Previous Annotation Research Articles

Insights into ADAR gene complement, expression patterns, and RNA editing landscape in Chlamys farreri

Adenosine Deaminases Acting on RNA (ADARs) are evolutionarily conserved enzymes known to convert adenosine to inosine in double-stranded RNAs and participate in host-virus interactions. Conducting a meta-analysis of available transcriptome data, we identified and characterised eight ADAR transcripts in Chlamys farreri, a farmed marine scallop susceptible to Acute viral necrosis virus (AVNV) infections and mortality outbreaks. Accordingly, we identified six ADAR genes in the Zhikong scallop genome, revised previous gene annotations, and traced alternative splicing variants. In detail, each ADAR gene encodes a unique combination of functional domains, always including the Adenosine deaminase domain, RNA binding domains and, in one case, two copies of a Z-DNA binding domain. After phylogenetic analysis, five C. farreri ADARs clustered in the ADAR1 clade along with sequences from diverse animal phyla. Gene expression analysis indicated CF051320 as the most expressed ADAR, especially in the eye and male gonad. The other four ADAR1 genes and one ADAR2 gene exhibited variable expression levels, with CF105370 and CF051320 significantly increasing during early scallop development. ADAR-mediated single-base editing, evaluated across adult C. farreri tissues and developmental stages, was mainly detectable in intergenic regions (83 % and 85 %, respectively). Overall, the expression patterns of the six ADAR genes together with the editing and hyper-editing values computed on scallops RNA-seq samples support the adaptive value of ADAR1-mediated editing, particularly in the pre-settling larval stages.

Genome-wide association analysis of four yield-related traits using a maize (Zea mays L.) F1 population.

Increasing the yield of maize F1 hybrid is one of the most important target for breeders. However, as a result of the genetic complexity and extremely low heritability, it is very difficult to directly dissect the genetic basis and molecular mechanisms of yield, and reports on genetic analysis of F1 hybrid yield are rare. Taking F1 hybrid as the research object and dividing the yield into different affect factors, this approach may be the best strategy for clarifying the genetic mechanism of yield. Therefore, in this study, a maize F1 population consisting of 300 hybrids with 17,652 single nucleotide polymorphisms (SNPs) markers was used for genome-wide association study (GWAS) to filtrate candidate genes associated with the four yield-related traits, i.e., kernel row number (KRN), kernel number per row (KNPR), ear tip-barrenness (ETB), and hundred kernel weight (HKW). Combined with the results of previous studies and functional annotation information of candidate genes, a total of six candidate genes were identified as being associated with the four traits, which were involved in plant growth and development, protein synthesis response, phytohormone biosynthesis and signal transduction. Our results improve the understanding of the genetic basis of the four yield-related traits and may be provide a new strategy for the genetic basis of maize yield.

Structure classification of the proteins from Salmonella enterica pangenome revealed novel potential pathogenicity islands

Salmonella enterica is a pathogenic bacterium known for causing severe typhoid fever in humans, making it important to study due to its potential health risks and significant impact on public health. This study provides evolutionary classification of proteins from Salmonella enterica pangenome. We classified 17,238 domains from 13,147 proteins from 79,758 Salmonella enterica strains and studied in detail domains of 272 proteins from 14 characterized Salmonella pathogenicity islands (SPIs). Among SPIs-related proteins, 90 proteins function in the secretion machinery. 41% domains of SPI proteins have no previous sequence annotation. By comparing clinical and environmental isolates, we identified 3682 proteins that are overrepresented in clinical group that we consider as potentially pathogenic. Among domains of potentially pathogenic proteins only 50% domains were annotated by sequence methods previously. Moreover, 36% (1330 out of 3682) of potentially pathogenic proteins cannot be classified into Evolutionary Classification of Protein Domains database (ECOD). Among classified domains of potentially pathogenic proteins the most populated homology groups include helix-turn-helix (HTH), Immunoglobulin-related, and P-loop domains-related. Functional analysis revealed overrepresentation of these protein in biological processes related to viral entry into host cell, antibiotic biosynthesis, DNA metabolism and conformation change, and underrepresentation in translational processes. Analysis of the potentially pathogenic proteins indicates that they form 119 clusters or novel potential pathogenicity islands (NPPIs) within the Salmonella genome, suggesting their potential contribution to the bacterium’s virulence. One of the NPPIs revealed significant overrepresentation of potentially pathogenic proteins. Overall, our analysis revealed that identified potentially pathogenic proteins are poorly studied.

Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT.

As a result of technological advancements, functional capacity assessments, such as the 6-minute walk test, can be performed remotely, at home and in the community. Current studies, however, tend to overlook the crucial aspect of data quality, often limiting their focus to idealised scenarios. Challenging conditions may arise when performing a test given the risk of collecting poor-quality GNSS signal, which can undermine the reliability of the results. This work shows the impact of applying filtering rules to avoid noisy samples in common algorithms that compute the walked distance from positioning data. Then, based on signal features, we assess the reliability of the distance estimation using logistic regression from the following two perspectives: error-based analysis, which relates to the estimated distance error, and user-based analysis, which distinguishes conventional from unconventional tests based on users' previous annotations. We highlight the impact of features associated with walked path irregularity and direction changes to establish data quality. We evaluate features within a binary classification task and reach an F1-score of 0.93 and an area under the curve of 0.97 for the user-based classification. Identifying unreliable tests is helpful to clinicians, who receive the recorded test results accompanied by quality assessments, and to patients, who can be given the opportunity to repeat tests classified as not following the instructions.

Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool.

The Interactive Tree Of Life (https://itol.embl.de) is an online tool for the management, display, annotation and manipulation of phylogenetic and other trees. It is freely available and open to everyone. iTOL version 6 introduces a modernized and completely rewritten user interface, together with numerous new features. A new dataset type has been introduced (colored/labeled ranges), greatly upgrading the functionality of the previous simple colored range annotation function. Additional annotation options have been implemented for several existing dataset types. Dataset template files now support simple assignment of annotations to multiple tree nodes through substring matching, including full regular expression support. Node metadata handling has been greatly extended with novel display and exporting options, and it can now be edited interactively or bulk updated through annotation files. Tree labels can be displayed using multiple simultaneous font styles, with precise positioning, sizing and styling of each individual label part. Various bulk label editing functions have been implemented, simplifying large scale changes of all tree node labels. iTOL's automatic taxonomy assignment functions now support trees based on the Genome Taxonomy Database (GTDB), in addition to the NCBI taxonomy. The functionality of the optional user account pages has been expanded, simplifying the management, navigation and sharing of projects and trees. iTOL currently handles more than one and a half million trees from >130000 individual user accounts.

A new atlas to study embryonic cell types in Xenopus

This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus, encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropicalis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues. Employing an unbiased approach for cell type assignment proves especially apt for embryonic contexts, given the considerable number of non-terminally differentiated cell types. An alternative cell type attribution here adopts a fuzzy, non-deterministic stance, capturing the transient nature of early embryo progenitor cells by presenting an ensemble of types in superposition. The value of the new resource is emphasized through numerous examples, with a focus on previously unexplored germ cell populations where we uncover novel transcription onset features. Offering interactive exploration via a user-friendly web portal and facilitating complete data downloads, this atlas serves as a comprehensive and accessible reference.

The Diverse Evolutionary Histories of Domesticated Metaviral Capsid Genes in Mammals.

Selfish genetic elements comprise significant fractions of mammalian genomes. In rare instances, host genomes domesticate segments of these elements for function. Using a complete human genome assembly and 25 additional vertebrate genomes, we re-analyzed the evolutionary trajectories and functional potential of capsid (CA) genes domesticated from Metaviridae, a lineage of retrovirus-like retrotransposons. Our study expands on previous analyses to unearth several new insights about the evolutionary histories of these ancient genes. We find that at least five independent domestication events occurred from diverse Metaviridae, giving rise to three universally retained single-copy genes evolving under purifying selection and two gene families unique to placental mammals, with multiple members showing evidence of rapid evolution. In the SIRH/RTL family, we find diverse amino-terminal domains, widespread loss of protein-coding capacity in RTL10 despite its retention in several mammalian lineages, and differential utilization of an ancient programmed ribosomal frameshift in RTL3 between the domesticated CA and protease domains. Our analyses also reveal that most members of the PNMA family in mammalian genomes encode a conserved putative amino-terminal RNA-binding domain (RBD) both adjoining and independent from domesticated CA domains. Our analyses lead to a significant correction of previous annotations of the essential CCDC8 gene. We show that this putative RBD is also present in several extant Metaviridae, revealing a novel protein domain configuration in retrotransposons. Collectively, our study reveals the divergent outcomes of multiple domestication events from diverse Metaviridae in the common ancestor of placental mammals.

