Selected cachaça yeast strains share a genomic profile related to traits relevant to industrial fermentation processes.

The isolation and selection of yeast strains to improve the quality of the cachaça-Brazilian Spirit-have been studied in our research group. Our strategy considers Saccharomyces cerevisiae as the predominant species involved in sugarcane juice fermentation and the presence of different stressors (osmolarity, temperature, ethanol content, and competition with other microorganisms). It also considers producing balanced concentrations of volatile compounds (higher alcohols and acetate and/or ethyl esters), flocculation capacity, and ethanol production. Since the genetic bases behind these traits of interest are not fully established, the whole genome sequencing of 11 different Saccharomyces cerevisiae strains isolated and selected from different places was analyzed to identify the presence of a specific genetic variation common to cachaça yeast strains. We have identified 20,128 single-nucleotide variants shared by all genomes. Of these shared variants, 37 were new variants (being six missenses), and 4,451 were identified as missenses. We performed a detailed functional annotation (using enrichment analysis, protein-protein interaction network analysis, and database and in-depth literature searches) of these new and missense variants. Many genes carrying these variations were involved in the phenotypes of flocculation, tolerance to fermentative stresses, and production of volatile compounds and ethanol. These results demonstrate the existence of a genetic profile shared by the 11 strains under study that could be associated with the applied selective strategy. Thus, this study points out genes and variants that may be used as molecular markers for selecting strains well suited to the fermentation process, including genetic improvement by genome editing, ultimately producing high-quality beverages and adding value.IMPORTANCEThis work demonstrates the existence of new genetic markers related to different phenotypes used to select yeast strains and mutations in genes directly involved in producing flavoring compounds and ethanol, and others related to flocculation and stress resistance.

A Reductionist Approach Using Primary and Metastatic Cell-Derived Extracellular Vesicles Reveals Hub Proteins Associated with Oral Cancer Prognosis.

Oral squamous cell carcinoma (OSCC) has high mortality rates that are largely associated with lymph node metastasis. However, the molecular mechanisms that drive OSCC metastasis are unknown. Extracellular vesicles (EVs) are membrane-bound particles that play a role in intercellular communication and impact cancer development and progression. Thus, profiling EVs would be of great significance to decipher their role in OSCC metastasis. For that purpose, we used a reductionist approach to map the proteomic, miRNA, metabolomic, and lipidomic profiles of EVs derived from human primary tumor (SCC-9) cells and matched lymph node metastatic (LN1) cells. Distinct omics profiles were associated with the metastatic phenotype, including 670 proteins, 217 miRNAs, 26 metabolites, and 63 lipids differentially abundant between LN1 cell- and SCC-9 cell-derived EVs. A multi-omics integration identified 11 'hub proteins' significantly decreased at the metastatic site compared with primary tumor-derived EVs. We confirmed the validity of these findings with analysis of data from multiple public databases and found that low abundance of seven 'hub proteins' in EVs from metastatic lymph nodes (ALDH7A1, CAD, CANT1, GOT1, MTHFD1, PYGB, and SARS) is correlated with reduced survival and tumor aggressiveness in patients with cancer. In summary, this multi-omics approach identified proteins transported by EVs that are associated with metastasis and which may potentially serve as prognostic markers in OSCC.

The experience of teaching introductory programming skills to bioscientists in Brazil.

Computational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID-19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term.

Modern Approaches for Transcriptome Analyses in Plants.

The collection of all transcripts in a cell, a tissue, or an organism is called the transcriptome, or meta-transcriptome when dealing with the transcripts of a community of different organisms. Nowadays, we have a vast array of technologies that allow us to assess the (meta-)transcriptome regarding its composition (which transcripts are produced) and the abundance of its components (what are the expression levels of each transcript), and we can do this across several samples, conditions, and time-points, at costs that are decreasing year after year, allowing experimental designs with ever-increasing complexity. Here we will present the current state of the art regarding the technologies that can be applied to the study of plant transcriptomes and their applications, including differential gene expression and coexpression analyses, identification of sequence polymorphisms, the application of machine learning for the identification of alternative splicing and ncRNAs, and the ranking of candidate genes for downstream studies. We continue with a collection of examples of these approaches in a diverse array of plant species to generate gene/transcript catalogs/atlases, population mapping, identification of genes related to stress phenotypes, and phylogenomics. We finalize the chapter with some of our ideas about the future of this dynamic field in plant physiology.

