Staff Publications

Staff Publications

  • external user (warningwarning)
  • Log in as
  • language uk
  • About

    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

    We have a manual that explains all the features 

Records 1 - 20 / 352

  • help
  • print

    Print search results

  • export
    A maximum of 250 titles can be exported. Please, refine your queryYou can also select and export up to 30 titles via your marked list.
  • alert
    We will mail you new results for this query: q=Ridder
Check title to add to marked list
Haplotype estimation in polyploids using DNA sequence data
Motazedi, Ehsan - \ 2019
Wageningen University. Promotor(en): D. de Ridder, co-promotor(en): C.A. Maliepaard; H.J. Finkers. - Wageningen : Wageningen University - ISBN 9789463951210 - 153
Application of high performance compute technology in bioinformatics
Warris, Sven - \ 2019
Wageningen University. Promotor(en): D. de Ridder, co-promotor(en): J.P. Nap. - Wageningen : Wageningen University - ISBN 9789463951128 - 156
Profile hidden Markov models trained on aligned KEGG Orthology sequences for enzyme annotation
Rodenburg, Y.A. ; Ridder, D. de; Govers, F. ; Seidl, M.F. - \ 2019
Wageningen University & Research
annotation - bioinformatics - enzymes - hidden Markov models - HMM - homology - KEGG - Kyoto Encyclopedia of Genes and Genomes - proteins
Profile hidden Markov models trained on aligned KEGG Orthology sequences for enzyme annotation. These HMMs were used to reconstruct metabolic networks for the manuscript: The genome of Peronospora belbahrii reveals high heterozygosity, a low number of canonical effectors and CT-rich promoters
The genome of Peronospora belbahrii reveals high heterozygosity, a low number of canonical effectors and CT-rich promoters
Thines, M. ; Sharma, R. ; Rodenburg, Y.A. ; Gogleva, A. ; Judelson, H.S. ; Xia, X. ; Hoogen, D.J. van den; Kitner, M. ; Klein, J. ; Neilen, M. ; Ridder, D. de; Seidl, M.F. ; Ackerveken, G. van den; Govers, F. ; Schornack, S. ; Studholme, D.J. - \ 2019
Along with Plasmopara destructor, Peronosopora belbahrii has arguably been the economically most important newly emerging downy mildew pathogen of the past two decades. Originating from Africa, it has started devastating basil production throughout the world, most likely due to the distribution of infested seed material. Here we present the genome of this pathogen and results from comparisons of its genomic features to other oomycetes. The assembly of the nuclear genome was ca. 35.4 Mbp in length, with an N50 scaffold length of ca. 248 kbp and an L50 scaffold count of 46. The circular mitochondrial genome consisted of ca. 40.1 kbp. From the repeat-masked genome 9049 protein-coding genes were predicted, out of which 335 were predicted to have extracellular functions, representing the smallest secretome so far found in peronosporalean oomycetes. About 16 % of the genome consists of repetitive sequences, and based on simple sequence repeat regions, we provide a set of microsatellites that could be used for population genetic studies of Pe. belbahrii. Peronospora belbahrii has undergone a high degree of convergent evolution, reflecting its obligate biotrophic lifestyle. Features of its secretome, signalling networks, and promoters are presented, and some patterns are hypothesised to reflect the high degree of host specificity in Peronospora species. In addition, we suggest the presence of additional virulence factors apart from classical effector classes that are promising candidates for future functional studies.
Designing Eukaryotic Gene Expression Regulation Using Machine Learning
Jongh, Ronald P.H. de; Dijk, Aalt D.J. van; Julsing, Mattijs K. ; Schaap, Peter J. ; Ridder, Dick de - \ 2019
Trends in Biotechnology (2019). - ISSN 0167-7799
DNA design - eukaryotic gene expression - gene regulation - machine learning - synthetic biology

Controlling the expression of genes is one of the key challenges of synthetic biology. Until recently fine-tuned control has been out of reach, particularly in eukaryotes owing to their complexity of gene regulation. With advances in machine learning (ML) and in particular with increasing dataset sizes, models predicting gene expression levels from regulatory sequences can now be successfully constructed. Such models form the cornerstone of algorithms that allow users to design regulatory regions to achieve a specific gene expression level. In this review we discuss strategies for data collection, data encoding, ML practices, design algorithm choices, and finally model interpretation. Ultimately, these developments will provide synthetic biologists with highly specific genetic building blocks to rationally engineer complex pathways and circuits.

