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Dive into the research topics where Henri van de Geest is active.

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Featured researches published by Henri van de Geest.


Nature Genetics | 2017

High-quality de novo assembly of the apple genome and methylome dynamics of early fruit development

Nicolas Daccord; Jean-Marc Celton; Gareth Linsmith; Claude Becker; Nathalie Choisne; Elio Schijlen; Henri van de Geest; Luca Bianco; Diego Micheletti; Riccardo Velasco; Erica A. Di Pierro; Jérôme Gouzy; Philippe Guérif; Hélène Muranty; Charles-Eric Durel; François Laurens; Yves Lespinasse; Sylvain Gaillard; Sébastien Aubourg; Hadi Quesneville; Detlef Weigel; Eric van de Weg; Michela Troggio; Etienne Bucher

Using the latest sequencing and optical mapping technologies, we have produced a high-quality de novo assembly of the apple (Malus domestica Borkh.) genome. Repeat sequences, which represented over half of the assembly, provided an unprecedented opportunity to investigate the uncharacterized regions of a tree genome; we identified a new hyper-repetitive retrotransposon sequence that was over-represented in heterochromatic regions and estimated that a major burst of different transposable elements (TEs) occurred 21 million years ago. Notably, the timing of this TE burst coincided with the uplift of the Tian Shan mountains, which is thought to be the center of the location where the apple originated, suggesting that TEs and associated processes may have contributed to the diversification of the apple ancestor and possibly to its divergence from pear. Finally, genome-wide DNA methylation data suggest that epigenetic marks may contribute to agronomically relevant aspects, such as apple fruit development.


BMC Genomics | 2013

Tomato breeding in the genomics era: insights from a SNP array

Marcela Víquez-Zamora; Ben Vosman; Henri van de Geest; Arnaud G. Bovy; Richard G. F. Visser; Richard Finkers; Adriaan W. van Heusden

BackgroundThe major bottle neck in genetic and linkage studies in tomato has been the lack of a sufficient number of molecular markers. This has radically changed with the application of next generation sequencing and high throughput genotyping. A set of 6000 SNPs was identified and 5528 of them were used to evaluate tomato germplasm at the level of species, varieties and segregating populations.ResultsFrom the 5528 SNPs, 1980 originated from 454-sequencing, 3495 from Illumina Solexa sequencing and 53 were additional known markers. Genotyping different tomato samples allowed the evaluation of the level of heterozygosity and introgressions among commercial varieties. Cherry tomatoes were especially different from round/beefs in chromosomes 4, 5 and 12. We were able to identify a set of 750 unique markers distinguishing S. lycopersicum ‘Moneymaker’ from all its distantly related wild relatives. Clustering and neighbour joining analysis among varieties and species showed expected grouping patterns, with S. pimpinellifolium as the most closely related to commercial tomatoesearlier results.ConclusionsOur results show that a SNP search in only a few breeding lines already provides generally applicable markers in tomato and its wild relatives. It also shows that the Illumina bead array generated data are highly reproducible. Our SNPs can roughly be divided in two categories: SNPs of which both forms are present in the wild relatives and in domesticated tomatoes (originating from common ancestors) and SNPs unique for the domesticated tomato (originating from after the domestication event). The SNPs can be used for genotyping, identification of varieties, comparison of genetic and physical linkage maps and to confirm (phylogenetic) relations. In the SNPs used for the array there is hardly any overlap with the SolCAP array and it is strongly recommended to combine both SNP sets and to select a core collection of robust SNPs completely covering the entire tomato genome.


Plant Physiology | 2016

Genome-Wide Association Mapping and Genomic Prediction Elucidate the Genetic Architecture of Morphological Traits in Arabidopsis

Rik Kooke; Willem Kruijer; Ralph Bours; Frank Becker; Andre Kuhn; Henri van de Geest; Jaap Buntjer; Timo Doeswijk; José Guerra; Harro J. Bouwmeester; Dick Vreugdenhil; Joost J. B. Keurentjes

