Anthony Bolger

Trimmomatic: a flexible trimmer for Illumina sequence data

Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.

RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics

Recent rapid advances in next generation RNA sequencing (RNA-Seq)-based provide researchers with unprecedentedly large data sets and open new perspectives in transcriptomics. Furthermore, RNA-Seq-based transcript profiling can be applied to non-model and newly discovered organisms because it does not require a predefined measuring platform (like e.g. microarrays). However, these novel technologies pose new challenges: the raw data need to be rigorously quality checked and filtered prior to analysis, and proper statistical methods have to be applied to extract biologically relevant information. Given the sheer volume of data, this is no trivial task and requires a combination of considerable technical resources along with bioinformatics expertise. To aid the individual researcher, we have developed RobiNA as an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input. It supports quality checking, flexible filtering and statistical analysis of differential gene expression based on state-of-the art biostatistical methods developed in the R/Bioconductor projects. In-line help and a step-by-step manual guide users through the analysis. Installer packages for Mac OS X, Windows and Linux are available under the LGPL licence from http://mapman.gabipd.org/web/guest/robin.

Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato

Significance One of the most important technological advances by humans is the domestication of plant species for the production of food. We have used high-throughput sequencing to identify changes in DNA sequence and gene expression that differentiate cultivated tomato and its wild relatives. We also identify hundreds of candidate genes that have evolved new protein sequences or have changed expression levels in response to natural selection in wild tomato relatives. Taken together, our analyses provide a snapshot of genome evolution under artificial and natural conditions. Although applied over extremely short timescales, artificial selection has dramatically altered the form, physiology, and life history of cultivated plants. We have used RNAseq to define both gene sequence and expression divergence between cultivated tomato and five related wild species. Based on sequence differences, we detect footprints of positive selection in over 50 genes. We also document thousands of shifts in gene-expression level, many of which resulted from changes in selection pressure. These rapidly evolving genes are commonly associated with environmental response and stress tolerance. The importance of environmental inputs during evolution of gene expression is further highlighted by large-scale alteration of the light response coexpression network between wild and cultivated accessions. Human manipulation of the genome has heavily impacted the tomato transcriptome through directed admixture and by indirectly favoring nonsynonymous over synonymous substitutions. Taken together, our results shed light on the pervasive effects artificial and natural selection have had on the transcriptomes of tomato and its wild relatives.

The genome of the stress-tolerant wild tomato species Solanum pennellii

Solanum pennellii is a wild tomato species endemic to Andean regions in South America, where it has evolved to thrive in arid habitats. Because of its extreme stress tolerance and unusual morphology, it is an important donor of germplasm for the cultivated tomato Solanum lycopersicum. Introgression lines (ILs) in which large genomic regions of S. lycopersicum are replaced with the corresponding segments from S. pennellii can show remarkably superior agronomic performance. Here we describe a high-quality genome assembly of the parents of the IL population. By anchoring the S. pennellii genome to the genetic map, we define candidate genes for stress tolerance and provide evidence that transposable elements had a role in the evolution of these traits. Our work paves a path toward further tomato improvement and for deciphering the mechanisms underlying the myriad other agronomic traits that can be improved with S. pennellii germplasm.

Evolution of a Complex Locus for Terpene Biosynthesis in Solanum

A region on chromosome 8 of several Solanum species contains genes for terpene synthases and cis-prenyl transferases, the latter encoding the enzymes that catalyze the formation of the substrates used by enzymes encoded by the former. Detailed sequence and biochemical analyses identify molecular events that gave rise to distinct gene composition and function in the different Solanum species. Functional gene clusters, containing two or more genes encoding different enzymes for the same pathway, are sometimes observed in plant genomes, most often when the genes specify the synthesis of specialized defensive metabolites. Here, we show that a cluster of genes in tomato (Solanum lycopersicum; Solanaceae) contains genes for terpene synthases (TPSs) that specify the synthesis of monoterpenes and diterpenes from cis-prenyl diphosphates, substrates that are synthesized by enzymes encoded by cis-prenyl transferase (CPT) genes also located within the same cluster. The monoterpene synthase genes in the cluster likely evolved from a diterpene synthase gene in the cluster by duplication and divergence. In the orthologous cluster in Solanum habrochaites, a new sesquiterpene synthase gene was created by a duplication event of a monoterpene synthase followed by a localized gene conversion event directed by a diterpene synthase gene. The TPS genes in the Solanum cluster encoding cis-prenyl diphosphate–utilizing enzymes are closely related to a tobacco (Nicotiana tabacum; Solanaceae) diterpene synthase encoding Z-abienol synthase (Nt-ABS). Nt-ABS uses the substrate copal-8-ol diphosphate, which is made from the all-trans geranylgeranyl diphosphate by copal-8-ol diphosphate synthase (Nt-CPS2). The Solanum gene cluster also contains an ortholog of Nt-CPS2, but it appears to encode a nonfunctional protein. Thus, the Solanum functional gene cluster evolved by duplication and divergence of TPS genes, together with alterations in substrate specificity to utilize cis-prenyl diphosphates and through the acquisition of CPT genes.

