Assembly and Analysis of Haemonchus contortus Transcriptome as a Tool for the Knowledge of Ivermectin Resistance Mechanisms.

Haemonchus contortus (Hc) is an important parasitic nematode of small ruminants. In this study we assembled the transcriptome of Hc as a model to contribute to the knowledge about the profile of the differential gene expression between two Mexican Hc strains under different anthelmintic resistance statuses, one susceptible and the other resistant to ivermectin (IVMs and IVMr, respectively), in order to improve and/or to have new strategies of control and diagnosis. The transcript sequence reads were assembled and annotated. Overall, ~127 Mbp were assembled and distributed into 77,422 transcript sequences, and 4394 transcripts of the de novo transcriptome were matched base on at least one of the following criteria: (1) Phylum Nemathelminthes and Platyhelminthes, important for animal health care, and (2) ≥55% of sequence identity with other organisms. The gene ontology (GO) enrichment analysis (GOEA) was performed to study the level of gene regulation to IVMr and IVMs strains using Log Fold Change (LFC) filtering values ≥ 1 and ≥ 2. The upregulated-displayed genes obtained via GOEA were: 1993 (for LFC ≥ 1) and 1241 (for LFC ≥ 2) in IVMr and 1929 (for LFC ≥ 1) and 835 (for LFC ≥ 2) in IVMs. The enriched GO terms upregulated per category identified the intracellular structure, intracellular membrane-bounded organelle and integral component of the cell membrane as some principal cellular components. Meanwhile, efflux transmembrane transporter activity, ABC-type xenobiotic transporter activity and ATPase-coupled transmembrane transporter activity were associated with molecular function. Responses to nematicide activity, pharyngeal pumping and positive regulation of synaptic assembly were classified as biological processes that might be involved in events related to the anthelmintic resistance (AR) and nematode biology. The filtering analysis of both LFC values showed similar genes related to AR. This study deepens our knowledge about the mechanisms behind the processes of H. contortus in order to help in tool production and to facilitate the reduction of AR and promote the development of other control strategies, such as anthelmintic drug targets and vaccines.

Transcriptome analysis of the spider Phonotimpus pennimani reveals novel toxin transcripts.

Background: Phonotimpus pennimani (Araneae, Phrurolithidae) is a small-sized (3-5 mm) spider endemic to the Tacaná volcano in Chiapas, Mexico, where it is found in soil litter of cloud forests and coffee plantations. Its venom composition has so far not been investigated, partly because it is not a species of medical significance. However, it does have an important impact on the arthropod populations of its natural habitat. Methods: Specimens were collected in Southeastern Mexico (Chiapas) and identified taxonomically by morphological characteristics. A partial sequence from the mitochondrial gene coxI was amplified. Sequencing on the Illumina platform of a transcriptome library constructed from 12 adult specimens revealed 25 toxin or toxin-like genes. Transcripts were validated (RT-qPCR) by assessing the differential expression of the toxin-like PpenTox1 transcript and normalising with housekeeping genes. Results: Analysis of the coxI-gene revealed a similarity to other species of the family Phrurolithidae. Transcriptome analysis also revealed similarity with venom components of species from the families Ctenidae, Lycosidae, and Sicariidae. Expression of the toxin-like PpenTox1 gene was different for each developmental stage (juvenile or adult) and also for both sexes (female or male). Additionally, a partial sequence was obtained for the toxin-like PpenTox1 from DNA. Conclusion: Data from the amplification of the mitochondrial coxI gene confirmed that P. pennimani belongs to the family Phrurolithidae. New genes and transcripts coding for venom components were identified.

Argonaute5 and its associated small RNAs modulate the transcriptional response during the rhizobia-Phaseolus vulgaris symbiosis.

Both plant- and rhizobia-derived small RNAs play an essential role in regulating the root nodule symbiosis in legumes. Small RNAs, in association with Argonaute proteins, tune the expression of genes participating in nodule development and rhizobial infection. However, the role of Argonaute proteins in this symbiosis has been overlooked. In this study, we provide transcriptional evidence showing that Argonaute5 (AGO5) is a determinant genetic component in the root nodule symbiosis in Phaseolus vulgaris. A spatio-temporal transcriptional analysis revealed that the promoter of PvAGO5 is active in lateral root primordia, root hairs from rhizobia-inoculated roots, nodule primordia, and mature nodules. Transcriptional analysis by RNA sequencing revealed that gene silencing of PvAGO5 affected the expression of genes involved in the biosynthesis of the cell wall and phytohormones participating in the rhizobial infection process and nodule development. PvAGO5 immunoprecipitation coupled to small RNA sequencing revealed the small RNAs bound to PvAGO5 during the root nodule symbiosis. Identification of small RNAs associated to PvAGO5 revealed miRNAs previously known to participate in this symbiotic process, further supporting a role for AGO5 in this process. Overall, the data presented shed light on the roles that PvAGO5 plays during the root nodule symbiosis in P. vulgaris.

