Comprehensive Functional Annotation Research Articles

Analyses of high spatial resolution datasets identify genes associated with multi-layered secondary cell wall thickening in Pinus bungeana.

Secondary cell wall (SCW) thickening is a major cellular developmental stage determining wood structure and properties. Although the molecular regulation of cell wall deposition during tracheary element differentiation has been well established in primary growth systems, less is known about the gene regulatory processes involved in the multi-layered SCW thickening of mature trees. Using third-generation [long-read single-molecule real-time (SMRT)] and second-generation [short-read sequencing by synthesis (SBS)] sequencing methods, we established a Pinus bungeana transcriptome resource with comprehensive functional and structural annotation for the first time. Using these approaches, we generated high spatial resolution datasets for the vascular cambium, xylem expansion regions, early SCW thickening, late SCW thickening and mature xylem tissues of 71-year-old Pinus bungeana trees. A total of 79 390 non-redundant transcripts, 31 808 long non-coding RNAs and 5147 transcription factors were annotated and quantified in different xylem tissues at all growth and differentiation stages. Furthermore, using this high spatial resolution dataset, we established a comprehensive transcriptomic profile and found that members of the NAC, WRKY, SUS, CESA and LAC gene families are major players in early SCW formation in tracheids, whereas members of the MYB and LBD transcription factor families are highly expressed during late SCW thickening. Our results provide new molecular insights into the regulation of multi-layered SCW thickening in conifers. The high spatial resolution datasets provided can serve as important gene resources for improving softwoods.

Functional metabolomics of the human scalp: a metabolic niche for Staphylococcus epidermidis.

Although metabolomics data acquisition and analysis technologies have become increasingly sophisticated over the past 5-10 years, deciphering a metabolite's function from a description of its structure and its abundance in a given experimental setting is still a major scientific and intellectual challenge. To point out ways to address this "data to knowledge" challenge, we developed a functional metabolomics strategy that combines state-of-the-art data analysis tools and applied it to a human scalp metabolomics data set: skin swabs from healthy volunteers with normal or oily scalp (Sebumeter score 60-120, n = 33; Sebumeter score > 120, n = 41) were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), yielding four metabolomics data sets for reversed phase chromatography (C18) or hydrophilic interaction chromatography (HILIC) separation in electrospray ionization (ESI) + or - ionization mode. Following our data analysis strategy, we were able to obtain increasingly comprehensive structural and functional annotations, by applying the Global Natural Product Social Networking (M. Wang, J. J. Carver, V. V. Phelan, L. M. Sanchez, et al., Nat Biotechnol 34:828-837, 2016, https://doi.org/10.1038/nbt.3597), SIRIUS (K. Dührkop, M. Fleischauer, M. Ludwig, A. A. Aksenov, et al., Nat Methods 16:299-302, 2019, https://doi.org/10.1038/s41592-019-0344-8), and MicrobeMASST (S. ZuffaS, R. Schmid, A. Bauermeister, P. W, P. Gomes, et al., bioRxiv:rs.3.rs-3189768, 2023, https://doi.org/10.21203/rs.3.rs-3189768/v1) tools. We finally combined the metabolomics data with a corresponding metagenomic sequencing data set using MMvec (J. T. Morton, A. A. Aksenov, L. F. Nothias, J. R. Foulds, et. al., Nat Methods 16:1306-1314, 2019, https://doi.org/10.1038/s41592-019-0616-3), gaining insights into the metabolic niche of one of the most prominent microbes on the human skin, Staphylococcus epidermidis.IMPORTANCESystems biology research on host-associated microbiota focuses on two fundamental questions: which microbes are present and how do they interact with each other, their host, and the broader host environment? Metagenomics provides us with a direct answer to the first part of the question: it unveils the microbial inhabitants, e.g., on our skin, and can provide insight into their functional potential. Yet, it falls short in revealing their active role. Metabolomics shows us the chemical composition of the environment in which microbes thrive and the transformation products they produce. In particular, untargeted metabolomics has the potential to observe a diverse set of metabolites and is thus an ideal complement to metagenomics. However, this potential often remains underexplored due to the low annotation rates in MS-based metabolomics and the necessity for multiple experimental chromatographic and mass spectrometric conditions. Beyond detection, prospecting metabolites' functional role in the host/microbiome metabolome requires identifying the biological processes and entities involved in their production and biotransformations. In the present study of the human scalp, we developed a strategy to achieve comprehensive structural and functional annotation of the metabolites in the human scalp environment, thus diving one step deeper into the interpretation of "omics" data. Leveraging a collection of openly accessible software tools and integrating microbiome data as a source of functional metabolite annotations, we finally identified the specific metabolic niche of Staphylococcus epidermidis, one of the key players of the human skin microbiome.

