Biology subjects

Nijveen, H.

Publications and source records attributed to Nijveen, H..

15 recordsLinked to original sources

bioRxiv2025

Translational landscape during Seed Germination at Sub-Codon resolution

Seed germination is crucial for agricultural reproduction. A deep understanding of this process can secure healthy growth at the early phases of plant development and therefore the yield. Recent research indicates that germination is a complex process involving translational regulation. A large group of seed stored mRNAs together with newly synthesized transcripts are regulated by post-transcriptional mechanisms and selectively translated at different stages to support the germination process. To investigate the mechanism of translational control, we performed ribosome profiling on mRNAs of distinct physiological stages during Arabidopsis thaliana seed germination. The 3-nucleotide periodicity of the ribosome association on mRNAs identified indicates their translational potential. Dry seeds, in which translation is on hold are characterized by a unique ribosome association landscape with high association at the 5 and 3 UTR, compared to physiological stages that show active translation. Start codon specific stalling of ribosomes in dry seeds is associated with an adenine enriched sequence motif. Throughout germination codons encoding glycine, aspartate, tyrosine and proline are the most frequent ribosome pausing sites. Moreover, the non-coding RNAs which we identified as associated to ribosomes are indeed translated as was revealed by investigating total seed proteome data. Seed specific upstream Open Reading Frames (uORFs) are identified which may be associated to translational control of adaptative response during early seed germination. Altogether, we present a first ribosome profiling analysis across seed germination that illuminates various regulatory mechanisms that potentially contribute to the seeds survival strategy.

plant biology↗

bioRxiv2025

Transcriptome Profiling of Resistance Genes Analogs in Soybean's Cross-Tolerance to Water Limitation and Rust Stress

Asian soybean rust (ASR), caused by Phakopsora pachyrhizi, is the most destructive foliar disease of soybean, with yield losses up to 90%. With climate change intensifying drought and expanding disease incidence, it is critical to understand how combined abiotic and biotic stresses influence plant defense. We investigated the transcriptomic response of a susceptible soybean cultivar to ASR infection under normal and water-limited conditions at four infection stages (12, 24, 72, and 192 hours after-inoculation). We observed a biphasic expression of defense-related genes, particularly resistance gene analogs (RGAs), with an early peak at 12 hours and a late resurgence at 192 hours. Combined stress induced a greater number of differentially expressed genes (DEGs) than rust alone, especially at early infection. Among the differentially expressed RGAs (RGADEs), over 64% belonged to the TM-LRR class, and NBS-LRR genes were the most enriched at known ASR resistance loci, particularly Rpp2. Water limitation strongly modulated gene expression at late stages, revealing stress-specific transcriptional reprogramming. These findings reveal cross-tolerance mechanisms in soybean, highlight the temporal dynamics of RGADEs under dual stress, and provide targets for developing cultivars with improved resilience to both rust and water scarcity.

plant biology↗

bioRxiv2024

SeedMatExplorer: The transcriptome atlas of Arabidopsis seed maturation

BackgroundSeed maturation is a critical developmental phase during which seeds acquire traits essential for nutritional value, desiccation tolerance, and long-term survival. Abscisic acid (ABA) signalling is a key regulator of this process, coordinating gene expression programs underlying the acquisition of seed quality traits. However, the molecular regulation of many of these traits remains poorly understood. To address this, we performed a comprehensive analysis of seed maturation in Arabidopsis thaliana, combining physiological and transcriptomic approaches across wild-type plants and mutants affected in ABA biosynthesis, signalling, and catabolism. ResultsWe generated a high-resolution transcriptome dataset covering seed development from 12 days after pollination to the dry seed stage in wild-type and ten mutant lines. In parallel, we characterized the temporal acquisition of multiple seed traits, including germination capacity, dormancy, chlorophyll fluorescence, longevity and desiccation tolerance. Integration of these datasets using weighted gene co-expression network analysis (WGCNA) identified gene modules associated with specific trait acquisition patterns. This approach enabled the identification of coordinated transcriptional programs linked to distinct seed quality traits, extending beyond individual gene-level analyses. Notably, modules associated with desiccation tolerance and longevity were enriched for genes involved in stress responses and ABA-regulated pathways, highlighting the complex and multifactorial regulation of these traits. ConclusionsThis study provides a comprehensive physiological and transcriptomic framework for understanding seed maturation and the acquisition of key seed quality traits in Arabidopsis thaliana. By linking gene expression dynamics to trait development, our work offers new insights into the regulatory networks underlying seed resilience and storage capacity. The dataset is made accessible through SeedMatExplorer (https://www.bioinformatics.nl/SeedMatExplorer), an open-access web platform that enables interactive exploration and supports hypothesis generation. Together, this resource represents a valuable tool for advancing research on seed biology and improving seed performance in agricultural contexts.