The One that I Want: Strong personal preferences render the center-stage nudge redundant
Venema, Tina A.G. ; Kroese, Floor M. ; Vet, E. De; Ridder, Denise T.D. De - \ 2019
Food Quality and Preference 78 (2019). - ISSN 0950-3293
Center-stage effect - Effectiveness - Healthy diet goals - Nudge - Preference - Soft drinks

In recent years there has been increased attention for nudging as a tool to alter consumer decisions. While nudges should in theory preserve freedom of choice by respecting consumers’ preferences, empirical scrutiny of this claim is sparse. This research investigates the effectiveness of a center-stage nudge to encourage the consumption of a small portion size of soda. Specifically, in all studies we measure the extent to which strong preferences that are incongruent with the aim of the nudge (i.e. thirst and liking) and nudge congruent preferences (i.e. intentions to reduce soda consumption (study 1); Healthy diet goals (observed in study 2; manipulated in study 3) could be expressed when a choice is nudged. In three studies (n = 119; n = 184; n = 202) it was found that strong preferences are not trumped by the nudge and in fact overrule the effectiveness of a center-stage nudge. These findings contribute to the debate about the ethical considerations that are voiced concerning nudge interventions, and urge choice architects to consider consumers’ prior preferences as an important boundary condition of effective nudge interventions.

Metabolic Model of the Phytophthora infestans-Tomato Interaction Reveals Metabolic Switches during Host Colonization
Rodenburg, Sander Y.A. ; Seidl, Michael F. ; Judelson, Howard S. ; Vu, Andrea L. ; Govers, Francine ; Ridder, Dick de - \ 2019
mBio 10 (2019)4. - ISSN 2150-7511
metabolic modeling - metabolism - oomycetes - Phytophthora infestans - tomato

The oomycete pathogen Phytophthora infestans causes potato and tomato late blight, a disease that is a serious threat to agriculture. P. infestans is a hemibiotrophic pathogen, and during infection, it scavenges nutrients from living host cells for its own proliferation. To date, the nutrient flux from host to pathogen during infection has hardly been studied, and the interlinked metabolisms of the pathogen and host remain poorly understood. Here, we reconstructed an integrated metabolic model of P. infestans and tomato (Solanum lycopersicum) by integrating two previously published models for both species. We used this integrated model to simulate metabolic fluxes from host to pathogen and explored the topology of the model to study the dependencies of the metabolism of P. infestans on that of tomato. This showed, for example, that P. infestans, a thiamine auxotroph, depends on certain metabolic reactions of the tomato thiamine biosynthesis. We also exploited dual-transcriptome data of a time course of a full late blight infection cycle on tomato leaves and integrated the expression of metabolic enzymes in the model. This revealed profound changes in pathogen-host metabolism during infection. As infection progresses, P. infestans performs less de novo synthesis of metabolites and scavenges more metabolites from tomato. This integrated metabolic model for the P. infestans-tomato interaction provides a framework to integrate data and generate hypotheses about in planta nutrition of P. infestans throughout its infection cycle.IMPORTANCE Late blight disease caused by the oomycete pathogen Phytophthora infestans leads to extensive yield losses in tomato and potato cultivation worldwide. To effectively control this pathogen, a thorough understanding of the mechanisms shaping the interaction with its hosts is paramount. While considerable work has focused on exploring host defense mechanisms and identifying P. infestans proteins contributing to virulence and pathogenicity, the nutritional strategies of the pathogen are mostly unresolved. Genome-scale metabolic models (GEMs) can be used to simulate metabolic fluxes and help in unravelling the complex nature of metabolism. We integrated a GEM of tomato with a GEM of P. infestans to simulate the metabolic fluxes that occur during infection. This yields insights into the nutrients that P. infestans obtains during different phases of the infection cycle and helps in generating hypotheses about nutrition in planta.