Sequencing, assembly, and genomic annotation of Leucoagaricus gongylophorus LEU18496, a dikarya mutualistic species.

The basidiomycete fungus Leucoagaricus gongylophorus is able to grow in the fungus garden of leaf-cutter ants. This mutualistic interaction has driven the evolutionary adaptation of L. gongylophorus, shaping its metabolism to produce enzymes adept at lignocellulosic biomass degradation. In this study, we undertook the comprehensive sequencing, assembly, and functional annotation of the genome of L. gongylophorus strain LEU18496, mutualistic fungus of the Atta mexicana. Our genomic analyses revealed a distinctive bimodal nature to the genome: a predominant region characterized by AT enrichment and low genetic density, alongside a smaller region exhibiting higher GC content and higher genetic density. The presence of transposable elements (TEs) within the AT-enriched region suggests genomic compartmentalization, facilitating differential evolutionary rates. With a gene count of 6748, the assembled genome of L. gongylophorus LEU18496 surpasses previous reports for this fungal species. Inspection of genes associated with central metabolism unveiled a remarkable abundance of carbohydrate-active enzymes (CAZymes) and fungal oxidative lignin enzymes (FOLymes), underscoring their pivotal roles in the life cycle of this fungus.

Integrated bulk and scRNA sequence identified anoikis-related diagnostic biomarkers and potential association with immune infiltration in type A aortic dissection.

Type-A aortic dissection (TAAD) is common life-threatening cardiovascular diseases with high-morbidity and mortality but the concrete etiology of disease remains unclear, which might disturb or delay the early diagnosis for TAAD. Anoikis is a special form of programmed cell-death (PCD) induced by detachment of anchorage-dependent cells from the extracellular matrix (ECM) or neighboring cells, and has been widely applied to identify anoikis-related biomarkers for the prediction and prognosis in oncological fields. However, the specific roles of anoikis-related genes (ARGs) in TAAD remain unclear. In this study, we first identified and validated eight diagnostic ARGs for TAAD based on multiple RNA-sequence datasets, including CHEK2, HIF1A, HK2, HMGA1, SERPINA1, PTPN1, SLC2A1 and VEGFA. The comprehensive functional annotation was evaluated by the integrated functional enrichments analysis. We identified the activation of inflammatory-related pathways, metabolic reprogramming and angiogenesis, and the inhibition of cardiovascular development pathways in TAAD. Immune cell infiltration (ICI) analysis further demonstrated that innate immune-cells were more dominant than adaptive immune-cells in TAAD tissues, especially in macrophages, monocytes, activated-DC, NKT cells and CD56+dim NK cells. The cellular landscape was further validated by single-cell RNA sequence technology with significant associations with anoikis in TAAD patients. Four vital ARGs (HIF1A, HMGA1, SERPINA1 and VEGFA) were ultimately identified along with the changes of differentiation trajectory, and major expressions were conformably concentrated on Macro1-3, Mono1-2 and Mono4 subtypes. These findings provide a promising diagnostic biomarker for the accurately diagnosing the disease and would be helpful to further explore the potential pathogenesis with anoikis process for TAAD.

Linc2function: A Comprehensive Pipeline and Webserver for Long Non-Coding RNA (lncRNA) Identification and Functional Predictions Using Deep Learning Approaches.