SOIRP: Subject-Object Interaction and Reasoning Path based joint relational triple extraction by table filling

Joint relational triple extraction methods based on table filling have gained considerable attention in recent years due to remarkable effectiveness and capabilities of extracting relational triples from complicated sentences. However, most of the existing methods disregard the impact of the information interaction between the subject and object in the relational triple and the intrinsic association among relational triples on relational overlapping triples extraction, resulting in the inability to extract the relational triples hidden in the sentence. Furthermore, previous sequence annotation methods failed to consider the case of entity nesting. Therefore, there is still room for improving the relational overlap problem and entity nesting problem. To address this issue, we propose a new joint relational triple extraction model based on table filling, SOIRP, which contains a Subject-Object Interaction (SOI) module consisting of several different interactions and a Reasoning Path Extraction (RPE) module based on the idea of decoder module in Transformer. We refine the subject-object interaction information captured by the former and the path inference information captured by the latter through multiple iterations. In addition, we introduce a new table filling method and decoding strategy, which can capture all entities in each sentence and align the boundary tokens of entity pairs for each relation. We evaluate our proposed model on two public datasets and the experimental results demonstrate that our model outperforms the baseline model. The code of our model can be available at: https://github.com/valentiner/SOIPR.

ToGC: a pipeline to correct gene model for functional excavation of dark GPCRs in Phytophthora sojae1

The accuracy of genomic annotation is crucial for subsequent functional investigations; however, computational protocols used in high-throughput annotation of open reading frames (ORFs) can introduce inconsistencies. These inconsistencies, which lead to non-uniform extension or truncation of sequence ends, pose challenges for downstream analyses. Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive, lacking specific approaches. To address this gap, we developed toGC, a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies. Using toGC, we achieved an accuracy of nearly 100% accuracy in correcting inconsistencies in published P. sojae ORFs. We applied this innovative pipeline to the GPCR-bigrams gene family, which was predicted to have 42 members in the P. sojae genome but lacked experimental validation. By employing toGC, we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and toGC-corrected sequences. Notably, among these were 5 genes (GPCR-TKL9, GPCR-TKL15, GPCR-PDE3, GPCR-AC3, and GPCR-AC4) showed substantial inconsistencies. Experimental gene annotation confirmed the effectiveness of toGC, as sequences obtained through cloning matched those annotated by toGC. Importantly, we discovered two novel GPCRs (GPCR-AC3 and GPCR-AC4), which were previously mispredicted as a single gene. CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production, further confirming their status as two separate genes. In addition to P. sojae, the reliability of the toGC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline. Our findings highlight the utility of toGC for reliable gene model correction, facilitating investigations into biological functions and offering potential applications in diverse species analyses.

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.

SEN1990 is a predicted winged helix-turn-helix protein involved in the pathogenicity of Salmonella enterica serovar Enteritidis and the expression of the gene oafB in the SPI-17.