Integration of genome wide association mapping and genomic prediction increases resolution of genetic architecture and uncovers missing heritability of quantitative traits in plants. Quantitative traits in plants are controlled by a large number of genes and their interaction with the environment. To disentangle the genetic architecture of such traits, natural variation within species can be explored by studying genotype-phenotype relationships. Genome-wide association studies that link phenotypes to thousands of single nucleotide polymorphism markers are nowadays common practice for such analyses. In many cases, however, the identified individual loci cannot fully explain the heritability estimates, suggesting missing heritability. We analyzed 349 Arabidopsis accessions and found extensive variation and high heritabilities for different morphological traits. The number of significant genome-wide associations was, however, very low. The application of genomic prediction models that take into account the effects of all individual loci may greatly enhance the elucidation of the genetic architecture of quantitative traits in plants. Here, genomic prediction models revealed different genetic architectures for the morphological traits. Integrating genomic prediction and association mapping enabled the assignment of many plausible candidate genes explaining the observed variation. These genes were analyzed for functional and sequence diversity, and good indications that natural allelic variation in many of these genes contributes to phenotypic variation were obtained. For ACS11, an ethylene biosynthesis gene, haplotype differences explaining variation in the ratio of petiole and leaf length could be identified.


The Plant Cell | 2017

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

Maximilian Schmidt; Alexander Vogel; Alisandra Denton; Benjamin Istace; Alexandra Wormit; Henri van de Geest; Marie E. Bolger; Saleh Alseekh; Janina Maß; Christian Pfaff; Ulrich Schurr; Roger T. Chetelat; Florian Maumus; Jean-Marc Aury; Sergey Koren; Alisdair R. Fernie; D. Zamir; Anthony M. Bolger; Bjoern Usadel

With no capital costs, inexpensive Oxford Nanopore sequencing can be applied to novel ∼1-Gb plant genomes. Updates in nanopore technology have made it possible to obtain gigabases of sequence data. Prior to this, nanopore sequencing technology was mainly used to analyze microbial samples. Here, we describe the generation of a comprehensive nanopore sequencing data set with a median read length of 11,979 bp for a self-compatible accession of the wild tomato species Solanum pennellii. We describe the assembly of its genome to a contig N50 of 2.5 MB. The assembly pipeline comprised initial read correction with Canu and assembly with SMARTdenovo. The resulting raw nanopore-based de novo genome is structurally highly similar to that of the reference S. pennellii LA716 accession but has a high error rate and was rich in homopolymer deletions. After polishing the assembly with Illumina reads, we obtained an error rate of <0.02% when assessed versus the same Illumina data. We obtained a gene completeness of 96.53%, slightly surpassing that of the reference S. pennellii. Taken together, our data indicate that such long read sequencing data can be used to affordably sequence and assemble gigabase-sized plant genomes.


BMC Genomics | 2013

Genomic analysis of the native European Solanum species, S. dulcamara

Nunzio D’Agostino; T. M. Golas; Henri van de Geest; Aureliano Bombarely; Thikra Dawood; Jan Zethof; Nicky Driedonks; Erik Wijnker; Joachim W. Bargsten; Jan-Peter Nap; Celestina Mariani; Ivo Rieu

BackgroundSolanum dulcamara (bittersweet, climbing nightshade) is one of the few species of the Solanaceae family native to Europe. As a common weed it is adapted to a wide range of ecological niches and it has long been recognized as one of the alternative hosts for pathogens and pests responsible for many important diseases in potato, such as Phytophthora. At the same time, it may represent an alternative source of resistance genes against these diseases. Despite its unique ecology and potential as a genetic resource, genomic research tools are lacking for S. dulcamara. We have taken advantage of next-generation sequencing to speed up research on and use of this non-model species.ResultsIn this work, we present the first large-scale characterization of the S. dulcamara transcriptome. Through comparison of RNAseq reads from two different accessions, we were able to predict transcript-based SNP and SSR markers. Using the SNP markers in combination with genomic AFLP and CAPS markers, the first genome-wide genetic linkage map of bittersweet was generated. Based on gene orthology, the markers were anchored to the genome of related Solanum species (tomato, potato and eggplant), revealing both conserved and novel chromosomal rearrangements. This allowed a better estimation of the evolutionary moment of rearrangements in a number of cases and showed that chromosomal breakpoints are regularly re-used.ConclusionKnowledge and tools developed as part of this study pave the way for future genomic research and exploitation of this wild Solanum species. The transcriptome assembly represents a resource for functional analysis of genes underlying interesting biological and agronomical traits and, in the absence of the full genome, provides a reference for RNAseq gene expression profiling aimed at understanding the unique biology of S. dulcamara. Cross-species orthology-based marker selection is shown to be a powerful tool to quickly generate a comparative genetic map, which may speed up gene mapping and contribute to the understanding of genome evolution within the Solanaceae family.