Long non-coding RNAs (lncRNAs), comprising a significant portion of the human transcriptome, serve as vital regulators of cellular processes and potential disease biomarkers. However, the function of most lncRNAs remains unknown, and furthermore, existing approaches have focused on gene-level investigation. Our work emphasizes the importance of transcript-level annotation to uncover the roles of specific transcript isoforms. We propose that understanding the mechanisms of lncRNA in pathological processes requires solving their structural motifs and interactomes. A complete lncRNA annotation first involves discriminating them from their coding counterparts and then predicting their functional motifs and target bio-molecules. Current in silico methods mainly perform primary-sequence-based discrimination using a reference model, limiting their comprehensiveness and generalizability. We demonstrate that integrating secondary structure and interactome information, in addition to using transcript sequence, enables a comprehensive functional annotation. Annotating lncRNA for newly sequenced species is challenging due to inconsistencies in functional annotations, specialized computational techniques, limited accessibility to source code, and the shortcomings of reference-based methods for cross-species predictions. To address these challenges, we developed a pipeline for identifying and annotating transcript sequences at the isoform level. We demonstrate the effectiveness of the pipeline by comprehensively annotating the lncRNA associated with two specific disease groups. The source code of our pipeline is available under the MIT licensefor local use by researchers to make new predictions using the pre-trained models or to re-train models on new sequence datasets. Non-technical users can access the pipeline through a web server setup.

Retraction of: Hayai-Annotation Plants: an ultra-fast and comprehensive functional gene annotation system in plants

Retraction of: Hayai-Annotation Plants: an ultra-fast and comprehensive functional gene annotation system in plants

Genome-wide multi-omics analysis reveals the nutrient-dependent metabolic features of mucin-degrading gut bacteria

ABSTRACT The prevalence and occurrence of mucin-degrading (MD) bacteria, such as Akkermansia muciniphila and Ruminococcus gnavus, is highly associated with human health and disease states. However, MD bacterial physiology and metabolism remain elusive. Here, we assessed functional modules of mucin catabolism, through a comprehensive bioinformatics-aided functional annotation, to identify 54 A. muciniphila genes and 296 R. gnavus genes. The reconstructed core metabolic pathways coincided with the growth kinetics and fermentation profiles of A. muciniphila and R. gnavus grown in the presence of mucin and its constituents. Genome-wide multi-omics analyses validated the nutrient-dependent fermentation profiles of the MD bacteria and identified their distinct mucolytic enzymes. The distinct metabolic features of the two MD bacteria induced differences in the metabolite receptor levels and inflammatory signals of the host immune cells. In addition, in vivo experiments and community-scale metabolic modeling demonstrated that different dietary intakes influenced the abundance of MD bacteria, their metabolic fluxes, and gut barrier integrity. Thus, this study provides insights into how diet-induced metabolic differences in MD bacteria determine their distinct physiological roles in the host immune response and the gut ecosystem.

Comprehensive proteomic characterization and functional annotation of Siberian sturgeon seminal plasma proteins

Siberian sturgeon (Acipenser baerii) is considered the most valuable species in aquaculture. The uniqueness of sturgeon reproduction implicates the need for studying semen composition at the protein level. Seminal plasma supports and protects the viability, motility and fertilizing capacity of spermatozoa by creating the optimal environment for storage and might be a rich source of biomarkers of reproductive physiology and/or disorders in male fishes. To our knowledge, there are no reports on the in-depth characterization of sturgeon seminal plasma proteins. The present study is the first to describe the in-depth proteomic characterization of Siberian sturgeon seminal plasma using two complementary proteomic approaches: gel-based (2DE and 2D blue native (BN)/SDS–PAGE) and gel-free (LC–MS/MS). LC–MS/MS allowed the identification of 657 proteins and 339 protein spots were identified after 2DE (almost 60% were present in various proteoforms). Combining the two proteomic strategies, we identified 665 proteins with high confidence (false positive rate below 1%), producing the largest catalogue of proteins from sturgeon seminal plasma to date. For the first time, we demonstrated interactions between seminal plasma proteins; four multiprotein complexes (MC1-MC4) were identified after 2D BN/SDS–PAGE, including (MC1) serotransferrin-2 (TF) and fish-egg lectin (FEL); (MC2) serum albumin 2 (ALB) and retinol-binding protein 4 (RBP4); (MC3) ALB and TF; and (MC4) apolipoprotein A-I (APOA1), riboflavin-binding protein (RfBP) and myoglobin (MB). BN/SDS–PAGE also revealed that immunoglobulin and TF formed homomultimeric (dimer, trimer, tetramer and pentamer) complexes in seminal plasma. ALB, TF, beta-Ala-His dipeptidase (CNDP1), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), IGH, APOA1, hemopexin (HPX), type-4 ice-structuring protein (AFP4), FEL, RfBP, ovochymase 2 (OVCH2) and glycogen phosphorylase, liver form-like (PYGL) were selected as major seminal plasma proteins. The functional analysis of the identified proteins indicated their involvement mainly in immune system processes and response to stimulus, metabolism, vesicle-mediated transport, proteolysis, and cadherin binding involved in cell–cell adhesion. Moreover, 69 proteins were associated with reproductive processes, including spermatogenesis, fertilization, acrosomal reaction and sperm motility. Comparative proteomic analysis of sturgeon seminal plasma showed common proteins between fish and humans and 172 proteins specific for sturgeons, which may reflect the specificity of sturgeon reproduction. To conclude, this integrative proteomic view offers a deeper insight into the physiological function of seminal plasma and processes occurring in the sturgeon reproductive tract. The availability of a catalogue of sturgeon seminal plasma proteins opens the way to future research into development of new biomarkers and possible application in the improvement of methods of controlled reproduction. The mass spectrometry proteomics data have been deposited into ProteomeXchange with the identifier PXD035351.

