Biology subjects

Ronald, P.

Publications and source records attributed to Ronald, P..

7 recordsLinked to original sources

bioRxiv2026

Expanding KitBase: Genome and Phenotype Integration of 3,268 Fast-Neutron Rice Mutants

Fast-neutron mutagenesis creates diverse genome-wide mutations, providing a powerful tool for crop functional genomics. Here, we present an expanded genomic and phenotypic analysis of 3,268 fast-neutron (FN)-induced mutant rice lines (Oryza sativa L. cv. Kitaake). All FN lines were whole-genome sequenced, and mutations were identified by alignment in the Nipponbare and KitaakeX reference genomes. We cataloged over 428,000 mutations affecting 78.49% of Nipponbare genes and 70.38% of KitaakeX genes. In silico expression analysis indicates that 575 non-mutated Nipponbare genes are highly expressed and likely essential for viability. Each mutant carries, on average, 68.5 mutations in the Nipponbare alignments or 63.2 mutations for KitaakeX alignments, distributed randomly across all 12 chromosomes with no evident hotspots. FN lines have approximately 8.5% fewer mutations when using the KitaakeX alignment, underscoring the unique contributions of each reference genome and the importance of utilizing both for comprehensive mutation discovery. The majority of mutations are small deletions and single-base substitutions, with deletions predominating in their effect on genes. We found that 74.4% of all transcription factor Nipponbare genes were mutated at least once. Phenotypic characterization of over 2,700 lines revealed a broad spectrum of variation in core agronomic traits (heading date, tiller number, plant height, panicle weight, seed yield components) and other morphological variants of interest. The integration of genomic and phenotypic data through the KitBase platform enabled the identification of candidate genes for several traits of interest. The KitBase website (https://kitbase.ucdavis.edu) has been updated to provide open access to all mutation data and seed stocks, as well as an intuitive query interface, facilitating forward and reverse genetic analyses in rice. This expanded resource enriches the rice functional genomics toolkit and highlights the value of coupling high-density mutation mapping with phenotypic data for rapid gene discovery and crop improvement.

plant biology↗

bioRxiv2025

Combining Directed Evolution with Machine Learning Enables Accurate Genotype-to-Phenotype Predictions

Linking sequence variation to phenotypic effects is critical for efficient exploitation of large genomic datasets. Here we present a novel approach combining directed evolution with protein language modeling to characterize naturally-evolved variants of a rice immune receptor. Using high-throughput directed evolution, we engineered the rice immune receptor Pik-1 to bind and recognize the fungal proteins Avr-PikC and Avr-PikF, which evade detection by currently characterized Pik-1 alleles. A protein language model was fine-tuned on this data to correlate sequence variation with ligand binding behavior. This modeling was then used to characterize Pik-1 variants found in the 3,000 Rice Genomes Project dataset. Two variants scored highly for binding against Avr-PikC, and in vitro analyses confirmed their improved ligand binding over the wild-type Pik-1 receptor. Overall, this machine learning approach identified promising sources of disease resistance in rice and shows potential utility for exploring the phenotypic variation of other proteins of interest.

bioinformatics↗

bioRxiv2024

Tyrosine-sulfated peptide hormone induces flavonol biosynthesis to control elongation and differentiation in Arabidopsis primary root.

In Arabidopsis roots, growth initiation and cessation are organized into distinct zones. How regulatory mechanisms are integrated to coordinate these processes and maintain proper growth progression over time is not well understood. Here, we demonstrate that the peptide hormone PLANT PEPTIDE CONTAINING SULFATED TYROSINE 1 (PSY1) promotes root growth by controlling cell elongation. Higher levels of PSY1 lead to longer differentiated cells with a shootward displacement of characteristics common to mature cells. PSY1 activates genes involved in the biosynthesis of flavonols, a group of plant-specific secondary metabolites. Using genetic and chemical approaches, we show that flavonols are required for PSY1 function. Flavonol accumulation downstream of PSY1 occurs in the differentiation zone, where PSY1 also reduces auxin and reactive oxygen species (ROS) activity. These findings support a model where PSY1 signals the developmental-specific accumulation of secondary metabolites to regulate the extent of cell elongation and the overall progression to maturation. Teaser PSY1-induced flavonol biosynthesis in Arabidopsis roots modulates the distance from the root tip at which cell elongation ceases.

plant biology↗

bioRxiv2020

A chimera including a GROWTH-REGULATING FACTOR (GRF) and its cofactor GRF-INTERACTING FACTOR (GIF) increases transgenic plant regeneration efficiency

