Annotation of protein coding genes in sequenced genomes has been routinely carried out using gene prediction programs guided by available transcript data. The advent of mass spectrometry has enabled the identification of proteins in a high-throughput manner. In addition to searching proteins annotated in public databases, mass spectrometry data can also be searched against conceptually translated genome as well as transcriptome to identify novel protein coding regions. This proteogenomics approach has resulted in the identification of novel protein coding regions in both prokaryotic and eukaryotic genomes. These studies have also revealed that some of the annotated noncoding RNAs and pseudogenes code for proteins. This approach is likely to become a part of most genome annotation workflows in the future. Here we describe a general methodology and approach that can be used for proteogenomics.

MSProGene: integrative proteogenomics beyond six-frames and single nucleotide polymorphisms

Summary: Ongoing advances in high-throughput technologies have facilitated accurate proteomic measurements and provide a wealth of information on genomic and transcript level. In proteogenomics, this multi-omics data is combined to analyze unannotated organisms and to allow more accurate sample-specific predictions. Existing analysis methods still mainly depend on six-frame translations or reference protein databases that are extended by transcriptomic information or known single nucleotide polymorphisms (SNPs). However, six-frames introduce an artificial sixfold increase of the target database and SNP integration requires a suitable database summarizing results from previous experiments. We overcome these limitations by introducing MSProGene, a new method for integrative proteogenomic analysis based on customized RNA-Seq driven transcript databases. MSProGene is independent from existing reference databases or annotated SNPs and avoids large six-frame translated databases by constructing sample-specific transcripts. In addition, it creates a network combining RNA-Seq and peptide information that is optimized by a maximum-flow algorithm. It thereby also allows resolving the ambiguity of shared peptides for protein inference. We applied MSProGene on three datasets and show that it facilitates a database-independent reliable yet accurate prediction on gene and protein level and additionally identifies novel genes.

Availability and implementation: MSProGene is written in Java and Python. It is open source and available at http://sourceforge.net/projects/msprogene/.

Contact:renardb@rki.de

A proteomic map of the unsequenced kala-azar vector Phlebotomus papatasi using cell line

The debilitating disease kala-azar or visceral leishmaniasis is caused by the kinetoplastid protozoan parasite Leishmania donovani. The parasite is transmitted by the hematophagous sand fly vector of the genus Phlebotomus in the old world and Lutzomyia in the new world. The predominant Phlebotomine species associated with the transmission of kala-azar are Phlebotomus papatasi and Phlebotomus argentipes. Understanding the molecular interaction of the sand fly and Leishmania, during the development of parasite within the sand fly gut is crucial to the understanding of the parasite life cycle. The complete genome sequences of sand flies (Phlebotomus and Lutzomyia) are currently not available and this hinders identification of proteins in the sand fly vector. The current study utilizes a three frame translated transcriptomic data of P. papatasi in the absence of genomic sequences to analyze the mass spectrometry data of P. papatasi cell line using a proteogenomic approach. Additionally, we have carried out the proteogenomic analysis of P. papatasi by comparative homology-based searches using related sequenced dipteran protein data. This study resulted in the identification of 1313 proteins from P. papatasi based on homology. Our study demonstrates the power of proteogenomic approaches in mapping the proteomes of unsequenced organisms.

Extensive identification and analysis of conserved small ORFs in animals

Background

There is increasing evidence that transcripts or transcript regions annotated as non-coding can harbor functional short open reading frames (sORFs). Loss-of-function experiments have identified essential developmental or physiological roles for a few of the encoded peptides (micropeptides), but genome-wide experimental or computational identification of functional sORFs remains challenging.

Results

Here, we expand our previously developed method and present results of an integrated computational pipeline for the identification of conserved sORFs in human, mouse, zebrafish, fruit fly, and the nematode C. elegans. Isolating specific conservation signatures indicative of purifying selection on amino acid (rather than nucleotide) sequence, we identify about 2,000 novel small ORFs located in the untranslated regions of canonical mRNAs or on transcripts annotated as non-coding. Predicted sORFs show stronger conservation signatures than those identified in previous studies and are sometimes conserved over large evolutionary distances. The encoded peptides have little homology to known proteins and are enriched in disordered regions and short linear interaction motifs. Published ribosome profiling data indicate translation of more than 100 novel sORFs, and mass spectrometry data provide evidence for more than 70 novel candidates.

Conclusions

Taken together, we identify hundreds of previously unknown conserved sORFs in major model organisms. Our computational analyses and integration with experimental data show that these sORFs are expressed, often translated, and sometimes widely conserved, in some cases even between vertebrates and invertebrates. We thus provide an integrated resource of putatively functional micropeptides for functional validation in vivo.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0742-x) contains supplementary material, which is available to authorized users.

Methods for distinguishing between protein-coding and long noncoding RNAs and the elusive biological purpose of translation of long noncoding RNAs

Long noncoding RNAs (lncRNAs) are a diverse class of RNAs with increasingly appreciated functions in vertebrates, yet much of their biology remains poorly understood. In particular, it is unclear to what extent the current catalog of over 10,000 annotated lncRNAs is indeed devoid of genes coding for proteins. Here we review the available computational and experimental schemes for distinguishing between coding and noncoding transcripts and assess the conclusions from their recent genome-wide applications. We conclude that the model most consistent with the available data is that a large number of mammalian lncRNAs undergo translation, but only a very small minority of such translation events results in stable and functional peptides. The outcomes of the majority of the translation events and their potential biological purposes remain an intriguing topic for future investigation. This article is part of a Special Issue entitled: Clues to long noncoding RNA taxonomy1, edited by Dr. Tetsuro Hirose and Dr. Shinichi Nakagawa.

Proteogenomic Analysis of Trichophyton rubrum Aided by RNA Sequencing

Infections caused by dermatophytes, Trichophyton rubrum in particular, are among the most common diseases in humans. In this study, we present a proteogenomic analysis of T. rubrum based on whole-genome proteomics and RNA-Seq studies. We confirmed 4291 expressed proteins in T. rubrum and validated their annotated gene structures based on 35 874 supporting peptides. In addition, we identified 323 novel peptides (not present in the current annotated protein database of T. rubrum) that can be used to enhance current T. rubrum annotations. A total of 104 predicted genes supported by novel peptides were identified, and 127 gene models suggested by the novel peptides that conflicted with existing annotations were manually assigned based on transcriptomic evidence. RNA-Seq confirmed the validity of 95% of the total peptides. Our study provides evidence that confirms and improves the genome annotation of T. rubrum and represents the first survey of T. rubrum genome annotations based on experimental evidence. Additionally, our integrated proteomics and multisourced transcriptomics approach provides stronger evidence for annotation refinement than proteomic data alone, which helps to address the dilemma of one-hit wonders (uncertainties supported by only one peptide).