Biology subjects

Nelissen, H.

Publications and source records attributed to Nelissen, H..

13 recordsLinked to original sources

bioRxiv2025

High-resolution transcriptional atlas of growing maize shoot organs throughout plant development under well-watered and drought conditions

Crop improvement goals for maize (Zea mays L.) involve the targeted optimization of various organs, making it crucial to understand the developmental characteristics and gene expression patterns during organ development and in response to environmental stresses such as drought. In this study, we investigated the development of maize leaves and internodes at both macroscopic and cellular level, and identified a shared fundamental growth design with distinct timing between the two organs. By transcriptome profiling developmental zones of leaves and internodes of different ranks, and of the ear, at different growth stages under both well-watered and drought conditions, we generated a high-resolution spatiotemporal transcriptome dataset on 272 different tissues and conditions, which we make available as a searchable database. While the gene regulatory networks governing cell division and cell elongation were highly conserved across organs, precise expression regulation of particular gene families was observed across organs and within the same organ. Additionally, we highlight the expression of key genes involved in regulating leaf angle and vascular development, showing spatiotemporal regulation of differentiation parallel to growth. This comprehensive expression atlas, combined with phenotypic data, offers a deeper understanding of the similarities and differences among shoot organs and tissues during development and drought response, and provides a valuable resource for engineering organ-specific traits in maize.

plant biology↗

bioRxiv2024

Tabula Glycine: The whole-soybean single-cell resolution transcriptome atlas

Soybean (Glycine max) is an essential source of protein and oil with high nutritional value for human and animal consumption. To enhance our understanding of soybean biology, it is essential to have accurate information regarding the expression of each of its 55,897 protein-coding genes. Here, we present "Tabula Glycine", the soybean single-cell resolution transcriptome atlas. This atlas is composed of single-nucleus RNA-sequencing data of nearly 120,000 nuclei isolated from 10 different Glycine max organs and morphological structures comprising the entire soybean plant. These nuclei are grouped into 157 different clusters based on their transcriptomic profiles. Among genes, the pattern of activity of transcription factor genes is sufficient to define most cell types and their organ/morphological structure of origin, suggesting that transcription factors are key determinants of cell identity and function. This unprecedented level of resolution makes the Tabula Glycine a unique resource for the plant and soybean communities.

plant biology↗

bioRxiv2024

SPArrOW: a flexible, interactive and scalable pipeline for spatial transcriptomics analysis

Current spatial transcriptomics technologies are increasingly able to measure large gene panels at subcellular resolution, but a major bottleneck in this rapidly advancing field is the computational analysis and interpretation of the data. To bridge this gap, here we present SPArrOW, a flexible, modular and scalable pipeline for processing spatial transcriptomics data. SPArrOW improves cell segmentation and leads to better overall data quality, resulting in more accurate cell annotations at the single-cell level. Furthermore, it provides the users with numerous visual quality checks that are crucial for the correct interpretation of the data, offering users more control in processing their data. Our workflow is designed to accommodate the various available spatial transcriptomics platforms. Finally, SPArrOW offers interactive visualization and data exploration, enabling sample-specific pipeline optimization by various tuneable parameters and an efficient comparison of different staining and gene allocation strategies.

bioinformatics↗

bioRxiv2024

Transit amplifying cells balance growth and differentiation in above-ground meristems

In both animals and plants, stem cell niches balance between cell-renewal and the generation of progeny cells that differentiate into specialized tissues. The multipotent and highly proliferative transit amplifying cells (TACs) integrate signals from stem cells and their differentiating progeny cells. Here we used spatial transcriptomics mapped to individual cells to illustrate the localization of TACs in maize meristems based on transcriptional gradients. Through genetic interactions and fluctuations in the transcriptional gradients we show that the multiplicative cell divisions are independently controlled from the TAC cell divisions. The dynamic nature of transcriptional variation in response to cell state or environment, together with the potential to improve yield by their modulation highlights the importance of finetuned modulation of networks rather than constitutive perturbations for crop improvement.

