Tom Ruttink

A Molecular Timetable for Apical Bud Formation and Dormancy Induction in Poplar

The growth of perennial plants in the temperate zone alternates with periods of dormancy that are typically initiated during bud development in autumn. In a systems biology approach to unravel the underlying molecular program of apical bud development in poplar (Populus tremula × Populus alba), combined transcript and metabolite profiling were applied to a high-resolution time course from short-day induction to complete dormancy. Metabolite and gene expression dynamics were used to reconstruct the temporal sequence of events during bud development. Importantly, bud development could be dissected into bud formation, acclimation to dehydration and cold, and dormancy. To each of these processes, specific sets of regulatory and marker genes and metabolites are associated and provide a reference frame for future functional studies. Light, ethylene, and abscisic acid signal transduction pathways consecutively control bud development by setting, modifying, or terminating these processes. Ethylene signal transduction is positioned temporally between light and abscisic acid signals and is putatively activated by transiently low hexose pools. The timing and place of cell proliferation arrest (related to dormancy) and of the accumulation of storage compounds (related to acclimation processes) were established within the bud by electron microscopy. Finally, the identification of a large set of genes commonly expressed during the growth-to-dormancy transitions in poplar apical buds, cambium, or Arabidopsis thaliana seeds suggests parallels in the underlying molecular mechanisms in different plant organs.

Bud set in poplar – genetic dissection of a complex trait in natural and hybrid populations

• The seasonal timing of growth events is crucial to tree distribution and conservation. The seasonal growth cycle is strongly adapted to the local climate that is changing because of global warming. We studied bud set as one cornerstone of the seasonal growth cycle in an integrative approach. • Bud set was dissected at the phenotypic level into several components, and phenotypic components with most genetic variation were identified. While phenotypic variation resided in the timing of growth cessation, and even so more in the duration from growth cessation to bud set, the timing of growth cessation had a stronger genetic component in both natural and hybrid populations. • Quantitative trait loci (QTL) were identified for the most discriminative phenotypic bud-set components across four poplar pedigrees. The QTL from different pedigrees were recurrently detected in six regions of the poplar genome. • These regions of 1.83-4.25 Mbp in size, containing between 202 and 394 genes, form the basis for further molecular-genetic dissection of bud set.

De novo assembly of red clover transcriptome based on RNA-Seq data provides insight into drought response, gene discovery and marker identification

BackgroundRed clover (Trifolium pratense L.) is a versatile forage crop legume, which can tolerate a variety of soils and is suitable for silage production for winter feed and for grazing. It is one of the most important forage legumes in temperate livestock agriculture. Its beneficial attributes include ability to fix nitrogen, improve soil and provide protein rich animal feed. It is however, a short-lived perennial providing good biomass yield for two or three years. Improved persistency is thus a major breeding target. Better water-stress tolerance is one of the key factors influencing persistency, but little is known about how red clover tolerates water stress.ResultsPlants from a full sib mapping family were used in a drought experiment, in which the growth rate and relative water content (RWC) identified two pools of ten plants contrasting in their tolerance to drought. Key metabolites were measured and RNA-Seq analysis was carried out on four bulked samples: the two pools sampled before and after drought. Massively parallel sequencing was used to analyse the bulked RNA samples. A de novo transcriptome reconstruction based on the RNA-Seq data was made, resulting in 45181 contigs, representing ‘transcript tags’. These transcript tags were annotated with gene ontology (GO) terms. One of the most striking results from the expression analysis was that the drought sensitive plants were characterised by having approximately twice the number of differentially expressed transcript tags than the tolerant plants after drought. This difference was evident in most of the major GO terms. Before onset of drought the sensitive plants overexpressed a number of genes annotated as senescence-related. Furthermore, the concentration of three metabolites, particularly pinitol, but also proline and malate increased in leaves after drought stress.ConclusionsThis de novo assembly of a red clover transcriptome from leaf material of droughted and non-droughted plants provides a rich source for gene identification, single nucleotide polymorphisms (SNP) and short sequence repeats (SSR). Comparison of gene expression levels between pools and treatments identified candidate genes for further analysis of the genetic basis of drought tolerance in red clover.

