Biology subjects

Storme, V.

Publications and source records attributed to Storme, V..

3 recordsLinked to original sources

bioRxiv2024

High-throughput phenotyping reveals multiple drought responses of wild and cultivated Phaseolinae beans

Crop production worldwide is increasingly affected by drought stress. Although drought tolerance of a plant may be achieved through morphological, structural, physiological, cellular, and molecular adaptations, most studies remain limited to quantifying the effect of drought on biomass yield. Using a high-throughput phenotypic imaging system, we evaluated the drought tolerance of 151 bean accessions (Phaseolinae; Fabaceae) by quantifying five different traits simultaneously: biomass, water use efficiency, relative water content, chlorophyll content, and root/shoot ratio. Since crop wild relatives are important resources for breeding programmes, both wild and cultivated accessions were analyzed, the majority never evaluated for drought tolerance before. We demonstrate that the five traits are affected very differently by drought in the studied accessions, although a cluster analysis grouped the accessions into five distinct clusters with similar responses. We correlated the results for each accession to local climate variables at their original collection sites. Except for the root/shoot ratio, the results of all indicators were related to precipitation data, confirming that drought tolerant accessions grow in arid environments. This broader knowledge on the complex responses of plants to drought stress may prove an invaluable resource for future crop production. HighlightThis study presents an innovative approach for the fast evaluation of different drought tolerance traits of legumes. Multiple responses to drought were observed in the economically important Phaseolinae beans.

plant biology↗

bioRxiv2020

Unraveling transcription factor functions through integrative inference of transcriptional networks in Arabidopsis thaliana yields novel regulators involved in reactive oxygen species stress signaling

Gene regulation is a dynamic process in which transcription factors (TFs) play an important role to control spatiotemporal gene expression. While gene regulatory networks describe the interactions between TFs and their target genes, our global knowledge about the complexity of TF control for different genes and biological processes is incomplete. To enhance our global understanding of regulatory interactions in Arabidopsis thaliana, different regulatory input networks capturing complementary information about DNA motifs, open chromatin, TF binding and expression-based regulatory interactions, were combined using a supervised learning approach, resulting in an integrated gene regulatory network (iGRN) covering 1,491 TFs and 31,393 target genes (1.7 million interactions). This iGRN outperforms the different input networks to predict known regulatory interactions and has a similar performance to recover functional interactions compared to state-of-the-art experimental methods like yeast one-hybrid and ChIP-seq. The iGRN correctly inferred known functions for 681 TFs and predicted new gene functions for hundreds of unknown TFs. For regulators predicted to be involved in reactive oxygen species stress regulation, we confirmed in total 75% of TFs with a function in ROS and/or physiological stress responses. This includes 13 novel ROS regulators, previously not connected to any ROS or stress function, that were experimentally validated in our ROS-specific phenotypic assays of loss- or gain-of-function lines. In conclusion, the presented iGRN offers a high-quality starting point to enhance our understanding of gene regulation in plants by integrating different experimental data types at the network level.

plant biology↗

bioRxiv2018

High-throughput yeast two-hybrid library screening using next generation sequencing

Yeast two-hybrid (Y2H) is a well-established genetics-based system that uses yeast to selectively display binary protein-protein interactions (PPIs). To meet the current need to unravel complex PPI networks, several adaptations have been made to establish medium- to high-throughput Y2H screening platforms, with several having successfully incorporated the use of the next-generation sequencing (NGS) technology to increase the scale and sensitivity of the method. However, these have been to date mainly restricted to the use of fully annotated custom-made open reading frame (ORF) libraries and subject to complex downstream data processing. Here, a streamlined high-throughput Y2H library screening strategy, based on integration of Y2H with NGS, called Y2H-seq, was developed, which allows efficient and reliable screening of Y2H cDNA libraries. To generate proof of concept, the method was applied to screen for interaction partners of two key components of the jasmonate signaling machinery in the model plant Arabidopsis thaliana, resulting in the identification of several previously reported as well as hitherto unknown interactors. Our Y2H-seq method offers a user-friendly, specific and sensitive screening method that allows high-throughput identification of PPIs without prior knowledge of the organisms ORFs, thereby extending the method to organisms of which the genome has not entirely been annotated yet. The quantitative NGS readout and the incorporation of background controls allow to increase genome coverage and ultimately dispose of recurrent false positives, thereby overcoming some of the bottlenecks of current Y2H technologies, which will further strengthen the value of the Y2H technology as a discovery platform.

molecular biology↗