Biology subjects

Van Hautegem, T.

Publications and source records attributed to Van Hautegem, T..

5 recordsLinked to original sources

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↗

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↗

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↗

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↗