plant biology↗

bioRxiv2023

Monitoring of drought stress and transpiration rate using proximal thermal and hyperspectral imaging in an indoor automated plant phenotyping platform

BackgroundThermography is a popular tool to assess plant water use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect drought stress. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated. ResultsThe sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic difference in the plants water use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple thermal infrared indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines. ConclusionOverall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

plant biology↗

bioRxiv2023

MINI-AC: Inference of plant gene regulatory networks using bulk or single-cell accessible chromatin profiles

Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. GRNs control transcriptional programs involved in growth, development and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFs binding sites. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.

bioinformatics↗

bioRxiv2022

Predicting yield traits of individual field-grown Brassica napus plants from rosette-stage leaf gene expression

BackgroundIn the plant sciences, results of laboratory studies often do not translate well to the field because lab growth conditions are very different from field conditions. To help close this lab-field gap, we developed a new strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants of the same genetic background grown in the same field. This single-plant omics strategy leverages uncontrolled micro-environmental variation across the field and stochastic variation among the individual plants as information sources, rather than controlled perturbations. Here, we use single-plant omics on winter-type Brassica napus (rapeseed) plants to investigate to what extent rosette-stage gene expression profiles can be linked to the early and late phenotypes of individual field-grown plants. ResultsWe find that rosette leaf gene expression in autumn has substantial predictive power for both autumnal leaf phenotypes and final yield in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. ConclusionsOur results show that profiling individual plants under uncontrolled field conditions is a valid strategy for identifying genes and processes influencing crop yield in the field.

systems biology↗

bioRxiv2022

BREEDIT: A novel multiplex genome editing strategy to improve complex quantitative traits in maize (Zea mays L.)

Ensuring food security for an ever-growing global population while adapting to climate change is the main challenge for agriculture in the 21st century. Though new technologies are being applied to tackle the problem, we are approaching a plateau in crop improvement using conventional breeding. Recent advances in gene engineering via the CRISPR/Cas technology pave the way to accelerate plant breeding and meet this increasing demand. Here, we present a gene discovery pipeline named BREEDIT that combines multiplex genome editing of whole gene families with crossing schemes to improve complex traits such as yield and drought resistance. We induced gene knockouts in 48 growth-related genes using CRISPR/Cas9 and generated a collection of over 1000 gene-edited maize plants. Edited populations displayed, on average, significant increases of 5 to 10% for leaf length and up to 20% for leaf width compared with controls. For each gene family, edits in subsets of genes could be associated with increased traits, allowing us to reduce the gene space needed to focus on for trait improvement. We propose BREEDIT as a gene discovery pipeline which can be rapidly applied to generate a diverse collection of mutants to identify subsets of promising candidates that could be later incorporated in breeding programs.

systems biology↗

bioRxiv2022

Modulation of the DA1 pathway in maize shows that translatability of information from Arabidopsis to crops is complex

Modern agriculture is struggling to meet the increasing food, silage and raw material demands due to the rapid growth of population and climate change. In Arabidopsis, DA1 and DAR1 are proteases that negatively regulate cell proliferation and control organ size. DA1 and DAR1 are activated by ubiquitination catalyzed by the E3 ligase BIG BROTHER (BB). Here, we characterized the DA1, DAR 1 and BB gene families in maize and analyzed whether perturbation of these genes regulates organ size similar to what was observed in Arabidopsis. We generated da1_dar1a_dar1b triple CRISPR maize mutants and bb1_bb2 double mutants. Detailed phenotypic analysis showed that the size of leaf, stem, cob, and seed was not consistently enlarged in these mutants. Also overexpression of a dominant-negative DA1R333K allele, resembling the da1-1 allele of Arabidopsis which has larger leaves and seeds, did not alter the maize phenotype. The mild negative effects on plant height of the DA1R333K_bb1_bb2 mutant indicate that the genes in the DA1 pathway may control organ size in maize, albeit less obvious than in Arabidopsis.

plant biology↗

bioRxiv2021

Identification of new leaf intrinsic yield genes using cross-species network analysis in plants