Molecular toolbox for the identification of unknown genetically modified organisms

AbstractCompetent laboratories monitor genetically modified organisms (GMOs) and products derived thereof in the food and feed chain in the framework of labeling and traceability legislation. In addition, screening is performed to detect the unauthorized presence of GMOs including asynchronously authorized GMOs or GMOs that are not officially registered for commercialization (unknown GMOs). Currently, unauthorized or unknown events are detected by screening blind samples for commonly used transgenic elements, such as p35S or t-nos. If (1) positive detection of such screening elements shows the presence of transgenic material and (2) all known GMOs are tested by event-specific methods but are not detected, then the presence of an unknown GMO is inferred. However, such evidence is indirect because it is based on negative observations and inconclusive because the procedure does not identify the causative event per se. In addition, detection of unknown events is hampered in products that also contain known authorized events. Here, we outline alternative approaches for analytical detection and GMO identification and develop new methods to complement the existing routine screening procedure. We developed a fluorescent anchor-polymerase chain reaction (PCR) method for the identification of the sequences flanking the p35S and t-nos screening elements. Thus, anchor-PCR fingerprinting allows the detection of unique discriminative signals per event. In addition, we established a collection of in silico calculated fingerprints of known events to support interpretation of experimentally generated anchor-PCR GM fingerprints of blind samples. Here, we first describe the molecular characterization of a novel GMO, which expresses recombinant human intrinsic factor in Arabidopsis thaliana. Next, we purposefully treated the novel GMO as a blind sample to simulate how the new methods lead to the molecular identification of a novel unknown event without prior knowledge of its transgene sequence. The results demonstrate that the new methods complement routine screening procedures by providing direct conclusive evidence and may also be useful to resolve masking of unknown events by known events. FigureMolecular toolbox for the identification of genetically modified organisms

Bacterial Community Profiling of Plastic Litter in the Belgian Part of the North Sea.

Bacterial colonization of marine plastic litter (MPL) is known for over four decades. Still, only a few studies on the plastic colonization process and its influencing factors are reported. In this study, seafloor MPL was sampled at different locations across the Belgian part of the North Sea to study bacterial community structure using 16S metabarcoding. These marine plastic bacterial communities were compared with those of sediment and seawater, and resin pellets sampled on the beach, to investigate the origin and uniqueness of plastic bacterial communities. Plastics display great variation of bacterial community composition, while each showed significant differences from those of sediment and seawater, indicating that plastics represent a distinct environmental niche. Various environmental factors correlate with the diversity of MPL bacterial composition across plastics. In addition, intrinsic plastic-related factors such as pigment content may contribute to the differences in bacterial colonization. Furthermore, the differential abundance of known primary and secondary colonizers across the various plastics may indicate different stages of bacterial colonization, and may confound comparisons of free-floating plastics. Our studies provide insights in the factors that shape plastic bacterial colonization and shed light on the possible role of plastic as transport vehicle for bacteria through the aquatic environment.

Statistical framework for detection of genetically modified organisms based on Next Generation Sequencing

Because the number and diversity of genetically modified (GM) crops has significantly increased, their analysis based on real-time PCR (qPCR) methods is becoming increasingly complex and laborious. While several pioneers already investigated Next Generation Sequencing (NGS) as an alternative to qPCR, its practical use has not been assessed for routine analysis. In this study a statistical framework was developed to predict the number of NGS reads needed to detect transgene sequences, to prove their integration into the host genome and to identify the specific transgene event in a sample with known composition. This framework was validated by applying it to experimental data from food matrices composed of pure GM rice, processed GM rice (noodles) or a 10% GM/non-GM rice mixture, revealing some influential factors. Finally, feasibility of NGS for routine analysis of GM crops was investigated by applying the framework to samples commonly encountered in routine analysis of GM crops.