Shining light on the transcriptome: Molecular regulatory networks leading to a fast-growth phenotype by continuous light in an environmentally sensitive teleost (Atherinopsidae).

Photoperiod can profoundly affect the physiology of teleost fish, including accelerated growth here defined as "fast growth phenotypes". However, molecular regulatory networks (MRNs) and biological processes being affected by continuous illumination and which allow some teleost species evident plasticity to thrive under this condition are not yet clear. Therefore, to provide a broad perspective of such mechanisms, Chirostoma estor fish were raised and sampled for growth under a simulated control (LD) 12 h Light: 12 h Dark or a continuous illumination (LL) 24 h Light: 0 h Dark since fertilization. The experiment lasted 12 weeks after hatching (wah), the time at which fish were sampled for growth, length, and whole-body cortisol levels. Additionally, 3 heads of fish from each treatment were used to perform a de novo transcriptome analysis using Next-Generation Sequencing. Fish in LL developed the fast growth phenotype with significant differences visible at 4 wah and gained 66% more mass by 12 wah than LD fish. Cortisol levels under LL were below basal levels at all times compared to fish in LD, suggesting circadian dysregulation effects. A strong effect of LL was observed in samples with a generalized down-regulation of genes except for Reactive Oxygen Species responses, genome stability, and growth biological processes. To our knowledge, this work is the first study using a transcriptomic approach to understand environmentally sensitive MRNs that mediate phenotypic plasticity in fish submitted to continuous illumination. This study gives new insights into the plasticity mechanisms of teleost fish under constant illumination.

Functional categorization of de novo transcriptome assembly of Vanilla planifolia Jacks. potentially points to a translational regulation during early stages of infection by Fusarium oxysporum f. sp. vanillae.

BACKGROUND: Upon exposure to unfavorable environmental conditions, plants need to respond quickly to maintain their homeostasis. For instance, physiological, biochemical and transcriptional changes occur during plant-pathogen interaction. In the case of Vanilla planifolia Jacks., a worldwide economically important crop, it is susceptible to Fusarium oxysporum f. sp. vanillae (Fov). This pathogen causes root and stem rot (RSR) in vanilla plants that lead to plant death. To investigate how vanilla plants, respond at the transcriptional level upon infection with Fov, here we employed the RNA-Seq approach to analyze the dynamics of whole-transcriptome changes during two-time frames of the infection. RESULTS: Analysis of global gene expression profiles upon infection by Fov indicated that the major transcriptional change occurred at 2 days post-inoculation (dpi), in comparison to 10 dpi. Briefly, the RNA-Seq analysis carried out in roots found that 3420 and 839 differentially expressed genes (DEGs) were detected at 2 and 10 dpi, respectively, as compared to the control. In the case of DEGs at 2 dpi, 1563 genes were found to be up-regulated, whereas 1857 genes were down-regulated. Moreover, functional categorization of DEGs at 2 dpi indicated that up-regulated genes are mainly associated to translation, whereas down-regulated genes are involved in cell wall remodeling. Among the translational-related transcripts, ribosomal proteins (RPs) were found increased their expression exclusively at 2 dpi. CONCLUSIONS: The screening of transcriptional changes of V. planifolia Jacks upon infection by Fov provides insights into the plant molecular response, particularly at early stages of infection. The accumulation of translational-related transcripts at early stages of infection potentially points to a transcriptional reprogramming coupled with a translational regulation in vanilla plants upon infection by Fov. Altogether, the results presented here highlight potential molecular players that might be further studied to improve Fov-induced resistance in vanilla plants.

Comparative and functional genomics of the protozoan parasite Babesia divergens highlighting the invasion and egress processes.