With the need to increase plant productivity, one of the challenges plant scientists are facing is to identify genes playing a role in beneficial plant traits. Moreover, even when such genes are found, it is generally not trivial to transfer this knowledge about gene function across species to identify functional orthologs. Here, we focused on the leaf to study plant growth. First, we built leaf growth transcriptional networks in Arabidopsis thaliana, maize (Zea mays), and aspen (Populus tremula). Next, known growth regulators, here defined as genes that when mutated or ectopically expressed alter plant growth, together with cross-species conserved networks, were used as guides to predict novel Arabidopsis growth regulators. Using an in-depth literature screening, 34 out of 100 top predicted growth regulators were confirmed to affect leaf phenotype when mutated or overexpressed and thus represent novel potential growth regulators. Globally, these new growth regulators were involved in cell cycle, plant defense responses, gibberellin, auxin, and brassinosteroid signaling. Phenotypic characterization of loss-of-function lines confirmed two newly predicted growth regulators to be involved in leaf growth (NPF6.4 and LATE MERISTEM IDENTITY2). In conclusion, the presented network approach offers an integrative cross-species strategy to identify new genes involved in plant growth and development. One-sentence summaryCross-species network analysis results in the identification and validation of new growth regulators in Arabidopsis.

plant biology↗

bioRxiv2021

SAMBA controls the rate of cell division in maize development through APC/C interaction

SAMBA has been identified as a plant-specific regulator of the anaphase-promoting complex (APC/C) which controls unidirectional cell cycle progression in Arabidopsis, but so far its role was not studied in monocots. Here, the association of SAMBA with APC/C was shown to be conserved in maize. Two samba CRISPR alleles showed growth defects that aggravated with plant age such as dwarfed plants due to shortened upper leaf length, erect leaf architecture, and reduced leaf size due to an altered cell division rate and cell expansion. Despite the fact that in both alleles the frameshift occurred at the same position, the two alleles differed in the severity and developmental onset of the phenotypes, because samba-1 represented a knock-out allele, while translation re-initiation in samba-3 resulted in a truncated protein that was still able to interact with the APC/C and regulate its function, albeit with altered APC/C activity or efficiency. Our data are consistent with a dosage-dependent role for SAMBA to control developmental processes for which a change in growth rate is pivotal.

plant biology↗

bioRxiv2020

Using single-plant -omics in the field to link maize genes to functions and phenotypes

Most of our current knowledge on plant molecular biology is based on experiments in controlled lab environments. Over the years, lab experiments have generated substantial insights in the molecular wiring of plant developmental processes, stress responses and phenotypes. However, translating these insights from the lab to the field is often not straightforward, in part because field growth conditions are very different from lab conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene-phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field, and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional lab-generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field-generated transcriptome and metabolome data can be used to quantitatively predict at least some individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab-field gap.

systems biology↗

bioRxiv2019

Cytokinin promotes jasmonic acid accumulation in the control of maize leaf growth.

Growth of plant organs results from the combined activity of cell division and cell expansion. The coordination of these two processes depends on the interplay between multiple hormones that determine final organ size. Using the semidominant Hairy Sheath Frayed1 (Hsf1) maize mutant, that hypersignals the perception of cytokinin (CK), we show that CK can reduce leaf size and growth rate by decreasing cell division. Linked to CK hypersignaling, the Hsf1 mutant has increased jasmonic acid (JA) content, a hormone that can inhibit cell division. Treatment of wild type seedlings with exogenous JA reduces maize leaf size and growth rate, while JA deficient maize mutants have increased leaf size and growth rate. Expression analysis revealed increased transcript accumulation of several JA pathway genes in the Hsf1 leaf growth zone. A transient treatment of growing wild type maize shoots with exogenous CK also induced JA pathway gene expression, although this effect was blocked by co-treatment with cycloheximide. Together our results suggest that CK can promote JA accumulation possibly through increased expression of specific JA pathway genes.\n\nOne sentence summaryCytokinin-signaling upregulates the jasmonate biosynthesis pathway, resulting in jasmonate accumulation and influences on maize leaf growth.

plant biology↗