New insights into genome annotation in Podospora anserina through re-exploiting multiple RNA-seq data

BackgroundPublicly available RNA-seq datasets are often underused although being helpful to improve functional annotation of eukaryotic genomes. This is especially true for filamentous fungi genomes which structure differs from most well annotated yeast genomes. Podospora anserina is a filamentous fungal model, which genome has been sequenced and annotated in 2008. Still, the current annotation lacks information about cis-regulatory elements, including promoters, transcription starting sites and terminators, which are instrumental to integrate epigenomic features into global gene regulation strategies.ResultsHere we took advantage of 37 RNA-seq experiments that were obtained in contrasted developmental and physiological conditions, to complete the functional annotation of P. anserina genome. Out of the 10,800 previously annotated genes, 5’UTR and 3’UTR were defined for 7554, among which, 3328 showed differential transcriptional signal starts and/or transcriptional end sites. In addition, alternative splicing events were detected for 2350 genes, mostly due alternative 3’splice sites and 1732 novel transcriptionally active regions (nTARs) in unannotated regions were identified.ConclusionsOur study provides a comprehensive genome-wide functional annotation of P. anserina genome, including chromatin features, cis-acting elements such as UTRs, alternative splicing events and transcription of non-coding regions. These new findings will likely improve our understanding of gene regulation strategies in compact genomes, such as those of filamentous fungi. Characterization of alternative transcripts and nTARs paves the way to the discovery of putative new genes, alternative peptides or regulatory non-coding RNAs.

FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.

Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizesand visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene-and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.

TripletProt: Deep Representation Learning of Proteins Based On Siamese Networks.

Pretrained representations have recently gained attention in various machine learning applications. Nonetheless, the high computational costs associated with training these models have motivated alternative approaches for representation learning. Herein we introduce TripletProt, a new approach for protein representation learning based on the Siamese neural networks. Representation learning of biological entities which capture essential features can alleviate many of the challenges associated with supervised learning in bioinformatics. The most important distinction of our proposed method is relying on the protein-protein interaction (PPI) network. The computational cost of the generated representations for any potential application is significantly lower than comparable methods since the length of the representations is significantly smaller than that in other approaches. TripletProt offers great potentials for the protein informatics tasks and can be widely applied to similar tasks. We evaluate TripletProt comprehensively in protein functional annotation tasks including sub-cellular localization (14 categories) and gene ontology prediction (more than 2000 classes), which are both challenging multi-class, multi-label classification machine learning problems. We compare the performance of TripletProt with the state-of-the-art approaches including a recurrent language model-based approach (i.e., UniRep), as well as a protein-protein interaction (PPI) network and sequence-based method (i.e., DeepGO). Our TripletProt showed an overall improvement of F1 score in the above mentioned comprehensive functional annotation tasks, solely relying on the PPI network. Availability: The source code and datasets are available at https://github.com/EsmaeilNourani/TripletProt.

Neuromaps: structural and functional interpretation of brain maps

Imaging technologies are increasingly used to generate high-resolution reference maps of brain structure and function. Comparing experimentally generated maps to these reference maps facilitates cross-disciplinary scientific discovery. Although recent data sharing initiatives increase the accessibility of brain maps, data are often shared in disparate coordinate systems, precluding systematic and accurate comparisons. Here we introduce neuromaps, a toolbox for accessing, transforming and analyzing structural and functional brain annotations. We implement functionalities for generating high-quality transformations between four standard coordinate systems. The toolbox includes curated reference maps and biological ontologies of the human brain, such as molecular, microstructural, electrophysiological, developmental and functional ontologies. Robust quantitative assessment of map-to-map similarity is enabled via a suite of spatial autocorrelation-preserving null models. neuromaps combines open-access data with transparent functionality for standardizing and comparing brain maps, providing a systematic workflow for comprehensive structural and functional annotation enrichment analysis of the human brain.