Family-based haplotype estimation and allele dosage correction for polyploids using short sequence reads
Motazedi, Ehsan ; Maliepaard, Chris ; Finkers, Richard ; Visser, Richard ; Ridder, Dick De - \ 2019
Frontiers in Genetics Livestock Genomics 10 (2019)MAR. - ISSN 1664-8021
Estimation - Family - Haplotype - Polyploid - Sequence data

DNA sequence reads contain information about the genomic variants located on a single chromosome. By extracting and extending this information using the overlaps between the reads, the haplotypes of an individual can be obtained. Using parent-offspring relationships in a population can considerably improve the quality of the haplotypes obtained from short reads, as pedigree information can be used to correct for spurious overlaps (due to sequencing errors) and insufficient overlaps (due to short read lengths, low genomic variation and shallow coverage). We developed a novel method, PopPoly, to estimate polyploid haplotypes in an F1-population from short sequence data by taking into consideration the transmission of the haplotypes from the parents to the offspring. In addition, this information is employed to improve genotype dosage estimation and to call missing genotypes in the population. Through simulations, we compare PopPoly to other haplotyping methods and show its better performance. We evaluate PopPoly by applying it to a tetraploid potato cross at nine genomic regions involved in tuber formation.

Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra
Rogers, Simon ; Wei Ong, Cher ; Wandy, Joe ; Ernst, Madeleine ; Ridder, Lars ; Hooft, Justin J.J. Van Der - \ 2019
Faraday Discussions 218 (2019). - ISSN 1359-6640 - p. 284 - 302.
Complex metabolite mixtures are challenging to unravel. Mass spectrometry (MS) is a widely used and sensitive technique to obtain structural information on complex mixtures. However, just knowing the molecular masses of the mixture’s constituents is almost always insufficient for confident assignment of the associated chemical structures. Structural information can be augmented through MS fragmentation experiments whereby detected metabolites are fragmented giving rise to MS/MS spectra. However, how can we maximize the structural information we gain from fragmentation spectra? We recently proposed a substructure-based strategy to enhance metabolite annotation for complex mixtures by considering metabolites as the sum of (bio)chemically relevant moieties that we can detect through mass spectrometry fragmentation approaches. Our MS2LDA tool allows us to discover - unsupervised - groups of mass fragments and/or neutral losses termed Mass2Motifs that often correspond to substructures. After manual annotation, these Mass2Motifs can be used in subsequent MS2LDA analyses of new datasets, thereby providing structural annotations for many molecules that are not present in spectral databases. Here, we describe how additional strategies, taking advantage of i) combinatorial in-silico matching of experimental mass features to substructures of candidate molecules, and ii) automated machine learning classification of molecules, can facilitate semi-automated annotation of substructures. We show how our approach accelerates the Mass2Motif annotation process and therefore broadens the chemical space spanned by characterized motifs. Our machine learning model used to classify fragmentation spectra learns the relationships between fragment spectra and chemical features. Classification prediction on these features can be aggregated for all molecules that contribute to a particular Mass2Motif and guide Mass2Motif annotations. To make annotated Mass2Motifs available to the community, we also present motifDB: an open database of Mass2Motifs that can be browsed and accessed programmatically through an API. MotifDB is integrated within, allowing users to efficiently search for characterized motifs in their own experiments. We expect that with an increasing number of Mass2Motif annotations available through a growing database we can more quickly gain insight in the constituents of complex mixtures. That will allow prioritization towards novel or unexpected chemistries and faster recognition of known biochemical building blocks.
Improved inference of intermolecular contacts through protein–protein interaction prediction using coevolutionary analysis
Correa Marrero, M. ; Immink, G.H. ; Ridder, D. de; Dijk, A.D.J. van - \ 2019
Bioinformatics 35 (2019)12. - ISSN 1367-4803 - p. 2036 - 2042.
Motivation: Predicting residue–residue contacts between interacting proteins is an important problem in bioinformatics. The growing wealth of sequence data can be used to infer these contacts through correlated mutation analysis on multiple sequence alignments of interacting homologs of the proteins of interest. This requires correct identification of pairs of interacting proteins for many species, in order to avoid introducing noise (i.e. non-interacting sequences) in the analysis that will decrease predictive performance.
Results: We have designed Ouroboros, a novel algorithm to reduce such noise in intermolecular contact prediction. Our method iterates between weighting proteins according to how likely they are to interact based on the correlated mutations signal, and predicting correlated mutations based on the weighted sequence alignment. We show that this approach accurately discriminates between protein interaction versus non-interaction and simultaneously improves the prediction of intermolecular contact residues compared to a naive application of correlated mutation analysis. This requires no training labels concerning interactions or contacts. Furthermore, the method relaxes the assumption of one-to-one interaction of previous approaches, allowing for the study of many-to-many interactions.
poreTally: run and publish de novo nanopore assembler benchmarks
Lannoy, Carlos de; Risse, J.E. ; Ridder, D. de - \ 2019
Bioinformatics 35 (2019)15. - ISSN 1367-4803 - p. 2663 - 2664.
Summary: Nanopore sequencing is a novel development in nucleic acid analysis. As such, nanopore-sequencing hardware and software are updated frequently and extensively, which quickly renders peer-reviewed publications on analysis pipeline benchmarking efforts outdated. To provide the user community with a faster, more flexible alternative to peer-reviewed benchmark papers for
de novo assembly tool performance we constructed poreTally, a comprehensive
benchmarking tool. poreTally automatically assembles a given read set using several often-used assembly pipelines, analyzes the resulting assemblies for correctness and continuity, and finally generates a quality report, which can immediately be published on Github/Gitlab.
Availability and implementation: poreTally is available on Github at, under an MIT license.
An analysis of characterized plant sesquiterpene synthases
Durairaj, Janani ; Girolamo, Alice Di; Bouwmeester, Harro J. ; Ridder, Dick de; Beekwilder, Jules ; Dijk, Aalt D.J. van - \ 2019
Phytochemistry 158 (2019). - ISSN 0031-9422 - p. 157 - 165.
Database - Enzyme - Product specificity - Sesquiterpene - Sesquiterpene synthase - Terpene synthase