plant biology↗

bioRxiv2024

Creating a biomedical knowledge base by addressing GPT inaccurate responses and benchmarking context

We created GNQA, a generative pre-trained transformer (GPT) knowledge base driven by a performant retrieval augmented generation (RAG) with a focus on aging, dementia, Alzheimers and diabetes. We uploaded a corpus of three thousand peer reviewed publications on these topics into the RAG. To address concerns about inaccurate responses and GPT hallucinations, we implemented a context provenance tracking mechanism that enables researchers to validate responses against the original material and to get references to the original papers. To assess the effectiveness of contextual information we collected evaluations and feedback from both domain expert users and citizen scientists on the relevance of GPT responses. A key innovation of our study is automated evaluation by way of a RAG assessment system (RAGAS). RAGAS combines human expert assessment with AI-driven evaluation to measure the effectiveness of RAG systems. When evaluating the responses to their questions, human respondents give a "thumbs-up" 76% of the time. Meanwhile, RAGAS scores 90% on answer relevance on questions posed by experts. And when GPT-generates questions, RAGAS scores 74% on answer relevance. With RAGAS we created a benchmark that can be used to continuously assess the performance of our knowledge base. Full GNQA functionality is embedded in the free GeneNetwork.org web service, an open-source system containing over 25 years of experimental data on model organisms and human. The code developed for this study is published under a free and open-source software license at https://git.genenetwork.org/gn-ai/tree/README.md.

scientific communication and education↗

bioRxiv2023

Comparative transcriptomics of Hirschfeldia incana and relatives highlights differences in photosynthetic pathways

Photosynthesis is the only yield-related trait that has not yet been substantially improved by plant breeding. The limited results of previous attempts to increase yield via improvement of photosynthetic pathways suggest that more knowledge is still needed to achieve this goal. To learn more about the genetic and physiological basis of high photosynthetic light-use efficiency (LUE) at high irradiance, we study Hirschfeldia incana. Here, we compare the transcriptomic response to high light of H. incana with that of three other members of the Brassicaceae, Arabidopsis thaliana, Brassica rapa, and Brassica nigra, which have a lower photosynthetic LUE. First, we built a high-light, high-uniformity growing environment in a climate-controlled room. Plants grown in this system developed normally and showed no signs of stress during the whole growth period. Then we compared gene expression in low and high-light conditions across the four species, utilizing a panproteome to group homologous proteins efficiently. As expected, all species actively regulate genes related to the photosynthetic process. An in-depth analysis on the expression of genes involved in three key photosynthetic pathways revealed a general trend of lower gene expression in high-light conditions. However, H. incana distinguishes itself from the other species through higher expression of certain genes in these pathways, either through constitutive higher expression, as for LHCB8, ordinary differential expression, as for PSBE, or cumulative higher expression obtained by simultaneous expression of multiple gene copies, as seen for LHCA6. These differentially expressed genes in photosynthetic path-ways are interesting leads to further investigate the exact relationship between gene expression, protein abundance and turnover, and ultimately the LUE phenotype. In addition, we can also exclude thousands of genes from "explaining" the phenotype, because they do not show differential expression between both light conditions. Finally, we deliver a transcriptomic resource of plant species fully grown under, rather than briefly exposed to, a very high irradiance, supporting efforts to develop highly efficient photosynthesis in crop plants.

bioinformatics↗

bioRxiv2023

The effect of developmental variation on expression QTLs in a multi parental C. elegans population

Regulation of gene expression plays a crucial role in the development and adaptation of organisms to changing environments. A population-based procedure used to investigate the genetic regulation of gene expression is eQTL mapping. Typically, the age of the population used for eQTL mapping at the time of sampling is strictly controlled. This is necessary because the developmental process causes changes in gene expression, complicating the interpretation of eQTL mapping experiments. However, organisms can differ in their "developmental age", even if they are of the same chronological age. As a result, eQTL patterns are affected by uncontrolled developmental variation in gene expression. The model organism C. elegans is particularly suited for studying the effect of developmental variation on eQTL mapping patterns. In a span of days C. elegans transitions from embryo through four larval stages to adult while undergoing massive changes to its transcriptome. Here we use C. elegans to investigate the effect of developmental age variation on eQTL patterns and an available normalization procedure. We used dynamical eQTL mapping, which includes developmental age as a cofactor, to separate the variation in development from genotypic variation and explain variation in gene expression levels. We compare classical single marker eQTL mapping and dynamical eQTL mapping using RNA-seq data of [~]200 multi-parental recombinant inbred lines of C. elegans. The results show that many eQTLs are actually caused by developmental variation, that most trans-bands are associated with developmental age and that dynamical eQTL mapping detects additional eQTLs not found with classical eQTL mapping.

genetics↗

bioRxiv2023

Modulation of quantitative trait loci for Arabidopsis thaliana seed performance by the maternal and germination environment.

