Biology subjects

Moody, D.

Publications and source records attributed to Moody, D..

7 recordsLinked to original sources

bioRxiv2026

Leveraging synthetic environmental covariates to explore crop genotype by environment interactions

Environments are unpredictable. Genotype by environment interactions (GEI) further complicate any assessment of genotype performance or stability across diverse environments posing a challenge for plant breeders. Several approaches exist to address this challenge. However existing approaches present a trade-off between scale and interpretability often acting in a 'black box' manner. Here we extend the Finlay-Wilkinson regression on synthetic environmental covariates of Piepho and Blancon (2023) to dissect GEI at the level of individual developmental windows, resolving which growth stages drive GEI and how genotype stability varies across them. Yield data for 961 genotypes from a barley breeding program, tested across 12 environments, is used as a case study to illustrate how this approach can provide valuable insight into the GEI present. Exploring the dynamic impact of environmental variables across growth stages revealed that environmental factors during early grain fill contributed the most to yield GEI variance. Stability was found to be dynamic across development windows, presenting growth-stage-specific yield stability as a new potential breeding target. This approach yields new, growth-stage-resolved measures of yield stability and a new means of dissecting GEI in complex traits, while also opening a route to environmental clustering based on stage-specific GEI patterns.

genetics↗

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↗

bioRxiv2026

Roseobacter enrichment early in life facilitates future colonization of Roseobacter bacteria and improves long-term survival against Vibrio aestuarianus in the Pacific oyster

Exposure to beneficial bacteria during early immune development may promote long-term survival against pathogens, known as "microbial education." As marine diseases intensify with ocean warming, methods to improve marine organisms robustness against disease will be valuable for mitigation. Here, we experimentally tested whether exposure to high temperature seawater, seawater enrichment with Roseobacter bacteria, or a combination of both during the first 24 hours of life enhances long-term survival of the Pacific oyster (Crassostrea gigas) against the widespread marine pathogen, Vibrio aestuarianus subsp. francensis, at high temperatures (24 {degrees}C). Exposure to high temperatures early in life did not improve future survival during disease challenges and caused high larval mortality. Conversely, Roseobacter enrichment during high temperature exposure resulted in a "microbial rescue effect," improving larval survival. We found that Roseobacter enrichment during the first 24 hours of life improved future survival against V. aestuarianus at high temperatures by up to [~]28% at 13 days post-fertilization (dpf) and [~]30% at 90 dpf. Ultimately, the supplemented Roseobacter species did not remain associated with the host microbiome but instead was replaced by a high abundance of other Roseobacter bacteria at 90 dpf. These findings suggest that early Roseobacter enrichment facilitates future colonization by other Roseobacter species, which may in turn protect against pathogenic V. aestuarianus, supporting the concept of microbial education in marine invertebrates and its potential use to combat marine diseases. ImportanceThis research identifies key aspects of early developmental processes in a marine invertebrate, Crassostrea gigas, and explores how these processes can be utilized to alter host-microbe interactions later in life.

microbiology↗

bioRxiv2025

An amplicon panel for high-throughput and low-cost genotyping of Yesso scallop Mizuhopecten yessoensis

The Yesso scallop Mizuhopecten yessoensis was imported from Japan to western Canada in the late 1980s to establish an economically viable scallop aquaculture industry. Since this time, the industry in Canada has operated with existing genetic diversity within the broodstock, which is considerably limited relative to wild populations. The sector has not been able to realise its full potential in part due to idiopathic hatchery failures and farm stock collapses due to disease outbreaks associated with the intracellular bacterial pathogen Francisella halioticida. To support Yesso scallop production and breeding, here we generate a low-density, genotyping-by-sequencing amplicon panel using single nucleotide polymorphism (SNP) markers that are evenly spaced across the M. yessoensis genome and that show high heterozygosity in Canada and Japan. The panel can also exploit the high genetic polymorphism of the M. yessoensis genome, with de novo SNP calling identifying over 2,500 high quality SNPs within the 579 sequenced amplicons. We demonstrate the utility and versatility of this new genotyping tool for breeding applications including parentage assignment, low density family-based genome-wide association study, trait heritability evaluation to determine potential for genomic selection, and species differentiation (against the weathervane scallop Patinopecten caurinus). We did not find any genomic regions significantly associated with F. halioticida resistance but did identify potential for genomic selection. We could separate the two species based on genotypes, and we did not see evidence of a past M. yessoensis x P. caurinus hybridization event within the M. yessoensis breeding population at Vancouver Island University. This low-cost genotyping panel is expected to accelerate selective breeding improvements for M. yessoensis in Canada and elsewhere.