Plants exhibit a vast array of sesquiterpenes, C15 hydrocarbons which often function as herbivore-repellents or pollinator-attractants. These in turn are produced by a diverse range of sesquiterpene synthases. A comprehensive analysis of these enzymes in terms of product specificity has been hampered by the lack of a centralized resource of sufficient functionally annotated sequence data. To address this, we have gathered 262 plant sesquiterpene synthase sequences with experimentally characterized products. The annotated enzyme sequences allowed for an analysis of terpene synthase motifs, leading to the extension of one motif and recognition of a variant of another. In addition, putative terpene synthase sequences were obtained from various resources and compared with the annotated sesquiterpene synthases. This analysis indicated regions of terpene synthase sequence space which so far are unexplored experimentally. Finally, we present a case describing mutational studies on residues altering product specificity, for which we analyzed conservation in our database. This demonstrates an application of our database in choosing likely-functional residues for mutagenesis studies aimed at understanding or changing sesquiterpene synthase product specificity.

Artificial intelligence in the lab : ask not what your computer can do for you
Ridder, Dick de - \ 2019
Microbial Biotechnology 12 (2019)1. - ISSN 1751-7907 - p. 38 - 40.
Comparative genomics including the basal pathogen Peronospora belbahrii reveal common evolutionary patterns and the monophyly of downy mildews in a paraphyletic Phytophthora
Thines, M. ; Sharma, R. ; Rodenburg, Y.A. ; Gogleva, A. ; Judelson, H.S. ; Xia, X. ; Hoogen, D.J. van den; Kitner, M. ; Klein, J. ; Ridder, D. de; Seidl, M.F. ; Ackerveken, G. van den; Govers, F. ; Schornack, S. ; Studholme, D.J. - \ 2018
PRJEB15119 - ERP016822 - Peronospora belbahrii
The obligate biotrophic downy mildew constitute the most species rich group of oomycetes. So far only handful of genomes of this group of pathogens has been sequenced. Most likely due to low taxon sampling, until now phylogenomic studies with few taxa were in stark contrast to multigene phylogenies with a large number of accessions with respect to the relationships of downy mildews and Phytophthora species. In the current study, we sequenced the whole genome of the economically important basil pathogen Peronospora belbahrii, and performed in-depth comparative genomics and phylogenomics towards clarifying some aspects of downy mildew and Phytophthora evolution.
Smartphone Apps Using Photoplethysmography for Heart Rate Monitoring: Meta-Analysis
Ridder, Benjamin De; Rompaey, Bart Van; Kampen, Jarl K. ; Haine, Steven ; Dilles, Tinne - \ 2018
JMIR Cardio 2 (2018)1. - ISSN 2561-1011
Background: Smartphone ownership is rising at a stunning rate. Moreover, smartphones prove to be suitable for use in health care due to their availability, portability, user-friendliness, relatively low price, wireless connectivity, far-reaching computing capabilities, and comprehensive memory. To measure vital signs, smartphones are often connected to a mobile sensor or a medical device. However, by using the white light-emitting diode as light source and the phone camera as photodetector, a smartphone could be used to perform photoplethysmography (PPG), enabling the assessment of vital signs. Objective: The objective of this meta-analysis was to evaluate the available evidence on the use of smartphone apps to measure heart rate by performing PPG in comparison with a validated method. Methods: PubMed and ISI Web of Knowledge were searched for relevant studies published between January 1, 