Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms

Comprehensive in silico analyses of fifty-one uncharacterized proteins from Vibrio cholerae

Due to the rise of multidrug-resistant strains of Vibrio cholerae and the recent cholera outbreaks in African and Asian nations, it is imperative to identify novel therapeutic targets and possible vaccine candidates. In this regard, this work primarily aims to identify and characterize new antigenic molecules using comparative RNA sequencing data and label-free proteomics data, carried out with essential GTPase cgtA knockdown and wild-type strain of V. cholerae. We identified hitherto 51 characterized proteins from high-throughput RNA-sequencing and proteomics data. This work involved the assessment of their physicochemical characteristics, subcellular localization, solubility, structures, and functional annotations. In addition, the immunoinformatic and reverse vaccinology technique was used to find new vaccine targets with high antigenicity, low allergenicity, and low toxicity profiles. Among the 51 proteins, 24 were selected based on their immunogenic profiles to identify B/T-cell epitopes. In addition, 20 prospective therapeutic targets were identified using virulence predictions and related investigations. Furthermore, two proteins, UniProt ID- Q9KRD2 and Q9KU58, with molecular weight of 92kDa and 12kDa, respectively, were chosen for cloning and expression towards in vitro biochemical characterization based on their range of expression patterns, high antigenic, low allergenic, and low toxicity properties. In conclusion, we believe that this study will reveal new facets and avenues for drug discovery and put us a step forward toward novel therapeutic interventions against the deadly disease of cholera.

Identification and Functional Annotation of Hypothetical Proteins of Pan-Drug-Resistant Providencia rettgeri Strain MRSN845308 Toward Designing Antimicrobial Drug Targets

Providencia rettgeri has increasingly been responsible for several infections, including urinary tract, post-burn wounds, neonatal sepsis, and others. The emergence of drug-resistant isolates of P rettgeri, accompanied by intrinsic and acquired antibiotic resistance, has exacerbated the challenge of treating such infections, necessitating the development of novel therapeutics. Hypothetical proteins (HPs) form a major portion of cellular proteins and can be targeted by these novel therapeutics. In this study, 410 HPs from a pan-drug-resistant (PDR) P rettgeri strain (MRSN845308) were functionally annotated and characterized by physicochemical properties, localization, virulence, essentiality, druggability, and functionality. Among 410 HPs, the VirulentPred 2.0 tool and VICMpred combinedly predicted 33 HPs as virulent, whereas 48 HPs were highly interacting proteins based on the STRING v12 database. BlastKOALA and eggNOG-mapper v2.1.12 predicted 13 HPs involved in several metabolic pathways like Riboflavin metabolism and Lipopolysaccharide biosynthesis. Overall, 83 HPs were selected as primary drug targets; however, only 80 remained after nonhomology searching and essentiality analysis. In addition, all were detected as novel drug targets according to DrugBank 5.1.12. Considering the potential of membrane and extracellular proteins, 29 HPs (extracellular, outer, and inner membrane) were selected based on the combined prediction from PSORTb v3.0.3, CELLO v.2.5, BUSCA, SOSUIGramN, and PSLpred. According to the prevalence of those HPs in different strains of P rettgeri sequences in National Center for Biotechnology Information Identical Protein Groups (NCBI-IPG), 5 HPs were selected as final drug targets. In addition, 5 other HPs annotated as transporter proteins were also added to the list. As no crystal structures of our targets are present, 3-dimensional structures of selected HPs were predicted by the AlphaFold Server powered by AlphaFold 3. Our findings might facilitate a better understanding of the mechanism of virulence and pathogenesis, and up-to-date annotations can make uncharacterized HPs easy to identify as targets for novel therapeutics.

Sargasso Sea Vibrio bacteria: Underexplored potential pathovars in a perturbed habitat

We fully sequenced the genomes of 16 Vibrio cultivars isolated from eel larvae, plastic marine debris (PMD), the pelagic brown macroalga Sargassum, and seawater samples collected from the Caribbean and Sargasso Seas of the North Atlantic Ocean. Annotation and mapping of these 16 bacterial genome sequences to a PMD-derived Vibrio metagenome-assembled genome created for this study showcased vertebrate pathogen genes closely-related to cholera and non-cholera pathovars. Phenotype testing of cultivars confirmed rapid biofilm formation, hemolytic, and lipophospholytic activities, consistent with pathogenic potential. Our study illustrates that open ocean vibrios represent a heretofore undescribed group of microbes, some representing potential new species, possessing an amalgam of pathogenic and low nutrient acquisition genes, reflecting their pelagic habitat and the substrates and hosts they colonize.

Genome-wide and constrained ordination-based analyses of EC code data support reclassification of the species of Massilia La Scola et al. 2000 into Telluria Bowman et al. 1993, Mokoshia gen. nov. and Zemynaea gen. nov

Based on genome-wide data, Massilia species belonging to the clade including Telluria mixta LMG 11547T should be entirely transferred to the genus Telluria owing to the nomenclatural priority of the type species Telluria mixta. This results in the transfer of 35 Massilia species to the genus Telluria. The presented data also supports the creation of two new genera since peripherally branching Massilia species are distinct from Telluria and other related genera. It is proposed that 13 Massilia species are transferred to Mokoshia gen. nov. with the type species designated Mokoshia eurypsychrophila comb. nov. The species Massilia arenosa is proposed to belong to the genus Zemynaea gen. nov. as the type species Zemynaea arenosa comb. nov. The genome-wide analysis was well supported by canonical ordination analysis of Enzyme Commission (EC) codes annotated from genomes via pannzer2. This new approach was performed to assess the conclusions of the genome-based data and reduce possible ambiguity in the taxonomic decision making. Cross-validation of EC code data compared within canonical plots validated the reclassifications and correctly visualized the expected genus-level taxonomic relationships. The approach is complementary to genome-wide methodology and could be used for testing sequence alignment based data across genetically related genera. In addition to the proposed broader reclassifications, invalidly described species 'Massilia antibiotica', 'Massilia aromaticivorans', 'Massilia cellulosiltytica' and 'Massilia humi' are described as Telluria antibiotica sp. nov., Telluria aromaticivorans sp. nov., Telluria cellulosilytica sp. nov. and Pseudoduganella humi sp. nov., respectively. In addition, Telluria chitinolytica is reclassified as Pseudoduganella chitinolytica comb. nov. The use of combined genome-wide and annotation descriptors compared using canonical ordination clarifies the taxonomy of Telluria and its sibling genera and provides another way to evaluate complex taxonomic data.

Gene Co-Expression Network Analysis Reveals Key Regulatory Genes in Metisa plana Hormone Pathways

Metisa plana Walker (Lepidoptera: Psychidae) is a major oil palm pest species distributed across Southeast Asia. M. plana outbreaks are regarded as serious ongoing threats to the oil palm industry due to their ability to significantly reduce fruit yield and subsequent productivity. Currently, conventional pesticide overuses may harm non-target organisms and severely pollute the environment. This study aims to identify key regulatory genes involved in hormone pathways during the third instar larvae stage of M. plana gene co-expression network analysis. A weighted gene co-expression network analysis (WGCNA) was conducted on the M. plana transcriptomes to construct a gene co-expression network. The transcriptome datasets were obtained from different development stages of M. plana, i.e., egg, third instar larvae, pupa, and adult. The network was clustered using the DPClusO algorithm and validated using Fisher's exact test and receiver operating characteristic (ROC) analysis. The clustering analysis was performed on the network and 20 potential regulatory genes (such as MTA1-like, Nub, Grn, and Usp) were identified from ten top-most significant clusters. Pathway enrichment analysis was performed to identify hormone signalling pathways and these pathways were identified, i.e., hormone-mediated signalling, steroid hormone-mediated signalling, and intracellular steroid hormone receptor signalling as well as six regulatory genes Hnf4, Hr4, MED14, Usp, Tai, and Trr. These key regulatory genes have a potential as important targets in future upstream applications and validation studies in the development of biorational pesticides against M. plana and the RNA interference (RNAi) gene silencing method.

