Biology subjects

Almeida-Silva, F.

Publications and source records attributed to Almeida-Silva, F..

At least 19 recordsLinked to original sources

bioRxiv2026

GraphExperiment: infrastructure for high-dimensional quantitative data and associated networks in R/Bioconductor

Networks are widely used to represent relationships among features (e.g. genes, proteins, and microbial taxa) and among observations (e.g. cells, samples, and species) in omics data, as well as their neighborhoods. The Bioconductor ecosystem provides users and developers with modular and interoperable software tools by relying on standard data structures that are reused across packages. However, Bioconductor lacks a standard data structure to store such networks together with the quantitative data from which they are inferred. Here, we present GraphExperiment, an R/Bioconductor package that provides an S4 class extending SingleCellExperiment with containers for feature- level (rowGraphs) and observation-level (colGraphs) networks stored as igraph objects. Networks are kept in sync with assays, row and column metadata, allowing the simultaneous manipulation of quantitative data and graphs. We demonstrate GraphExperiment in seven use cases covering bulk and single-cell transcriptomics, single-cell proteomics, microbiome, and comparative genomics data, with networks ranging from gene coexpression and protein co-abundance networks to cell-cell communication and phylogenetic networks. GraphExperiment is available on Bioconductor (https://bioconductor.org/packages/GraphExperiment).

bioinformatics↗

bioRxiv2026

The Arabidopsis PAL3 is a carboxy-tyrosine ammonia lyase

Phenylalanine ammonia lyase (PAL) catalyses the deamination of L-phenylalanine, which is the first step of the plant-specific phenylpropanoid pathway. Its position at the intersection of primary and specialized metabolism, combined with its important role in plant growth and adaptive stress response, has made it a subject of extensive studies. We identified key amino acids in the catalytic pocket of several PAL enzymes, including PAL3 of Arabidopsis, that are different from the canonical PAL sites, suggesting these enzymes have a different substrate specificity and have been miscategorised for decades. By combining untargeted metabolomics with enzyme assays, we discovered that PAL3 converts 3-carboxy-tyrosine into carboxy-p-coumaric acid. Based on this specific function, we propose to denote it as a 3-carboxy-tyrosine ammonia lyase (CAL). In addition to its discovery as a novel enzyme class, paving the way for biotechnological applications, we introduce the carboxy-phenylpropanoids as a new class of specialised metabolites.

biochemistry↗

bioRxiv2025

Microsynteny Analysis Clarifies the Early Diversification of Cypriniform Fishes

While genomic data are powerfully informative for phylogenetic inference, traditional sequence-based analyses can be confounded by issues like homoplasy and incomplete lineage sorting, leaving deep nodes unresolved. Synteny, the conservation of gene order along a chromosome, presents a promising alternative source of phylogenetic information that is potentially less prone to these issues. Here we compare sequence and synteny phylogenetic phylogenomic approaches to unravel the evolutionary history of Cypriniformes, one of the most species-rich lineages of freshwater fishes. This clade has been plagued by uncertainty, particularly concerning the phylogenetic relationships between its four major subclades: Gyrinocheilidae (algae eaters), Catostomidae (suckers), Cobitoidei (loaches), and Cyprinoidei (minnows and carps). Phylogenomic approaches require high-quality genomic resources, which have been lacking for the family Gyrinocheilidae, a key lineage for understanding cypriniform evolution. To address this, we generated the first chromosome-level genome assembly and annotation for the Chinese Algae Eater (Gyrinocheilus aymonieri). We utilized this new genome along with 42 other fish genomes to conduct comprehensive phylogenomic analyses and compare results from sequence-based methods with a microsynteny-based approach. Although chromosome-level macrosynteny is broadly conserved among cypriniforms, we demonstrate that microsynteny has impressive power to resolve deep phylogenetic nodes. Both sequence-based and microsynteny-based analyses find that Gyrinocheilidae is the sister lineage to all other cypriniforms, resolving a long-standing phylogenetic point of contention. However, while sequence-based analyses provided weak support for the relationships among the remaining subclades, our microsynteny analysis revealed a novel and strongly supported sister relationship between Catostomidae and Cyprinoidei. This conclusion is supported by a 3- to 12-fold greater number of shared microsynteny clusters (synapomorphies) compared to the alternative topologies. We also demonstrate that microsynteny synapomorphies often arise from gene family expansions. Conservation of synteny concentrated in specific genomic regions may harbor the genomic underpinnings of the unique aspects of these clades and have played an important role in the evolutionary history of these taxa. Together, these results provide a robust phylogenomic backbone for Cypriniformes. More broadly, our findings highlight the power of microsynteny to resolve recalcitrant phylogenetic nodes where sequence data is uninformative, while also underscoring the critical importance of high-quality reference genomes, as our work also shows that including fragmented assemblies can lead to spurious results. Beyond phylogenomics, our results also provide a functional genomics glimpse into how conserved, clade-specific blocks of collinear genes (synteny synapomorphies) might contribute to what makes this hyperdiverse clade so unique and evolutionarily successful.

