Ramon Vidal

Genome structure of a Saccharomyces cerevisiae strain widely used in bioethanol production

Bioethanol is a biofuel produced mainly from the fermentation of carbohydrates derived from agricultural feedstocks by the yeast Saccharomyces cerevisiae. One of the most widely adopted strains is PE-2, a heterothallic diploid naturally adapted to the sugar cane fermentation process used in Brazil. Here we report the molecular genetic analysis of a PE-2 derived diploid (JAY270), and the complete genome sequence of a haploid derivative (JAY291). The JAY270 genome is highly heterozygous (approximately 2 SNPs/kb) and has several structural polymorphisms between homologous chromosomes. These chromosomal rearrangements are confined to the peripheral regions of the chromosomes, with breakpoints within repetitive DNA sequences. Despite its complex karyotype, this diploid, when sporulated, had a high frequency of viable spores. Hybrid diploids formed by outcrossing with the laboratory strain S288c also displayed good spore viability. Thus, the rearrangements that exist near the ends of chromosomes do not impair meiosis, as they do not span regions that contain essential genes. This observation is consistent with a model in which the peripheral regions of chromosomes represent plastic domains of the genome that are free to recombine ectopically and experiment with alternative structures. We also explored features of the JAY270 and JAY291 genomes that help explain their high adaptation to industrial environments, exhibiting desirable phenotypes such as high ethanol and cell mass production and high temperature and oxidative stress tolerance. The genomic manipulation of such strains could enable the creation of a new generation of industrial organisms, ideally suited for use as delivery vehicles for future bioenergy technologies.

The Genome Sequence of Leishmania (Leishmania) amazonensis: Functional Annotation and Extended Analysis of Gene Models

We present the sequencing and annotation of the Leishmania (Leishmania) amazonensis genome, an etiological agent of human cutaneous leishmaniasis in the Amazon region of Brazil. L. (L.) amazonensis shares features with Leishmania (L.) mexicana but also exhibits unique characteristics regarding geographical distribution and clinical manifestations of cutaneous lesions (e.g. borderline disseminated cutaneous leishmaniasis). Predicted genes were scored for orthologous gene families and conserved domains in comparison with other human pathogenic Leishmania spp. Carboxypeptidase, aminotransferase, and 3′-nucleotidase genes and ATPase, thioredoxin, and chaperone-related domains were represented more abundantly in L. (L.) amazonensis and L. (L.) mexicana species. Phylogenetic analysis revealed that these two species share groups of amastin surface proteins unique to the genus that could be related to specific features of disease outcomes and host cell interactions. Additionally, we describe a hypothetical hybrid interactome of potentially secreted L. (L.) amazonensis proteins and host proteins under the assumption that parasite factors mimic their mammalian counterparts. The model predicts an interaction between an L. (L.) amazonensis heat-shock protein and mammalian Toll-like receptor 9, which is implicated in important immune responses such as cytokine and nitric oxide production. The analysis presented here represents valuable information for future studies of leishmaniasis pathogenicity and treatment.

An EST-based analysis identifies new genes and reveals distinctive gene expression features of Coffea arabica and Coffea canephora

BackgroundCoffee is one of the worlds most important crops; it is consumed worldwide and plays a significant role in the economy of producing countries. Coffea arabica and C. canephora are responsible for 70 and 30% of commercial production, respectively. C. arabica is an allotetraploid from a recent hybridization of the diploid species, C. canephora and C. eugenioides. C. arabica has lower genetic diversity and results in a higher quality beverage than C. canephora. Research initiatives have been launched to produce genomic and transcriptomic data about Coffea spp. as a strategy to improve breeding efficiency.ResultsAssembling the expressed sequence tags (ESTs) of C. arabica and C. canephora produced by the Brazilian Coffee Genome Project and the Nestlé-Cornell Consortium revealed 32,007 clusters of C. arabica and 16,665 clusters of C. canephora. We detected different GC3 profiles between these species that are related to their genome structure and mating system. BLAST analysis revealed similarities between coffee and grape (Vitis vinifera) genes. Using KA/KS analysis, we identified coffee genes under purifying and positive selection. Protein domain and gene ontology analyses suggested differences between Coffea spp. data, mainly in relation to complex sugar synthases and nucleotide binding proteins. OrthoMCL was used to identify specific and prevalent coffee protein families when compared to five other plant species. Among the interesting families annotated are new cystatins, glycine-rich proteins and RALF-like peptides. Hierarchical clustering was used to independently group C. arabica and C. canephora expression clusters according to expression data extracted from EST libraries, resulting in the identification of differentially expressed genes. Based on these results, we emphasize gene annotation and discuss plant defenses, abiotic stress and cup quality-related functional categories.ConclusionWe present the first comprehensive genome-wide transcript profile study of C. arabica and C. canephora, which can be freely assessed by the scientific community at http://www.lge.ibi.unicamp.br/coffea. Our data reveal the presence of species-specific/prevalent genes in coffee that may help to explain particular characteristics of these two crops. The identification of differentially expressed transcripts offers a starting point for the correlation between gene expression profiles and Coffea spp. developmental traits, providing valuable insights for coffee breeding and biotechnology, especially concerning sugar metabolism and stress tolerance.