Identification of potential functional variants and genes at 18q21.1 associated with the carcinogenesis of colorectal cancer.

Genome-wide association studies (GWAS) have identified more than 160 susceptibility loci for colorectal cancer (CRC). The effects of these variants, particularly their mechanisms, however, remain unclear. In this study, a comprehensive functional annotation of CRC-related GWAS signals was firstly conducted to identify the potential causal variants. We found that the SNP rs7229639 in intron 3 of SMAD7 at 18q21.1 might serve as a putative functional variant in CRC. The SNP rs7229639 is located in a region with evidence of regulatory potential. Dual-luciferase reporter assays revealed that three other SNPs (rs77544449, rs60385309 and rs72917785), in strong linkage disequilibrium (LD) with rs7229639, exhibited allele-specific enhancer activity, of which one of the target genes may conceivably be LIPG, as suggested by eQTL association data and Hi-C data. We also verified that LIPG promoted malignancy of CRC cells in vitro, with supporting clinical data indicating that LIPG is upregulated and correlated with a poor prognosis in CRC. Finally, pitavastatin was observed to exhibit an anti-CRC activity and modest inhibition of LIPG mRNA levels. Collectively, our data suggest that these functional variants at 18q21.1 are involved in the pathogenesis of CRC by modulating enhancer activity, and possibly LIPG expression, thus indicating a promising therapeutic target for CRC. The results of functional annotation in our investigation could also serve as an inventory for CRC susceptibility SNPs and offer guides for post-GWAS downstream functional studies.

De novo Transcriptome Assembly of Senna occidentalis Sheds Light on the Anthraquinone Biosynthesis Pathway.

Senna occidentalis is an annual leguminous herb that is rich in anthraquinones, which have various pharmacological activities. However, little is known about the genetics of S. occidentalis, particularly its anthraquinone biosynthesis pathway. To broaden our understanding of the key genes and regulatory mechanisms involved in the anthraquinone biosynthesis pathway, we used short RNA sequencing (RNA-Seq) and long-read isoform sequencing (Iso-Seq) to perform a spatial and temporal transcriptomic analysis of S. occidentalis. This generated 121,592 RNA-Seq unigenes and 38,440 Iso-Seq unigenes. Comprehensive functional annotation and classification of these datasets using public databases identified unigene sequences related to major secondary metabolite biosynthesis pathways and critical transcription factor families (bHLH, WRKY, MYB, and bZIP). A tissue-specific differential expression analysis of S. occidentalis and measurement of the amount of anthraquinones revealed that anthraquinone accumulation was related to the gene expression levels in the different tissues. In addition, the amounts and types of anthraquinones produced differ between S. occidentalis and S. tora. In conclusion, these results provide a broader understanding of the anthraquinone metabolic pathway in S. occidentalis.

TCF11 Has a Potent Tumor-Repressing Effect Than Its Prototypic Nrf1α by Definition of Both Similar Yet Different Regulatory Profiles, With a Striking Disparity From Nrf2.

Nrf1 and Nrf2, as two principal CNC-bZIP transcription factors, regulate similar but different targets involved in a variety of biological functions for maintaining cell homeostasis and organ integrity. Of note, the unique topobiological behavior of Nrf1 makes its functions more complicated than Nrf2, because it is allowed for alternatively transcribing and selectively splicing to yield multiple isoforms (e.g., TCF11, Nrf1α). In order to gain a better understanding of their similarities and differences in distinct regulatory profiles, all four distinct cell models for stably expressing TCF11, TCF11ΔN, Nrf1α or Nrf2 have been herein established by an Flp-In™ T-REx™-293 system and then identified by transcriptomic sequencing. Further analysis revealed that Nrf1α and TCF11 have similar yet different regulatory profiles, although both contribute basically to positive regulation of their co-targets, which are disparate from those regulated by Nrf2. Such disparity in those gene regulations by Nrf1 and Nrf2 was further corroborated by scrutinizing comprehensive functional annotation of their specific and/or common target genes. Conversely, the mutant TCF11ΔN, resulting from a deletion of the N-terminal amino acids 2–156 from TCF11, resembles Nrf2 with the largely consistent structure and function. Interestingly, our further experimental evidence demonstrates that TCF11 acts as a potent tumor-repressor relative to Nrf1α, albeit both isoforms possess a congruous capability to prevent malignant growth of tumor and upregulate those genes critical for improving the survival of patients with hepatocellular carcinoma.