Gene regulatory networks on transfer entropy (GRNTE): a novel approach to reconstruct gene regulatory interactions applied to a case study for the plant pathogen Phytophthora infestans.

BACKGROUND: The increasing amounts of genomics data have helped in the understanding of the molecular dynamics of complex systems such as plant and animal diseases. However, transcriptional regulation, although playing a central role in the decision-making process of cellular systems, is still poorly understood. In this study, we linked expression data with mathematical models to infer gene regulatory networks (GRN). We present a simple yet effective method to estimate transcription factors' GRNs from transcriptional data. METHOD: We defined interactions between pairs of genes (edges in the GRN) as the partial mutual information between these genes that takes into account time and possible lags in time from one gene in relation to another. We call this method Gene Regulatory Networks on Transfer Entropy (GRNTE) and it corresponds to Granger causality for Gaussian variables in an autoregressive model. To evaluate the reconstruction accuracy of our method, we generated several sub-networks from the GRN of the eukaryotic yeast model, Saccharomyces cerevisae. Then, we applied this method using experimental data of the plant pathogen Phytophthora infestans. We evaluated the transcriptional expression levels of 48 transcription factors of P. infestans during its interaction with one moderately resistant and one susceptible cultivar of yellow potato (Solanum tuberosum group Phureja), using RT-qPCR. With these data, we reconstructed the regulatory network of P. infestans during its interaction with these hosts. RESULTS: We first evaluated the performance of our method, based on the transfer entropy (GRNTE), on eukaryotic datasets from the GRNs of the yeast S. cerevisae. Results suggest that GRNTE is comparable with the state-of-the-art methods when the parameters for edge detection are properly tuned. In the case of P. infestans, most of the genes considered in this study, showed a significant change in expression from the onset of the interaction (0 h post inoculum - hpi) to the later time-points post inoculation. Hierarchical clustering of the expression data discriminated two distinct periods during the infection: from 12 to 36 hpi and from 48 to 72 hpi for both the moderately resistant and susceptible cultivars. These distinct periods could be associated with two phases of the life cycle of the pathogen when infecting the host plant: the biotrophic and necrotrophic phases. CONCLUSIONS: Here we presented an algorithmic solution to the problem of network reconstruction in time series data. This analytical perspective makes use of the dynamic nature of time series data as it relates to intrinsically dynamic processes such as transcription regulation, were multiple elements of the cell (e.g., transcription factors) act simultaneously and change over time. We applied the algorithm to study the regulatory network of P. infestans during its interaction with two hosts which differ in their level of resistance to the pathogen. Although the gene expression analysis did not show differences between the two hosts, the results of the GRN analyses evidenced rewiring of the genes' interactions according to the resistance level of the host. This suggests that different regulatory processes are activated in response to different environmental cues. Applications of our methodology showed that it could reliably predict where to place edges in the transcriptional networks and sub-networks. The experimental approach used here can help provide insights on the biological role of these interactions on complex processes such as pathogenicity. The code used is available at https://github.com/jccastrog/GRNTE under GNU general public license 3.0.

Genome sequence of the H2-producing Clostridium beijerinckii strain Br21 isolated from a sugarcane vinasse treatment plant.

We report on the nearly complete genome sequence of Clostridium beijerinckii strain Br21, formerly isolated from a sugarcarne vinasse wastewater treatment plant. The resulting genome is ca. 5.9 Mbp in length and resembles the size of previously published C. beijerinckii genomes. We annotated the genome sequence and predicted a total of 5323 genes. Strain Br21 has a genetic toolkit that allows it to exploit diverse sugars that are often found after lignocellulosic biomass pretreatment to yield products of commercial interest. Besides the whole set of genes encoding for enzymes underlying hydrogen production, the genome of the new strain includes genes that enable carbon sources conversion into butanol, ethanol, acetic acid, butyric acid, and the chemical block 1,3-propanediol, which is used to obtain polymers. Moreover, the genome of strain Br21 has a higher number of ORFs with predicted beta-glucosidase activity as compared to other C. beijerinckii strains described in the KEGG database. These characteristics make C. beijerinckii strain Br21 a remarkable candidate for direct use in biotechnological processes and attest that it is a potential biocatalyst supplier.