A transcriptomic analysis of gene expression in the venom gland of the snake Bothrops alternatus (urutu)

BackgroundThe genus Bothrops is widespread throughout Central and South America and is the principal cause of snakebite in these regions. Transcriptomic and proteomic studies have examined the venom composition of several species in this genus, but many others remain to be studied. In this work, we used a transcriptomic approach to examine the venom gland genes of Bothrops alternatus, a clinically important species found in southeastern and southern Brazil, Uruguay, northern Argentina and eastern Paraguay.ResultsA cDNA library of 5,350 expressed sequence tags (ESTs) was produced and assembled into 838 contigs and 4512 singletons. BLAST searches of relevant databases showed 30% hits and 70% no-hits, with toxin-related transcripts accounting for 23% and 78% of the total transcripts and hits, respectively. Gene ontology analysis identified non-toxin genes related to general metabolism, transcription and translation, processing and sorting, (polypeptide) degradation, structural functions and cell regulation. The major groups of toxin transcripts identified were metalloproteinases (81%), bradykinin-potentiating peptides/C-type natriuretic peptides (8.8%), phospholipases A2 (5.6%), serine proteinases (1.9%) and C-type lectins (1.5%). Metalloproteinases were almost exclusively type PIII proteins, with few type PII and no type PI proteins. Phospholipases A2 were essentially acidic; no basic PLA2 were detected. Minor toxin transcripts were related to L-amino acid oxidase, cysteine-rich secretory proteins, dipeptidylpeptidase IV, hyaluronidase, three-finger toxins and ohanin. Two non-toxic proteins, thioredoxin and double-specificity phosphatase Dusp6, showed high sequence identity to similar proteins from other snakes. In addition to the above features, single-nucleotide polymorphisms, microsatellites, transposable elements and inverted repeats that could contribute to toxin diversity were observed.ConclusionsBothrops alternatus venom gland contains the major toxin classes described for other Bothrops venoms based on trancriptomic and proteomic studies. The predominance of type PIII metalloproteinases agrees with the well-known hemorrhagic activity of this venom, whereas the lower content of serine proteases and C-type lectins could contribute to less marked coagulopathy following envenoming by this species. The lack of basic PLA2 agrees with the lower myotoxicity of this venom compared to other Bothrops species with these toxins. Together, these results contribute to our understanding of the physiopathology of envenoming by this species.

Integration of High-Resolution Methylome and Transcriptome Analyses to Dissect Epigenomic Changes in Childhood Acute Lymphoblastic Leukemia

B-cell precursor acute lymphoblastic leukemia (pre-B ALL) is the most common pediatric cancer. Although the genetic determinants underlying disease onset remain unclear, epigenetic modifications including DNA methylation are suggested to contribute significantly to leukemogenesis. Using the Illumina 450K array, we assessed DNA methylation in matched tumor-normal samples of 46 childhood patients with pre-B ALL, extending single CpG-site resolution analysis of the pre-B ALL methylome beyond CpG-islands (CGI). Unsupervised hierarchical clustering of CpG-site neighborhood, gene, or microRNA (miRNA) gene-associated methylation levels separated the tumor cohort according to major pre-B ALL subtypes, and methylation in CGIs, CGI shores, and in regions around the transcription start site was found to significantly correlate with transcript expression. Focusing on samples carrying the t(12;21) ETV6-RUNX1 fusion, we identified 119 subtype-specific high-confidence marker CpG-loci. Pathway analyses linked the CpG-loci-associated genes with hematopoiesis and cancer. Further integration with whole-transcriptome data showed the effects of methylation on expression of 17 potential drivers of leukemogenesis. Independent validation of array methylation and sequencing-derived transcript expression with Sequenom Epityper technology and real-time quantitative reverse transcriptase PCR, respectively, indicates more than 80% empirical accuracy of our genome-wide findings. In summary, genome-wide DNA methylation profiling enabled us to separate pre-B ALL according to major subtypes, to map epigenetic biomarkers specific for the t(12;21) subtype, and through a combined methylome and transcriptome approach to identify downstream effects on candidate drivers of leukemogenesis.