Genome-wide CRISPR/Cas9 deletion screen defines mitochondrial gene essentiality and identifies routes for tumour cell viability in hypoxia

Mitochondria are typically essential for the viability of eukaryotic cells, and utilize oxygen and nutrients (e.g. glucose) to perform key metabolic functions that maintain energetic homeostasis and support proliferation. Here we provide a comprehensive functional annotation of mitochondrial genes that are essential for the viability of a large panel (625) of tumour cell lines. We perform genome-wide CRISPR/Cas9 deletion screening in normoxia-glucose, hypoxia-glucose and normoxia-galactose conditions, and identify both unique and overlapping genes whose loss influences tumour cell viability under these different metabolic conditions. We discover that loss of certain oxidative phosphorylation (OXPHOS) genes (e.g. SDHC) improves tumour cell growth in hypoxia-glucose, but reduces growth in normoxia, indicating a metabolic switch in OXPHOS gene function. Moreover, compared to normoxia-glucose, loss of genes involved in energy-consuming processes that are energetically demanding, such as translation and actin polymerization, improve cell viability under both hypoxia-glucose and normoxia-galactose. Collectively, our study defines mitochondrial gene essentiality in tumour cells, highlighting that essentiality is dependent on the metabolic environment, and identifies routes for regulating tumour cell viability in hypoxia.

Reciprocal interaction between depression and pain: results from a comprehensive bidirectional Mendelian randomization study and functional annotation analysis.

To understand a putative causal link for depression and pain, we retrieved summary statistics from genome-wide association studies conducted for pain at 7 different body sites (N = 151,922-226,683) and major depression disorder (MDD, Ncase/control = 246,363/561,190). We conducted a bidirectional Mendelian randomization analysis using distinct genome-wide association studies-identified single nucleotide polymorphisms for each trait as instrumental variables and performed several sensitivity analyses to verify Mendelian randomization assumptions. We also conducted functional annotation analysis using 396 tissue-specific annotations from the roadmap project. Across 7 different body sites, genetic predisposition to depression was associated with pain at the neck/shoulder (odds ratio [OR] = 1.08 per one log-unit increase in depression risk, 95% confidence interval [CI]: 1.06-1.10), back (OR = 1.05, 95% CI: 1.04-1.07), abdominal/stomach (OR = 1.03, 95% CI: 1.02-1.04), as well as headache (OR = 1.10, 95% CI: 1.07-1.12), but not with pain on the face, hip, and knee. In the reverse direction, genetically instrumented multisite chronic pain (OR = 1.78 per one increment in the number of pain site, 95% CI: 1.51-2.11) and headache (OR = 1.55 per one log-unit increase in headache risk, 95% CI = 1.13-2.10) were associated with MDD. Functional annotation analysis showed differential clustering patterns where depression clustered closely with headache and neck/shoulder pain, exhibiting substantial brain tissue enrichment. Our study indicates that depression is a causal risk factor for headache and pain localized at neck/shoulder, back, and abdominal/stomach, rather than pain at face, hip, and knee, and suggests common neurological pathologies underlying the development of depression, headache, and neck/shoulder pain.

MicrobeAnnotator: a user-friendly, comprehensive functional annotation pipeline for microbial genomes