Transcriptome and secretome analysis of Aspergillus fumigatus in the presence of sugarcane bagasse.

BACKGROUND: Sugarcane bagasse has been proposed as a lignocellulosic residue for second-generation ethanol (2G) produced by breaking down biomass into fermentable sugars. The enzymatic cocktails for biomass degradation are mostly produced by fungi, but low cost and high efficiency can consolidate 2G technologies. A. fumigatus plays an important role in plant biomass degradation capabilities and recycling. To gain more insight into the divergence in gene expression during steam-exploded bagasse (SEB) breakdown, this study profiled the transcriptome of A. fumigatus by RNA sequencing to compare transcriptional profiles of A. fumigatus grown on media containing SEB or fructose as the sole carbon source. Secretome analysis was also performed using SDS-PAGE and LC-MS/MS. RESULTS: The maximum activities of cellulases (0.032 U mL-1), endo-1,4-ß--xylanase (10.82 U mL-1) and endo-1,3-ß glucanases (0.77 U mL-1) showed that functional CAZymes (carbohydrate-active enzymes) were secreted in the SEB culture conditions. Correlations between transcriptome and secretome data identified several CAZymes in A. fumigatus. Particular attention was given to CAZymes related to lignocellulose degradation and sugar transporters. Genes encoding glycoside hydrolase classes commonly expressed during the breakdown of cellulose, such as GH-5, 6, 7, 43, 45, and hemicellulose, such as GH-2, 10, 11, 30, 43, were found to be highly expressed in SEB conditions. Lytic polysaccharide monooxygenases (LPMO) classified as auxiliary activity families AA9 (GH61), CE (1, 4, 8, 15, 16), PL (1, 3, 4, 20) and GT (1, 2, 4, 8, 20, 35, 48) were also differentially expressed in this condition. Similarly, the most important enzymes related to biomass degradation, including endoxylanases, xyloglucanases, ß-xylosidases, LPMOs, α-arabinofuranosidases, cellobiohydrolases, endoglucanases and ß-glucosidases, were also identified in the secretome. CONCLUSIONS: This is the first report of a transcriptome and secretome experiment of Aspergillus fumigatus in the degradation of pretreated sugarcane bagasse. The results suggest that this strain employs important strategies for this complex degradation process. It was possible to identify a set of genes and proteins that might be applied in several biotechnology fields. This knowledge can be exploited for the improvement of 2G ethanol production by the rational design of enzymatic cocktails.

ploidyNGS: visually exploring ploidy with Next Generation Sequencing data.

SUMMARY: ploidyNGS is a model-free, open source tool to visualize and explore ploidy levels in a newly sequenced genome, exploiting short read data. We tested ploidyNGS using both simulated and real NGS data of the model yeast Saccharomyces cerevisiae. ploidyNGS allows the identification of the ploidy level of a newly sequenced genome in a visual way. AVAILABILITY AND IMPLEMENTATION: ploidyNGS is available under the GNU General Public License (GPL) at https://github.com/diriano/ploidyNGS. ploidyNGS is implemented in Python and R. CONTACT: diriano@gmail.com.

Comparative transcriptome analysis reveals different strategies for degradation of steam-exploded sugarcane bagasse by Aspergillus niger and Trichoderma reesei.

