Biology subjects

Doonan, J. H.

Publications and source records attributed to Doonan, J. H..

4 recordsLinked to original sources

bioRxiv2024

GIBBERELLIN SIGNALING THROUGH RGA SUPPRESSES GCN5 EFFECT ON STAMEN ELONGATION OF ARABIDOPSIS FLOWERS

Histone acetyltransferases (HAT) modify the amino-terminal tails of the core histone proteins via acetylation, regulating chromatin structure and transcription. The GENERAL CONTROL NON-DEREPRESSIBLE 5 (GCN5) is a HAT that specifically acetylates H3K14 residues. GCN5 has been associated with cell division and differentiation, meristem function, root, stem, foliar and floral development, and plant environmental response. The flowers of gcn5-6 plants display reduced length of stamen and exhibit male sterility relative to the wild-type plants. We show these effects may arise from gibberellin (GA) signaling defects. The signaling pathway of bioactive GAs depends on the proteolysis of their repressors, DELLA proteins. The DELLA protein, REPRESSOR OF GA (RGA), represses plant growth, inflorescence, flower and seed development. Our molecular data indicate that GCN5 is required for activation and H3K14 acetylation of genes involved in the late stages of GA biosynthesis and catabolism. We studied the genetic interaction of RGA and GCN5; RGA can partially suppress GCN5 action. The reduced elongation of the stamen filament of gcn5-6 mutants is reversed in the rga-t2;gcn5-6 double mutants. This mechanism involved suppressing the GCN5 effect on the expression and histone acetylation in GAI-locus by RGA. Interestingly, RGA and RGL2 do not suppress ADA2b function, suggesting that ADA2b acts downstream in GA signaling and is distinct from GCN5 activity. In conclusion, we propose that the action of GCN5 on stamen elongation is mediated partially by RGA and GA signaling.

plant biology↗

bioRxiv2023

Integrated Phenomics and Genomics reveals genetic loci associated with inflorescence growth in Brassica napus

A fundamental challenge to the production of climate-resilient crops is how to measure dynamic yield-relevant responses to the environment, such as growth rate, at a scale which informs mechanistic understanding and accelerates breeding. The timing, duration and architectural characteristics of inflorescence growth are crucial for optimising crop productivity and have been targets of selection during domestication. We report a robust and versatile procedure for computationally assessing environmentally-responsive flowering dynamics. In the oilseed crop, Brassica napus, there is wide variation in flowering response to winter cold (vernalization). We subjected a diverse set of B. napus accessions to different vernalization temperatures and monitored shoot responses using automated image acquisition. We developed methods to computationally infer multiple aspects of flowering from this dynamic data, enabling characterisation of speed, duration and peaks of inflorescence development across different crop types. We input these multiple traits to genome- and transcriptome-wide association studies, and identified potentially causative variation in a priori phenology genes (including EARLY FLOWERING3) for known traits and in uncharacterised genes for computed traits. These results could be used in marker assisted breeding to design new ideotypes for improved yield and better adaptation to changing climatic conditions.

plant biology↗

bioRxiv2020

Increased and ectopic expression of Triticum polonicum VRT-A2 underlies elongated glumes and grains in hexaploid wheat in a dosage-dependent manner

Flower development is a major determinant of yield in crops. In wheat, natural variation for the size of spikelet and floral organs is particularly evident in Triticum polonicum, a tetraploid subspecies of wheat with long glumes, lemmas, and grains. Using map-based cloning, we identified VRT2, a MADS-box transcription factor belonging to the SVP family, as the gene underlying the T. polonicum long-glume (P1) locus. The causal P1 mutation is a sequence re-arrangement in intron-1 that results in both increased and ectopic expression of the T. polonicum VRT-A2 allele. Based on allelic variation studies, we propose that the intron-1 mutation in VRT-A2 is the unique T. polonicum species defining polymorphism, which was later introduced into hexaploid wheat via natural hybridizations. Near-isogenic lines differing for the P1 locus revealed a gradient effect of P1 across florets. Transgenic lines of hexaploid wheat carrying the T. polonicum VRT-A2 allele show that expression levels of VRT-A2 are highly correlated with spike, glume, grain, and floral organ length. These results highlight how changes in expression profiles, through variation in cis-regulation, can impact on agronomic traits in a dosage-dependent manner in polyploid crops. One-sentence summaryAn intron-1 rearrangement in the MADS-box transcription factor VRT-A2 leads to its misexpression and defines the long-glume phenotype of Polish wheat (T. polonicum).

plant biology↗

bioRxiv2020

KnetMiner - Intelligent search and visualisation of connected data to explain complex traits and diseases

Generating new ideas and scientific hypotheses is often the result of extensive literature and database reviews, overlaid with scientists own novel data and a creative process of making connections that were not made before. We have developed a comprehensive approach to guide this technically challenging data integration task and to make knowledge discovery and hypotheses generation easier for plant and crop researchers. KnetMiner can digest large volumes of scientific literature and biological research to find and visualise links between the genetic and biological properties of complex traits and diseases. Here we report the main design principles behind KnetMiner and provide use cases for mining public datasets to identify unknown links between traits such grain colour and pre-harvest sprouting in Triticum aestivum, as well as, an evidence-based approach to identify candidate genes under an Arabidopsis thaliana petal size QTL. We have developed KnetMiner knowledge graphs and applications for a range of species including plants, crops and pathogens. KnetMiner is the first open-source gene discovery platform that can leverage genome-scale knowledge graphs, generate evidence-based biological networks and be deployed for any species with a sequenced genome. KnetMiner is available at http://knetminer.org.

bioinformatics↗