Genome editing allows precise DNA manipulation, but its potential is limited in many crops by low regeneration efficiencies and few transformable genotypes. Here, we show that expression of a chimeric protein including wheat GROWTH-REGULATING FACTOR 4 (GRF4) and its cofactor GRF-INTERACTING FACTOR 1 (GIF1) dramatically increases the efficiency and speed of regeneration in wheat, triticale and rice and expands the number of transformable wheat genotypes. Moreover, GRF4-GIF1 induces efficient wheat regeneration in the absence of exogenous cytokinins, which facilitates selection of transgenic plants without selectable markers. By combining GRF4-GIF1 and CRISPR-Cas9 technologies, we were able to generate large numbers of edited wheat plants. The GRF4-GIF1 transgenic plants were fertile and without obvious developmental defects, likely due to post-transcriptional regulatory mechanisms operating on GRF4 in adult tissues. Finally, we show that a dicot GRF-GIF chimera improves regeneration efficiency in citrus suggesting that this strategy can be expanded to dicot crops.

plant biology↗

bioRxiv2017

Distribution and inheritance of a gene cluster encoding a sulfated tyrosine peptide in Xanthomonas spp.

The rice XA21-mediated immune response is activated upon recognition of the RaxX peptide produced by the bacterium Xanthomonas oryzae pv. oryzae (Xoo). The 60 residue RaxX precursor is posttranslationally modified to form a sulfated tyrosine peptide that shares sequence and functional similarity with the plant sulfated tyrosine (PSY) peptide hormones. The five kb raxX-raxSTAB gene cluster of Xoo encodes RaxX, the RaxST tyrosylprotein sulfotransferase, and the RaxA and RaxB components of a predicted type one secretion system. The identified the complete raxX-raxSTAB gene cluster is present only in Xanthomonas spp., in five distinct lineages in addition to X. oryzae. The phylogenetic distribution of the raxX-raxSTAB gene cluster is consistent with the occurrence of multiple lateral transfer events during Xanthomonas speciation. RaxX variants representing each of the five lineages, and three Xoo RaxX variants, fail to activate the XA21-mediated immune response yet retain peptide hormone activity. These RaxX variants contain a restricted set of missense mutations, consistent with the hypothesis that selection acts to maintain peptide hormone-like function. These observations are also consistent with the hypothesis that the XA21 receptor evolved specifically to recognize Xoo RaxX.

microbiology↗

bioRxiv2017

The Rice XA21 Ectodomain Fused to the Arabidopsis EFR Cytoplasmic Domain Confers Resistance to Xanthomonas oryzae pv. oryzae

O_LIRice (Oryza sativa) plants expressing the XA21 cell surface receptor kinase are resistant to Xanthomonas oryzae pv.oryzae (Xoo) infection. We previously demonstrated that expressing a chimeric protein containing the EFR (ELONGATION FACTOR Tu RECEPTOR) ectodomain and the XA21 endodomain (EFR:XA21) in rice does not confer robust resistance to Xoo.\nC_LIO_LITo test if the XA21 ectodomain is required for Xoo resistance, we produced transgenic rice lines expressing a chimeric protein consisting of the XA21 ectodomain and EFR endodomain (XA21:EFR) and inoculated these lines with Xoo. We also tested if the XA21:EFR rice plants respond to a synthetic sulfated 21 amino acid derivative (RaxX21-sY) derived from the activator of XA21-mediated immunity, RaxX.\nC_LIO_LIWe found that five independently transformed XA21:EFR rice lines displayed resistance to Xoo as measured by lesion length analysis, and showed that five lines express markers of the XA21 defense response (generation of reactive oxygen species and defense response gene expression) after treatment with RaxX21-sY.\nC_LIO_LIOur results indicate that expression of the XA21:EFR chimeric receptor in rice confers resistance to Xoo. These results suggest that the endodomain of the EFR and XA21 immune receptors are interchangeable and the XA21 ectodomain is the key determinant conferring robust resistance to Xoo.\nC_LI

plant biology↗

bioRxiv2017

WheatNet: A genome-scale functional network for hexaploid bread wheat, Triticum aestivum

Gene networks provide a system-level overview of genetic organizations and enable the dissection of functional modules underlying complex traits. Here we report the generation of WheatNet, the first genome-scale functional network for T. aestivum and a companion web server (www.inetbio.org/wheatnet). WheatNet was constructed by integrating 20 distinct genomics datasets, including 156,000 wheat-specific co-expression links mined from 1,929 microarray data. A unique feature of WheatNet is that each network node represents either a single gene or a group of genes. We computationally partitioned gene groups mimicking homeologous genes by clustering 99,386 wheat genes, resulting in 20,248 gene groups comprising 63,401 genes and 35,985 individual genes. Thus, WheatNet was constructed using 56,233 nodes, and the final integrated network has 20,230 nodes and 567,000 edges. The edge information of the integrated WheatNet and all 20 component networks are available for download.

genetics↗