Babesiosis is considered an emerging disease because its incidence has significantly increased in the last 30 years, providing evidence of the expanding range of this rare but potentially life-threatening zoonotic disease. Babesia divergens is a causative agent of babesiosis in humans and cattle in Europe. The recently sequenced genome of B. divergens revealed over 3,741 protein coding-genes and the 10.7-Mb high-quality draft become the first reference tool to study the genome structure of B. divergens. Now, by exploiting this sequence data and using new computational tools and assembly strategies, we have significantly improved the quality of the B. divergens genome. The new assembly shows better continuity and has a higher correspondence to B. bovis chromosomes. Moreover, we present a differential expression analysis using RNA sequencing of the two different stages of the asexual lifecycle of B. divergens: the free merozoite capable of invading erythrocytes and the intraerythrocytic parasite stage that remains within the erythrocyte until egress. Comparison of mRNA levels of both stages identified 1,441 differentially expressed genes. From these, around half were upregulated and the other half downregulated in the intraerythrocytic stage. Orthogonal validation by real-time quantitative reverse transcription PCR confirmed the differential expression. A moderately increased expression level of genes, putatively involved in the invasion and egress processes, were revealed in the intraerythrocytic stage compared with the free merozoite. On the basis of these results and in the absence of molecular models of invasion and egress for B. divergens, we have proposed the identified genes as putative molecular players in the invasion and egress processes. Our results contribute to an understanding of key parasitic strategies and pathogenesis and could be a valuable genomic resource to exploit for the design of diagnostic methods, drugs and vaccines to improve the control of babesiosis.

Integrative Differential Expression Analysis for Multiple EXperiments (IDEAMEX): A Web Server Tool for Integrated RNA-Seq Data Analysis.

The current DNA sequencing technologies and their high-throughput yield, allowed the thrive of genomic and transcriptomic experiments but it also have generated big data problem. Due to this exponential growth of sequencing data, also the complexity of managing, processing and interpreting it in order to generate results, has raised. Therefore, the demand of easy-to-use friendly software and websites to run bioinformatic tools is imminent. In particular, RNA-Seq and differential expression analysis have become a popular and useful method to evaluate the genetic expression change in any organism. However, many scientists struggle with the data analysis since most of the available tools are implemented in a UNIX-based environment. Therefore, we have developed the web server IDEAMEX (Integrative Differential Expression Analysis for Multiple EXperiments). The IDEAMEX pipeline needs a raw count table for as many desired replicates and conditions, allowing the user to select which conditions will be compared, instead of doing all-vs.-all comparisons. The whole process consists of three main steps (1) Data Analysis: that allows a preliminary analysis for quality control based on the data distribution per sample, using different types of graphs; (2) Differential expression: performs the differential expression analysis with or without batch effect error awareness, using the bioconductor packages, NOISeq, limma-Voom, DESeq2 and edgeR, and generate reports for each method; (3) Result integration: the obtained results the integrated results are reported using different graphical outputs such as correlograms, heatmaps, Venn diagrams and text lists. Our server allows an easy and friendly visualization for results, providing an easy interaction during the analysis process, as well as error tracking and debugging by providing output log files. The server is currently available and can be accessed at http://www.uusmb.unam.mx/ideamex/ where the documentation and example input files are provided. We consider that this web server can help other researchers with no previous bioinformatic knowledge, to perform their analyses in a simple manner.

Whole-exome sequencing in maya indigenous families: variant in PPP1R3A is associated with type 2 diabetes.

It has been presumed that increased susceptibility in Mexicans to type 2 diabetes (T2D) is attributed to the Native American genetic ancestry. Nonetheless, it is not known if there are private genetic variants that confer susceptibility to develop T2D in our population. The Maya indigenous group has the highest proportion of Native American ancestry (98%) which makes it a representative group of the original peoples of Mexico. Thus, the aim of the present study is to identify new genetic variants associated with T2D in Maya families. Whole-exome sequencing was performed on DNA samples from Maya families with a third-generation family history of T2D only in one parental line. Four variants were identified for APOB, PPP1R3A, TPPP2, and GPR1 genes, and were further tested for association with T2D in 600 unrelated Maya in a case-control study. For the first time, rs1799999 in PPP1R3A was associated with risk of T2D in Mayan Mexican individuals (OR = 1.625, P = 0.014). Interestingly, carriers of rs1799999 presented increased values of HOMA-IR. In addition, rs1801702 in APOB was associated with total cholesterol and LDL-C (P = 0.019 and P = 0.020, respectively) in normoglycemic individuals; rs3732083 in GPR1 with HOMA-IR (P = 0.016) and rs9624 in TPPP2 with total cholesterol and triglycerides (P = 0.002 and P = 0.005, respectively) in T2D subjects. Overall, these findings support the idea that there are other genetic variants yet to be described, involved in T2D development in Maya population, being insulin resistance and lipid metabolism the main mechanisms implicated. Thus, these results can contribute to the understanding of diabetes genetic background in Mexican population.

