Biology subjects

Aldiss, Z.

Publications and source records attributed to Aldiss, Z..

3 recordsLinked to original sources

bioRxiv2026

Identifying water stress response haplotypes in barley using latent environmental covariates

PurposeGenotype-by-environment (G x E) interactions represent a major obstacle to increasing genetic gain in crop breeding, with the underlying physiological drivers often remaining obscured within conventional statistical models. This case study presents a novel framework that transforms the latent factors from Factor Analytic (FA) multi-environment trial (MET) models into heritable quantitative traits, enabling the genetic dissection of adaptive response patterns. MethodsA Factor Analytical Linear Mixed Model (FA-LMM) was fit to plot-level yield data for 1,036 barley genotypes across eight Australian trials. ResultsCorrelation of the factor loadings with APSIM-simulated environmental covariates demonstrated that the second latent factor FA2 was strongly correlated with the Water Stress Index (r = -0.83) during the critical flowering period, establishing water availability as the main biological axis of crossover Gx E. Genotypic scores for the derived traits, Overall Performance (OP) and Water Stress Response (WSR), were subjected to high-resolution haplotype-based mapping using local Genomic Estimated Breeding Values (GEBV). ConclusionThis analysis successfully identified major genomic regions that accounted for a substantial proportion of the additive genetic variance. Gene Ontology enrichment of candidate genes within the top haploblocks implicated fundamental pathways related to energy homeostasis, root development, and stress response, with notable candidates including FTsH11, BPS1, and TDP1. The distribution of favourable Haplotypes of Interest (HOI) in elite cultivars suggested a historical signature of inadvertent selection for these adaptive mechanisms. This framework provides an explicit bridge between statistical modelling and functional genomics, offering breeders actionable genetic targets for accelerated development of climate-resilient cereals.

plant biology↗

bioRxiv2024

Phenotyping the hidden half: Combining UAV phenotyping and machine learning to predict barley root traits in the field

Improving crop root systems for enhanced adaptation and productivity remains challenging due to limitations in scalable non-destructive phenotyping approaches, inconsistent translation of root phenotypes from controlled environment to the field, and a lack of understanding of the genetic controls. This study serves as a proof of concept, evaluating a panel of Australian barley breeding lines and cultivars (Hordeum vulgare L) in two field experiments. Integrated ground-based root and shoot phenotyping was performed at key growth stages. UAV-captured vegetation indices (VIs) were explored for their potential to predict root distribution and above-ground biomass. Machine learning models, trained on a subset of 20 diverse lines, with the most accurate model applied to predict traits across a broader panel of 395 lines. Unlike previous studies focusing on above-ground traits or indirect proxies, this research directly predicts root traits in field conditions using VIs, machine learning and root phenotyping. Root trait predictions for the broader panel enabled genomic analysis using a haplotype-based approach, identifying key genetic drivers, including EGT1 and EGT2 which regulate root gravitropism. This approach offers the potential to advance root research across various crops and integrate root traits into breeding programs, fostering the development of varieties adapted to future environments. HighlightIntegrating UAV phenotyping and machine learning can be used to predict RSA traits non-destructively and offers a new approach to support root research and crop improvement.

physiology↗

bioRxiv2024

The PIN2 ortholog in barley modifies root gravitropism and architecture without impacting the shoot

Roots provide the critical interface where plants acquire nutrients and water, but our limited understanding of the genetic controls modulating root system architecture (RSA) in crop species constrains opportunities to develop future cultivars with improved root systems. However, there is vast knowledge of root developmental genes in model plant species, which has the potential to accelerate progress in crops with more complex genomes, particularly given that genome editing protocols are now available for most species. PIN-FORMED2 (PIN2) encodes a root specific polar auxin transporter, where its absence resulted in roots being unable to orient themselves using gravity, producing a significantly wider root system. To explore the role of PIN2 in a cereal crop, we used CRISPR/Cas9 editing to knockout of PIN2 in barley (Hordeum vulgare). Like Arabidopsis, the roots of barley pin2 loss-of-function mutants displayed an agravitropic response at seedling growth stages, resulting in a significantly shallower and wider root system at later growth stages. Notably, despite the significant change in RSA, there was no change in shoot architecture or total shoot biomass. We discuss the future challenges and opportunities to harness the PIN2 pathway to optimise RSA in crops for a range of production scenarios without a shoot trade-off.

plant biology↗