The quality of seeds contributes to plant performance, especially during germination and in the young seedling stage, and hence affects the economic value of seed crops. A seeds innate quality is determined during seed development and the following seed maturation phase. It is tightly controlled by the genetic make-up of the mother plant and further shaped by the environmental conditions of the mother plant. The interaction between genotype and environment can result in substantial quantitative variation in seed traits like dormancy and viability. Making use of naturally occurring variation within the Arabidopsis thaliana germplasm, we studied the interaction between seed production environments and the genetic architecture of mother plants on diverse seed quality traits. An Arabidopsis Bayreuth-0 x Shahdara recombinant inbred line (RIL) population was grown in four different seed production environments: high temperature, high light, low phosphate, and control conditions. The seeds harvested from the mother plants that were exposed to these environments from flowering until seed harvest were subsequently subjected to germination assays under standard and mild stress conditions (cold, heat, osmotic stress and added phytohormone ABA). Quantitative trait locus (QTL) analysis identified many environmental-sensitive QTLs (QTL x E) as well as several interactions between the maternal and germination environments. Variation in the number and position of the QTLs was largely determined by the germination conditions, however effects of the maternal environment were clearly present regarding the genomic location as well as significance of the individual QTLs. Together, our findings uncover the extensive environmental modulation of the genetic influence on seed performance and how this is shaped by the genetic make-up of the mother plant. Our data provides a systems-view of the complex genetic basis of genotype-by-environment interactions determining seed quality.

plant biology↗

bioRxiv2022

Prioritizing Candidate eQTL Causal Genes in Arabidopsis using Random Forests

Expression quantitative trait locus (eQTL) mapping has been widely used to study the genetic regulation of gene expression in Arabidopsis thaliana. As a result, a large amount of eQTL data has been generated for this model plant; however, only a few causal eQTL genes have been identified, and experimental validation is costly and laborious. A prioritization method could help speed up the identification of causal eQTL genes. This study extends the machine-learning-based QTG-Finder2 method for prioritizing candidate causal genes in phenotype QTLs to be used for eQTLs by adding gene structure, protein interaction, and gene expression. Independent validation shows that the new algorithm can prioritize sixteen out of twenty-five potential eQTL causal genes within the 20% rank percentile. Several new features are important in prioritizing causal eQTL genes, including the number of protein-protein interactions, unique domains, and introns. Overall, this study provides a foundation for developing computational methods to prioritize candidate eQTL causal genes. The prediction of all genes is available in the AraQTL workbench (https://www.bioinformatics.nl/AraQTL/) to support the identification of gene expression regulators in Arabidopsis.

plant biology↗

bioRxiv2021

Plasticity of maternal environment dependent expression-QTLs of tomato seeds

Seeds are essential for plant reproduction, survival, and dispersal. Germination ability and successful establishment of young seedlings strongly depends on seed quality and on environmental factors such as nutrient availability. In tomato (Solanum lycopersicum) and many other species, seed quality and seedling establishment characteristics are determined by genetic variation, as well as the maternal environment in which the seeds develop and mature. The genetic contribution to variation in seed and seedling quality traits and environmental responsiveness can be estimated at transcriptome level in the dry seed by mapping genomic loci that affect gene expression (expression QTLs) in contrasting maternal environments. In this study, we applied RNA-sequencing to measure gene expression of seeds of a tomato RIL population derived from a cross between S. lycopersicum (cv. Moneymaker) and S. pimpinellifolium (G1.1554). The seeds matured on plants cultivated under different nutritional environments; i.e. on high phosphorus or low nitrogen. The obtained SNPs were subsequently used to construct a high-density genetic map. We show how the genetic landscape of plasticity in gene regulation in dry seeds is affected by the maternal nutrient environment. The combined information on natural genetic variation mediating (variation in) responsiveness to the environment may contribute to knowledge-based breeding programs aiming to develop crop cultivars that are resilient to stressful environments.

plant biology↗

bioRxiv2021

The genetics of gene expression in a C. elegans multi parental recombinant inbred line population.

