Biology subjects

Snowdon, R.

Publications and source records attributed to Snowdon, R..

7 recordsLinked to original sources

bioRxiv2026

High-throughput stomatal phenotyping provides selection targets for stress-resilient wheat

Phenotyping stomatal traits and their developmental plasticity is time-consuming but holds potential to improve water use efficiency and photosynthesis for designing stress-tolerant crops under climate change. Here, we develop a robust, high-throughput pipeline for phenotyping 14 stomatal traits in winter wheat related to size, variation, maximum conductance, and spatial patterning. We (1) analyze over 25,000 images from 60 wheat cultivars grown in growth chamber, greenhouse, and field conditions; (2) investigate the impact of light, temperature, and reduced water and nitrogen supply on stomatal traits and their developmental plasticity across adaxial and abaxial surfaces; and (3) evaluate genetic diversity and breeding progress of stomatal traits. Stomatal traits were highly broad-sense heritable, were largely plastic in response to environmental conditions, and showed genotype-specific responses. Stomatal traits of third leaves under controlled environments with stable light and temperature conditions reliably captured the genetic variance of flag leaves under field conditions. Our data suggests that the upper leaf surface contributed more to transpiration and cooling through consistently higher stomatal density, area, and maximum conductance, while the lower surface facilitated CO2 diffusion via systematic proper patterning and spacing. Breeding maintains the genetic diversity of stomatal traits, and our pipeline facilitates breeders to target them to enhance water use efficiency in high-yielding modern cultivars.

plant biology↗

bioRxiv2026

Progeny differentiation in faba bean using hyperspectral images and machine learning

Though currently a minor crop, faba bean is a promising source of plant-based protein as global diets shift towards more plant-based nutrition. To realise this potential, advances in breeding and cultivation are crucial. To exploit heterosis, faba bean breeding frequently utilises synthetic cultivars, which involves open pollination of inbred lines to produce a mixture of F1 hybrid seeds and self-pollinated offspring. Pure F1 hybrid cultivars are currently unavailable due to unstable cytoplasmic male sterility (CMS) systems. An ability to distinguish F1 seeds from their parental inbreds via characteristics associated with xenia effects could change this. The xenia effect refers to the influence of paternal pollen on seed traits, for example seed weight and cotyledon cells in faba bean. In this study, we exploited the xenia effect captured in hyperspectral imaging data to develop machine learning scenarios for discriminating between parental and F1 seeds of open pollinated synthetic combinations (Syn-1). The hyperspectral data were pre-processed using Savitzky-Golay filtering to reduce noise and smooth the spectra. Various machine learning algorithms were applied, incorporating Bayesian hyperparameter optimisation. The scenarios achieved up to 98.9 % accuracy in separating parental components of Syn-1. When including all seeds, the model achieved 40.7 %, indicating moderate detection and classification performance. As the harmonic mean of precision and recall, the F1 score accounts for both the correctness of F1 seed detections and the completeness with which F1 seeds were detected. While this approach does not yet enable the development of full hybrid cultivars, it paves the way for hybrid-enriched cultivars. These could help to streamline breeding for synthetic cultivars and potentially increase yields, for example by increasing the proportion of F1 hybrid seeds in synthetic cultivars. This study extends knowledge of the xenia effect in faba bean and provides a basis for further research aimed at enhancing breeding methods and productivity.

genetics↗

bioRxiv2026

Homoeo-alleles of wheat GNI2 fuel grain yields across input environments

Grain yield in wheat is frequently driven by pre-anthesis growth and how carbon is directed to reproductive parts, determining the potential size of the grain-producing sink. However, the genetic mechanisms controlling this carbon allocation remain unclear. In this study we discovered a series of loci in tetraploid and hexaploid wheats that, when combined, confer an average grain yield advantage in hexaploid winter wheat of approx. 5-7% under high-input farming while approx. 10-15% under low-input conditions. The responsible gene is GRAIN NUMBER INCREASE 2 (GNI2), ancestral to its duplicate GNI1, and represented by the homoeo-allelic series GNI-A2, GNI-B2, and GNI-D2. GNI1 and all GNI2 copies additively affect floral growth and fertility by modulating reproductive allocation and harvest index. Herewith, we describe a series of grain yield-relevant GNI2 homoeo-alleles with a proven track record for being beneficial in both high- and low-input environments. Their deployment offers a sustainable pathway to raise global grain yields in the future.

plant biology↗

bioRxiv2025

Integrative epigenomic analysis uncovers asymmetry of enhancer activity in Brassica napus