evolutionary biology↗

bioRxiv2025

Gene family expansions and nodule-specific expression patterns reveal the recruitment of Beta-Glucosidases and Cytochrome P450 genes to nodulation in soybean

Nodulation is a symbiotic interaction between legumes and rhizobia that is essential for biological nitrogen fixation and regulated by complex gene networks, which are partially shaped by whole-genome duplication (WGD) events. Although many core nodulation genes have been identified, the contribution of lineage-specific gene expansions and WGD-derived duplicates remains poorly understood. In this study, we performed a genome-wide analysis of gene family expansions in legumes and integrated expression data from over 5,000 soybean RNA-Seq samples to identify genes involved in nodulation. Our analysis not only recovered well-characterized nodulation genes among the most expanded families but also revealed several differentially expressed genes in nodules, including nodulins, aspartic proteases, NLP proteins, and GRAS transcription factors. Notably, we identified previously unreported {beta}-glucosidase and cytochrome P450 genes with high nodule-specific expression, suggesting their involvement as novel components of the nodulation machinery.

plant biology↗

bioRxiv2025

Artemisia Database: A Comprehensive Resource for Gene Expression and Functional Insights in Artemisia annua

Artemisia annua is renowned for producing artemisinin, a compound that revolutionized malaria treatment and holds therapeutic promise for other diseases, including cancer and diabetes. However, low natural yields of artemisinin remain a major bottleneck, necessitating a deeper understanding of the genetic and regulatory networks involved in its biosynthesis. Although several transcriptomic studies on A. annua exist, they are often limited in scope, and a comprehensive, tissue-resolved gene expression resource has been lacking. Here, we present the Artemisia Database (Artemisia-DB)--a high-resolution expression atlas constructed from an extensive integration of publicly available RNA-seq datasets. The database provides transcript- and gene-level abundance estimates across major tissues and includes functional annotations such as Gene Ontology (GO) terms, KEGG pathways, and InterPro domains. As a case study, we investigated the coexpression profile of HMGR (3-hydroxy-3-methylglutaryl- CoA reductase), a key enzyme in the mevalonate pathway and an early step in artemisinin biosynthesis. Coexpression analysis in leaf tissue revealed a subset of Auxin Response Factor (ARF) transcription factors strongly correlated to HMGR. This finding suggests a potential regulatory link between auxin signaling and artemisinin biosynthesis, providing new hypotheses for functional validation. Artemisia-DB is freely accessible at https://artemisia-db.com and offers an interactive interface for exploring expression data, functional annotations, transcription factors, CRISPR targets, and more. By combining high-quality transcriptome data with regulatory and functional insights, Artemisia-DB serves as a valuable resource for the plant research community and facilitates deeper investigation into the transcriptional dynamics and specialized metabolism of A. annua.

bioinformatics↗

bioRxiv2025

Gene expression divergence following gene and genome duplications in spatially resolved plant transcriptomes