2009 and December 7, 2016. The reference lists of included studies were hand-searched to find additional eligible studies. Critical Appraisal Skills Programme (CASP) Diagnostic Test Study checklist and some extra items were used for quality assessment. A fixed effects model of the mean difference and a random effects model of Pearson correlation coefficient were applied to pool the outcomes of the studies. Results: In total, 14 studies were included. The pooled result showed no significant difference between heart rate measurements with a smartphone and a validated method (mean difference −0.32; 99% CI −1.24 to 0.60; P=.37). In adults, the Pearson correlation coefficient of the relation between heart rate measurement with a smartphone and a validated method was always ≥.90. In children, the results varied depending on measuring point and heart rate. The pooled result showed a strong correlation that was significant (correlation coefficient .951; 95% CI 0.906-0.975; P<.001). The reported limits of agreement showed good agreement between a smartphone and a validated method. There was a moderately strong significant negative correlation between the year of publication of the included studies and the mean difference (r=−.69; P<.001). Conclusions: Smartphone apps measuring heart rate by performing PPG appear to agree with a validated method in an adult population during resting sinus rhythm. In a pediatric population, the use of these apps is currently not validated.
In silico predictions of variant deleteriousness in the genomes of pig species
Gross, Christian ; Derks, M. ; Ridder, D. de; Reinders, M. - \ 2018
- 1 p.
TriPoly : haplotype estimation for polyploids using sequencing data of related individuals
Motazedi, Ehsan ; Ridder, Dick de; Finkers, Richard ; Baldwin, Samantha ; Thomson, Susan ; Monaghan, Katrina ; Maliepaard, Chris - \ 2018
Bioinformatics 34 (2018)22. - ISSN 1367-4803 - p. 3864 - 3872.

Motivation: Knowledge of haplotypes, i.e. phased and ordered marker alleles on a chromosome, is essential to answer many questions in genetics and genomics. By generating short pieces of DNA sequence, high-throughput modern sequencing technologies make estimation of haplotypes possible for single individuals. In polyploids, however, haplotype estimation methods usually require deep coverage to achieve sufficient accuracy. This often renders sequencing-based approaches too costly to be applied to large populations needed in studies of Quantitative Trait Loci. Results: We propose a novel haplotype estimation method for polyploids, TriPoly, that combines sequencing data with Mendelian inheritance rules to infer haplotypes in parent-offspring trios. Using realistic simulations of both short and long-read sequencing data for banana (Musa acuminata) and potato (Solanum tuberosum) trios, we show that TriPoly yields more accurate progeny haplotypes at low coverages compared to existing methods that work on single individuals. We also apply TriPoly to phase Single Nucleotide Polymorphisms on chromosome 5 for a family of tetraploid potato with 2 parents and 37 offspring sequenced with an RNA capture approach. We show that TriPoly haplotype estimates differ from those of the other methods mainly in regions with imperfect sequencing or mapping difficulties, as it does not rely solely on sequence reads and aims to avoid phasings that are not likely to have been passed from the parents to the offspring. Availability and implementation: TriPoly has been implemented in Python 3.5.2 (also compatible with Python 2.7.3 and higher) and can be freely downloaded at Supplementary information: Supplementary data are available at Bioinformatics online.