Studying genetic variation of gene expression provides a powerful way to unravel the molecular components underlying complex traits. Expression QTL studies have been performed in several different model species, yet most of these linkage studies have been based on genetic segregation of two parental alleles. Recently we developed a multi-parental segregating population of 200 recombinant inbred lines (mpRILs) derived from four wild isolates (JU1511, JU1926, JU1931 and JU1941) in the nematode Caenorhabditis elegans. We used RNA-seq to investigate how multiple alleles affect gene expression in these mpRILs. We found 1,789 genes differentially expressed between the parental lines. Transgression, expression beyond any of the parental lines in the mpRILs, was found for 7,896 genes. For expression QTL mapping almost 9,000 SNPs were available. By combining these SNPs and the RNA-seq profiles of the mpRILs, we detected almost 6,800 eQTLs. Most trans-eQTLs (63%) co-locate in six newly identified trans-bands. The trans-eQTLs found in previous 2-parental allele eQTL experiments and this study showed some overlap (17.5%- 46.8%), highlighting on the one hand that a large group of genes is affected by polymorphic regulators across populations and conditions, on the other hand it shows that the mpRIL population allows identification of novel gene expression regulatory loci. Taken together, the analysis of our mpRIL population provides a more refined insight into C. elegans complex trait genetics and eQTLs in general, as well as a starting point to further test and develop advanced statistical models for detection of multi-allelic eQTLs and systems genetics studying the genotype-phenotype relationship.

genetics↗

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↗

bioRxiv2019

Extracting the GEMs: Genotype, Environment and Microbiome interactions shaping host phenotypes

One of the fundamental tenets of biology is that the phenotype of an organism (Y) is determined by its genotype (G), the environment (E) and their interaction (GE). Quantitative phenotypes can then be modeled as Y=G+E+GE+e, where e is the biological variance. This simple and tractable model has long served as the basis for studies investigating the heritability of traits and decomposing the variability in fitness. Increasingly, the importance of microbe interactions on organismal phenotypes is being recognized, but it is currently unclear what the relative contribution of microbiomes to a given host phenotype is and how this translates into the traditional GE model. Here we address this fundamental question and propose an expansion of the original model, referred to as GEM, which explicitly incorporates the contribution of the microbiome (M) to the host phenotype, while maintaining the simplicity and tractability of the original GE model. We show that by keeping host, environment and microbiome as separate but interacting variables, the GEM model can capture the nuanced ecological interactions between these variables. Finally, we demonstrate with an in vitro experiment how the GEM model can be used to statistically disentangle the relative contributions of each component on specific host phenotypes.

microbiology↗

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

A blueprint of seed desiccation sensitivity in the genome of Castanospermum australe

O_LIMost angiosperms produce seeds that are desiccated on dispersal with the ability to retain viability in storage facilities for prolonged periods. However, some species produce desiccation sensitive seeds which rapidly lose viability in storage, precluding ex situ conservation. Current consensus is that desiccation sensitive seeds either lack or do not express mechanisms necessary for the acquisition of desiccation tolerance.\nC_LIO_LIWe sequenced the genome of Castanospermum australe, a legume species producing desiccation sensitive seeds, and characterized its seed developmental physiology and - transcriptomes.\nC_LIO_LIC. australe has a low rate of evolution, likely due to its perennial life-cycle and long generation times. The genome is syntenic with itself, with several orthologs of genes from desiccation tolerant legume seeds, from gamma whole-genome duplication events being retained. Changes in gene expression during development of C. australe seeds, as compared to desiccation tolerant Medicago truncatula seeds, suggest they remain metabolically active, prepared for immediate germination.\nC_LIO_LIOur data indicates that the phenotype of C. australe seeds arose through few changes in specific signalling pathways, precluding or bypassing activation of mechanisms necessary for acquisition of desiccation tolerance. Such changes have been perpetuated as the habitat in which dispersal occurs is favourable for prompt germination.\nC_LI

plant biology↗

bioRxiv2018

A multi-parent recombinant inbred line population of Caenorhabditis elegans enhances mapping resolution and identification of novel QTLs for complex life-history traits

Local populations of the bacterivorous nematode Caenorhabditis elegans can be genetically almost as diverse as global populations. To investigate the effect of local genetic variation on heritable traits, we developed a new recombinant inbred line (RIL) population derived from four wild isolates. The wild isolates were collected from two closely located sites in France: Orsay and Santeuil. By crossing these four genetically diverse parental isolates a population of 200 RILs was constructed. RNA-seq was used to obtain sequence polymorphisms identifying almost 9000 SNPs variable between the four genotypes with an average spacing of 11 kb, possibly doubling the mapping resolution relative to currently available RIL panels. The SNPs were used to construct a genetic map to facilitate QTL analysis. Life history traits, such as lifespan, stress resistance, developmental speed and population growth were measured in different environments. For most traits substantial variation was found, and multiple QTLs could be detected, including novel QTLs not found in previous QTL analysis, for example for lifespan or pathogen responses. This shows that recombining genetic variation across C. elegans populations that are in geographical close proximity provides ample variation for QTL mapping. Taken together, we show that RNA-seq can be used for genotyping, that using more parents than the classical two parental genotypes to construct a RIL population facilitates the detection of QTLs and that the use of wild isolates permits analysis of local adaptation and life history trade-offs.

genetics↗