Latent generative landscapes as maps of functional diversity in protein sequence space

Variational autoencoders are unsupervised learning models with generative capabilities, when applied to protein data, they classify sequences by phylogeny and generate de novo sequences which preserve statistical properties of protein composition. While previous studies focus on clustering and generative features, here, we evaluate the underlying latent manifold in which sequence information is embedded. To investigate properties of the latent manifold, we utilize direct coupling analysis and a Potts Hamiltonian model to construct a latent generative landscape. We showcase how this landscape captures phylogenetic groupings, functional and fitness properties of several systems including Globins, β-lactamases, ion channels, and transcription factors. We provide support on how the landscape helps us understand the effects of sequence variability observed in experimental data and provides insights on directed and natural protein evolution. We propose that combining generative properties and functional predictive power of variational autoencoders and coevolutionary analysis could be beneficial in applications for protein engineering and design.

Analysis of amplification and association polymorphisms in the bovine beta-defensin 129 (BBD129) gene revealed its function in bull fertility

β-defensins are adsorbable on the sperm surface in the male reproductive tract (MRT) and enhance sperm functional characteristics. The beta-defensin 129 (DEFB129) antimicrobial peptide is involved in sperm maturation, motility, and fertilization. However, its role in bovine fertility has not been well investigated. This study examines the relationship between the bovine BBD129 gene and Bos indicus x Bos taurus bull fertility. The complete coding sequence of BBD129 mRNA was identified by RNA Ligase Mediated-Rapid Amplification of cDNA End (RLM-RACE) and Sanger sequencing methodologies. It consisted of 582 nucleotides (nts) including 5' untranslated region (UTR) (46nts) and 3'UTR (23nts). It conserves all beta-defensin-like features. The expression level of BBD129 was checked by RT-qPCR and maximal expression was detected in the corpus-epididymis region compared to other parts of MRT. Polymorphism in BBD129 was also confirmed by Sanger sequencing of 254 clones from 5 high fertile (HF) and 6 low fertile (LF) bulls at two positions, 169 T > G and 329A > G, which change the S57A and N110S in the protein sequence respectively. These two mutations give rise to four types of BBD129 haplotypes. The non-mutated TA-BBD129 (169 T/329A) haplotype was substantially more prevalent among high-fertile bulls (P < 0.005), while the double-site mutated GG-BBD129 (169 T > G/329A > G) haplotype was significantly more prevalent among low-fertile bulls (P < 0.005). The in silico analysis confirmed that the polymorphism in BBD129 results in changes in mRNA secondary structure, protein conformations, protein stability, extracellular-surface availability, post-translational modifications (O-glycosylation and phosphorylation), and affects antibacterial and immunomodulatory capabilities. In conclusion, the mRNA expression of BBD129 in the MRT indicates its region-specific dynamics in sperm maturation. BBD129 polymorphisms were identified as the deciding elements accountable for the changed proteins with impaired functionality, contributing to cross-bred bulls' poor fertility.

Neural Network and Random Forest Models in Protein Function Prediction

Over the past decade, the demand for automated protein function prediction has increased due to the volume of newly sequenced proteins. In this paper, we address the function prediction task by developing an ensemble system automatically assigning Gene Ontology (GO) terms to the given input protein sequence. We develop an ensemble system which combines the GO predictions made by random forest (RF) and neural network (NN) classifiers. Both RF and NN models rely on features derived from BLAST sequence alignments, taxonomy and protein signature analysis tools. In addition, we report on experiments with a NN model that directly analyzes the amino acid sequence as its sole input, using a convolutional layer. The Swiss-Prot database is used as the training and evaluation data. In the CAFA3 evaluation, which relies on experimental verification of the functional predictions, our submitted ensemble model demonstrates competitive performance ranking among top-10 best-performing systems out of over 100 submitted systems. In this paper, we evaluate and further improve the CAFA3-submitted system. Our machine learning models together with the data pre-processing and feature generation tools are publicly available as an open source software at https://github.com/TurkuNLP/CAFA3.

Evolution of Protein Functional Annotation: Text Mining Study

Within the Human Proteome Project initiative framework for creating functional annotations of uPE1 proteins, the neXt-CP50 Challenge was launched in 2018. In analogy with the missing-protein challenge, each command deciphers the functional features of the proteins in the chromosome-centric mode. However, the neXt-CP50 Challenge is more complicated than the missing-protein challenge: the approaches and methods for solving the problem are clear, but neither the concept of protein function nor specific experimental and/or bioinformatics protocols have been standardized to address it. We proposed using a retrospective analysis of the key HPP repository, the neXtProt database, to identify the most frequently used experimental and bioinformatic methods for analyzing protein functions, and the dynamics of accumulation of functional annotations. It has been shown that the dynamics of the increase in the number of proteins with known functions are greater than the progress made in the experimental confirmation of the existence of questionable proteins in the framework of the missing-protein challenge. At the same time, the functional annotation is based on the guilty-by-association postulate, according to which, based on large-scale experiments on API-MS and Y2H, proteins with unknown functions are most likely mapped through “handshakes” to biochemical processes.

Wei2GO: weighted sequence similarity-based protein function prediction

BACKGROUND

Protein function prediction is an important part of bioinformatics and genomics studies. There are many different predictors available, however most of these are in the form of web-servers instead of open-source locally installable versions. Such local versions are necessary to perform large scale genomics studies due to the presence of limitations imposed by web servers such as queues, prediction speed, and updatability of databases.

METHODS

This paper describes Wei2GO: a weighted sequence similarity and python-based open-source protein function prediction software. It uses DIAMOND and HMMScan sequence alignment searches against the UniProtKB and Pfam databases respectively, transfers Gene Ontology terms from the reference protein to the query protein, and uses a weighing algorithm to calculate a score for the Gene Ontology annotations.

RESULTS

Wei2GO is compared against the Argot2 and Argot2.5 web servers, which use a similar concept, and DeepGOPlus which acts as a reference. Wei2GO shows an increase in performance according to precision and recall curves, Fmax scores, and Smin scores for biological process and molecular function ontologies. Computational time compared to Argot2 and Argot2.5 is decreased from several hours to several minutes.

AVAILABILITY

Wei2GO is written in Python 3, and can be found at https://gitlab.com/mreijnders/Wei2GO.

Integrated bioinformatics based subtractive genomics approach to decipher the therapeutic function of hypothetical proteins from Salmonella typhi XDR H-58 strain

Purpose

The efficacy of drugs against Salmonella infection have compromised due to emerging XDR H58 strain. There is a dire need to find novel antimicrobial drug targets as well as drug candidates to cure by the XDR strain of Salmonella. It is observed that the complete genome sequence of the XDR H58 strain contains a large number of hypothetical proteins with unknown cellular and biological functions. Hence, it is indispensable to annotate these proteins functionally as well as structurally to identify novel drug targets.