Gene and genome duplications are key drivers of plant genome evolution, expanding genetic repertoires and facilitating functional innovation. However, genes originating from different duplication mechanisms undergo different outcomes, especially at the expression level. Previous studies have demonstrated that segmental or whole-genome duplications generate duplicates with similar and somewhat redundant expression profiles across multiple tissues, while other duplicates display increased divergence, ultimately leading to functional innovations. However, little is known about how duplicates diverge in expression across cell types in a single tissue. Here, we used high-resolution spatial transcriptomic data from five species (Arabidopsis thaliana, Glycine max, Phalaenopsis aphrodite, Zea mays, and Hordeum vulgare) to investigate the evolution of gene expression following gene duplications. We found that genes originating from segmental or whole-genome duplications display increased expression levels, expression breadths, spatial variability, and number of coexpression partners. Duplication mechanisms that preserve cis-regulatory landscapes typically generate paralogs with more preserved expression profiles, but such differences by duplication mode disappear over time. Expression divergence also depends on gene functions, with dosage-sensitive gene families displaying highly preserved expression profiles, while families involved in more specialized processes (e.g., flowering and phytohormone biosynthesis) display increased divergence. Paralogs originating from large-scale (including whole-genome) duplications display redundant and/or overlapping expression profiles, indicating functional redundancy and/or subfunctionalization, while small-scale duplicates diverge asymmetrically, indicating neofunctionalization. Collectively, our findings provide new insights into the tempo and mode of gene expression evolution, helping understand how gene and genome duplications shape cell identities.

evolutionary biology↗

bioRxiv2025

Comprehensive annotation of olfactory and gustatory receptor genes and transposable elements revealed their evolutionary dynamics in aphids

Understanding the molecular evolution of genes involved in parasite adaptation and the role of transposable elements (TEs) in driving their diversification is key to unraveling how populations adapt to their environments. In phytophagous insects like aphids, olfactory (OR) and gustatory receptor (GR) genes are crucial for host recognition, yet their post-duplication evolution remains insufficiently explored. Here, we analyzed 521 OR and 399 GR genes, alongside TEs, across 12 aphid genomes with varying host ranges. Aphid lineages with broader host ranges exhibited higher evolutionary rates, driven by gene family expansions linked to host interaction, including lipid metabolism, immune function, and transposase activity. The evolution of OR and GR genes post-duplication was shaped by diversifying selection, with bursts of positive selection followed by long periods of purifying selection, consistent with adaptation to new hosts. OR and GR genes originated from proximal and tandem duplications, with younger TE activity enriched near these genes compared to other genomic regions, suggesting a role for TEs in catalyzing tandem duplications and fueling diversification. The star-like topology of the OR phylogenetic tree, low synteny, and recent TE activity around OR genes support a faster evolutionary rate for ORs than GRs - a trend observed in other insect taxa. This study provides insights into molecular mechanisms underlying host adaptation in aphids and presents the first high-quality genome assembly of Dysaphis plantaginea, a major apple pest, with a comprehensive annotation of chemosensory genes and TEs. These resources offer a foundation for research on aphid genome evolution, insect-plant interactions.

molecular biology↗

bioRxiv2024

The Rise of Polyploids During Environmental Catastrophes

Polyploidy, or whole-genome duplication (WGD), serves as both a significant evolutionary force and a potential evolutionary dead end, occurring extensively across the tree of life, particularly among angiosperms. Despite the prevalence of polyploid organisms, instances of ancient polyploidy are surprisingly rare, presenting a paradox that remains poorly understood. In this study, we constructed a comprehensive genomic dataset of 470 angiosperm species to address this issue. We developed a highly congruent evolutionary timescale and dated 132 ancient WGD events that are non-randomly distributed, revealing a clustering around pivotal periods of environmental upheaval and extinction. Notably, our findings highlight a strong correlation between waves of paleopolyploidization and significant events such as the Middle Miocene Disruption, the Eocene-Oligocene transition (EOT), the Paleocene-Eocene Thermal Maximum (PETM), the Cretaceous-Paleogene (K-Pg) extinction, and different oceanic anoxic (OAE) events, several of which can be linked to extinction events impacting flowering plant genera. By integrating multiple lines of evidence, we propose that polyploid organisms have an increased chance of survival during times of great environmental turmoil, a conclusion with important implications in the context of contemporary climate change and rapid global warming.

evolutionary biology↗

bioRxiv2024

Cannabis Expression Atlas: a comprehensive resource for integrative analysis of Cannabis sativa L. gene expression