Excisable genomic islands (EGIs) are horizontally acquired genetic elements that harbor an array of genes with diverse functions. ROD21 is an EGI found integrated in the chromosome of Salmonella enterica serovar Enteritidis (Salmonella ser. Enteritidis). While this island is known to be involved in the capacity of Salmonella ser. Enteritidis to cross the epithelial barrier and colonize sterile organs, the role of most ROD21 genes remains unknown, and thus, the identification of their function is fundamental to understanding the impact of this EGI on bacterium pathogenicity. Therefore, in this study, we used a bioinformatical approach to evaluate the function of ROD21-encoded genes and delve into the characterization of SEN1990, a gene encoding a putative DNA-binding protein. We characterized the predicted structure of SEN1990, finding that this protein contains a three-stranded winged helix-turn-helix (wHTH) DNA-binding domain. Additionally, we identified homologs of SEN1990 among other members of the EARL EGIs. Furthermore, we deleted SEN1990 in Salmonella ser. Enteritidis, finding no differences in the replication or maintenance of the excised ROD21, contrary to what the previous Refseq annotation of the protein suggests. High-throughput RNA sequencing was carried out to evaluate the effect of the absence of SEN1990 on the bacterium's global transcription. We found a downregulated expression of oafB, an SPI-17-encoded acetyltransferase involved in O-antigen modification, which was restored when the deletion mutant was complemented ectopically. Additionally, we found that strains lacking SEN1990 had a reduced capacity to colonize sterile organs in mice. Our findings suggest that SEN1990 encodes a wHTH domain-containing protein that modulates the transcription of oafB from the SPI-17, implying a crosstalk between these pathogenicity islands and a possible new role of ROD21 in the pathogenesis of Salmonella ser. Enteritidis.

Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks.

Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which uses a convolutional neural network to predict pairwise TMRCAs and allele ages from sequencing or SNP array data. CoalNN is trained through simulation and can be adapted to varying parameters, such as demographic history, using transfer learning. Across several simulated scenarios, CoalNN matched or outperformed the accuracy of model-based approaches for pairwise TMRCA and allele age prediction. We applied CoalNN to settings for which model-based approaches are under-developed and performed analyses to gain insights into the set of features it uses to perform TMRCA prediction. We next used CoalNN to analyze 2,504 samples from 26 populations in the 1,000 Genome Project data set, inferring the age of ∼80 million variants. We observed substantial variation across populations and for variants predicted to be pathogenic, reflecting heterogeneous demographic histories and the action of negative selection. We used CoalNN's predicted allele ages to construct genome-wide annotations capturing the signature of past negative selection. We performed LD-score regression analysis of heritability using summary association statistics from 63 independent complex traits and diseases (average N=314k), observing increased annotation-specific effects on heritability compared to a previous allele age annotation. These results highlight the effectiveness of using likelihood-free, simulation-trained models to infer properties of gene genealogies in large genomic data sets.

Sequential interactive image segmentation

Interactive image segmentation (IIS) is an important technique for obtaining pixel-level annotations. In many cases, target objects share similar semantics. However, IIS methods neglect this connection and in particular the cues provided by representations of previously segmented objects, previous user interaction, and previous prediction masks, which can all provide suitable priors for the current annotation. In this paper, we formulate a sequential interactive image segmentation (SIIS) task for minimizing user interaction when segmenting sequences of related images, and we provide a practical approach to this task using two pertinent designs. The first is a novel interaction mode. When annotating a new sample, our method can automatically propose an initial click proposal based on previous annotation. This dramatically helps to reduce the interaction burden on the user. The second is an online optimization strategy, with the goal of providing semantic information when annotating specific targets, optimizing the model with dense supervision from previously labeled samples. Experiments demonstrate the effectiveness of regarding SIIS as a particular task, and our methods for addressing it.

Functional annotation and importance of marine bacterial transporters of plankton exometabolites

Metabolite exchange within marine microbial communities transfers carbon and other major elements through global cycles and forms the basis of microbial interactions. Yet lack of gene annotations and concern about the quality of existing ones remain major impediments to revealing currencies of carbon flux. We employed an arrayed mutant library of the marine bacterium Ruegeria pomeroyi DSS-3 to experimentally annotate substrates of organic compound transporter systems, using mutant growth and compound drawdown analyses to link transporters to their cognate substrates. Mutant experiments verified substrates for thirteen R. pomeroyi transporters. Four were previously hypothesized based on gene expression data (taurine, glucose/xylose, isethionate, and cadaverine/putrescine/spermidine); five were previously hypothesized based on homology to experimentally annotated transporters in other bacteria (citrate, glycerol, N-acetylglucosamine, fumarate/malate/succinate, and dimethylsulfoniopropionate); and four had no previous annotations (thymidine, carnitine, cysteate, and 3-hydroxybutyrate). These bring the total number of experimentally-verified organic carbon influx transporters to 18 of 126 in the R. pomeroyi genome. In a longitudinal study of a coastal phytoplankton bloom, expression patterns of the experimentally annotated transporters linked them to different stages of the bloom, and also led to the hypothesis that citrate and 3-hydroxybutyrate were among the most highly available bacterial substrates. Improved functional annotation of the gatekeepers of organic carbon uptake is critical for deciphering carbon flux and fate in microbial ecosystems.

Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions-a pilot study.

Low microbial biomass in the lungs, high host-DNA contamination and sampling difficulty limit the study on lung microbiome. Therefore, little is still known about lung microbial communities and their functions. Here, we perform a preliminary exploratory study to investigate the composition of swine lung microbial community using shotgun metagenomic sequencing and compare the microbial communities between healthy and severe-lesion lungs. We collected ten lavage-fluid samples from swine lungs (five from healthy lungs and five from severe-lesion lungs), and obtained their metagenomes by shotgun metagenomic sequencing. After filtering host genomic DNA contamination (93.5% ± 1.2%) in the lung metagenomic data, we annotated swine lung microbial communities ranging from four domains to 645 species. Compared with previous taxonomic annotation of the same samples by the 16S rRNA gene amplicon sequencing, it annotated the same number of family taxa but more genera and species. We next performed an association analysis between lung microbiome and host lung-lesion phenotype. We found three species (Mycoplasma hyopneumoniae, Ureaplasma diversum, and Mycoplasma hyorhinis) were associated with lung lesions, suggesting they might be the key species causing swine lung lesions. Furthermore, we successfully reconstructed the metagenome-assembled genomes (MAGs) of these three species using metagenomic binning. This pilot study showed us the feasibility and relevant limitations of shotgun metagenomic sequencing for the characterization of swine lung microbiome using lung lavage-fluid samples. The findings provided an enhanced understanding of the swine lung microbiome and its role in maintaining lung health and/or causing lung lesions.

In Silico and In Vitro Approach for Validating the Inhibition of Matrix Metalloproteinase-9 by Quercetin.

To validate the mechanism and inhibitory activity of quercetin against matrix metalloproteinase-9 (MMP-9) using a hybrid in silico and in vitro approach. The structure of MMP-9 was obtained from the Protein Data Bank, and the active site was identified using previous annotations from the Universal Protein Resource. The structure of quercetin was obtained from ZINC15. Molecular docking was performed to quantify the binding affinity of quercetin to the active site of MMP-9. The inhibitory effect of various concentrations of quercetin (0.0025, 0.025, 0.25, 1.0, and 1.5 mM) on MMP-9 was quantified using a commercially available fluorometric assay. The cytotoxicity of quercetin to immortalized human corneal epithelial cells (HCECs) was quantified by obtaining the metabolic activities of the cells exposed to various concentrations of quercetin for 24 hr. Quercetin interacts with MMP-9 by binding within the active site pocket and interacting with residues LEU 188, ALA 189, GLU 227, and MET 247. The binding affinity predicted by molecular docking was -9.9 kcal/mol. All concentrations of quercetin demonstrated significant inhibition of MMP-9 enzyme activity (all P <0.03). There was little to no reduction of HCEC metabolic activity after a 24-hr exposure to all concentrations of quercetin ( P >0.99). Quercetin inhibited MMP-9 in a dose-dependent manner and was well-tolerated by HCECs, suggesting a potential role in therapy for diseases with upregulated MMP-9 as part of its pathogenesis.

Excretory/Secretory Proteome of Females and Males of the Hookworm Ancylostoma ceylanicum.