Methods

In the current study, a comparative genomics and proteomics based approach was applied to find the novel drug targets in XDR strain while comparing the MDR and NR strains of Salmonella typhi.

Results

The characterization of ~ 350 hypothetical proteins were performed through determination of their physio-chemical properties, sub-cellular localization, functional annotation, and structure-based studies. As a result, only five proteins were prioritized as essential, druggable, and virulent proteins. Moreover, only one protein i.e. WP_000916613.1 was functionally annotated with high confidence and subjected to further structure-based analysis.

Conclusion

The current study presents a hypothetical protein from the XDR S. typhi proteome as a potential pharmacological target against which novel therapeutic candidates may be predicted. The outcome of the current study may lead to formulate a general set of pipelines for better understanding of the role of hypothetical proteins in pathogenesis of not only Salmonella but also for other pathogens.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10529-021-03219-6.

Transcriptomic Analysis of Quinoa Reveals a Group of Germin-Like Proteins Induced by Trichoderma

Symbiotic strains of fungi in the genus Trichoderma affect growth and pathogen resistance of many plant species, but the interaction is not known in molecular detail. Here we describe the transcriptomic response of two cultivars of the crop Chenopodium quinoa to axenic co-cultivation with Trichoderma harzianum BOL-12 and Trichoderma afroharzianum T22. The response of C. quinoa roots to BOL-12 and T22 in the early phases of interaction was studied by RNA sequencing and RT-qPCR verification. Interaction with the two fungal strains induced partially overlapping gene expression responses. Comparing the two plant genotypes, a broad spectrum of putative quinoa defense genes were found activated in the cultivar Kurmi but not in the Real cultivar. In cultivar Kurmi, relatively small effects were observed for classical pathogen response pathways but instead a C. quinoa-specific clade of germin-like genes were activated. Germin-like genes were found to be more rapidly induced in cultivar Kurmi as compared to Real. The same germin-like genes were found to also be upregulated systemically in the leaves. No strong correlation was observed between any of the known hormone-mediated defense response pathways and any of the quinoa-Trichoderma interactions. The differences in responses are relevant for the capabilities of applying Trichoderma agents for crop protection of different cultivars of C. quinoa.

An Oil Hyper-Accumulator Mutant Highlights Peroxisomal ATP Import as a Regulatory Step for Fatty Acid Metabolism in Aurantiochytrium limacinum

Thraustochytrids are marine protists that naturally accumulate triacylglycerol with long chains of polyunsaturated fatty acids, such as ω3-docosahexaenoic acid (DHA). They represent a sustainable response to the increasing demand for these "essential" fatty acids (FAs). Following an attempt to transform a strain of Aurantiochytrium limacinum, we serendipitously isolated a clone that did not incorporate any recombinant DNA but contained two to three times more DHA than the original strain. Metabolic analyses indicated a deficit in FA catabolism. However, whole transcriptome analysis did not show down-regulation of genes involved in FA catabolism. Genome sequencing revealed extensive DNA deletion in one allele encoding a putative peroxisomal adenylate transporter. Phylogenetic analyses and yeast complementation experiments confirmed the gene as a peroxisomal adenylate nucleotide transporter (AlANT1), homologous to yeast ScANT1 and plant peroxisomal adenylate nucleotide carrier AtPNC genes. In yeast and plants, a deletion of the peroxisomal adenylate transporter inhibits FA breakdown and induces FA accumulation, a phenotype similar to that described here. In response to this metabolic event, several compensatory mechanisms were observed. In particular, genes involved in FA biosynthesis were upregulated, also contributing to the high FA accumulation. These results support AlANT1 as a promising target for enhancing DHA production in Thraustochytrids.

Viviparity and habitat restrictions may influence the evolution of male reproductive genes in tsetse fly (Glossina) species

BACKGROUND

Glossina species (tsetse flies), the sole vectors of African trypanosomes, maintained along their long evolutionary history a unique reproductive strategy, adenotrophic viviparity. Viviparity reduces their reproductive rate and, as such, imposes strong selective pressures on males for reproductive success. These species live in sub-Saharan Africa, where the distributions of the main sub-genera Fusca, Morsitans, and Palpalis are restricted to forest, savannah, and riverine habitats, respectively. Here we aim at identifying the evolutionary patterns of the male reproductive genes of six species belonging to these three main sub-genera. We then interpreted the different patterns we found across the species in the light of viviparity and the specific habitat restrictions, which are known to shape reproductive behavior.

RESULTS

We used a comparative genomic approach to build consensus evolutionary trees that portray the selective pressure acting on the male reproductive genes in these lineages. Such trees reflect the long and divergent demographic history that led to an allopatric distribution of the Fusca, Morsitans, and Palpalis species groups. A dataset of over 1700 male reproductive genes remained conserved over the long evolutionary time scale (estimated at 26.7 million years) across the genomes of the six species. We suggest that this conservation may result from strong functional selective pressure on the male imposed by viviparity. It is noteworthy that more than half of these conserved genes are novel sequences that are unique to the Glossina genus and are candidates for selection in the different lineages.

CONCLUSIONS

Tsetse flies represent a model to interpret the evolution and differentiation of male reproductive biology under different, but complementary, perspectives. In the light of viviparity, we must take into account that these genes are constrained by a post-fertilization arena for genomic conflicts created by viviparity and absent in ovipositing species. This constraint implies a continuous antagonistic co-evolution between the parental genomes, thus accelerating inter-population post-zygotic isolation and, ultimately, favoring speciation. Ecological restrictions that affect reproductive behavior may further shape such antagonistic co-evolution.

The Differential Growth Inhibition of Phytophthora spp. Caused by the Rare Sugar Tagatose Is Associated With Species-Specific Metabolic and Transcriptional Changes

Tagatose is a rare sugar with no negative impacts on human health and selective inhibitory effects on plant-associated microorganisms. Tagatose inhibited mycelial growth and negatively affected mitochondrial processes in Phytophthora infestans, but not in Phytophthora cinnamomi. The aim of this study was to elucidate metabolic changes and transcriptional reprogramming activated by P. infestans and P. cinnamomi in response to tagatose, in order to clarify the differential inhibitory mechanisms of tagatose and the species-specific reactions to this rare sugar. Phytophthora infestans and P. cinnamomi activated distinct metabolic and transcriptional changes in response to the rare sugar. Tagatose negatively affected mycelial growth, sugar content and amino acid content in P. infestans with a severe transcriptional reprogramming that included the downregulation of genes involved in transport, sugar metabolism, signal transduction, and growth-related process. Conversely, tagatose incubation upregulated genes related to transport, energy metabolism, sugar metabolism and oxidative stress in P. cinnamomi with no negative effects on mycelial growth, sugar content and amino acid content. Differential inhibitory effects of tagatose on Phytophthora spp. were associated with an attempted reaction of P. infestans, which was not sufficient to attenuate the negative impacts of the rare sugar and with an efficient response of P. cinnamomi with the reprogramming of multiple metabolic processes, such as genes related to glucose transport, pentose metabolism, tricarboxylic acid cycle, reactive oxygen species detoxification, mitochondrial and alternative respiration processes. Knowledge on the differential response of Phytophthora spp. to tagatose represent a step forward in the understanding functional roles of rare sugars.