BMC Plant Biology | 2014

Over-expression of Arabidopsis AtCHR23 chromatin remodeling ATPase results in increased variability of growth and gene expression

Adam Folta; Edouard Severing; Julian Krauskopf; Henri van de Geest; Jan Verver; Jan-Peter Nap; Ludmila Mlynárová

BackgroundPlants are sessile organisms that deal with their -sometimes adverse- environment in well-regulated ways. Chromatin remodeling involving SWI/SNF2-type ATPases is thought to be an important epigenetic mechanism for the regulation of gene expression in different developmental programs and for integrating these programs with the response to environmental signals. In this study, we report on the role of chromatin remodeling in Arabidopsis with respect to the variability of growth and gene expression in relationship to environmental conditions.ResultsAlready modest (2-fold) over-expression of the AtCHR23 ATPase gene in Arabidopsis results in overall reduced growth compared to the wild-type. Detailed analyses show that in the root, the reduction of growth is due to reduced cell elongation. The reduced-growth phenotype requires sufficient light and is magnified by applying deliberate abiotic (salt, osmotic) stress. In contrast, the knockout mutation of AtCHR23 does not lead to such visible phenotypic effects. In addition, we show that over-expression of AtCHR23 increases the variability of growth in populations of genetically identical plants. These data indicate that accurate and controlled expression of AtCHR23 contributes to the stability or robustness of growth. Detailed RNAseq analyses demonstrate that upon AtCHR23 over-expression also the variation of gene expression is increased in a subset of genes that associate with environmental stress. The larger variation of gene expression is confirmed in individual plants with the help of independent qRT-PCR analysis.ConclusionsOver-expression of AtCHR23 gives Arabidopsis a phenotype that is markedly different from the growth arrest phenotype observed upon over-expression of AtCHR12, the paralog of AtCHR23, in response to abiotic stress. This demonstrates functional sub-specialization of highly similar ATPases in Arabidopsis. Over-expression of AtCHR23 increases the variability of growth among genetically identical individuals in a way that is consistent with increased variability of expression of a distinct subset of genes that associate with environmental stress. We propose that ATCHR23-mediated chromatin remodeling is a potential component of a buffer system in plants that protects against environmentally-induced phenotypic and transcriptional variation.


bioRxiv | 2017

Reconstructing The Gigabase Plant Genome Of Solanum pennellii Using Nanopore Sequencing

Maximilian Schmidt; Alxander Vogel; Alisandra Denton; Benjamin Istace; Alexandra Wormit; Henri van de Geest; Marie E. Bolger; Saleh Alseekh; Janina Mass; Christian Pfaff; Ulrich Schurr; Roger T. Chetelat; Florian Maumus; Jean-Marc Aury; Alisdair R. Fernie; Dani Zamir; Anthony M. Bolger; Bjoern Usadel

Recent updates in sequencing technology have made it possible to obtain Gigabases of sequence data from one single flowcell. Prior to this update, the nanopore sequencing technology was mainly used to analyze and assemble microbial samples1-3. Here, we describe the generation of a comprehensive nanopore sequencing dataset with a median fragment size of 11,979 bp for the wild tomato species Solanum pennellii featuring an estimated genome size of ca 1.0 to 1.1 Gbases. We describe its genome assembly to a contig N50 of 2.5 MB using a pipeline comprising a Canu4 pre-processing and a subsequent assembly using SMARTdenovo. We show that the obtained nanopore based de novo genome reconstruction is structurally highly similar to that of the reference S. pennellii LA7165 genome but has a high error rate caused mostly by deletions in homopolymers. After polishing the assembly with Illumina short read data we obtained an error rate of <0.02 % when assessed versus the same Illumina data. More importantly however we obtained a gene completeness of 96.53% which even slightly surpasses that of the reference S. pennellii genome5. Taken together our data indicate such long read sequencing data can be used to affordably sequence and assemble Gbase sized diploid plant genomes. Raw data is available at http://www.plabipd.de/portal/solanum-pennellii and has been deposited as PRJEB19787.


