Biology subjects

de Ridder, D.

Publications and source records attributed to de Ridder, D..

54 records · Page 3Linked to original sources

bioRxiv2020

Network analysis prioritizes DEWAX and ICE1 as the candidate genes for two major eQTL hotspots in seed germination

Seed germination is characterized by a constant change of gene expression across different time points. These changes are related to specific processes, which eventually determine the onset of seed germination. To get a better understanding on the regulation of gene expression during seed germination, we performed a quantitative trait locus mapping of gene expression (eQTL) at four important seed germination stages (primary dormant, after-ripened, six-hour after imbibition, and radicle protrusion stage) using Arabidopsis thaliana Bay x Sha recombinant inbred lines (RILs). The mapping displayed the distinctness of the eQTL landscape for each stage. We found several eQTL hotspots across stages associated with the regulation of expression of a large number of genes. Interestingly, an eQTL hotspot on chromosome five collocates with hotspots for phenotypic and metabolic QTLs in the same population. Finally, we constructed a gene co-expression network to prioritize the regulatory genes for two major eQTL hotspots. The network analysis prioritizes transcription factors DEWAX and ICE1 as the most likely regulatory genes for the hotspot. Together, we have revealed that the genetic regulation of gene expression is dynamic along the course of seed germination. One-sentence summaryTwo transcription factors, DEWAX and ICE1, may be important regulators of gene expression during seed germination, based on network analysis of eQTL hotspots.

plant biology↗

bioRxiv2020

Evolutionarily conserved non-protein-coding regions in the chicken genome harbor functionally important variation

The availability of genomes for many species has advanced our understanding of the non-protein-coding fraction of the genome. Comparative genomics has proven to be an invaluable approach for the systematic, genome-wide identification of conserved non-protein-coding elements (CNEs). However, for many non-mammalian model species, including chicken, our capability to interpret the functional importance of variants overlapping CNEs has been limited by current genomic annotations, which rely on a single information type (e.g. conservation). We here studied CNEs in chicken using a combination of population genomics and comparative genomics. To investigate the functional importance of variants found in CNEs we develop a ch(icken) Combined Annotation-Dependent Depletion (chCADD), a variant effect prediction tool first introduced for humans and later on for mouse and pig. We show that 73 Mb of the chicken genome has been conserved across more than 280 million years of vertebrate evolution. The vast majority of the conserved elements are in non-protein-coding regions, which display SNP densities and allele frequency distributions characteristic of genomic regions constrained by purifying selection. By annotating SNPs with the chCADD score we are able to pinpoint specific subregions of the CNEs to be of higher functional importance, as supported by SNPs found in these subregions are associated with known disease genes in humans, mice, and rats. Taken together, our findings indicate that CNEs harbor variants of functional significance that should be object of further investigation along with protein-coding mutations. We therefore anticipate chCADD to be of great use to the scientific community and breeding companies in future functional studies in chicken.

genomics↗

bioRxiv2020

Widespread targeting of development-related host transcription factors by phytoplasma effectors

Phytoplasmas are pathogenic bacteria that reprogram plant host development for their own benefit. Previous studies have characterized a few different phytoplasma effector proteins that destabilize specific plant transcription factors. However, these are only a small fraction of the potential effectors used by phytoplasmas; therefore, the molecular mechanisms through which phytoplasmas modulate their hosts require further investigation. To obtain further insights into the phytoplasma infection mechanisms, we generated a protein-protein interaction network between a broad set of phytoplasma effectors and a large, unbiased collection of Arabidopsis thaliana transcription factors and transcriptional regulators. We found widespread, but specific, interactions between phytoplasma effectors and host transcription factors, especially those related to host developmental processes. In particular, many unrelated effectors target specific sets of TCP transcription factors, which regulate plant development and immunity. Comparison with other host-pathogen protein interaction networks shows that phytoplasma effectors have unusual targets, indicating that phytoplasmas have evolved a unique and unusual infection strategy. This study contributes a rich and solid data source that guides further investigations of the functions of individual effectors, as demonstrated for some herein. Moreover, the dataset provides insights into the underlying molecular mechanisms of phytoplasma infection.