Gene Ontology Meta Annotator for Plants (GOMAP)

Annotating gene structures and functions to genome assemblies is necessary to make assembly resources useful for biological inference. Gene Ontology (GO) term assignment is the most used functional annotation system, and new methods for GO assignment have improved the quality of GO-based function predictions. The Gene Ontology Meta Annotator for Plants (GOMAP) is an optimized, high-throughput, and reproducible pipeline for genome-scale GO annotation of plants. We containerized GOMAP to increase portability and reproducibility and also optimized its performance for HPC environments. Here we report on the pipeline's availability and performance for annotating large, repetitive plant genomes and describe how GOMAP was used to annotate multiple maize genomes as a test case. Assessment shows that GOMAP expands and improves the number of genes annotated and annotations assigned per gene as well as the quality (based on [Formula: see text]) of GO assignments in maize. GOMAP has been deployed to annotate other species including wheat, rice, barley, cotton, and soy. Instructions and access to the GOMAP Singularity container are freely available online at https://bioinformapping.com/gomap/ . A list of annotated genomes and links to data is maintained at https://dill-picl.org/projects/gomap/ .

Gene function finding through cross-organism ensemble learning

Background

Structured biological information about genes and proteins is a valuable resource to improve discovery and understanding of complex biological processes via machine learning algorithms. Gene Ontology (GO) controlled annotations describe, in a structured form, features and functions of genes and proteins of many organisms. However, such valuable annotations are not always reliable and sometimes are incomplete, especially for rarely studied organisms. Here, we present GeFF (Gene Function Finder), a novel cross-organism ensemble learning method able to reliably predict new GO annotations of a target organism from GO annotations of another source organism evolutionarily related and better studied.

Results

Using a supervised method, GeFF predicts unknown annotations from random perturbations of existing annotations. The perturbation consists in randomly deleting a fraction of known annotations in order to produce a reduced annotation set. The key idea is to train a supervised machine learning algorithm with the reduced annotation set to predict, namely to rebuild, the original annotations. The resulting prediction model, in addition to accurately rebuilding the original known annotations for an organism from their perturbed version, also effectively predicts new unknown annotations for the organism. Moreover, the prediction model is also able to discover new unknown annotations in different target organisms without retraining.We combined our novel method with different ensemble learning approaches and compared them to each other and to an equivalent single model technique. We tested the method with five different organisms using their GO annotations: Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum. The outcomes demonstrate the effectiveness of the cross-organism ensemble approach, which can be customized with a trade-off between the desired number of predicted new annotations and their precision.A Web application to browse both input annotations used and predicted ones, choosing the ensemble prediction method to use, is publicly available at http://tiny.cc/geff/.

Conclusions

Our novel cross-organism ensemble learning method provides reliable predicted novel gene annotations, i.e., functions, ranked according to an associated likelihood value. They are very valuable both to speed the annotation curation, focusing it on the prioritized new annotations predicted, and to complement known annotations available.

Mycena genomes resolve the evolution of fungal bioluminescence

Mushroom-forming fungi in the order Agaricales represent an independent origin of bioluminescence in the tree of life; yet the diversity, evolutionary history, and timing of the origin of fungal luciferases remain elusive. We sequenced the genomes and transcriptomes of five bonnet mushroom species (Mycena spp.), a diverse lineage comprising the majority of bioluminescent fungi. Two species with haploid genome assemblies ∼150 Mb are among the largest in Agaricales, and we found that a variety of repeats between Mycena species were differentially mediated by DNA methylation. We show that bioluminescence evolved in the last common ancestor of mycenoid and the marasmioid clade of Agaricales and was maintained through at least 160 million years of evolution. Analyses of synteny across genomes of bioluminescent species resolved how the luciferase cluster was derived by duplication and translocation, frequently rearranged and lost in most Mycena species, but conserved in the Armillaria lineage. Luciferase cluster members were coexpressed across developmental stages, with the highest expression in fruiting body caps and stipes, suggesting fruiting-related adaptive functions. Our results contribute to understanding a de novo origin of bioluminescence and the corresponding gene cluster in a diverse group of enigmatic fungal species.

Structural and functional annotation of PR/SET Domain (PRDM) protein family: In-silico study elaborating role of PRDM12 mutation in congenital insensitivity to pain

Congenital insensitivity to pain (CIP), classified as a type of hereditary sensory and autonomic neuropathies, is a rare disease in which the affected individuals fail to perceive sensation of pain. One of the PR/SET Domain Proteins, PRDM12, has been identified in recent past as a candidate gene for congenital insensitivity to pain. In the present study, we performed whole exome sequencing in a Pakistani family with CIP phenotype to ascertain the causative mutation. We identified a previously described alanine repeat duplication in PRDM12 (Ala353_Ala359dup) in this family. After this, we performed structural annotations for PR/SET Domain (PRDM) containing protein family to prognosticate the potential hypothetical structure of PRDM proteins with physical and chemical parameters. Out of nineteen members of this family, four members (PRDM5, PRDM8, PRDM12 and PRDM13) were specially focused because of their role in neurological disorders. Predictions about structure and interactions of these proteins revealed novel interacting molecules and pathways. Detailed in silico analysis of PRDM12 was performed to elaborate importance of its domain structure in interaction with other proteins and its role in pain insensitivity phenotype. These results have substantially enhanced our understanding regarding the etiology of congenital pain insensitivity and would stimulate further research on therapy and prevention.

SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice

Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data produced a set of 200-dimension feature vectors for each gene. Pathways were represented by summing the vectors of the pathway member genes. Thus, the similarities between genes and pathways were assessed. Additionally, the gene feature vectors were correlated with external gene data, including gene expression and gene network connectivity, to elucidate the associated functions. The gene feature vectors were decoded, and their applications were demonstrated. A simple online tool, SemanticGO (http://bioinformatics.fafu.edu.cn/semanticGO/), is herein provided to enable researchers to explore the similarities between genes and pathways in both Arabidopsis and rice.

Illumina and PacBio DNA sequencing data, de novo assembly and annotation of the genome of Aurantiochytrium limacinum strain CCAP_4062/1

The complete genome of the thraustochytrid Aurantiochytrium limacinum strain CCAP_4062/1 was sequenced using both Illumina Novaseq 6000 and third generation sequencing technology PacBio RSII in order to obtain trustworthy assembly and annotation. The reads from both platforms were combined at multiple levels in order to obtain a reliable assembly, then compared to the A. limacinum ATCCⓇ MYA1381™ reference genome. The final assembly was annotated with the help of strain CCAP_4062/1 RNAseq data. A. limacinum strain CCAP_4062/1 is an industrial strain used for the production of very long chain polyunsaturated fatty acids, like the docosahexaenoic acid that is an essential fatty acid synthesised only at very low pace in humans and vertebrates . Thraustochytrids in general and Aurantiochytrium more specifically, are used for carotenoid and squalene production as well. Beside their biotechnological interest, thraustochytrids play a crucial role in both inshore and oceanic basins ecosystems. Genome sequences will foster biotechnological as well as ecological studies.

Genomic Analysis of Intrinsically Disordered Proteins in the Genus Camelus

Intrinsically disordered proteins/regions (IDPs/IDRs) fail to fold completely into 3D structures, but have major roles in determining protein function. While natively disordered proteins/regions have been found to fulfill a wide variety of primary cellular roles, the functions of many disordered proteins in numerous species remain to be uncovered. Here, we perform the first large-scale study of IDPs/IDRs in the genus Camelus, one of the most important mammalians in Asia and North Africa, in order to explore the biological roles of these proteins. The study includes the prediction of disordered proteins/regions in Camelus species and in humans using multiple state-of-the-art prediction tools. Additionally, we provide a comparative analysis of Camelus and Homo sapiens IDPs/IDRs for the sake of highlighting the distinctive use of disorder in each genus. Our findings indicate that the human proteome is more disordered than the Camelus proteome. Gene Ontology analysis also revealed that Camelus IDPs are enriched in glutathione catabolism and lactose biosynthesis.