Non-coding regulatory regions are essential to the determination of gene expression and plant phenotypes. In this work, we investigated the cis-regulatory landscape of a winter type rapeseed, Express617, across multiple sample types. Combining chromatin accessibility, DNA methylation and gene expression, we annotated thousands of novel regulatory elements in the Brassica napus genome. Among those regions, we discovered and functionally characterized super-enhancers, observing an asymmetrical distribution of these regulatory elements favoring the Cn subgenome. Super-enhancer (SE) associated genes were found enriched in tissue identity and responses to stimuli related processes. We further establish and apply an in-silico validation pipeline for super-enhancers, integrating population-level expression analysis and machine learning (ML) models predicting gene expression levels. Almost 50% of the newly identified SE-associated genes had an observed expression higher than the expression levels predicted by the ML model. Moreover, structural variants disrupting super-enhancer elements correlate with a reduction of expression in the associated genes, both consistent with the positive effect of these regulatory regions. These results greatly expand the functional annotation of rapeseed and contribute to a better understanding of the link between regulatory elements and their target genes and processes, providing novel insights and targets for B. napus (epi)-genome editing strategies.

plant biology↗

bioRxiv2024

Electrical charge-mediated transformation for efficient plant genome editing

Genome editing technologies possess significant potential to enhance plant breeding; however, the delivery of editing constructs poses challenges in numerous crop species due to their resistance to transformation or tissue culture. This study introduces an innovative approach for the delivery of ribonucleoprotein (RNP) complexes and plasmid vectors into intact, regenerable faba bean plant tissues. This is accomplished by applying an electric current that makes plant cell walls and membranes permeable, thereby allowing the entry of macromolecular constructs into the cell and nucleus. This study assessed the efficacy of electric pulse-mediated transfection in faba bean by generating stable GFP-expressing faba bean plants. Furthermore, we incorporated it into faba bean leaf tissue and demonstrated its application in both embryos and leaf tissues. We demonstrate DNA-free genome editing by targeting the endogenous phytoene desaturase gene (PDS), achieving a mutation success rate of 50%. This method is efficient and economical, necessitating limited technical training. It is applicable to both leaf and embryo tissues, thereby enhancing its utility for crop improvement. This technique shows potential for the development of new crop varieties that can more effectively address global climate challenges.

plant biology↗

bioRxiv2024

VC2 regulates baseline vicine content in faba bean

Faba bean (Vicia faba) is a valuable legume crop desired globally for its high nutritional composition. However, the seed vicine and convicine (v-c) content reduces the nutritional quality of faba bean protein and can induce favism in individuals with glucose-6-phosphate dehydrogenase deficiency. Recently, VC1 gene, encoding a bi-functional riboflavin protein, was reported to be responsible for initiating the biosynthetic pathway in V. faba. In low v-c cultivars, a 2 bp insertion in this gene results in a loss of function, but the mutation only partially eliminates v-c biosynthesis, indicating the involvement of other genes. Here, we demonstrate that a novel V. faba riboflavin gene, VC2, is responsible for the residual v-c contents in faba bean. VC2 shares nearly identical functional domains with VC1 and has GTP cyclohydrolase II activity, catalyzing the conversion of GTP into an intermediate molecule in the biosynthetic pathway. Gene expression analysis reveals that VC2 contributes a minor effect to the trait, accounting for approximately 5-10% of total riboflavin gene transcripts which significantly correlates with the baseline contents in low v-c cultivars. Our results illustrate that cultivars carrying the 2 bp inactivating insertion in VC1 still have residual v-c levels due to VC2 activity. Furthermore, we find that VC1 has multiple alleles and exhibits copy number variations, complicating molecular marker development. Conversely, single nucleotide polymorphisms within VC2 provide a reliable alternative for marker-assisted selection in faba bean breeding. In conclusion, our study elucidates the complex genetic regulation of v-c biosynthesis and provides valuable insights to facilitate its elimination in faba bean.

genetics↗

bioRxiv2022

Genetic diversity analysis and characterization of Ugandan sorghum

The National Genebank of Uganda houses diverse and rich Sorghum bicolor germplasm collection. This genetic diversity resource is untapped, under-utilized and has not been systematically incorporated into sorghum breeding programs. In this study, we characterized the germplasm collection using whole genome SNP markers. Discriminant analysis of principal components (DAPC) was implemented to study racial ancestry of the accessions in comparison to a global sorghum diversity set and characterize sub-groups and admixture in the Ugandan germplasm. Genetic structure and phylogenetic analysis was conducted to identify distinct genotypes in the Ugandan collection and relationships among groups. Furthermore, in a case study for identification of potentially useful adaptive trait variation for breeding, we performed genome-wide association studies for juvenile cold tolerance. Genomic regions potentially involved in adaptation of Ugandan sorghum varieties to cooler climatic conditions were identified that could be of interest for expansion of sorghum production into temperate latitudes. The study demonstrates how genebank genomics can potentially facilitate effective and efficient usage of valuable, untapped germplasm collections for agronomic trait evaluation and subsequent allele mining.

plant biology↗