Deep Sequencing Reveals Differences in the Transcriptional Landscapes of Fibers from Two Cultivated Species of Cotton

Cotton (Gossypium) fiber is the most prevalent natural product used in the textile industry. The two major cultivated species, G. hirsutum (Gh) and G. barbadense (Gb), are allotetraploids with contrasting fiber quality properties. To better understand the molecular basis for their fiber differences, EST pyrosequencing was used to document the fiber transcriptomes at two key development stages, 10 days post anthesis (dpa), representing the peak of fiber elongation, and 22 dpa, representing the transition to secondary cell wall synthesis. The 617,000 high quality reads (89% of the total 692,000 reads) from 4 libraries were assembled into 46,072 unigenes, comprising 38,297 contigs and 7,775 singletons. Functional annotation of the unigenes together with comparative digital gene expression (DGE) revealed a diverse set of functions and processes that were partly linked to specific fiber stages. Globally, 2,770 contigs (7%) showed differential expression (>2-fold) between 10 and 22 dpa (irrespective of genotype), with 70% more highly expressed at 10 dpa, while 2,248 (6%) were differentially expressed between the genotypes (irrespective of stage). The most significant genes with differential DGE at 10 dpa included expansins and lipid transfer proteins (higher in Gb), while at 22 dpa tubulins, cellulose, and sucrose synthases showed higher expression in Gb. DGE was compared with expression data of 10 dpa-old fibers from Affymetrix microarrays. Among 543 contigs showing differential expression on both platforms, 74% were consistent in being either over-expressed in Gh (242 genes) or in Gb (161 genes). Furthermore, the unigene set served to identify 339 new SSRs and close to 21,000 inter-genotypic SNPs. Subsets of 88 SSRs and 48 SNPs were validated through mapping and added 65 new loci to a RIL genetic map. The new set of fiber ESTs and the gene-based markers complement existing available resources useful in basic and applied research for crop improvement in cotton.

Phylogenetic and functional diversity of metagenomic libraries of phenol degrading sludge from petroleum refinery wastewater treatment system

In petrochemical refinery wastewater treatment plants (WWTP), different concentrations of pollutant compounds are received daily in the influent stream, including significant amounts of phenolic compounds, creating propitious conditions for the development of particular microorganisms that can rapidly adapt to such environment. In the present work, the microbial sludge from a refinery WWTP was enriched for phenol, cloned into fosmid vectors and pyrosequenced. The fosmid libraries yielded 13,200 clones and a comprehensive bioinformatic analysis of the sequence data set revealed a complex and diverse bacterial community in the phenol degrading sludge. The phylogenetic analyses using MEGAN in combination with RDP classifier showed a massive predominance of Proteobacteria, represented mostly by the genera Diaphorobacter, Pseudomonas, Thauera and Comamonas. The functional classification of phenol degrading sludge sequence data set generated by MG-RAST showed the wide metabolic diversity of the microbial sludge, with a high percentage of genes involved in the aerobic and anaerobic degradation of phenol and derivatives. In addition, genes related to the metabolism of many other organic and xenobiotic compounds, such as toluene, biphenyl, naphthalene and benzoate, were found. Results gathered herein demonstrated that the phenol degrading sludge has complex phylogenetic and functional diversities, showing the potential of such community to degrade several pollutant compounds. This microbiota is likely to represent a rich resource of versatile and unknown enzymes which may be exploited for biotechnological processes such as bioremediation.

Identification of SNPs in RNA-seq data of two cultivars of Glycine max (soybean) differing in drought resistance.