BackgroundHigh-throughput sequencing has increased the number of available microbial genomes recovered from isolates, single cells, and metagenomes. Accordingly, fast and comprehensive functional gene annotation pipelines are needed to analyze and compare these genomes. Although several approaches exist for genome annotation, these are typically not designed for easy incorporation into analysis pipelines, do not combine results from different annotation databases or offer easy-to-use summaries of metabolic reconstructions, and typically require large amounts of computing power for high-throughput analysis not available to the average user.ResultsHere, we introduce MicrobeAnnotator, a fully automated, easy-to-use pipeline for the comprehensive functional annotation of microbial genomes that combines results from several reference protein databases and returns the matching annotations together with key metadata such as the interlinked identifiers of matching reference proteins from multiple databases [KEGG Orthology (KO), Enzyme Commission (E.C.), Gene Ontology (GO), Pfam, and InterPro]. Further, the functional annotations are summarized into Kyoto Encyclopedia of Genes and Genomes (KEGG) modules as part of a graphical output (heatmap) that allows the user to quickly detect differences among (multiple) query genomes and cluster the genomes based on their metabolic similarity. MicrobeAnnotator is implemented in Python 3 and is freely available under an open-source Artistic License 2.0 from https://github.com/cruizperez/MicrobeAnnotator.ConclusionsWe demonstrated the capabilities of MicrobeAnnotator by annotating 100 Escherichia coli and 78 environmental Candidate Phyla Radiation (CPR) bacterial genomes and comparing the results to those of other popular tools. We showed that the use of multiple annotation databases allows MicrobeAnnotator to recover more annotations per genome compared to faster tools that use reduced databases and is computationally efficient for use in personal computers. The output of MicrobeAnnotator can be easily incorporated into other analysis pipelines while the results of other annotation tools can be seemingly incorporated into MicrobeAnnotator to generate summary plots.

HybridMine: A Pipeline for Allele Inheritance and Gene Copy Number Prediction in Hybrid Genomes and Its Application to Industrial Yeasts

Genome-scale computational approaches are opening opportunities to model and predict favorable combination of traits for strain development. However, mining the genome of complex hybrids is not currently an easy task, due to the high level of redundancy and presence of homologous. For example, Saccharomyces pastorianus is an allopolyploid sterile yeast hybrid used in brewing to produce lager-style beers. The development of new yeast strains with valuable industrial traits such as improved maltose utilization or balanced flavor profiles are now a major ambition and challenge in craft brewing and distilling industries. Moreover, no genome annotation for most of these industrial strains have been published. Here, we developed HybridMine, a new user-friendly, open-source tool for functional annotation of hybrid aneuploid genomes of any species by predicting parental alleles including paralogs. Our benchmark studies showed that HybridMine produced biologically accurate results for hybrid genomes compared to other well-established software. As proof of principle, we carried out a comprehensive structural and functional annotation of complex yeast hybrids to enable system biology prediction studies. HybridMine is developed in Python, Perl, and Bash programming languages and is available in GitHub.

Transcriptome profiling helps to elucidate the mechanisms of ripening and epidermal senescence in passion fruit (Passiflora edulia Sims).

Passion fruit (Passiflora edulia Sims), an important tropical and subtropical species, is classified as a respiration climacteric fruit, and its quality deteriorates rapidly after harvest. To elucidate the mechanisms involved in ripening and rapid fruit senescence, phytochemical characteristic analysis and RNA sequencing were performed in purple passion fruit with different treatments, that is, 1-methylcyclopropene (1-MCP) and preservative film (PF). Comprehensive functional annotation and KEGG enrichment analysis showed that starch and sucrose metabolism, plant hormone signal transduction, phenylpropanoid biosynthesis, flavonoid biosynthesis, and carotenoid biosynthesis were involved in fruit ripening. Treatment with PF and 1-MCP significantly affected the transcription levels of passion fruit during postharvest storage. A large number of differentially expressed unigenes (DEGs) were identified as significantly enriched in starch and sucrose metabolism, plant hormone signal transduction and phenylpropanoid biosynthesis at the postharvest stage. The PF and 1-MCP treatments increased superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) gene expression levels and enzyme activities, accelerated lignin accumulation, and decreased β-galactosidase (β-Gal), polygalacturonase (PG) and cellulose activities and gene expression levels to delay cell wall degradation during fruit senescence. The RNA sequencing data for cell wall metabolism and hormone signal transduction pathway-related unigenes were verified by RT-qPCR. The results of this study indicate that the cell wall metabolism and hormone signaling pathways are closely related to passion fruit ripening. PF and 1-MCP treatment might inhibit ethylene signaling and regulate cell wall metabolism pathways to inhibit cell wall degradation. Our results demonstrate the involvement of ripening- and senescence-related networks in passion fruit ripening and may establish a foundation for future research investigating the effects of PF and 1-MCP treatment on fruit ripening.