The dynamic host-parasite mechanisms underlying hookworm infection establishment and maintenance in mammalian hosts remain poorly understood but are primarily mediated by hookworm's excretory/secretory products (ESPs), which have a wide spectrum of biological functions. We used ultra-high performance mass spectrometry to comprehensively profile and compare female and male ESPs from the zoonotic human hookworm Ancylostoma ceylanicum, which is a natural parasite of dogs, cats, and humans. We improved the genome annotation, decreasing the number of protein-coding genes by 49% while improving completeness from 92 to 96%. Compared to the previous genome annotation, we detected 11% and 10% more spectra in female and male ESPs, respectively, using this improved version, identifying a total of 795 ESPs (70% in both sexes, with the remaining sex-specific). Using functional databases (KEGG, GO and Interpro), common and sex-specific enriched functions were identified. Comparisons with the exclusively human-infective hookworm Necator americanus identified species-specific and conserved ESPs. This is the first study identifying ESPs from female and male A. ceylanicum. The findings provide a deeper understanding of hookworm protein functions that assure long-term host survival and facilitate future engineering of transgenic hookworms and analysis of regulatory elements mediating the high-level expression of ESPs. Furthermore, the findings expand the list of potential vaccine and diagnostic targets and identify biologics that can be explored for anti-inflammatory potential.

An informatic workflow for the enhanced annotation of excretory/secretory proteins of Haemonchus contortus

Major advances in genomic and associated technologies have demanded reliable bioinformatic tools and workflows for the annotation of genes and their products via comparative analyses using well-curated reference data sets, accessible in public repositories. However, the accurate in silico annotation of molecules (proteins) encoded in organisms (e.g., multicellular parasites) which are evolutionarily distant from those for which these extensive reference data sets are available, including invertebrate model organisms (e.g., Caenorhabditis elegans – free-living nematode, and Drosophila melanogaster – the vinegar fly) and vertebrate species (e.g., Homo sapiens and Mus musculus), remains a major challenge. Here, we constructed an informatic workflow for the enhanced annotation of biologically-important, excretory/secretory (ES) proteins (“secretome”) encoded in the genome of a parasitic roundworm, called Haemonchus contortus (commonly known as the barber’s pole worm). We critically evaluated the performance of five distinct methods, refined some of them, and then combined the use of all five methods to comprehensively annotate ES proteins, according to gene ontology, biological pathways and/or metabolic (enzymatic) processes. Then, using optimised parameter settings, we applied this workflow to comprehensively annotate 2591 of all 3353 proteins (77.3%) in the secretome of H. contortus. This result is a substantial improvement (10–25%) over previous annotations using individual, “off-the-shelf” algorithms and default settings, indicating the ready applicability of the present, refined workflow to gene/protein sequence data sets from a wide range of organisms in the Tree-of-Life.

Annotate_my_genomes: an easy-to-use pipeline to improve genome annotation and uncover neglected genes by hybrid RNA sequencing.

The advancement of hybrid sequencing technologies is increasingly expanding genome assemblies that are often annotated using hybrid sequencing transcriptomics, leading to improved genome characterization and the identification of novel genes and isoforms in a wide variety of organisms. We developed an easy-to-use genome-guided transcriptome annotation pipeline that uses assembled transcripts from hybrid sequencing data as input and distinguishes between coding and long non-coding RNAs by integration of several bioinformatic approaches, including gene reconciliation with previous annotations in GTF format. We demonstrated the efficiency of this approach by correctly assembling and annotating all exons from the chicken SCO-spondin gene (containing more than 105 exons), including the identification of missing genes in the chicken reference annotations by homology assignments. Our method helps to improve the current transcriptome annotation of the chicken brain. Our pipeline, implemented on Anaconda/Nextflow and Docker is an easy-to-use package that can be applied to a broad range of species, tissues, and research areas helping to improve and reconcile current annotations. The code and datasets are publicly available at https://github.com/cfarkas/annotate_my_genomes.

Towards an inclusive system for the annotation of (dis)fluency in typical and atypical speech

ABSTRACT This paper presents an operational annotation system for (dis)fluencies in typical and atypical speech, based on existing standard annotation schemes previously established in the literature. Grounded in a functional approach to (dis)fluency, we address some of the conceptual and technical limitations found in previous annotation models, and offer an integrated and inclusive system which is compatible with different multi-layered annotation software such as Praat or ELAN. Our aim is twofold: to create comparable annotated corpora both in typical and atypical speech, and to provide natural language processing and the health sector with applications for diagnostic and therapy in speech disorders.