Global transcriptional start site mapping in Geobacter sulfurreducens during growth with two different electron acceptors.

Geobacter sulfurreducens is an anaerobic soil bacterium that is involved in biogeochemical cycles of elements such as Fe and Mn. Although significant progress has been made in the understanding of the electron transfer processes in G. sulfurreducens, little is known about the regulatory mechanisms involved in their control. To expand the study of gene regulation in G. sulfurreducens, we carried out a genome-wide identification of transcription start sites (TSS) by 5'RACE and by deep RNA sequencing of primary mRNAs in two growth conditions. TSSs were identified along G. sulfurreducens genome and over 50% of them were located in the upstream region of the associated gene, and in some cases we detected genes with more than one TSS. Our global mapping of TSSs contributes with valuable information, which is needed for the study of transcript structure and transcription regulation signals and can ultimately contribute to the understanding of transcription initiation phenomena in G. sulfurreducens.

RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more.

This article summarizes our progress with RegulonDB (http://regulondb.ccg.unam.mx/) during the past 2 years. We have kept up-to-date the knowledge from the published literature regarding transcriptional regulation in Escherichia coli K-12. We have maintained and expanded our curation efforts to improve the breadth and quality of the encoded experimental knowledge, and we have implemented criteria for the quality of our computational predictions. Regulatory phrases now provide high-level descriptions of regulatory regions. We expanded the assignment of quality to various sources of evidence, particularly for knowledge generated through high-throughput (HT) technology. Based on our analysis of most relevant methods, we defined rules for determining the quality of evidence when multiple independent sources support an entry. With this latest release of RegulonDB, we present a new highly reliable larger collection of transcription start sites, a result of our experimental HT genome-wide efforts. These improvements, together with several novel enhancements (the tracks display, uploading format and curational guidelines), address the challenges of incorporating HT-generated knowledge into RegulonDB. Information on the evolutionary conservation of regulatory elements is also available now. Altogether, RegulonDB version 8.0 is a much better home for integrating knowledge on gene regulation from the sources of information currently available.

RegulonDB version 7.0: transcriptional regulation of Escherichia coli K-12 integrated within genetic sensory response units (Gensor Units).

RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database of the best-known regulatory network of any free-living organism, that of Escherichia coli K-12. The major conceptual change since 3 years ago is an expanded biological context so that transcriptional regulation is now part of a unit that initiates with the signal and continues with the signal transduction to the core of regulation, modifying expression of the affected target genes responsible for the response. We call these genetic sensory response units, or Gensor Units. We have initiated their high-level curation, with graphic maps and superreactions with links to other databases. Additional connectivity uses expandable submaps. RegulonDB has summaries for every transcription factor (TF) and TF-binding sites with internal symmetry. Several DNA-binding motifs and their sizes have been redefined and relocated. In addition to data from the literature, we have incorporated our own information on transcription start sites (TSSs) and transcriptional units (TUs), obtained by using high-throughput whole-genome sequencing technologies. A new portable drawing tool for genomic features is also now available, as well as new ways to download the data, including web services, files for several relational database manager systems and text files including BioPAX format.

The BioPAX community standard for pathway data sharing.

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

Genome-wide identification of transcription start sites, promoters and transcription factor binding sites in E. coli.

Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5' RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of sigma factors that control the expression of about 80% of these genes. As expected, the housekeeping sigma(70) was the most common type of promoter, followed by sigma(38). The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli.

RegulonDB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation.

RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database offering curated knowledge of the transcriptional regulatory network of Escherichia coli K12, currently the best-known electronically encoded database of the genetic regulatory network of any free-living organism. This paper summarizes the improvements, new biology and new features available in version 6.0. Curation of original literature is, from now on, up to date for every new release. All the objects are supported by their corresponding evidences, now classified as strong or weak. Transcription factors are classified by origin of their effectors and by gene ontology class. We have now computational predictions for sigma(54) and five different promoter types of the sigma(70) family, as well as their corresponding -10 and -35 boxes. In addition to those curated from the literature, we added about 300 experimentally mapped promoters coming from our own high-throughput mapping efforts. RegulonDB v.6.0 now expands beyond transcription initiation, including RNA regulatory elements, specifically riboswitches, attenuators and small RNAs, with their known associated targets. The data can be accessed through overviews of correlations about gene regulation. RegulonDB associated original literature, together with more than 4000 curation notes, can now be searched with the Textpresso text mining engine.

The partitioned Rhizobium etli genome: genetic and metabolic redundancy in seven interacting replicons.