BACKGROUND: Second generation (2G) ethanol is produced by breaking down lignocellulosic biomass into fermentable sugars. In Brazil, sugarcane bagasse has been proposed as the lignocellulosic residue for this biofuel production. The enzymatic cocktails for the degradation of biomass-derived polysaccharides are mostly produced by fungi, such as Aspergillus niger and Trichoderma reesei. However, it is not yet fully understood how these microorganisms degrade plant biomass. In order to identify transcriptomic changes during steam-exploded bagasse (SEB) breakdown, we conducted a RNA-seq comparative transcriptome profiling of both fungi growing on SEB as carbon source. RESULTS: Particular attention was focused on CAZymes, sugar transporters, transcription factors (TFs) and other proteins related to lignocellulose degradation. Although genes coding for the main enzymes involved in biomass deconstruction were expressed by both fungal strains since the beginning of the growth in SEB, significant differences were found in their expression profiles. The expression of these enzymes is mainly regulated at the transcription level, and A. niger and T. reesei also showed differences in TFs content and in their expression. Several sugar transporters that were induced in both fungal strains could be new players on biomass degradation besides their role in sugar uptake. Interestingly, our findings revealed that in both strains several genes that code for proteins of unknown function and pro-oxidant, antioxidant, and detoxification enzymes were induced during growth in SEB as carbon source, but their specific roles on lignocellulose degradation remain to be elucidated. CONCLUSIONS: This is the first report of a time-course experiment monitoring the degradation of pretreated bagasse by two important fungi using the RNA-seq technology. It was possible to identify a set of genes that might be applied in several biotechnology fields. The data suggest that these two microorganisms employ different strategies for biomass breakdown. This knowledge can be exploited for the rational design of enzymatic cocktails and 2G ethanol production improvement.

Identification, classification and transcriptional profiles of dirigent domain-containing proteins in sugarcane.

Dirigent (DIR) proteins, encoded by DIR genes, are referred to as "dirigent" because they direct the outcome of the coupling of the monolignol coniferyl alcohol into (+) or (-) pinoresinol, the first intermediates in the enantiocomplementary pathways for lignan biosynthesis. DIR domain-containing or DIR-like proteins are, thus, termed for not having a clear characterization. A transcriptome- and genome-wide survey of DIR domain-containing proteins in sugarcane was carried out, in addition to phylogenetic, physicochemical and transcriptional analyses. A total of 120 non-redundant sequences containing the DIR domain were identified and classified into 64 groups according to phylogenetic and sequence alignment analyses. In silico analysis of transcript abundance showed that these sequences are expressed at low levels in leaves and genes in the same phylogenetic clade have similar expression patterns. Expression analysis of ShDIR1-like transcripts in the culm internodes of sugarcane demonstrates their abundance in mature internodes, their induction by nitrogen fertilization and their predominant expression in cells that have a lignified secondary cell wall, such as vascular bundles of young internodes and parenchymal cells of the pith of mature internodes. Due to the lack of information about the functional role of DIR in plants, a possible relationship is discussed between the ShDIR1-like transcriptional profile and cell wall development in parenchyma cells of sugarcane culm, which typically accumulates large amounts of sucrose. The number of genes encoding the DIR domain-containing proteins in sugarcane is intriguing and is an indication per se that these proteins may have an important metabolic role and thus deserve to be better studied.

Structural and functional characterization of a highly secreted α-l-arabinofuranosidase (GH62) from Aspergillus nidulans grown on sugarcane bagasse.

Carbohydrate-Active Enzymes are key enzymes for biomass-to-bioproducts conversion. α-l-Arabinofuranosidases that belong to the Glycoside Hydrolase family 62 (GH62) have important applications in biofuel production from plant biomass by hydrolyzing arabinoxylans, found in both the primary and secondary cell walls of plants. In this work, we identified a GH62 α-l-arabinofuranosidase (AnAbf62Awt) that was highly secreted when Aspergillus nidulans was cultivated on sugarcane bagasse. The gene AN7908 was cloned and transformed in A. nidulans for homologous production of AnAbf62Awt, and we confirmed that the enzyme is N-glycosylated at asparagine 83 by mass spectrometry analysis. The enzyme was also expressed in Escherichia coli and the studies of circular dichroism showed that the melting temperature and structural profile of AnAbf62Awt and the non-glycosylated enzyme from E. coli (AnAbf62Adeglyc) were highly similar. In addition, the designed glycomutant AnAbf62AN83Q presented similar patterns of secretion and activity to the AnAbf62Awt, indicating that the N-glycan does not influence the properties of this enzyme. The crystallographic structure of AnAbf62Adeglyc was obtained and the 1.7Å resolution model showed a five-bladed ß-propeller fold, which is conserved in family GH62. Mutants AnAbf62AY312F and AnAbf62AY312S showed that Y312 was an important substrate-binding residue. Molecular dynamics simulations indicated that the loop containing Y312 could access different conformations separated by moderately low energy barriers. One of these conformations, comprising a local minimum, is responsible for placing Y312 in the vicinity of the arabinose glycosidic bond, and thus, may be important for catalytic efficiency.