plant biology↗

bioRxiv2020

Oomycete metabolism is highly dynamic and reflects lifestyle adaptations

Pathogen-host symbiosis drives metabolic adaptations. Animal and plant pathogenic oomycetes are thought to adapt their metabolism to facilitate interactions with their hosts. Here, we performed a large-scale comparison of oomycete metabolism and uncovered considerable variation in oomycete metabolism that could be linked to differences in lifestyle. Pathway comparisons revealed that plant pathogenic oomycetes can be divided in two parts; a conserved part and an accessory part. The accessory part could be associated with the degradation of plant compounds produced during defence responses. Obligate biotrophic oomycetes have smaller metabolic networks, and this group displays converged evolution by repeated gene losses affecting the same metabolic pathways. A comparison of the metabolic networks of obligate biotrophic oomycetes with those of plant pathogenic oomycetes as a whole revealed that the losses of metabolic enzymes in biotrophs are not random and that the network of biotrophs contracts from the periphery inwards. Our analyses represent the first metabolism-focused comparison of oomycetes at this scale and will contribute to a better understanding of the evolution and relationship between metabolism and lifestyle adaptation. ORIGINALITY & SIGNFICANCE STATEMENTThe intimate interaction between pathogens and their hosts exerts strong selection pressure leading to rapid adaptation. How this shapes the metabolism of pathogens is largely unknown. Here, we used comparative genomics to systematically characterize the metabolisms of animal and plant pathogenic oomycetes, a group of eukaryotes comprising many important animal and plant pathogens with significant economic and ecological impact. Core- and pan-genome as well as metabolic network analyses of distantly related oomycetes and their non-pathogenic relatives revealed considerable lifestyle- and lineage-specific adaptations. Extreme lifestyle adaptation could be observed in the metabolism of obligate biotrophic oomycetes - a group of pathogens that require a living host for proliferation. The metabolic networks of obligate biotrophic oomycetes reflect profound patterns of reductive evolution, converging to a loss the same metabolic enzymes during acquisition of an obligate parasitic lifestyle. These findings contribute to a be better understanding of oomycete evolution and the relationship between metabolism and lifestyle adaptation.

evolutionary biology↗

bioRxiv2020

Hap10: reconstructing accurate and long polyploid haplotypes using linked reads

BackgroundHaplotype information is essential for many genetic and genomic analyses, including genotype-phenotype associations in human, animals and plants. Haplotype assembly is a method for reconstructing haplotypes from DNA sequencing reads. By the advent of new sequencing technologies, new algorithms are needed to ensure long and accurate haplotypes. While a few linked-read haplotype assembly algorithms are available for diploid genomes, there are no algorithms yet for polyploids. ResultsThe first haplotyping algorithm designed for 10X linked reads generated from a polyploid genome is presented, built on a typical short-read haplotyping method, SDhaP. Using the input aligned reads and called variants, the haplotype-relevant information is extracted. Next, reads with the same barcodes are combined to produce molecule-specific fragments. Then, these fragments are clustered into strongly connected components which are then used as input of a haplotype assembly core in order to estimate accurate and long haplotypes. ConclusionsHap10 is a novel algorithm for haplotype assembly of polyploid genomes using linked reads. The performance of the algorithms is evaluated in a number of simulation scenarios and its applicability is demonstrated on a real dataset of sweet potato.

bioinformatics↗

bioRxiv2019

Pangenomic read mapping

In modern genomics, mapping reads to a single reference genome is common practice. However, a reference genome does not necessarily accurately represent a population or species and as a result a substantial percentage of reads often cannot be mapped. A number of graph-based variation-aware mapping methods have recently been proposed to remedy this. Here, we propose an alternative multi-reference approach, which aligns reads to large collections of genomes simultaneously. Our approach, an extension to our pangenomics suite PanTools (https://git.wur.nl/bioinformatics/pantools), is as accurate as state-of the-art tools but more efficient on large numbers of genomes. We successfully applied PanTools to map genomic and metagenomic reads to large collections of viral, archaeal, bacterial, fungal and plant genomes.

bioinformatics↗

bioRxiv2019

WormQTL2: an interactive platform for systems genetics in Caenorhabditis elegans

Quantitative genetics provides the tools for linking polymorphic loci (QTLs) to trait variation. Linkage analysis of gene expression is an established and widely applied method, leading to the identification of expression quantitative trait loci (eQTLs). (e)QTL detection facilitates the identification and understanding of the underlying molecular components and pathways, yet (e)QTL data access and mining often is a bottleneck. Here we present WormQTL2 (www.bioinformatics.nl/WormQTL2/), a database and platform for comparative investigations and meta-analyses of published (e)QTL datasets in the model nematode worm C. elegans. WormQTL2 integrates six eQTL studies spanning 11 conditions as-well-as over 1000 traits from 32 studies and allows experimental results to be compared, reused, and extended upon to guide further experiments and conduct systems-genetic analyses. For example, one can easily screen a locus for specific cis-eQTLs that could be linked to variation in other traits, detect gene-by-environment interactions by comparing eQTLs under different conditions, or find correlations between QTL profiles of classical traits and gene expression.