We report the complete 6,530,228-bp genome sequence of the symbiotic nitrogen fixing bacterium Rhizobium etli. Six large plasmids comprise one-third of the total genome size. The chromosome encodes most functions necessary for cell growth, whereas few essential genes or complete metabolic pathways are located in plasmids. Chromosomal synteny is disrupted by genes related to insertion sequences, phages, plasmids, and cell-surface components. Plasmids do not show synteny, and their orthologs are mostly shared by accessory replicons of species with multipartite genomes. Some nodulation genes are predicted to be functionally related with chromosomal loci encoding for the external envelope of the bacterium. Several pieces of evidence suggest an exogenous origin for the symbiotic plasmid (p42d) and p42a. Additional putative horizontal gene transfer events might have contributed to expand the adaptive repertoire of R. etli, because they include genes involved in small molecule metabolism, transport, and transcriptional regulation. Twenty-three putative sigma factors, numerous isozymes, and paralogous families attest to the metabolic redundancy and the genomic plasticity necessary to sustain the lifestyle of R. etli in symbiosis and in the soil.

RegulonDB (version 5.0): Escherichia coli K-12 transcriptional regulatory network, operon organization, and growth conditions.

RegulonDB is the internationally recognized reference database of Escherichia coli K-12 offering curated knowledge of the regulatory network and operon organization. It is currently the largest electronically-encoded database of the regulatory network of any free-living organism. We present here the recently launched RegulonDB version 5.0 radically different in content, interface design and capabilities. Continuous curation of original scientific literature provides the evidence behind every single object and feature. This knowledge is complemented with comprehensive computational predictions across the complete genome. Literature-based and predicted data are clearly distinguished in the database. Starting with this version, RegulonDB public releases are synchronized with those of EcoCyc since our curation supports both databases. The complex biology of regulation is simplified in a navigation scheme based on three major streams: genes, operons and regulons. Regulatory knowledge is directly available in every navigation step. Displays combine graphic and textual information and are organized allowing different levels of detail and biological context. This knowledge is the backbone of an integrated system for the graphic display of the network, graphic and tabular microarray comparisons with curated and predicted objects, as well as predictions across bacterial genomes, and predicted networks of functionally related gene products. Access RegulonDB at http://regulondb.ccg.unam.mx.

RegulonDB (version 4.0): transcriptional regulation, operon organization and growth conditions in Escherichia coli K-12.

RegulonDB is the primary database of the major international maintained curation of original literature with experimental knowledge about the elements and interactions of the network of transcriptional regulation in Escherichia coli K-12. This includes mechanistic information about operon organization and their decomposition into transcription units (TUs), promoters and their sigma type, binding sites of specific transcriptional regulators (TRs), their organization into 'regulatory phrases', active and inactive conformations of TRs, as well as terminators and ribosome binding sites. The database is complemented with clearly marked computational predictions of TUs, promoters and binding sites of TRs. The current version has been expanded to include information beyond specific mechanisms aimed at gathering different growth conditions and the associated induced and/or repressed genes. RegulonDB is now linked with Swiss-Prot, with microarray databases, and with a suite of programs to analyze and visualize microarray experiments. We provide a summary of the biological knowledge contained in RegulonDB and describe the major changes in the design of the database. RegulonDB can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/regulondb/.

Environmental conditions and transcriptional regulation in Escherichia coli: a physiological integrative approach.

Bacteria develop a number of devices for sensing, responding, and adapting to different environmental conditions. Understanding within a genomic perspective how the transcriptional machinery of bacteria is modulated, as a response for changing conditions, is a major challenge for biologists. Knowledge of which genes are turned on or turned off under specific conditions is essential for our understanding of cell behavior. In this study we describe how the information pertaining to gene expression and associated growth conditions (even with very little knowledge of the associated regulatory mechanisms) is gathered from the literature and incorporated into RegulonDB, a database on transcriptional regulation and operon organization in E. coli. The link between growth conditions, signal transduction, and transcriptional regulation is modeled in the database in a simple format that highlights biological relevant information. As far as we know, there is no other database that explicitly clarifies the effect of environmental conditions on gene transcription. We discuss how this knowledge constitutes a benchmark that will impact future research aimed at integration of regulatory responses in the cell; for instance, analysis of microarrays, predicting culture behavior in biotechnological processes, and comprehension of dynamics of regulatory networks. This integrated knowledge will contribute to the future goal of modeling the behavior of E. coli as an entire cell. The RegulonDB database can be accessed on the web at the URL: http://www.cifn.unam.mx/Computational_Biology/regulondb/.