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 dynamics of cellular processes. Here, we present the Soybean Expression Atlas v2, an updated version of our database with a fourfold 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.

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 (SSDs) 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, whereas SSD-derived genes in motifs are associated with response to biotic and abiotic stress. Recent polyploids have higher motif frequencies than ancient polyploids, whereas 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.

Genomic Insights into Adaptation to Karst Limestone and Incipient Speciation in East Asian Platycarya spp. (Juglandaceae).

When challenged by similar environmental conditions, phylogenetically distant taxa often independently evolve similar traits (convergent evolution). Meanwhile, adaptation to extreme habitats might lead to divergence between taxa that are otherwise closely related. These processes have long existed in the conceptual sphere, yet molecular evidence, especially for woody perennials, is scarce. The karst endemic Platycarya longipes and its only congeneric species, Platycarya strobilacea, which is widely distributed in the mountains in East Asia, provide an ideal model for examining the molecular basis of both convergent evolution and speciation. Using chromosome-level genome assemblies of both species, and whole-genome resequencing data from 207 individuals spanning their entire distribution range, we demonstrate that P. longipes and P. strobilacea form two species-specific clades, which diverged around 2.09 million years ago. We find an excess of genomic regions exhibiting extreme interspecific differentiation, potentially due to long-term selection in P. longipes, likely contributing to the incipient speciation of the genus Platycarya. Interestingly, our results unveil underlying karst adaptation in both copies of the calcium influx channel gene TPC1 in P. longipes. TPC1 has previously been identified as a selective target in certain karst-endemic herbs, indicating a convergent adaptation to high calcium stress among karst-endemic species. Our study reveals the genic convergence of TPC1 among karst endemics and the driving forces underneath the incipient speciation of the two Platycarya lineages.

Genomic Insights into Adaptation to Karst Limestone and Incipient Speciation in East Asian Platycarya spp. (Juglandaceae).

When challenged by similar environmental conditions, phylogenetically distant taxa often independently evolve similar traits (convergent evolution). Meanwhile, adaptation to extreme habitats might lead to divergence between taxa that are otherwise closely related. These processes have long existed in the conceptual sphere, yet molecular evidence, especially for woody perennials, is scarce. The karst endemic Platycarya longipes, and its only congeneric species, P. strobilacea, which is widely distributed in the mountains in East Asia, provide an ideal model for examining the molecular basis of both convergent evolution and speciation. Using chromosome-level genome assemblies of both species, and whole genome resequencing data from 207 individuals spanning their entire distribution range, we demonstrate that P. longipes and P. strobilacea form two species-specific clades, which diverged around 2.09 million years ago. We find an excess of genomic regions exhibiting extreme interspecific differentiation, potentially due to long-term selection in P. longipes, likely contributing to the incipient speciation of the genus Platycarya. Interestingly, our results unveil underlying karst adaptation in both copies of the calcium influx channel gene TPC1 in P. longipes. TPC1 has previously been identified as a selective target in certain karst-endemic herbs, indicating a convergent adaptation to high calcium stress among karst-endemic species. Our study reveals the genic convergence of TPC1 among karst endemics, and the driving forces underneath the incipient speciation of the two Platycarya lineages.

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

SUMMARY: 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 IMPLEMENTATION: syntenet is available on Bioconductor (https://bioconductor.org/packages/syntenet), and the source code is available on a GitHub repository (https://github.com/almeidasilvaf/syntenet). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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 nonadditive 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. 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).

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

Genome merging is a common phenomenon causing a wide range of consequences on phenotype, adaptation, and gene expression, yet its broader implications are not well-understood. Two consequences of genome merging on gene expression remain particularly poorly understood: dosage effects and evolution of expression. 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 experiment. Utilizing fitness assays, flow cytometry, and RNA-Seq, we assessed the immediate consequences of genome merging and subsequent evolution. Our findings reveal substantial alterations in genome size, gene expression, protein homeostasis, and cytonuclear stoichiometry. 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. Despite major genomic and 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.

The immediate metabolomic effects of whole-genome duplication in the greater duckweed, Spirodela polyrhiza.