Correcting palindromes in long reads after whole-genome amplification
Warris, S. ; Schijlen, E.G.W.M. ; Geest, H.C. van de; Vegesna, R. ; Hesselink, T. ; Lintel Hekkert, B. te; Sanchez Perez, G.F. ; Medvedev, P. ; Makova, K.D. ; Ridder, D. de - \ 2018
BMC Genomics 19 (2018). - ISSN 1471-2164
Background: Next-generation sequencing requires sufficient DNA to be available. If limited, whole-genome amplification is applied to generate additional amounts of DNA. Such amplification often results in many chimeric DNA fragments, in particular artificial palindromic sequences, which limit the usefulness of long sequencing reads. Results: Here, we present Pacasus, a tool for correcting such errors. Two datasets show that it markedly improves read mapping and de novo assembly, yielding results similar to these that would be obtained with non-amplified DNA. Conclusions: With Pacasus long-read technologies become available for sequencing targets with very small amounts of DNA, such as single cells or even single chromosomes.
Predicting variant deleteriousness in non-human species : Applying the CADD approach in mouse
Groß, Christian ; Ridder, Dick de; Reinders, Marcel - \ 2018
BMC Bioinformatics 19 (2018)1. - ISSN 1471-2105
Genome annotation - Genomics - Mouse genetics - Sequence annotation - Variant annotation

Background: Predicting the deleteriousness of observed genomic variants has taken a step forward with the introduction of the Combined Annotation Dependent Depletion (CADD) approach, which trains a classifier on the wealth of available human genomic information. This raises the question whether it can be done with less data for non-human species. Here, we investigate the prerequisites to construct a CADD-based model for a non-human species. Results: Performance of the mouse model is competitive with that of the human CADD model and better than established methods like PhastCons conservation scores and SIFT. Like in the human case, performance varies for different genomic regions and is best for coding regions. We also show the benefits of generating a species-specific model over lifting variants to a different species or applying a generic model. With fewer genomic annotations, performance on the test set as well as on the three validation sets is still good. Conclusions: It is feasible to construct species-specific CADD models even when annotations such as epigenetic markers are not available. The minimal requirement for these models is the availability of a set of genomes of closely related species that can be used to infer an ancestor genome and substitution rates for the data generation.

Efficient inference of homologs in large eukaryotic pan-proteomes
Sheikhizadeh Anari, Siavash ; Ridder, Dick de; Schranz, M.E. ; Smit, Sandra - \ 2018
BMC Bioinformatics 19 (2018)1. - ISSN 1471-2105 - 11 p.
Homologous genes - k-mer - Orthology - Pan-genome - Protein similarity

BACKGROUND: Identification of homologous genes is fundamental to comparative genomics, functional genomics and phylogenomics. Extensive public homology databases are of great value for investigating homology but need to be continually updated to incorporate new sequences. As new sequences are rapidly being generated, there is a need for efficient standalone tools to detect homologs in novel data.

RESULTS: To address this, we present a fast method for detecting homology groups across a large number of individuals and/or species. We adopted a k-mer based approach which considerably reduces the number of pairwise protein alignments without sacrificing sensitivity. We demonstrate accuracy, scalability, efficiency and applicability of the presented method for detecting homology in large proteomes of bacteria, fungi, plants and Metazoa.

CONCLUSIONS: We clearly observed the trade-off between recall and precision in our homology inference. Favoring recall or precision strongly depends on the application. The clustering behavior of our program can be optimized for particular applications by altering a few key parameters. The program is available for public use at as an extension to our pan-genomic analysis tool, PanTools.

Check title to add to marked list
<< previous | next >>

Show 20 50 100 records per page

Please log in to use this service. Login as Wageningen University & Research user or guest user in upper right hand corner of this page.