Clues of in vivo nuclear gene regulation by mitochondrial short non-coding RNAs

Gene expression involves multiple processes, from transcription to translation to the mature, functional peptide, and it is regulated at multiple levels. Small RNA molecules are known to bind RNA messengers affecting their fate in the cytoplasm (a process generically termed ‘RNA interference’). Such small regulatory RNAs are well-known to be originated from the nuclear genome, while the role of mitochondrial genome in RNA interference was largely overlooked. However, evidence is growing that mitochondrial DNA does provide the cell a source of interfering RNAs. Small mitochondrial highly transcribed RNAs (smithRNAs) have been proposed to be transcribed from the mitochondrion and predicted to regulate nuclear genes. Here, for the first time, we show in vivo clues of the activity of two smithRNAs in the Manila clam, Ruditapes philippinarum. Moreover, we show that smithRNAs are present and can be annotated in representatives of the three main bilaterian lineages; in some cases, they were already described and assigned to a small RNA category (e.g., piRNAs) given their biogenesis, while in other cases their biogenesis remains unclear. If mitochondria may affect nuclear gene expression through RNA interference, this opens a plethora of new possibilities for them to interact with the nucleus and makes metazoan mitochondrial DNA a much more complex genome than previously thought.

Improving protein function prediction using protein sequence and GO-term similarities

MOTIVATION

Most automatic functional annotation methods assign Gene Ontology (GO) terms to proteins based on annotations of highly similar proteins. We advocate that proteins that are less similar are still informative. Also, despite their simplicity and structure, GO terms seem to be hard for computers to learn, in particular the Biological Process ontology, which has the most terms (>29 000). We propose to use Label-Space Dimensionality Reduction (LSDR) techniques to exploit the redundancy of GO terms and transform them into a more compact latent representation that is easier to predict.

RESULTS

We compare proteins using a sequence similarity profile (SSP) to a set of annotated training proteins. We introduce two new LSDR methods, one based on the structure of the GO, and one based on semantic similarity of terms. We show that these LSDR methods, as well as three existing ones, improve the Critical Assessment of Functional Annotation performance of several function prediction algorithms. Cross-validation experiments on Arabidopsis thaliana proteins pinpoint the superiority of our GO-aware LSDR over generic LSDR. Our experiments on A.thaliana proteins show that the SSP representation in combination with a kNN classifier outperforms state-of-the-art and baseline methods in terms of cross-validated F-measure.

AVAILABILITY AND IMPLEMENTATION

Source code for the experiments is available at https://github.com/stamakro/SSP-LSDR.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

EnTAP: Bringing faster and smarter functional annotation to non-model eukaryotic transcriptomes

EnTAP (Eukaryotic Non-Model Transcriptome Annotation Pipeline) was designed to improve the accuracy, speed, and flexibility of functional gene annotation for de novo assembled transcriptomes in non-model eukaryotes. This software package addresses the fragmentation and related assembly issues that result in inflated transcript estimates and poor annotation rates of protein-coding transcripts. Following filters applied through assessment of true expression and frame selection, open-source tools are leveraged to functionally annotate the reduced set of translated proteins. Downstream features include fast similarity search across five repositories, protein domain assignment, orthologous gene family assessment, and Gene Ontology (GO) term assignment. The final annotation integrates across multiple databases and selects an optimal assignment from a combination of weighted metrics describing similarity search score, taxonomic relationship, and informativeness. Researchers have the option to include additional filters to identify and remove contaminants, identify associated pathways, and prepare the transcripts for enrichment analysis. This fully featured pipeline is easy to install, configure, and runs significantly faster than comparable annotation packages. EnTAP is optimized to generate extensive functional information for the gene space of organisms with limited or poorly characterized genomic resources.

De Novo Transcriptome Analysis of Durum Wheat Flag Leaves Provides New Insights Into the Regulatory Response to Elevated CO2 and High Temperature

Global warming is becoming a significant problem for food security, particularly in the Mediterranean basin. The use of molecular techniques to study gene-level responses to environmental changes in non-model organisms is increasing and may help to improve the mechanistic understanding of durum wheat response to elevated CO2 and high temperature. With this purpose, we performed transcriptome RNA sequencing (RNA-Seq) analyses combined with physiological and biochemical studies in the flag leaf of plants grown in field chambers at ear emergence. Enhanced photosynthesis by elevated CO2 was accompanied by an increase in biomass and starch and fructan content, and a decrease in N compounds, as chlorophyll, soluble proteins, and Rubisco content, in association with a decline of nitrate reductase and initial and total Rubisco activities. While high temperature led to a decline of chlorophyll, Rubisco activity, and protein content, the glucose content increased and starch decreased. Furthermore, elevated CO2 induced several genes involved in mitochondrial electron transport, a few genes for photosynthesis and fructan synthesis, and most of the genes involved in secondary metabolism and gibberellin and jasmonate metabolism, whereas those related to light harvesting, N assimilation, and other hormone pathways were repressed. High temperature repressed genes for C, energy, N, lipid, secondary, and hormone metabolisms. Under the combined increases in atmospheric CO2 and temperature, the transcript profile resembled that previously reported for high temperature, although elevated CO2 partly alleviated the downregulation of primary and secondary metabolism genes. The results suggest that there was a reprogramming of primary and secondary metabolism under the future climatic scenario, leading to coordinated regulation of C-N metabolism towards C-rich metabolites at elevated CO2 and a shift away from C-rich secondary metabolites at high temperature. Several candidate genes differentially expressed were identified, including protein kinases, receptor kinases, and transcription factors.

Learning a functional grammar of protein domains using natural language word embedding techniques

In this paper, using Word2vec, a widely-used natural language processing method, we demonstrate that protein domains may have a learnable implicit semantic "meaning" in the context of their functional contributions to the multi-domain proteins in which they are found. Word2vec is a group of models which can be used to produce semantically meaningful embeddings of words or tokens in a fixed-dimension vector space. In this work, we treat multi-domain proteins as "sentences" where domain identifiers are tokens which may be considered as "words." Using all InterPro (Finn et al. 2017) pfam domain assignments we observe that the embedding could be used to suggest putative GO assignments for Pfam (Finn et al. 2016) domains of unknown function.

Predicting bacterial virulence factors - evaluation of machine learning and negative data strategies

Bacterial proteins dubbed virulence factors (VFs) are a highly diverse group of sequences, whose only obvious commonality is the very property of being, more or less directly, involved in virulence. It is therefore tempting to speculate whether their prediction, based on direct sequence similarity (seqsim) to known VFs, could be enhanced or even replaced by using machine-learning methods. Specifically, when trained on a large and diverse set of VFs, such may be able to detect putative, non-trivial characteristics shared by otherwise unrelated VF families and therefore better predict novel VFs with insignificant similarity to each individual family. We therefore first reassess the performance of dimer-based Support Vector Machines, as used in the widely used MP3 method, in light of seqsim-only and seqsim/dimer-hybrid classifiers. We then repeat the analysis with a novel, considerably more diverse data set, also addressing the important problem of negative data selection. Finally, we move on to the real-world use case of proteome-wide VF prediction, outlining different approaches to estimating specificity in this scenario. We find that direct seqsim is of unparalleled importance and therefore should always be exploited. Further, we observe strikingly low correlations between different feature and classifier types when ranking proteins by VF likeness. We therefore propose a 'best of each world' approach to prioritize proteins for experimental testing, focussing on the top predictions of each classifier. Further, classifiers for individual VF families should be developed.