PREMISE: In plants, whole-genome duplication (WGD) is a common mutation with profound evolutionary potential. Given the costs associated with a superfluous genome copy, polyploid establishment is enigmatic. However, in the right environment, immediate phenotypic changes following WGD can facilitate establishment. Metabolite abundances are the direct output of the cell's regulatory network and determine much of the impact of environmental and genetic change on the phenotype. While it is well known that an increase in the bulk amount of genetic material can increase cell size, the impact of gene dosage multiplication on the metabolome remains largely unknown. METHODS: We used untargeted metabolomics on four genetically distinct diploid-neoautotetraploid pairs of the greater duckweed, Spirodela polyrhiza, to investigate how WGD affects metabolite abundances per cell and per biomass. RESULTS: Autopolyploidy increased metabolite levels per cell, but the response of individual metabolites varied considerably. However, the impact on metabolite level per biomass was restricted because the increased cell size reduced the metabolite concentration per cell. Nevertheless, we detected both quantitative and qualitative effects of WGD on the metabolome. Many effects were strain-specific, but some were shared by all four strains. CONCLUSIONS: The nature and impact of metabolic changes after WGD depended strongly on the genotype. Dosage effects have the potential to alter the plant metabolome qualitatively and quantitatively, but were largely balanced out by the reduction in metabolite concentration due to an increase in cell size in this species.

BioNERO: an all-in-one R/Bioconductor package for comprehensive and easy biological network reconstruction.

Currently, standard network analysis workflows rely on many different packages, often requiring users to have a solid statistics and programming background. Here, we present BioNERO, an R package that aims to integrate all aspects of network analysis workflows, including expression data preprocessing, gene coexpression and regulatory network inference, functional analyses, and intraspecies and interspecies network comparisons. The state-of-the-art methods implemented in BioNERO ensure that users can perform all analyses with a single package in a simple pipeline, without needing to learn a myriad of package-specific syntaxes. BioNERO offers a user-friendly framework that can be easily incorporated in systems biology pipelines.

Systematic analysis of 1298 RNA-Seq samples and construction of a comprehensive soybean (Glycine max) expression atlas.

Soybean (Glycine max [L.] Merr.) is a major crop in animal feed and human nutrition, mainly for its rich protein and oil contents. The remarkable rise in soybean transcriptome studies over the past 5 years generated an enormous amount of RNA-seq data, encompassing various tissues, developmental conditions and genotypes. In this study, we have collected data from 1298 publicly available soybean transcriptome samples, processed the raw sequencing reads and mapped them to the soybean reference genome in a systematic fashion. We found that 94% of the annotated genes (52 737/56 044) had detectable expression in at least one sample. Unsupervised clustering revealed three major groups, comprising samples from aerial, underground and seed/seed-related parts. We found 452 genes with uniform and constant expression levels, supporting their roles as housekeeping genes. On the other hand, 1349 genes showed heavily biased expression patterns towards particular tissues. A transcript-level analysis revealed that 95% (70 963 of 74 490) of the assembled transcripts have intron chains exactly matching those from known transcripts, whereas 3256 assembled transcripts represent potentially novel splicing isoforms. The dataset compiled here constitute a new resource for the community, which can be downloaded or accessed through a user-friendly web interface at http://venanciogroup.uenf.br/resources/. This comprehensive transcriptome atlas will likely accelerate research on soybean genetics and genomics.

Exploring the complexity of soybean (Glycine max) transcriptional regulation using global gene co-expression networks.

MAIN CONCLUSION: We report a soybean gene co-expression network built with data from 1284 RNA-Seq experiments, which was used to identify important regulators, modules and to elucidate the fates of gene duplicates. Soybean (Glycine max (L.) Merr.) is one of the most important crops worldwide, constituting a major source of protein and edible oil. Gene co-expression networks (GCN) have been extensively used to study transcriptional regulation and evolution of genes and genomes. Here, we report a soybean GCN using 1284 publicly available RNA-Seq samples from 15 distinct tissues. We found modules that are differentially regulated in specific tissues, comprising processes such as photosynthesis, gluconeogenesis, lignin metabolism, and response to biotic stress. We identified transcription factors among intramodular hubs, which probably integrate different pathways and shape the transcriptional landscape in different conditions. The top hubs for each module tend to encode proteins with critical roles, such as succinate dehydrogenase and RNA polymerase subunits. Importantly, gene essentiality was strongly correlated with degree centrality and essential hubs were enriched in genes involved in nucleic acids metabolism and regulation of cell replication. Using a guilt-by-association approach, we predicted functions for 93 of 106 hubs without functional description in soybean. Most of the duplicated genes had different transcriptional profiles, supporting their functional divergence, although paralogs originating from whole-genome duplications (WGD) are more often preserved in the same module than those from other mechanisms. Together, our results highlight the importance of GCN analysis in unraveling key functional aspects of the soybean genome, in particular those associated with hub genes and WGD events.