Cannabis sativa L., a plant originating from Central Asia, is a versatile crop with applications spanning textiles, construction, pharmaceuticals, and food products. This study aimed to compile and analyze publicly available Cannabis RNA-Seq data and develop an integrated database tool to help advance Cannabis research in various topics such as fiber production, cannabinoid biosynthesis, sex determination, and plant development. We identified 515 publicly available RNA-Seq samples that, after stringent quality control, resulted in a high-quality dataset of 394 samples. Utilizing the Jamaican Lion genome as reference, we constructed a comprehensive database and developed the Cannabis Expression Atlas (https://cannatlas.venanciogroup.uenf.br/), a web application for visualization of gene expression, annotation, and functional classification. Key findings include the quantification of 27,640 Cannabis genes and their classification into seven expression categories: not-expressed, low-expressed, housekeeping, tissue-specific, group-enriched, mixed, and expressed-in-all tissues. The study revealed substantial variability and coherence in gene expression across different tissues and chemotypes. We found 2,382 tissue-specific genes, including 177 transcription factors.. The Cannabis Expression Atlas constitutes a valuable tool for exploring gene expression patterns and offers insights into Cannabis biology, supporting research in plant breeding, genetic engineering, biochemistry, and functional genomics.

plant biology↗

bioRxiv2024

Asymmetric genome merging leads to gene expression novelty through nucleo-cytoplasmic disruptions and transcriptomic shock in Chlamydomonas triploids

Genome merging is a common phenomenon in many organisms, causing a wide range of consequences on phenotype, adaptation, and gene expression, among other effects, yet its broader implications are not well understood. Two consequences of genome merging on gene expression remain poorly understood: dosage effects and evolution of expression. In this study, we employed Chlamydomonas reinhardtii as a model to investigate the effects of asymmetric genome merging by crossing a diploid with a haploid strain to create a novel triploid line. Five independent clonal lineages derived from this triploid line were evolved for 425 asexual generations in a laboratory natural selection (LNS) experiment. Utilizing fitness assays, qPCR, and RNA-Seq, we assessed the immediate consequences of genome merging and subsequent evolution over time. Our findings reveal substantial alterations in gene expression, protein homeostasis (proteostasis) and cytonuclear stoichiometry. Notably, gene expression exhibited expression level dominance and transgressivity (i.e., expression level higher or lower than either parent). Ongoing expression level dominance and a pattern of "functional dominance" from the haploid parent was observed, alongside remarkable stability in expression patterns across generations. Despite major nucleo-cytoplasmic disruptions, enhanced fitness was detected in the triploid strain. By comparing gene expression across generations, our results indicate that proteostasis restoration is a critical component of rapid adaptation following genome merging in Chlamydomonas reinhardtii and possibly other systems.

evolutionary biology↗

bioRxiv2024

Multiomic analysis of genes related to oil traits in legumes provide insights into lipid metabolism and oil richness in soybean

Soybean (Glycine max) and common bean (Phaseolus vulgaris) diverged approximately 19 million years ago. While these species share a whole-genome duplication (WGD), the Glycine lineage experienced a second, independent WGD. Despite the significance of these WGDs, their impact on gene families related to oil-traits remains poorly understood. Here, we report an in-depth investigation of oil-related gene families in soybean, common bean, and twenty-eight other legume species. We adopted a systematic approach that included transcriptome and co-expression analysis, identification of orthologous groups, gene duplication modes and evolutionary rates, and family expansions and contractions. We curated a list of oil candidate genes and found that 91.5% of the families containing these genes expanded in soybean in comparison to common bean. Notably, we observed an expansion of triacylglycerol (TAG) biosynthesis ([~]3:1) and an erosion of TAG degradation ([~]1.4:1) families in soybean in comparison to common bean. In addition, TAG degradation genes were two-fold more expressed in common bean than in soybean, suggesting that oil degradation is also important for the sharply contrasting seed oil contents in these species. We found 17 transcription factor hub genes that are likely regulators of lipid metabolism. Finally, we inferred expanded and contracted families and correlated these patterns with oil content found in different legume species. In summary, our results do not only shed light on the evolution of oil metabolism genes in soybean, but also present multifactorial evidence supporting the prioritization of candidates for crop improvement.

plant biology↗

bioRxiv2024

HybridExpress: an R/Bioconductor package for comparative transcriptomic analyses of hybrids and their progenitors