Physiological and transcriptional analyses of developmental stages along sugarcane leaf.

BACKGROUND: Sugarcane is one of the major crops worldwide. It is cultivated in over 100 countries on 22 million ha. The complex genetic architecture and the lack of a complete genomic sequence in sugarcane hamper the adoption of molecular approaches to study its physiology and to develop new varieties. Investments on the development of new sugarcane varieties have been made to maximize sucrose yield, a trait dependent on photosynthetic capacity. However, detailed studies on sugarcane leaves are scarce. In this work, we report the first molecular and physiological characterization of events taking place along a leaf developmental gradient in sugarcane. RESULTS: Photosynthetic response to CO2 indicated divergence in photosynthetic capacity based on PEPcase activity, corroborated by activity quantification (both in vivo and in vitro) and distinct levels of carbon discrimination on different segments along leaf length. Additionally, leaf segments had contrasting amount of chlorophyll, nitrogen and sugars. RNA-Seq data indicated a plethora of biochemical pathways differentially expressed along the leaf. Some transcription factors families were enriched on each segment and their putative functions corroborate with the distinct developmental stages. Several genes with higher expression in the middle segment, the one with the highest photosynthetic rates, were identified and their role in sugarcane productivity is discussed. Interestingly, sugarcane leaf segments had a different transcriptional behavior compared to previously published data from maize. CONCLUSION: This is the first report of leaf developmental analysis in sugarcane. Our data on sugarcane is another source of information for further studies aiming to understand and/or improve C4 photosynthesis. The segments used in this work were distinct in their physiological status allowing deeper molecular analysis. Although limited in some aspects, the comparison to maize indicates that all data acquired on one C4 species cannot always be easily extrapolated to other species. However, our data indicates that some transcriptional factors were segment-specific and the sugarcane leaf undergoes through the process of suberizarion, photosynthesis establishment and senescence.

Pseudozyma brasiliensis sp. nov., a xylanolytic, ustilaginomycetous yeast species isolated from an insect pest of sugarcane roots.

A novel ustilaginomycetous yeast isolated from the intestinal tract of an insect pest of sugarcane roots in Ribeirão Preto, São Paulo State, Brazil, represents a novel species of the genus Pseudozyma based on molecular analyses of the D1/D2 rDNA large subunit and the internal transcribed spacer (ITS1+ITS2) regions. The name Pseudozyma brasiliensis sp. nov. is proposed for this species, with GHG001(T) ( = CBS 13268(T) = UFMG-CM-Y307(T)) as the type strain. P. brasiliensis sp. nov. is a sister species of Pseudozyma vetiver, originally isolated from leaves of vetiver grass and sugarcane in Thailand. P. brasiliensis sp. nov. is able to grow well with xylan as the sole carbon source and produces high levels of an endo-1,4-xylanase that has a higher specific activity in comparison with other eukaryotic xylanases. This enzyme has a variety of industrial applications, indicating the great biotechnological potential of P. brasiliensis.

Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development.

Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.

PlnTFDB: updated content and new features of the plant transcription factor database.

The Plant Transcription Factor Database (PlnTFDB; http://plntfdb.bio.uni-potsdam.de/v3.0/) is an integrative database that provides putatively complete sets of transcription factors (TFs) and other transcriptional regulators (TRs) in plant species (sensu lato) whose genomes have been completely sequenced and annotated. The complete sets of 84 families of TFs and TRs from 19 species ranging from unicellular red and green algae to angiosperms are included in PlnTFDB, representing >1.6 billion years of evolution of gene regulatory networks. For each gene family, a basic description is provided that is complemented by literature references, and multiple sequence alignments of protein domains. TF or TR gene entries include information of expressed sequence tags, 3D protein structures of homologous proteins, domain architecture and cross-links to other computational resources online. Moreover, the different species in PlnTFDB are linked to each other by means of orthologous genes facilitating cross-species comparisons.

CoCoView - A codon conservation viewer via sequence logos.