The legume Glycine max (soybean) plays an important economic role in the international commodities market, with a world production of almost 260 million tons for the 2009/2010 harvest. The increase in drought events in the last decade has caused production losses in recent harvests. This fact compels us to understand the drought tolerance mechanisms in soybean, taking into account its variability among commercial and developing cultivars. In order to identify single nucleotide polymorphisms (SNPs) in genes up-regulated during drought stress, we evaluated suppression subtractive libraries (SSH) from two contrasting cultivars upon water deprivation: sensitive (BR 16) and tolerant (Embrapa 48). A total of 2,222 soybean genes were up-regulated in both cultivars. Our method identified more than 6,000 SNPs in tolerant and sensitive Brazilian cultivars in those drought stress related genes. Among these SNPs, 165 (in 127 genes) are positioned at soybean chromosome ends, including transcription factors (MYB, WRKY) related to tolerance to abiotic stress.

IIS – Integrated Interactome System: A Web-Based Platform for the Annotation, Analysis and Visualization of Protein-Metabolite-Gene-Drug Interactions by Integrating a Variety of Data Sources and Tools

Background High-throughput screening of physical, genetic and chemical-genetic interactions brings important perspectives in the Systems Biology field, as the analysis of these interactions provides new insights into protein/gene function, cellular metabolic variations and the validation of therapeutic targets and drug design. However, such analysis depends on a pipeline connecting different tools that can automatically integrate data from diverse sources and result in a more comprehensive dataset that can be properly interpreted. Results We describe here the Integrated Interactome System (IIS), an integrative platform with a web-based interface for the annotation, analysis and visualization of the interaction profiles of proteins/genes, metabolites and drugs of interest. IIS works in four connected modules: (i) Submission module, which receives raw data derived from Sanger sequencing (e.g. two-hybrid system); (ii) Search module, which enables the user to search for the processed reads to be assembled into contigs/singlets, or for lists of proteins/genes, metabolites and drugs of interest, and add them to the project; (iii) Annotation module, which assigns annotations from several databases for the contigs/singlets or lists of proteins/genes, generating tables with automatic annotation that can be manually curated; and (iv) Interactome module, which maps the contigs/singlets or the uploaded lists to entries in our integrated database, building networks that gather novel identified interactions, protein and metabolite expression/concentration levels, subcellular localization and computed topological metrics, GO biological processes and KEGG pathways enrichment. This module generates a XGMML file that can be imported into Cytoscape or be visualized directly on the web. Conclusions We have developed IIS by the integration of diverse databases following the need of appropriate tools for a systematic analysis of physical, genetic and chemical-genetic interactions. IIS was validated with yeast two-hybrid, proteomics and metabolomics datasets, but it is also extendable to other datasets. IIS is freely available online at: http://www.lge.ibi.unicamp.br/lnbio/IIS/.

Large-scale analysis of differential gene expression in coffee genotypes resistant and susceptible to leaf miner–toward the identification of candidate genes for marker assisted-selection

BackgroundA successful development of herbivorous insects into plant tissues depends on coordination of metabolic processes. Plants have evolved complex mechanisms to recognize such attacks, and to trigger a defense response. To understand the transcriptional basis of this response, we compare gene expression profiles of two coffee genotypes, susceptible and resistant to leaf miner (Leucoptera coffella). A total of 22000 EST sequences from the Coffee Genome Database were selected for a microarray analysis. Fluorescence probes were synthesized using mRNA from the infested and non-infested coffee plants. Array hybridization, scanning and data normalization were performed using Nimble Scan® e ArrayStar® platforms. Genes with foldchange values +/-2 were considered differentially expressed. A validation of 18 differentially expressed genes was performed in infected plants using qRT-PCR approach.ResultsThe microarray analysis indicated that resistant plants differ in gene expression profile. We identified relevant transcriptional changes in defense strategies before insect attack. Expression changes (>2.00-fold) were found in resistant plants for 2137 genes (1266 up-regulated and 873 down-regulated). Up-regulated genes include those responsible for defense mechanisms, hypersensitive response and genes involved with cellular function and maintenance. Also, our analyses indicated that differential expression profiles between resistant and susceptible genotypes are observed in the absence of leaf-miner, indicating that defense is already build up in resistant plants, as a priming mechanism. Validation of selected genes pointed to four selected genes as suitable candidates for markers in assisted-selection of novel cultivars.ConclusionsOur results show evidences that coffee defense responses against leaf-miner attack are balanced with other cellular functions. Also analyses suggest a major metabolic reconfiguration that highlights the complexity of this response.