Differential Chloroplast Proteomics of Temperature Adaptation in Apple (Malus x domestica Borkh.) Microshoots

Temperature stress is one of the most common external factors that plants have to adapt to. Accordingly, plants have developed several adaptation mechanisms to deal with temperature stress. Chloroplasts are one of the organelles that are responsible for the sensing of the temperature signal and triggering a response. Here, chloroplasts are purified from low temperature (4° C), control (22° C) and high temperature (30° C) grown Malus x domestica microshoots. The purity of the chloroplast fractions is evaluated by marker proteins, as well as by using in silico subcellular localization predictions. The proteins are digested using filter-aided sample processing and analyzed using nano-LC MS/MS. 733 proteins are observed corresponding to published Malus x domestica gene models and 16 chloroplast genome -encoded proteins in the chloroplast preparates. In ANOVA, 56 proteins are found to be significantly differentially abundant (p < 0.01) between chloroplasts isolated from plants grown in different conditions. The differentially abundant proteins are involved in protein digestion, cytoskeleton structure, cellular redox state and photosynthesis, or have protective functions. Additionally, a putative chloroplastic aquaporin is observed. Data are available via ProteomeXchange with identifier PXD014212.

PANNZER2: a rapid functional annotation web server

The unprecedented growth of high-throughput sequencing has led to an ever-widening annotation gap in protein databases. While computational prediction methods are available to make up the shortfall, a majority of public web servers are hindered by practical limitations and poor performance. Here, we introduce PANNZER2 (Protein ANNotation with Z-scoRE), a fast functional annotation web server that provides both Gene Ontology (GO) annotations and free text description predictions. PANNZER2 uses SANSparallel to perform high-performance homology searches, making bulk annotation based on sequence similarity practical. PANNZER2 can output GO annotations from multiple scoring functions, enabling users to see which predictions are robust across predictors. Finally, PANNZER2 predictions scored within the top 10 methods for molecular function and biological process in the CAFA2 NK-full benchmark. The PANNZER2 web server is updated on a monthly schedule and is accessible at http://ekhidna2.biocenter.helsinki.fi/sanspanz/. The source code is available under the GNU Public Licence v3.

Environmental conditions shape the nature of a minimal bacterial genome

Of the 473 genes in the genome of the bacterium with the smallest genome generated to date, 149 genes have unknown function, emphasising a universal problem; less than 1% of proteins have experimentally determined annotations. Here, we combine the results from state-of-the-art in silico methods for functional annotation and assign functions to 66 of the 149 proteins. Proteins that are still not annotated lack orthologues, lack protein domains, and/ or are membrane proteins. Twenty-four likely transporter proteins are identified indicating the importance of nutrient uptake into and waste disposal out of the minimal bacterial cell in a nutrient-rich environment after removal of metabolic enzymes. Hence, the environment shapes the nature of a minimal genome. Our findings also show that the combination of multiple different state-of-the-art in silico methods for annotating proteins is able to predict functions, even for difficult to characterise proteins and identify crucial gaps for further development.

The 4-Celled Tetrabaena socialis Nuclear Genome Reveals the Essential Components for Genetic Control of Cell Number at the Origin of Multicellularity in the Volvocine Lineage

Multicellularity is the premier example of a major evolutionary transition in individuality and was a foundational event in the evolution of macroscopic biodiversity. The volvocine chlorophyte lineage is well suited for studying this process. Extant members span unicellular, simple colonial, and obligate multicellular taxa with germ-soma differentiation. Here, we report the nuclear genome sequence of one of the most morphologically simple organisms in this lineage-the 4-celled colonial Tetrabaena socialis and compare this to the three other complete volvocine nuclear genomes. Using conservative estimates of gene family expansions a minimal set of expanded gene families was identified that associate with the origin of multicellularity. These families are rich in genes related to developmental processes. A subset of these families is lineage specific, which suggests that at a genomic level the evolution of multicellularity also includes lineage-specific molecular developments. Multiple points of evidence associate modifications to the ubiquitin proteasomal pathway (UPP) with the beginning of coloniality. Genes undergoing positive or accelerating selection in the multicellular volvocines were found to be enriched in components of the UPP and gene families gained at the origin of multicellularity include components of the UPP. A defining feature of colonial/multicellular life cycles is the genetic control of cell number. The genomic data presented here, which includes diversification of cell cycle genes and modifications to the UPP, align the genetic components with the evolution of this trait.

The genome of a novel isolate of Prochlorococcus from the Red Sea contains transcribed genes for compatible solute biosynthesis

Marine microbes possess genomic and physiological adaptations to cope with varying environmental conditions. So far, the effects of high salinity on the most abundant marine photoautotrophic organism, Prochlorococcus, in marine oligotrophic environments, are mostly unknown. Here, we report the isolation of a new Prochlorococcus strain (RSP50) belonging to high-light (HL) clade II from the Red Sea, one of the warmest and most saline bodies of water in the global oceans. A comparative genomic analysis identified a set of 59 genes that were exclusive to RSP50 relative to currently available Prochlorococcus genomes, the majority of which (70%) encode for hypothetical proteins of unknown function. However, three of the unique genes encode for a complete pathway for the biosynthesis of the compatible solute glucosylglycerol, and are homologous to enzymes found in the sister lineage Synechococcus. Metatranscriptomic analyses of this metabolic pathway in the water column of the Red Sea revealed that the corresponding genes were constitutively transcribed, independent of depth and light, suggesting that osmoregulation using glucosylglycerol is a general feature of HL II Prochlorococcus in the Red Sea.

Comparative Transcriptomics in Two Bivalve Species Offers Different Perspectives on the Evolution of Sex-Biased Genes

Comparative genomics has become a central tool for evolutionary biology, and a better knowledge of understudied taxa represents the foundation for future work. In this study, we characterized the transcriptome of male and female mature gonads in the European clam Ruditapes decussatus, compared with that in the Manila clam Ruditapes philippinarum providing, for the first time in bivalves, information about transcription dynamics and sequence evolution of sex-biased genes. In both the species, we found a relatively low number of sex-biased genes (1,284, corresponding to 41.3% of the orthologous genes between the two species), probably due to the absence of sexual dimorphism, and the transcriptional bias is maintained in only 33% of the orthologs. The dN/dS is generally low, indicating purifying selection, with genes where the female-biased transcription is maintained between the two species showing a significantly higher dN/dS. Genes involved in embryo development, cell proliferation, and maintenance of genome stability show a faster sequence evolution. Finally, we report a lack of clear correlation between transcription level and evolutionary rate in these species, in contrast with studies that reported a negative correlation. We discuss such discrepancy and call into question some methodological approaches and rationales generally used in this type of comparative studies.