Hybridization, the process of crossing individuals from diverse genetic backgrounds, plays a pivotal role in evolution, biological invasiveness, and crop breeding. At the transcriptional level, hybridization often leads to complex non-additive effects, presenting challenges for understanding its consequences. Although standard transcriptomic analyses exist to compare hybrids to their progenitors, such analyses have not been implemented in a software package, hindering reproducibility. Here, we introduce HybridExpress, an R/Bioconductor package designed to facilitate the analysis, visualization, and comparison of gene expression patterns in hybrid triplets (hybrids and their progenitors). HybridExpress provides users with a user-friendly and comprehensive workflow that includes all standard comparative analyses steps, including data normalization, calculation of midparent expression values, sample clustering, expression-based gene classification into categories and classes, and overrepresentation analysis for functional terms. We illustrate the utility of HybridExpress through comparative transcriptomic analyses of cotton allopolyploidization and rice root trait heterosis. HybridExpress is designed to streamline comparative transcriptomic studies of hybrid triplets, advancing our understanding of evolutionary dynamics in allopolyploids, and enhancing plant breeding strategies. HybridExpress is freely accessible from Bioconductor (https://bioconductor.org/packages/HybridExpress) and its source code is available on GitHub (https://github.com/almeidasilvaf/HybridExpress).

bioinformatics↗

bioRxiv2024

doubletrouble: an R/Bioconductor package for the identification, classification, and analysis of gene and genome duplications

Gene and genome duplications are major evolutionary forces that shape the diversity and complexity of life. However, different duplication modes have distinct impacts on gene function, expression, and regulation. Existing tools for identifying and classifying duplicated genes are either outdated or not user-friendly. Here, we present doubletrouble, an R/Bioconductor package that provides a comprehensive and robust framework for analyzing duplicated genes from genomic data. doubletrouble can detect and classify gene pairs as derived from six duplication modes (segmental, tandem, proximal, retrotransposon-derived, DNA transposon-derived, and dispersed duplications), calculate substitution rates, detect signatures of putative whole-genome duplication events, and visualize results as publication-ready figures. We applied doubletrouble to classify the duplicated gene repertoire in 822 eukaryotic genomes, which we made available through a user-friendly web interface (available at https://almeidasilvaf.github.io/doubletroubledb). doubletrouble is freely accessible from Bioconductor (https://bioconductor.org/packages/doubletrouble), and it provides a valuable resource to study the evolutionary consequences of gene and genome duplications.

bioinformatics↗

bioRxiv2023

The Soybean Expression Atlas v2: a comprehensive database of over 5000 RNA-seq samples

Soybean is a crucial crop worldwide, used as a source of food, feed, and industrial products due to its high protein and oil content. Previously, the rapid accumulation of soybean RNA-seq data in public databases and the computational challenges of processing raw RNA-seq data motivated us to develop the Soybean Expression Atlas, a gene expression database of over a thousand RNA-seq samples. Over the past few years, our database has allowed researchers to explore the expression profiles of important gene families, discover genes associated with agronomic traits, and understand the transcriptional dynamic of cellular processes. Here, we present the Soybean Expression Atlas v2, an updated version of our database with a 4-fold increase in the number of samples, featuring transcript- and gene-level transcript abundance matrices for 5481 publicly available RNA-seq samples. New features in our database include the availability of transcript-level abundance estimates and equivalence classes to explore differential transcript usage, abundance estimates in bias-corrected counts to increase the accuracy of differential gene expression analyses, a new web interface with improved data visualization and user experience, and a reproducible and scalable pipeline available as an R package. The Soybean Expression Atlas v2 is available at https://soyatlas.venanciogroup.uenf.br/, and it will accelerate soybean research, empowering researchers with high-quality and easily accessible gene expression data.

plant biology↗

bioRxiv2023

Assessing the quality of comparative genomics data and results with the cogeqc R/Bioconductor package

