Alexis Dereeper

An Improved Method for TAL Effectors DNA-Binding Sites Prediction Reveals Functional Convergence in TAL Repertoires of Xanthomonas oryzae Strains

Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs.

SAT, a flexible and optimized Web application for SSR marker development

BackgroundSimple Sequence Repeats (SSRs), or microsatellites, are among the most powerful genetic markers known. A common method for the development of SSR markers is the construction of genomic DNA libraries enriched for SSR sequences, followed by DNA sequencing. However, designing optimal SSR markers from bulk sequence data is a laborious and time-consuming process.ResultsSAT (SSR Analysis Tool) is a user-friendly Web application developed to minimize tedious manual operations and reduce errors. This tool facilitates the integration, analysis and display of sequence data from SSR-enriched libraries.SAT is designed to successively perform base calling and quality evaluation of chromatograms, eliminate cloning vector, adaptors and low quality sequences, detect chimera or partially digested sequences, search for SSR motifs, cluster and assemble the redundant sequences, and design SSR primer pairs. An additional virtual PCR step establishes primer specificity. Users may modify the different parameters of each step of the SAT analysis.Although certain steps are compulsory, such as SSR motifs search and sequence assembly, users do not have to run the entire pipeline, and they can choose selectively which steps to perform. A database allows users to store and query results, and to redo individual steps of the workflow.ConclusionThe SAT Web application is available at http://sat.cirad.fr/sat, and a standalone command-line version is also freely downloadable. Users must send an email to the SAT administrator tropgene@cirad.fr to request a login and password.

The coffee genome hub: a resource for coffee genomes

The whole genome sequence of Coffea canephora, the perennial diploid species known as Robusta, has been recently released. In the context of the C. canephora genome sequencing project and to support post-genomics efforts, we developed the Coffee Genome Hub (http://coffee-genome.org/), an integrative genome information system that allows centralized access to genomics and genetics data and analysis tools to facilitate translational and applied research in coffee. We provide the complete genome sequence of C. canephora along with gene structure, gene product information, metabolism, gene families, transcriptomics, syntenic blocks, genetic markers and genetic maps. The hub relies on generic software (e.g. GMOD tools) for easy querying, visualizing and downloading research data. It includes a Genome Browser enhanced by a Community Annotation System, enabling the improvement of automatic gene annotation through an annotation editor. In addition, the hub aims at developing interoperability among other existing South Green tools managing coffee data (phylogenomics resources, SNPs) and/or supporting data analyses with the Galaxy workflow manager.

Regulatory Divergence between Parental Alleles Determines Gene Expression Patterns in Hybrids

Both hybridization and allopolyploidization generate novel phenotypes by conciliating divergent genomes and regulatory networks in the same cellular context. To understand the rewiring of gene expression in hybrids, the total expression of 21,025 genes and the allele-specific expression of over 11,000 genes were quantified in interspecific hybrids and their parental species, Coffea canephora and Coffea eugenioides using RNA-seq technology. Between parental species, cis- and trans-regulatory divergences affected around 32% and 35% of analyzed genes, respectively, with nearly 17% of them showing both. The relative importance of trans-regulatory divergences between both species could be related to their low genetic divergence and perennial habit. In hybrids, among divergently expressed genes between parental species and hybrids, 77% was expressed like one parent (expression level dominance), including 65% like C. eugenioides. Gene expression was shown to result from the expression of both alleles affected by intertwined parental trans-regulatory factors. A strong impact of C. eugenioides trans-regulatory factors on the upregulation of C. canephora alleles was revealed. The gene expression patterns appeared determined by complex combinations of cis- and trans-regulatory divergences. In particular, the observed biased expression level dominance seemed to be derived from the asymmetric effects of trans-regulatory parental factors on regulation of alleles. More generally, this study illustrates the effects of divergent trans-regulatory parental factors on the gene expression pattern in hybrids. The characteristics of the transcriptional response to hybridization appear to be determined by the compatibility of gene regulatory networks and therefore depend on genetic divergences between the parental species and their evolutionary history.

SNiPloid: A Utility to Exploit High-Throughput SNP Data Derived from RNA-Seq in Allopolyploid Species

High-throughput sequencing is a common approach to discover SNP variants, especially in plant species. However, methods to analyze predicted SNPs are often optimized for diploid plant species whereas many crop species are allopolyploids and combine related but divergent subgenomes (homoeologous chromosome sets). We created a software tool, SNiPloid, that exploits and interprets putative SNPs in the context of allopolyploidy by comparing SNPs from an allopolyploid with those obtained in its modern-day diploid progenitors. SNiPloid can compare SNPs obtained from a sample to estimate the subgenome contribution to the transcriptome or SNPs obtained from two polyploid accessions to search for SNP divergence.