Fast Regulation of Hormone Metabolism Contributes to Salt Tolerance in Rice (Oryzasativa spp. Japonica, L.) by Inducing Specific Morpho-Physiological Responses

Clear evidence has highlighted a role for hormones in the plant stress response, including salt stress. Interplay and cross-talk among different hormonal pathways are of vital importance in abiotic stress tolerance. A genome-wide transcriptional analysis was performed on leaves and roots of three-day salt treated and untreated plants of two Italian rice varieties, Baldo and Vialone Nano, which differ in salt sensitivity. Genes correlated with hormonal pathways were identified and analyzed. The contents of abscisic acid, indoleacetic acid, cytokinins, and gibberellins were measured in roots, stems, and leaves of seedlings exposed for one and three days to salt stress. From the transcriptomic analysis, a huge number of genes emerged as being involved in hormone regulation in response to salt stress. The expression profile of genes involved in biosynthesis, signaling, response, catabolism, and conjugation of phytohormones was analyzed and integrated with the measurements of hormones in roots, stems, and leaves of seedlings. Significant changes in the hormone levels, along with differences in morphological responses, emerged between the two varieties. These results support the faster regulation of hormones metabolism in the tolerant variety that allows a prompt growth reprogramming and the setting up of an acclimation program, leading to specific morpho-physiological responses and growth recovery.

HPO2GO: prediction of human phenotype ontology term associations for proteins using cross ontology annotation co-occurrences

Analysing the relationships between biomolecules and the genetic diseases is a highly active area of research, where the aim is to identify the genes and their products that cause a particular disease due to functional changes originated from mutations. Biological ontologies are frequently employed in these studies, which provides researchers with extensive opportunities for knowledge discovery through computational data analysis. In this study, a novel approach is proposed for the identification of relationships between biomedical entities by automatically mapping phenotypic abnormality defining HPO terms with biomolecular function defining GO terms, where each association indicates the occurrence of the abnormality due to the loss of the biomolecular function expressed by the corresponding GO term. The proposed HPO2GO mappings were extracted by calculating the frequency of the co-annotations of the terms on the same genes/proteins, using already existing curated HPO and GO annotation sets. This was followed by the filtering of the unreliable mappings that could be observed due to chance, by statistical resampling of the co-occurrence similarity distributions. Furthermore, the biological relevance of the finalized mappings were discussed over selected cases, using the literature. The resulting HPO2GO mappings can be employed in different settings to predict and to analyse novel gene/protein—ontology term—disease relations. As an application of the proposed approach, HPO term—protein associations (i.e., HPO2protein) were predicted. In order to test the predictive performance of the method on a quantitative basis, and to compare it with the state-of-the-art, CAFA2 challenge HPO prediction target protein set was employed. The results of the benchmark indicated the potential of the proposed approach, as HPO2GO performance was among the best (Fmax = 0.35). The automated cross ontology mapping approach developed in this work may be extended to other ontologies as well, to identify unexplored relation patterns at the systemic level. The datasets, results and the source code of HPO2GO are available for download at: https://github.com/cansyl/HPO2GO.

Characterization of a large sex determination region in Salix purpurea L. (Salicaceae)

Dioecy has evolved numerous times in plants, but heteromorphic sex chromosomes are apparently rare. Sex determination has been studied in multiple Salix and Populus (Salicaceae) species, and P. trichocarpa has an XY sex determination system on chromosome 19, while S. suchowensis and S. viminalis have a ZW system on chromosome 15. Here we use whole genome sequencing coupled with quantitative trait locus mapping and a genome-wide association study to characterize the genomic composition of the non-recombining portion of the sex determination region. We demonstrate that Salix purpurea also has a ZW system on chromosome 15. The sex determination region has reduced recombination, high structural polymorphism, an abundance of transposable elements, and contains genes that are involved in sex expression in other plants. We also show that chromosome 19 contains sex-associated markers in this S. purpurea assembly, along with other autosomes. This raises the intriguing possibility of a translocation of the sex determination region within the Salicaceae lineage, suggesting a common evolutionary origin of the Populus and Salix sex determination loci.

Genome-wide analysis of Excretory/Secretory proteins in Trypanosoma brucei brucei: Insights into functional characteristics and identification of potential targets by immunoinformatics approach

Trypanosoma brucei brucei (T.b.brucei) is an extra-cellular parasite that causes Animal African Trypanosomiasis (AAT) disease in animals. Till day, this disease is more difficult to treat and control due to lack of efficient vaccines and early diagnosis of the parasite infection. T.b.brucei Excretory/Secretory (ES) proteins were involved in pathogenesis and key for understanding the host-parasite interactions. Functions of T.b.brucei's ES proteins were poorly investigated and experimental identification is expensive and time-consuming. Bioinformatics approaches are cost-effective by facilitating the experimental analysis of potential drug targets for parasitic diseases. Here we applied several bioinformatics tools to predict and functionalize the annotation of 1104 ES proteins and immunoinformatics approaches carried out to predict and evaluate the epitopes in T.b.brucei. Secretory information, functional annotations and potential epitopes of each ES proteins were available at http://tbb.insilico.in. This study provides functional information of T.b.brucei for experimental studies to identify potential targets for diagnosis and therapeutics development.

Maize GO Annotation-Methods, Evaluation, and Review (maize-GAMER)

We created a new high-coverage, robust, and reproducible functional annotation of maize protein-coding genes based on Gene Ontology (GO) term assignments. Whereas the existing Phytozome and Gramene maize GO annotation sets only cover 41% and 56% of maize protein-coding genes, respectively, this study provides annotations for 100% of the genes. We also compared the quality of our newly derived annotations with the existing Gramene and Phytozome functional annotation sets by comparing all three to a manually annotated gold standard set of 1,619 genes where annotations were primarily inferred from direct assay or mutant phenotype. Evaluations based on the gold standard indicate that our new annotation set is measurably more accurate than those from Phytozome and Gramene. To derive this new high-coverage, high-confidence annotation set, we used sequence similarity and protein domain presence methods as well as mixed-method pipelines that were developed for the Critical Assessment of Function Annotation (CAFA) challenge. Our project to improve maize annotations is called maize-GAMER (GO Annotation Method, Evaluation, and Review), and the newly derived annotations are accessible via MaizeGDB (http://download.maizegdb.org/maize-GAMER) and CyVerse (B73 RefGen_v3 5b+ at doi.org/10.7946/P2S62P and B73 RefGen_v4 Zm00001d.2 at doi.org/10.7946/P2M925).

Strong phenotypic plasticity limits potential for evolutionary responses to climate change

Phenotypic plasticity, the expression of multiple phenotypes from one genome, is a widespread adaptation to short-term environmental fluctuations, but whether it facilitates evolutionary adaptation to climate change remains contentious. Here, we investigate seasonal plasticity and adaptive potential in an Afrotropical butterfly expressing distinct phenotypes in dry and wet seasons. We assess the transcriptional architecture of plasticity in a full-factorial analysis of heritable and environmental effects across 72 individuals, and reveal pervasive gene expression differences between the seasonal phenotypes. Strikingly, intra-population genetic variation for plasticity is largely absent, consistent with specialisation to a particular environmental cue reliably predicting seasonal transitions. Under climate change, deteriorating accuracy of predictive cues will likely aggravate maladaptive phenotype-environment mismatches and increase selective pressures on reaction norms. However, the observed paucity of genetic variation for plasticity limits evolutionary responses, potentially weakening prospects for population persistence. Thus, seasonally plastic species may be especially vulnerable to climate change.