genomics↗

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↗

bioRxiv2021

Novel design of imputation-enabled SNP arrays for breeding and research applications supporting multi-species hybridisation

Array-based SNP genotyping platforms have low genotype error and missing data rates compared to genotyping-by-sequencing technologies. However, design decisions used to create array-based SNP genotyping assays for both research and breeding applications are critical to their success. We describe a novel approach applicable to any animal or plant species for the design of cost-effective imputation-enabled SNP genotyping arrays with broad utility and demonstrate its application through the development of the Infinium Wheat Barley 40K SNP array. We show the approach delivers high-quality and high-resolution data for wheat and barley, including when samples are jointly hybridised. The new array aims to maximally capture haplotypic diversity in globally diverse wheat and barley germplasm while minimising ascertainment bias. Comprising mostly biallelic markers designed to be species-specific and single-copy, it permits highly accurate imputation in diverse germplasm to improve statistical power for GWAS and genomic selection. The SNP content captures tetraploid wheat (A- and B-genome) and Ae. tauschii (D-genome) diversity and delineates synthetic and tetraploid wheat from other wheats, as well as tetraploid species and subgroups. The content includes SNP tagging key trait loci in wheat and barley and that directly connect to other genotyping platforms and legacy datasets. The utility of the array is enhanced through the web-based tool Pretzel (https://plantinformatics.io/) which enables the arrays content to be visualised and interrogated interactively in the context of numerous genetic and genomic resources to more seamlessly connect research and breeding. The array is available for use by the international wheat and barley community. Short summaryDesigning SNP genotyping arrays for closely related species with broad applicability in both research and breeding is challenging. Here we describe a novel generic approach to select SNP content for such arrays and demonstrate its utility in wheat and barley to: O_LIcapture haplotypic diversity while minimising ascertainment bias; C_LIO_LIaccurately impute to high SNP density in diverse germplasm; C_LIO_LIgenerate high-quality high-resolution genotypic data; and C_LIO_LIjointly hybridise samples to the same bead chip array. C_LI

genetics↗

bioRxiv2019

Genetic, morphometric, and molecular analyses of interspecies differences in head shape and hybrid developmental defects in the wasp genus Nasonia

Males in the parasitoid wasp genus Nasonia (N. vitripennis, N. giraulti, N. longicornis) have distinct, species specific, head shapes. Fertile hybrids among the species are readily produced in the lab allowing genetic analysis of the evolved differences. In addition, the obligate haploidy of males makes these wasps a uniquely powerful model for analyzing the role of complex gene interactions in development and evolution. Previous analyses have shown that complex gene interactions underpin different aspects of the shape differences, and developmental incompatibilities that are specific to the head in F2 haploid hybrid males are also governed by networks of gene interaction. Here we use the genetic tools available in Nasonia to extend our understanding of the gene interactions that affect development and morphogenesis in male heads. Using artificial diploid male hybrids, we show that alleles affecting head shape are codominant, leading to uniform, averaged hybrid F1 diploid male heads, while the alleles mediating developmental defects are recessive, and are not visible in the diploid hybrids. We also determine that divergence in time, rather than in morphological disparity is the primary driver of hybrid developmental defects. In addition, we show that doublesex is necessary for the male head shape differences, but is not the only important factor. Finally we demonstrate that we can dissect complex interspecies gene interaction networks using introgression in this system. These advances represent significant progress in the complex web of gene interactions that govern morphological development, and chart the connections between genomic and phenotypic variation.

evolutionary biology↗