Plant Cell Reports | 2017

Re-sequencing transgenic plants revealed rearrangements at T-DNA inserts, and integration of a short T-DNA fragment, but no increase of small mutations elsewhere

Henk J. Schouten; Henri van de Geest; Sofia Papadimitriou; Marian Bemer; Jan G. Schaart; M.J.M. Smulders; Gabino Sanchez Perez; Elio Schijlen

Key messageTransformation resulted in deletions and translocations at T-DNA inserts, but not in genome-wide small mutations. A tiny T-DNA splinter was detected that probably would remain undetected by conventional techniques.AbstractWe investigated to which extent Agrobacterium tumefaciens-mediated transformation is mutagenic, on top of inserting T-DNA. To prevent mutations due to in vitro propagation, we applied floral dip transformation of Arabidopsis thaliana. We re-sequenced the genomes of five primary transformants, and compared these to genomic sequences derived from a pool of four wild-type plants. By genome-wide comparisons, we identified ten small mutations in the genomes of the five transgenic plants, not correlated to the positions or number of T-DNA inserts. This mutation frequency is within the range of spontaneous mutations occurring during seed propagation in A. thaliana, as determined earlier. In addition, we detected small as well as large deletions specifically at the T-DNA insert sites. Furthermore, we detected partial T-DNA inserts, one of these a tiny 50-bp fragment originating from a central part of the T-DNA construct used, inserted into the plant genome without flanking other T-DNA. Because of its small size, we named this fragment a T-DNA splinter. As far as we know this is the first report of such a small T-DNA fragment insert in absence of any T-DNA border sequence. Finally, we found evidence for translocations from other chromosomes, flanking T-DNA inserts. In this study, we showed that next-generation sequencing (NGS) is a highly sensitive approach to detect T-DNA inserts in transgenic plants.


Frontiers in Behavioral Neuroscience | 2015

Differentially expressed genes linked to natural variation in long-term memory formation in Cotesia parasitic wasps.

Joke J. F. A. van Vugt; Katja M. Hoedjes; Henri van de Geest; Elio W. G. M. Schijlen; Louise E. M. Vet; Hans M. Smid

Even though learning and memory are universal traits in the Animal Kingdom, closely related species reveal substantial variation in learning rate and memory dynamics. To determine the genetic background of this natural variation, we studied two congeneric parasitic wasp species, Cotesia glomerata and C. rubecula, which lay their eggs in caterpillars of the large and small cabbage white butterfly. A successful egg laying event serves as an unconditioned stimulus (US) in a classical conditioning paradigm, where plant odors become associated with the encounter of a suitable host caterpillar. Depending on the host species, the number of conditioning trials and the parasitic wasp species, three different types of transcription-dependent long-term memory (LTM) and one type of transcription-independent, anesthesia-resistant memory (ARM) can be distinguished. To identify transcripts underlying these differences in memory formation, we isolated mRNA from parasitic wasp heads at three different time points between induction and consolidation of each of the four memory types, and for each sample three biological replicates, where after strand-specific paired-end 100 bp deep sequencing. Transcriptomes were assembled de novo and differential expression was determined for each memory type and time point after conditioning, compared to unconditioned wasps. Most differentially expressed (DE) genes and antisense transcripts were only DE in one of the LTM types. Among the DE genes that were DE in two or more LTM types, were many protein kinases and phosphatases, small GTPases, receptors and ion channels. Some genes were DE in opposing directions between any of the LTM memory types and ARM, suggesting that ARM in Cotesia requires the transcription of genes inhibiting LTM or vice versa. We discuss our findings in the context of neuronal functioning, including RNA splicing and transport, epigenetic regulation, neurotransmitter/peptide synthesis and antisense transcription. In conclusion, these brain transcriptomes provide candidate genes that may be involved in the observed natural variation in LTM in closely related Cotesia parasitic wasp species.


PLOS ONE | 2018

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment

Sven Warris; N. Roshan N. Timal; Marcel Kempenaar; Arne M. Poortinga; Henri van de Geest; Ana Lucia Varbanescu; Jan-Peter Nap

Background Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python. Results The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS. Conclusions pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.

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Sven Warris

Wageningen University and Research Centre

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Elio Schijlen

Wageningen University and Research Centre

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Jan-Peter Nap

Wageningen University and Research Centre

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Arnaud G. Bovy

Wageningen University and Research Centre

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Cees Waalwijk

Wageningen University and Research Centre

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Theo van der Lee

Wageningen University and Research Centre

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Florian Maumus

Université Paris-Saclay

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