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 a 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 we inferred in this work 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.

Transcriptome-based strategies for identifying aluminum tolerance genes in popcorn (Zea mays L. var. everta).

Aluminum (Al) toxicity limits crop production worldwide. Although studies have identified genes associated with Al tolerance in crops, a large amount of data remains unexplored using other strategies. Here, we searched for single substitutions and InDels across differentially expressed genes (DEGs), linked DEGs to Al-tolerance QTLs reported in the literature for common maize, and investigated the alternative splicing regulated by Al3+ toxicity. We found 929 substitutions between DEGs in Al-tolerant and 464 in Al-sensitive inbred lines, of which 165 and 80 were non-synonymous, respectively. Only 12 NS variants had deleterious predicted effect on protein function in Al-tolerant and 13 in Al-sensitive. Moreover, 378 DEGs were mapped in Al-QTL regions for the Al-tolerant and 213 for the Al-sensitive. Furthermore, Al stress is primarily regulated at the transcriptional level in popcorn. Important genes identified, such as HDT1, SWEET4a, GSTs, SAD9, PIP2-2, CASP-like 5, and AGP, may benefit molecular assisted popcorn breeding or be useful in biotechnological approaches. These findings offer insights into the mechanisms of Al tolerance in popcorn and provide a 'hypothesis-free' strategy for identifying and prioritizing candidate genes that could be used to develop molecular markers or cultivars resilient to acidic soils.

Structural and Biochemical Characterization of Three Antimicrobial Peptides from Capsicum annuum L. var. annuum Leaves for Anti-Candida Use.

The emergence of resistant microorganisms has reduced the effectiveness of currently available antimicrobials, necessitating the development of new strategies. Plant antimicrobial peptides (AMPs) are promising candidates for novel drug development. In this study, we aimed to isolate, characterize, and evaluate the antimicrobial activities of AMPs isolated from Capsicum annuum. The antifungal potential was tested against Candida species. Three AMPs from C. annuum leaves were isolated and characterized: a protease inhibitor, a defensin-like protein, and a lipid transporter protein, respectively named CaCPin-II, CaCDef-like, and CaCLTP2. All three peptides had a molecular mass between 3.5 and 6.5 kDa and caused morphological and physiological changes in four different species of the genus Candida, such as pseudohyphae formation, cell swelling and agglutination, growth inhibition, reduced cell viability, oxidative stress, membrane permeabilization, and metacaspase activation. Except for CaCPin-II, the peptides showed low or no hemolytic activity at the concentrations used in the yeast assays. CaCPin-II inhibited α-amylase activity. Together, these results suggest that these peptides have the potential as antimicrobial agents against species of the genus Candida and can serve as scaffolds for the development of synthetic peptides for this purpose.

Pathogenesis-related protein 1 (PR-1) genes in soybean: Genome-wide identification, structural analysis and expression profiling under multiple biotic and abiotic stresses.

Plant pathogenesis-related (PR) proteins are a large group of proteins, classified in 17 families, that are induced by pathological conditions. Here, we characterized the soybean PR-1 (GmPR-1) gene repertoire at the sequence, structural and expression levels. We found 24 GmPR-1 genes, clustered in two phylogenetic groups. GmPR-1 genes are under strong purifying selection, particularly those that emerged by tandem duplications. GmPR-1 promoter regions are abundant in cis-regulatory elements associated with major stress-related transcription factor families, namely WRKY, ERF, HD-Zip, C2H2, NAC, and GATA. We observed that 23 GmPR-1 genes are induced by stress conditions or exclusively expressed upon stress. We explored 1972 transcriptome samples, including 26 stress conditions, revealing that most GmPR-1 genes are differentially expressed in a plethora of biotic and abiotic stresses. Our findings highlight stress-responsive GmPR-1 genes with potential biotechnological applications, such as the development of transgenic lines with increased resistance to biotic and abiotic stresses.