PANDA: Protein function prediction using domain architecture and affinity propagation

We developed PANDA (Propagation of Affinity and Domain Architecture) to predict protein functions in the format of Gene Ontology (GO) terms. PANDA at first executes profile-profile alignment algorithm to search against PfamA, KOG, COG, and SwissProt databases, and then launches PSI-BLAST against UniProt for homologue search. PANDA integrates a domain architecture inference algorithm based on the Bayesian statistics that calculates the probability of having a GO term. All the candidate GO terms are pooled and filtered based on Z-score. After that, the remaining GO terms are clustered using an affinity propagation algorithm based on the GO directed acyclic graph, followed by a second round of filtering on the clusters of GO terms. We benchmarked the performance of all the baseline predictors PANDA integrates and also for every pooling and filtering step of PANDA. It can be found that PANDA achieves better performances in terms of area under the curve for precision and recall compared to the baseline predictors. PANDA can be accessed from http://dna.cs.miami.edu/PANDA/ .

Transcriptome and Cell Physiological Analyses in Different Rice Cultivars Provide New Insights Into Adaptive and Salinity Stress Responses

Salinity tolerance has been extensively investigated in recent years due to its agricultural importance. Several features, such as the regulation of ionic transporters and metabolic adjustments, have been identified as salt tolerance hallmarks. Nevertheless, due to the complexity of the trait, the results achieved to date have met with limited success in improving the salt tolerance of rice plants when tested in the field, thus suggesting that a better understanding of the tolerance mechanisms is still required. In this work, differences between two varieties of rice with contrasting salt sensitivities were revealed by the imaging of photosynthetic parameters, ion content analysis and a transcriptomic approach. The transcriptomic analysis conducted on tolerant plants supported the setting up of an adaptive program consisting of sodium distribution preferentially limited to the roots and older leaves, and in the activation of regulatory mechanisms of photosynthesis in the new leaves. As a result, plants resumed grow even under prolonged saline stress. In contrast, in the sensitive variety, RNA-seq analysis revealed a misleading response, ending in senescence and cell death. The physiological response at the cellular level was investigated by measuring the intracellular profile of H₂O₂ in the roots, using a fluorescent probe. In the roots of tolerant plants, a quick response was observed with an increase in H₂O₂ production within 5 min after salt treatment. The expression analysis of some of the genes involved in perception, signal transduction and salt stress response confirmed their early induction in the roots of tolerant plants compared to sensitive ones. By inhibiting the synthesis of apoplastic H₂O₂, a reduction in the expression of these genes was detected. Our results indicate that quick H₂O₂ signaling in the roots is part of a coordinated response that leads to adaptation instead of senescence in salt-treated rice plants.

Large-scale automated function prediction of protein sequences and an experimental case study validation on PTEN transcript variants

Recent advances in computing power and machine learning empower functional annotation of protein sequences and their transcript variations. Here, we present an automated prediction system UniGOPred, for GO annotations and a database of GO term predictions for proteomes of several organisms in UniProt Knowledgebase (UniProtKB). UniGOPred provides function predictions for 514 molecular function (MF), 2909 biological process (BP), and 438 cellular component (CC) GO terms for each protein sequence. UniGOPred covers nearly the whole functionality spectrum in Gene Ontology system and it can predict both generic and specific GO terms. UniGOPred was run on CAFA2 challenge target protein sequences and it is categorized within the top 10 best performing methods for the molecular function category. In addition, the performance of UniGOPred is higher compared to the baseline BLAST classifier in all categories of GO. UniGOPred predictions are compared with UniProtKB/TrEMBL database annotations as well. Furthermore, the proposed tool's ability to predict negatively associated GO terms that defines the functions that a protein does not possess, is discussed. UniGOPred annotations were also validated by case studies on PTEN protein variants experimentally and on CHD8 protein variants with literature. UniGOPred protein functional annotation system is available as an open access tool at http://cansyl.metu.edu.tr/UniGOPred.html.

Identification of New Features from Known Bacterial Protective Vaccine Antigens Enhances Rational Vaccine Design

With many protective vaccine antigens reported in the literature and verified experimentally, how to use the knowledge mined from these antigens to support rational vaccine design and study underlying design mechanism remains unclear. In order to address the problem, a systematic bioinformatics analysis was performed on 291 Gram-positive and Gram-negative bacterial protective antigens with experimental evidence manually curated in the Protegen database. The bioinformatics analyses evaluated included subcellular localization, adhesin probability, peptide signaling, transmembrane α-helix and β-barrel, conserved domain, Clusters of Orthologous Groups, and Gene Ontology functional annotations. Here we showed the critical role of adhesins, along with subcellular localization, peptide signaling, in predicting secreted extracellular or surface-exposed protective antigens, with mechanistic explanations supported by functional analysis. We also found a significant negative correlation of transmembrane α-helix to antigen protectiveness in Gram-positive and Gram-negative pathogens, while a positive correlation of transmembrane β-barrel was observed in Gram-negative pathogens. The commonly less-focused cytoplasmic and cytoplasmic membrane proteins could be potentially predicted with the help of other selection criteria such as adhesin probability and functional analysis. The significant findings in this study can support rational vaccine design and enhance our understanding of vaccine design mechanisms.

Quantitative multiplexed proteomics of Taenia solium cysts obtained from the skeletal muscle and central nervous system of pigs

In human and porcine cysticercosis caused by the tapeworm Taenia solium, the larval stage (cysts) can infest several tissues including the central nervous system (CNS) and the skeletal muscles (SM). The cyst’s proteomics changes associated with the tissue localization in the host tissues have been poorly studied. Quantitative multiplexed proteomics has the power to evaluate global proteome changes in response to different conditions. Here, using a TMT-multiplexed strategy we identified and quantified over 4,200 proteins in cysts obtained from the SM and CNS of pigs, of which 891 were host proteins. To our knowledge, this is the most extensive intermixing of host and parasite proteins reported for tapeworm infections.Several antigens in cysticercosis, i.e., GP50, paramyosin and a calcium-binding protein were enriched in skeletal muscle cysts. Our results suggested the occurrence of tissue-enriched antigen that could be useful in the improvement of the immunodiagnosis for cysticercosis. Using several algorithms for epitope detection, we selected 42 highly antigenic proteins enriched for each tissue localization of the cysts. Taking into account the fold changes and the antigen/epitope contents, we selected 10 proteins and produced synthetic peptides from the best epitopes. Nine peptides were recognized by serum antibodies of cysticercotic pigs, suggesting that those peptides are antigens. Mixtures of peptides derived from SM and CNS cysts yielded better results than mixtures of peptides derived from a single tissue location, however the identification of the ‘optimal’ tissue-enriched antigens remains to be discovered. Through machine learning technologies, we determined that a reliable immunodiagnostic test for porcine cysticercosis required at least five different antigenic determinants.

Human and porcine cysticercosis caused by Taenia solium is a parasite disease still endemic in developing countries. The cysts can be located in different host tissues, including different organs of the central nervous system and the skeletal muscles. The molecular mechanisms associated with the tissue localization of the cysts are not well understood. Here, we described the proteome changes of the cysts obtained from different host tissues from infected pigs using quantitative multiplex proteomics. We explored the diversity of host proteins identified in the cyst’s protein extracts and we also explored the immune-localization of several host-related proteins within the cysts, and propose their possible function. We identified several proteins and antigens enriched for a given tissue localization. Several synthetic peptides designed from these tissue-enriched antigens were tested trough ELISA. Using a combination of peptide mixtures and machine learning technologies we were able to distinguish non cysticercotic and cysticercotic pig’s sera. The tissue-enriched proteins/antigens could be useful for the development of improved immuno-diagnostic tests capable of discriminate the tissue-localization of the cysts.