Transcriptomic and histological responses of African rice (Oryza glaberrima) to Meloidogyne graminicola provide new insights into root-knot nematode resistance in monocots

Background and Aims The root‐knot nematode Meloidogyne graminicola is responsible for production losses in rice (Oryza sativa) in Asia and Latin America. The accession TOG5681 of African rice, O. glaberrima, presents improved resistance to several biotic and abiotic factors, including nematodes. The aim of this study was to assess the cytological and molecular mechanisms underlying nematode resistance in this accession. Methods Penetration and development in M. graminicola in TOG5681 and the susceptible O. sativa genotype ‘Nipponbare’ were compared by microscopic observation of infected roots and histological analysis of galls. In parallel, host molecular responses to M. graminicola were assessed by root transcriptome profiling at 2, 4 and 8 d post‐infection (dpi). Specific treatments with hormone inhibitors were conducted in TOG5681 to assess the impact of the jasmonic acid and salicylic acid pathways on nematode penetration and reproduction. Key Results Penetration and development of M. graminicola juveniles were reduced in the resistant TOG5681 in comparison with the susceptible accession, with degeneration of giant cells observed in the resistant genotype from 15 dpi onwards. Transcriptome changes were observed as early as 2 dpi, with genes predicted to be involved in defence responses, phenylpropanoid and hormone pathways strongly induced in TOG5681, in contrast to ‘Nipponbare’. No specific hormonal pathway could be identified as the major determinant of resistance in the rice‐nematode incompatible interaction. Candidate genes proposed as involved in resistance to M. graminicola in TOG5681 were identified based on their expression pattern and quantitative trait locus (QTL) position, including chalcone synthase, isoflavone reductase, phenylalanine ammonia lyase, WRKY62 transcription factor, thionin, stripe rust resistance protein, thaumatins and ATPase3. Conclusions This study provides a novel set of candidate genes for O. glaberrima resistance to nematodes and highlights the rice‐M. graminicola pathosystem as a model to study plant‐nematode incompatible interactions.

SNiPlay3: a web-based application for exploration and large scale analyses of genomic variations

SNiPlay is a web-based tool for detection, management and analysis of genetic variants including both single nucleotide polymorphisms (SNPs) and InDels. Version 3 now extends functionalities in order to easily manage and exploit SNPs derived from next generation sequencing technologies, such as GBS (genotyping by sequencing), WGRS (whole gre-sequencing) and RNA-Seq technologies. Based on the standard VCF (variant call format) format, the application offers an intuitive interface for filtering and comparing polymorphisms using user-defined sets of individuals and then establishing a reliable genotyping data matrix for further analyses. Namely, in addition to the various scaled-up analyses allowed by the application (genomic annotation of SNP, diversity analysis, haplotype reconstruction and network, linkage disequilibrium), SNiPlay3 proposes new modules for GWAS (genome-wide association studies), population stratification, distance tree analysis and visualization of SNP density. Additionally, we developed a suite of Galaxy wrappers for each step of the SNiPlay3 process, so that the complete pipeline can also be deployed on a Galaxy instance using the Galaxy ToolShed procedure and then be computed as a Galaxy workflow. SNiPlay is accessible at http://sniplay.southgreen.fr.

The generation challenge programme platform: semantic standards and workbench for crop science.

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

The Greater Phenotypic Homeostasis of the Allopolyploid Coffea arabica Improved the Transcriptional Homeostasis Over that of Both Diploid Parents

Polyploidy impacts the diversity of plant species, giving rise to novel phenotypes and leading to ecological diversification. In order to observe adaptive and evolutionary capacities of polyploids, we compared the growth, primary metabolism and transcriptomic expression level in the leaves of the newly formed allotetraploid Coffea arabica species compared with its two diploid parental species (Coffea eugenioides and Coffea canephora), exposed to four thermal regimes (TRs; 18–14, 23–19, 28–24 and 33–29°C). The growth rate of the allopolyploid C. arabica was similar to that of C. canephora under the hottest TR and that of C. eugenioides under the coldest TR. For metabolite contents measured at the hottest TR, the allopolyploid showed similar behavior to C. canephora, the parent which tolerates higher growth temperatures in the natural environment. However, at the coldest TR, the allopolyploid displayed higher sucrose, raffinose and ABA contents than those of its two parents and similar linolenic acid leaf composition and Chl content to those of C. eugenioides. At the gene expression level, few differences between the allopolyploid and its parents were observed for studied genes linked to photosynthesis, respiration and the circadian clock, whereas genes linked to redox activity showed a greater capacity of the allopolyploid for homeostasis. Finally, we found that the overall transcriptional response to TRs of the allopolyploid was more homeostatic compared with its parents. This better transcriptional homeostasis of the allopolyploid C. arabica afforded a greater phenotypic homeostasis when faced with environments that are unsuited to the diploid parental species.

Gigwa-Genotype investigator for genome-wide analyses.

BackgroundExploring the structure of genomes and analyzing their evolution is essential to understanding the ecological adaptation of organisms. However, with the large amounts of data being produced by next-generation sequencing, computational challenges arise in terms of storage, search, sharing, analysis and visualization. This is particularly true with regards to studies of genomic variation, which are currently lacking scalable and user-friendly data exploration solutions.DescriptionHere we present Gigwa, a web-based tool that provides an easy and intuitive way to explore large amounts of genotyping data by filtering it not only on the basis of variant features, including functional annotations, but also on genotype patterns. The data storage relies on MongoDB, which offers good scalability properties. Gigwa can handle multiple databases and may be deployed in either single- or multi-user mode. In addition, it provides a wide range of popular export formats.ConclusionsThe Gigwa application is suitable for managing large amounts of genomic variation data. Its user-friendly web interface makes such processing widely accessible. It can either be simply deployed on a workstation or be used to provide a shared data portal for a given community of researchers.