Integrating omics approaches to discover and prioritize candidate genes involved in oil biosynthesis in soybean.

Soybean is a major source of edible protein and oil. Oil content is a quantitative trait that is significantly determined by genetic and environmental factors. Over the past 30 years, a large volume of soybean genetic, genomic, and transcriptomic data have been accumulated. Nevertheless, integrative analyses of such data remain scarce, in spite of their importance for crop improvement. We hypothesized that the co-occurrence of genomic regions for oil-related traits in different studies may reveal more stable regions encompassing important genetic determinants of oil content and quality in soybean. We integrated publicly available data, obtained with distinct techniques, to discover and prioritize candidate genes involved in oil biosynthesis and regulation in soybean. We detected key fatty acid biosynthesis genes (e.g., BCCP2 and ACCase, FADs, KAS family proteins) and several transcription factors, which are likely regulators of oil biosynthesis. In addition, we identified new candidates for seed oil accumulation and quality, such as Glyma.03G213300 and Glyma.19G160700, which encode a translocator protein homolog and a histone acetyltransferase, respectively. Further, oil and protein genomic hotspots are strongly associated with breeding and not with domestication, suggesting that soybean domestication prioritized other traits. The genes identified here are promising targets for breeding programs and for the development of soybean lines with increased oil content and quality.

Multiomic Approaches Reveal Hormonal Modulation and Nitrogen Uptake and Assimilation in the Initial Growth of Maize Inoculated with Herbaspirillum seropedicae.

Herbaspirillum seropedicae is an endophytic bacterium that can fix nitrogen and synthesize phytohormones, which can lead to a plant growth-promoting effect when used as a microbial inoculant. Studies focused on mechanisms of action are crucial for a better understanding of the bacteria-plant interaction and optimization of plant growth-promoting response. This work aims to understand the underlined mechanisms responsible for the early stimulatory growth effects of H. seropedicae inoculation in maize. To perform these studies, we combined transcriptomic and proteomic approaches with physiological analysis. The results obtained eight days after inoculation (d.a.i) showed increased root biomass (233 and 253%) and shoot biomass (249 and 264%), respectively, for the fresh and dry mass of maize-inoculated seedlings and increased green content and development. Omics data analysis, before a positive biostimulation phenotype (5 d.a.i.) revealed that inoculation increases N-uptake and N-assimilation machinery through differentially expressed nitrate transporters and amino acid pathways, as well carbon/nitrogen metabolism integration by the tricarboxylic acid cycle and the polyamine pathway. Additionally, phytohormone levels of root and shoot tissues increased in bacterium-inoculated-maize plants, leading to feedback regulation by the ubiquitin-proteasome system. The early biostimulatory effect of H. seropedicae partially results from hormonal modulation coupled with efficient nutrient uptake-assimilation and a boost in primary anabolic metabolism of carbon-nitrogen integrative pathways.

Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens.

Soybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application ( https://soyfungigcn.venanciogroup.uenf.br/ ) and an R/Shiny package ( https://github.com/almeidasilvaf/SoyFungiGCN ) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.

Genome-Wide Analysis of the COBRA-Like Gene Family Supports Gene Expansion through Whole-Genome Duplication in Soybean (Glycine max).

The COBRA-like (COBL) gene family has been associated with the regulation of cell wall expansion and cellulose deposition. COBL mutants result in reduced levels and disorganized deposition of cellulose causing defects in the cell wall and inhibiting plant development. In this study, we report the identification of 24 COBL genes (GmCOBL) in the soybean genome. Phylogenetic analysis revealed that the COBL proteins are divided into two groups, which differ by about 170 amino acids in the N-terminal region. The GmCOBL genes were heterogeneously distributed in 14 of the 20 soybean chromosomes. This study showed that segmental duplication has contributed significantly to the expansion of the COBL family in soybean during all Glycine-specific whole-genome duplication events. The expression profile revealed that the expression of the paralogous genes is highly variable between organs and tissues of the plant. Only 20% of the paralogous gene pairs showed similar expression patterns. The high expression levels of some GmCOBLs suggest they are likely essential for regulating cell expansion during the whole soybean life cycle. Our comprehensive overview of the COBL gene family in soybean provides useful information for further understanding the evolution and diversification of COBL genes in soybean.