genetics↗

bioRxiv2019

Hecaton: reliably detecting copy number variation in plant genomes using short read sequencing data

Copy number variation (CNV) is thought to actively contribute to adaptive evolution of plant species. While many computational algorithms are available to detect copy number variation from whole genome sequencing datasets, the typical complexity of plant data likely introduces false positive calls.\n\nTo enable reliable and comprehensive detection of CNV in plant genomes, we developed Hecaton, a novel computational workflow tailored to plants, that integrates calls from multiple state-of-the-art algorithms through a machine-learning approach. In this paper, we demonstrate that Hecaton outperforms current methods when applied to short read sequencing data of A. thaliana, rice, maize, and tomato. Moreover, it correctly detects dispersed duplications, a type of CNV commonly found in plant species, in contrast to several state-of-the-art tools that erroneously represent this type of CNV as overlapping deletions and tandem duplications. Finally, Hecaton scales well in terms of memory usage and running time when applied to short read datasets of domesticated and wild tomato accessions. Hecaton provides a robust method to detect CNV in plants. We expect it to be of immediate interest to both applied and fundamental research on the relationship between genotype and phenotype in plants.

bioinformatics↗

bioRxiv2019

The genome of Peronospora belbahrii reveals high heterozygosity, a low number of canonical effectors and CT-rich promoters

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.

genomics↗

bioRxiv2018

An Analysis of Characterized Plant Sesquiterpene Synthases

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.

bioinformatics↗

bioRxiv2018

poreTally: run and publish de novo Nanopore assembler benchmarks

Nanopore sequencing is a novel approach to nucleic acid analysis that generates long, error-prone reads. Since device components, base calling software and best practices for sample preparation are updated frequently and extensively, the nature of the produced data also changes frequently. As a result, peer-reviewed publications on de novo assembly pipeline benchmarking efforts are quickly rendered outdated by the next major improvement to the sequencing platforms. 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. Results can immediately be shared with peers in a Github/Gitlab repository. Furthermore, we aim to give a more inclusive overview of assembly pipeline performance than any individual research group can, by offering users the possibility to submit their results to a collective benchmarking effort. poreTally is available on Github.

bioinformatics↗

bioRxiv2018

Family-based haplotype estimation and allele dosage correction for polyploids using short sequence reads

DNA sequence reads contain information about the genomic variants located on a single chromosome. By extracting and extending this information (using the overlaps of the reads), the haplotypes of an individual can be obtained. Adding parent-offspring relationships to the read information in a population can considerably improve the quality of the haplotypes obtained from short reads, as pedigree information can compensate for spurious overlaps (due to sequencing errors) and insufficient overlaps (due to shallow coverage). This improvement is especially beneficial for polyploid organisms, which have more than two copies of each chromosome and are therefore more difficult to be haplotyped compared to diploids. We develop a novel method, PopPoly, to estimate polyploid haplotypes in an F1-population from short sequence data by considering the transmission of the haplotypes from the parents to the offspring. In addition, PopPoly employs this information to improve genotype dosage estimation and to call missing genotypes in the population. Through realistic simulations, we compare PopPoly to other haplotyping methods and show its better performance in terms of phasing accuracy and the accuracy of phased genotypes. We apply PopPoly to estimate the parental and offspring haplotypes for a tetraploid potato cross with 10 offspring, using Illumina HiSeq sequence data of 9 genomic regions involved in plant maturity and tuberisation.

bioinformatics↗

bioRxiv2018

Improving intermolecular contact prediction through protein-protein interaction prediction using coevolutionary analysis with expectation-maximization