Sequence logos are a simple way to display a set of aligned sequences, and they are useful to identify conserved patterns. Since their introduction, several tools have been developed for generating these representations at the single residue level (amino acids or nucleotides). We have developed a tool to build sequence logos of protein-coding sequences at the codon level, allowing more accurate analysis of coding-sequences as they represent synonymous and non-synonymous changes instead of showing only changes that imply on amino acid substitutions. We built CoCoView on top of the Logomaker Python API. It creates codon sequence logos from a multiple sequence alignment of protein-coding sequences. Some properties of the data and the generated logos can be controlled by the end-users, such as data redundancy, plot type and alphabet color. • Split aligned sequences into codon positions; • For each position compute codon frequency and information content; • Use the computed information to plot the graphic.

Bioinformatic analyses to uncover genes involved in trehalose metabolism in the polyploid sugarcane.

Trehalose-6-phosphate (T6P) is an intermediate of trehalose biosynthesis that plays an essential role in plant metabolism and development. Here, we comprehensively analyzed sequences from enzymes of trehalose metabolism in sugarcane, one of the main crops used for bioenergy production. We identified protein domains, phylogeny, and in silico expression levels for all classes of enzymes. However, post-translational modifications and residues involved in catalysis and substrate binding were analyzed only in trehalose-6-phosphate synthase (TPS) sequences. We retrieved 71 putative full-length TPS, 93 trehalose-6-phosphate phosphatase (TPP), and 3 trehalase (TRE) of sugarcane, showing all their conserved domains, respectively. Putative TPS (Classes I and II) and TPP sugarcane sequences were categorized into well-known groups reported in the literature. We measured the expression levels of the sequences from one sugarcane leaf transcriptomic dataset. Furthermore, TPS Class I has specific N-glycosylation sites inserted in conserved motifs and carries catalytic and binding residues in its TPS domain. Some of these residues are mutated in TPS Class II members, which implies loss of enzyme activity. Our approach retrieved many homo(eo)logous sequences for genes involved in trehalose metabolism, paving the way to discover the role of T6P signaling in sugarcane.

GabiPD: the GABI primary database--a plant integrative 'omics' database.

The GABI Primary Database, GabiPD (http://www.gabipd.org/), was established in the frame of the German initiative for Genome Analysis of the Plant Biological System (GABI). The goal of GabiPD is to collect, integrate, analyze and visualize primary information from GABI projects. GabiPD constitutes a repository and analysis platform for a wide array of heterogeneous data from high-throughput experiments in several plant species. Data from different 'omics' fronts are incorporated (i.e. genomics, transcriptomics, proteomics and metabolomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for text-based retrieval of all data types in GabiPD (e.g. clones, genes, mutant lines). All data types point to a central Gene GreenCard, where gene information is integrated from genome projects or NCBI UniGene sets. The centralized Gene GreenCard allows visualizing ESTs aligned to annotated transcripts as well as displaying identified protein domains and gene structure. Moreover, GabiPD makes available interactive genetic maps from potato and barley, and protein 2DE gels from Arabidopsis thaliana and Brassica napus. Gene expression and metabolic-profiling data can be visualized through MapManWeb. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of the data.

Genomic and transcriptomic resources for candidate gene discovery in the Ranunculids.

PREMISE: Multiple transitions from insect to wind pollination are associated with polyploidy and unisexual flowers in Thalictrum (Ranunculaceae), yet the underlying genetics remains unknown. We generated a draft genome of Thalictrum thalictroides, a representative of a clade with ancestral floral traits (diploid, hermaphrodite, and insect pollinated) and a model for functional studies. Floral transcriptomes of T. thalictroides and of wind-pollinated, andromonoecious T. hernandezii are presented as a resource to facilitate candidate gene discovery in flowers with different sexual and pollination systems. METHODS: A draft genome of T. thalictroides and two floral transcriptomes of T. thalictroides and T. hernandezii were obtained from HiSeq 2000 Illumina sequencing and de novo assembly. RESULTS: The T. thalictroides de novo draft genome assembly consisted of 44,860 contigs (N50 = 12,761 bp, 243 Mbp total length) and contained 84.5% conserved embryophyte single-copy genes. Floral transcriptomes contained representatives of most eukaryotic core genes, and most of their genes formed orthogroups. DISCUSSION: To validate the utility of these resources, potential candidate genes were identified for the different floral morphologies using stepwise data set comparisons. Single-copy gene analysis and simple sequence repeat markers were also generated as a resource for population-level and phylogenetic studies.