Comparative genomics has become an indispensable part of modern biology due to the advancements in high-throughput sequencing technologies and the accumulation of genomic data in public databases. However, the quality of genomic data and the choice of parameters used in software tools used for comparative genomics can greatly impact the accuracy of results. To address these issues, we present cogeqc, an R/Bioconductor package that provides researchers with a toolkit to assess genome assembly and annotation quality, orthogroup inference, and synteny detection. The package offers context-guided assessments of assembly and annotation statistics by comparing observed statistics to those of closely-related species on NCBI. To assess orthogroup inference, cogeqc calculates a protein domain-aware orthogroup score that aims at maximizing the number of shared protein domains within the same orthogroup. The assessment of synteny detection consists in representing anchor gene pairs as a synteny network and analyzing its graph properties, such as clustering coefficient, node count, and scale-free topology fit. The application of cogeqc to real data sets allowed for an evaluation of multiple parameter combinations for orthogroup inference and synteny detection, providing researchers with guidelines to aid in the selection of the most appropriate tools and parameters for their specific data.

bioinformatics↗

bioRxiv2023

Whole-genome duplications and the long-term evolution of gene regulatory networks in angiosperms

Angiosperms have a complex history of whole-genome duplications (WGDs), with varying numbers and ages of WGD events across clades. These WGDs have greatly affected the composition of plant genomes due to the biased retention of genes belonging to certain functional categories following their duplication. In particular, regulatory genes and genes encoding proteins that act in multiprotein complexes have been retained in excess following WGD. Here, we inferred protein-protein interaction (PPI) networks and gene regulatory networks (GRNs) for seven well-characterized angiosperm species and explored the impact of both WGD and small-scale duplications (SSD) in network topology by analyzing changes in frequency of network motifs. We found that PPI networks are enriched in WGD-derived genes associated with dosage-sensitive intricate systems, and strong selection pressures constrain the divergence of WGD-derived genes at the sequence and PPI levels. WGD-derived genes in network motifs are mostly associated with dosage-sensitive processes, such as regulation of transcription and cell cycle, translation, photosynthesis, and carbon metabolism, while SSD-derived genes in motifs are associated with response to biotic and abiotic stress. Recent polyploids have higher motif frequencies than ancient polyploids, while WGD-derived network motifs tend to be disrupted on the longer term. Our findings demonstrate that both WGD and SSD have contributed to the evolution of angiosperm GRNs, but in different ways, with WGD events likely having a more significant impact on the short-term evolution of polyploids.

evolutionary biology↗

bioRxiv2022

syntenet: an R/Bioconductor package for the inference and analysis of synteny networks

Interpreting and visualizing synteny relationships across several genomes is a challenging task. We previously proposed a network-based approach for better visualization and interpretation of large-scale microsynteny analyses. Here, we present syntenet, an R package to infer and analyze synteny networks from whole-genome protein sequence data. The package offers a simple and complete framework, including data preprocessing, synteny detection and network inference, network clustering and phylogenomic profiling, and microsynteny-based phylogeny inference. Graphical functions are also available to create publication-ready plots. Synteny networks inferred with syntenet can highlight taxon-specific gene clusters that likely contributed to the evolution of important traits, and microsynteny-based phylogenies can help resolve phylogenetic relationships under debate. Availability and ImplementationThe package is available on Bioconductor (https://bioconductor.org/packages/syntenet), and the source code is available on a GitHub repository (https://github.com/almeidasilvaf/syntenet).

bioinformatics↗

bioRxiv2022

Discovering and prioritizing candidate resistance genes against soybean pests by integrating GWAS and gene coexpression networks

Soybean is one of the most important legume crops worldwide. Soybean pests have considerable impact on crop yield. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate resistance genes against the insects Aphis glycines and Spodoptera litura, and the nematode Heterodera glycines. We identified 171, 7, and 228 high-confidence candidate resistance genes against A. glycines, S. litura, and H. glycines, respectively. We found some overlap of candidate genes between insect species, but not between insects and H. glycines. Although 15% of the prioritized candidate genes encode proteins of unknown function, the vast majority of the candidates are related to plant immunity processes, such as transcriptional regulation, signaling, oxidative stress, recognition, and physical defense. Based on the number of resistance alleles, we selected the ten most promising accessions against each pest species in the soybean USDA germplasm. The most resistant accessions do not reach the maximum theoretical resistance potential, indicating that they might be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression networks generated here are available in a user-friendly web application (https://soypestgcn.venanciogroup.uenf.br/) and an R/Shiny package (https://github.com/almeidasilvaf/SoyPestGCN) that serve as a public resource to explore soybean-pest interactions at the transcriptional level.

plant biology↗