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. 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 noninteraction and simultaneously improves the prediction of intermolecular contact residues compared to a naive application of correlated mutation analysis. Furthermore, the method relaxes the assumption of one-to-one interaction of previous approaches, allowing for the study of many-to-many interactions. Source code and test data are available at www.bif.wur.nl/

bioinformatics↗

bioRxiv2017

Correcting palindromes in long reads after whole-genome amplification

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 reads from technologies such as PacBio and Oxford Nanopore. Here, we present Pacasus, a tool for correcting such errors in long reads. We demonstrate on two real-world datasets that it markedly improves subsequent read mapping and de novo assembly, yielding results similar to these that would be obtained with non-amplified DNA. With Pacasus long-read technologies become readily available for sequencing targets with very small amounts of DNA, such as single cells or even single chromosomes.

genomics↗

bioRxiv2017

Genome-wide characterization of Phytophthora infestansmetabolism: a systems biology approach

Genome-scale metabolic models (GEMs) provide a functional view of the complex network of biochemical reactions in the living cell. Initially mainly applied to reconstruct the metabolism of model organisms, the availability of increasingly sophisticated reconstruction methods and more extensive biochemical databases now make it possible to reconstruct GEMs for less characterized organisms as well, and have the potential to unravel the metabolism in pathogen-host systems. Here we present a GEM for the oomycete plant pathogen Phytophthora infestans as a first step towards an integrative model with its host. We predict the biochemical reactions in different cellular compartments and investigate the gene-protein-reaction associations in this model to get an impression of the biochemical capabilities of P. infestans. Furthermore, we generate life stage-specific models to place the transcriptomic changes of genes encoding metabolic enzymes into a functional context. In sporangia and zoospores there is an overall downregulation, most strikingly reflected in the fatty acid biosynthesis pathway. To investigate the robustness of the GEM, we simulate gene deletions to predict which enzymes are essential for in vitro growth. While there is room for improvement, this first model is an essential step towards an understanding of P. infestans and its interactions with plants as a system, which will help to formulate new hypotheses on infection mechanisms and disease prevention.

systems biology↗

bioRxiv2017

TriPoly: a haplotype estimation approach for polyploids using sequencing data of related individuals

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 (QTL).\n\nWe 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 short- read sequencing data for potato (Solanum tuberosum) and banana (Musa acuminata) trios, we show that TriPoly yields more accurate progeny haplotypes at low coverages compared to the existing methods that work on single individuals.

bioinformatics↗

bioRxiv2017

A Sequencer Coming Of Age: De Novo Genome Assembly Using MinION Reads

Nanopore technology provides a novel approach to DNA sequencing that yields long, label-free reads of constant quality. The first commercial implementation of this approach, the MinION, has shown promise in various sequencing applications. The presented literature review gives an up-to-date overview of the MinIONs utility as a de novo sequencing device. It is argued that the MinION may allow for portable and affordable de novo sequencing of even complex genomes in the near future, despite the currently error-prone nature of its reads. Through continuous updates to the MinION hardware and the development of new assembly pipelines, both sequencing accuracy and assembly quality have already risen rapidly. However, this fast pace of development has also lead to a lack of oversight in the expanding landscape of analysis tools, as performance evaluations are outdated quickly. Now that the MinION is approaching a state of maturity, a thorough comparative benchmarking effort of de novo assembly pipelines may be at place.

genetics↗

bioRxiv2016

Exploiting Next Generation Sequencing to solve the Haplotyping puzzle in Polyploids: a Simulation study

Haplotypes are the units of inheritance in an organism, and many genetic analyses depend on their precise determination. Methods for haplotyping single individuals use the phasing information available in Next Generation sequencing reads, by matching overlapping sNPs while penalizing post hoc nucleotide corrections made. Haplotyping diploids is relatively easy, but the complexity of the problem increases drastically for polyploid genomes, which are found in both model organisms and in economically relevant plant and animal species. While a number of tools are available for haplotyping polyploids, the effects of the genomic makeup and the sequencing strategy followed on the accuracy of these methods have hitherto not been thoroughly evaluated.\n\nWe developed the simulation pipeline haplosim to evaluate the performance of haplotype estimation algorithms for polyploids: HapCompass, HapTree and SDhaP, in settings varying in sequencing approach, ploidy levels and genomic diversity, using tetraploid potato as the model. Our results show that sequencing depth is the major determinant of haplotype estimation quality, that 1kb PacBio CCS reads and Illumina reads with large insert-sizes are competitive, and that all methods fail to produce good haplotypes when ploidy levels increase. Comparing the three methods, HapTree produces the most accurate estimates, but also consumes the most resources. There is clearly room for improvement in polyploid haplotyping algorithms.

bioinformatics↗