Dual Resistance of Melon to Fusarium oxysporum Races 0 and 2 and to Papaya ring-spot virus is Controlled by a Pair of Head-to-Head-Oriented NB-LRR Genes of Unusual Architecture

Dear Editor, Potyviruses such as Papaya ring-spot virus (PRSV) cause important yield losses in cucurbits.Two distinct resistant alleles were identified in the Cucumis melo germplasm.Accession PI 414723 (Supplemental Table 1) possesses monogenic resistance,controlled by the Prv2 allele,and reacts to PRSV by systemic necrotic lesions;plants with the Prv1 allele,described in cultivar WMR-29,remain symptomless (Pitrat and Lecoq,1983).Fusarium oxysporum f.sp.melonis (FUS)exclusively attacks melon,causing severe wilt.Monogenic dominant resistance was described against races 0,1,and 2.The Fom-2 gene,controlling resistance to races 0 and 1,was cloned by Joobeur et al.(2004),and encodes a nucleotide binding domain (NB)-leucine rich repeat (LRR) protein.Our study focused on the Fom-1 gene,which confers resistance to races 0 and 2 (Risser et al.,1976),and on the Prv gene;the two are tightly linked on melon linkage group iX.Molecular markers were developed for the Fom-1/Prv locus,but no study has provided the resolution required for positional cloning.

Algorithm-driven Artifacts in median polish summarization of Microarray data

BackgroundHigh-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification.ResultsIn the present paper we benchmark the three most used normalization procedures (MAS5, RMA and GCRMA) in the context of inter-array correlation analysis, confirming and extending the finding that RMA and GCRMA consistently overestimate sample similarity upon normalization. We determine that median polish summarization is responsible for generating a large proportion of these over-similarity artifacts. Furthermore, we show that most affected probesets show also internal signal disagreement, and tend to be composed by individual probes hitting different gene transcripts. We finally provide a correction to the RMA/GCRMA summarization procedure that massively reduces inter-array correlation artifacts, without affecting the detection of differentially expressed genes.ConclusionsWe propose tRMA as a modification of RMA to normalize microarray experiments for correlation-based analysis.

Identification of candidate genes for phenolics accumulation in tomato fruit

Phenolics are antioxidants present in tomato fruit that confer healthy benefits and exhibit crucial roles for plant metabolism and response to environmental stimuli. An approach based on two genomics platforms was undertaken to identify candidate genes associated to higher phenolics content in tomato fruit. A comparative transcriptomic analysis between the S. pennellii Introgression Line 7-3, which produced an average higher level of fruit phenolics, and the cultivated variety M82, revealed that their differences are attributed to genes involved in phenolics accumulation into the vacuole. The up-regulation of genes coding for one MATE-transporter, one vacuolar sorting protein and three GSTs supported this hypothesis. The observed balancing effect between two ethylene responsive factors (ERF1 and ERF4) was also hypothesized to drive the transcriptional regulation of these transport genes. In order to confirm such model a TILLING platform was explored. A mutant was isolated harbouring a point mutation in the ERF1 cds that affects the protein sequence and its expected function. Fruits of the mutant exhibited a significant reduced level of phenolics than the control variety. Changes in the expression of genes involved in sequestration of phenolics in vacuole also supported the hypothesized key-role of ERF1 in orchestrating these genes.

Visualizing large, high-throughput datasets based on the cognitive representation of biological pathways

The data explosion in the biological sciences has led to many novel challenges for the individual researcher. One of these is to interpret the sheer mass of data at hand. Typical high-throughput data sets from transcriptomic data can easily comprise hundred thousand data points. It is thus necessary to provide tools to interactively visualize these data sets in a way that aids in their interpretation. Thus we have developed the MAPMAN application. This application renders individual data points from different domains as different glyphs that are color coded to reflect underlying changes in the magnitude/abundance of the underlying data. In order to augment the human comprehensibility of the biologist domain experts these data are organized on meaningful pathway diagrams that the biologist has encountered numerous times. Using these representations together with a high level organization thus helps to quickly realize the main outcome of such a high throughput study and to further decide on additional tasks that should be performed to explore the data.