Orthology Guided Assembly in highly heterozygous crops: creating a reference transcriptome to uncover genetic diversity in Lolium perenne

Despite current advances in next-generation sequencing data analysis procedures, de novo assembly of a reference sequence required for SNP discovery and expression analysis is still a major challenge in genetically uncharacterized, highly heterozygous species. High levels of polymorphism inherent to outbreeding crop species hamper De Bruijn Graph-based de novo assembly algorithms, causing transcript fragmentation and the redundant assembly of allelic contigs. If multiple genotypes are sequenced to study genetic diversity, primary de novo assembly is best performed per genotype to limit the level of polymorphism and avoid transcript fragmentation. Here, we propose an Orthology Guided Assembly procedure that first uses sequence similarity (tBLASTn) to proteins of a model species to select allelic and fragmented contigs from all genotypes and then performs CAP3 clustering on a gene-by-gene basis. Thus, we simultaneously annotate putative orthologues for each protein of the model species, resolve allelic redundancy and fragmentation and create a de novo transcript sequence representing the consensus of all alleles present in the sequenced genotypes. We demonstrate the procedure using RNA-seq data from 14 genotypes of Lolium perenne to generate a reference transcriptome for gene discovery and translational research, to reveal the transcriptome-wide distribution and density of SNPs in an outbreeding crop and to illustrate the effect of polymorphisms on the assembly procedure. The results presented here illustrate that constructing a non-redundant reference sequence is essential for comparative genomics, orthology-based annotation and candidate gene selection but also for read mapping and subsequent polymorphism discovery and/or read count-based gene expression analysis.

Assessment of primer/template mismatch effects on real-time PCR amplification of target taxa for GMO quantification.

GMO quantification, based on real-time PCR, relies on the amplification of an event-specific transgene assay and a species-specific reference assay. The uniformity of the nucleotide sequences targeted by both assays across various transgenic varieties is an important prerequisite for correct quantification. Single nucleotide polymorphisms (SNPs) frequently occur in the maize genome and might lead to nucleotide variation in regions used to design primers and probes for reference assays. Further, they may affect the annealing of the primer to the template and reduce the efficiency of DNA amplification. We assessed the effect of a minor DNA template modification, such as a single base pair mismatch in the primer attachment site, on real-time PCR quantification. A model system was used based on the introduction of artificial mismatches between the forward primer and the DNA template in the reference assay targeting the maize starch synthase (SSIIb) gene. The results show that the presence of a mismatch between the primer and the DNA template causes partial to complete failure of the amplification of the initial DNA template depending on the type and location of the nucleotide mismatch. With this study, we show that the presence of a primer/template mismatch affects the estimated total DNA quantity to a varying degree.

Are We There Yet? Reliably Estimating the Completeness of Plant Genome Sequences

Based on the strengths and weaknesses of different measures to estimate genome assembly and gene space completeness, guidelines for future plant genome projects are provided. Genome sequencing is becoming cheaper and faster thanks to the introduction of next-generation sequencing techniques. Dozens of new plant genome sequences have been released in recent years, ranging from small to gigantic repeat-rich or polyploid genomes. Most genome projects have a dual purpose: delivering a contiguous, complete genome assembly and creating a full catalog of correctly predicted genes. Frequently, the completeness of a species’ gene catalog is measured using a set of marker genes that are expected to be present. This expectation can be defined along an evolutionary gradient, ranging from highly conserved genes to species-specific genes. Large-scale population resequencing studies have revealed that gene space is fairly variable even between closely related individuals, which limits the definition of the expected gene space, and, consequently, the accuracy of estimates used to assess genome and gene space completeness. We argue that, based on the desired applications of a genome sequencing project, different completeness scores for the genome assembly and/or gene space should be determined. Using examples from several dicot and monocot genomes, we outline some pitfalls and recommendations regarding methods to estimate completeness during different steps of genome assembly and annotation.

Knowledge-technology-based discovery of unauthorized genetically modified organisms

Various legislations worldwide provide a framework for the authorization of genetically modified organisms (GMOs) and products derived therefrom [1]. Despite these regulations, novel GMOs occasionally enter the market without authorization [2–22] (Table 1) and are referred to as unauthorized GMOs (UGMs). The presence of UGMs in food and feed raises safety and labeling concerns, and challenges international trade [23, 24]. Recently reported UGM incidents have created an urgent need to harmonize regulations at a global level, and call for appropriate strategies to discover UGMs. However, some novel UGMs are intrinsically difficult to detect using current analytical strategies for reasons outlined herein. We therefore propose a paradigm shift in the way UGMs can be discovered: a documentationbased screening for products that potentially contain UGMs using knowledge technologies, followed by analytical confirmation. Here, we will describe the main concepts of the novel approach, illustrate it with a case study, and outline benefits, limitations, and complementarities compared with the current analytical detection strategy.