Biology subjects

Halpin-McCormick, A.

Publications and source records attributed to Halpin-McCormick, A..

9 recordsLinked to original sources

bioRxiv2026

Managing the genetic diversity of Dioscorea yams for adaptation to climate change

Understanding adaptation to environmental variation is fundamental to climate-resilient agriculture. Here, we analyzed a georeferenced collection of 167 Dioscorea accessions spanning a wide range of bioclimatic and biophysical variation, from dry sahelian environment to rainforest environment. Genome-wide association analyses revealed that the genetic architecture of environmental adaptation is largely driven by large-effect loci, although precipitation-related traits were associated with many small-effect loci. This mixed architecture could lead to multiple breeding strategies, including marker-assisted backcrossing and the targeted use of wild and semi-wild relatives. We identified a core collection of accessions that captures much of the genetic and environmental diversity, and highlighted accessions as potential parents for abiotic stress tolerance. Projections under future climate scenarios using genomic offset identified regions and accessions at elevated risk of maladaptation, as well as others with broad adaptive potentiality. Maximizing the use of available material may facilitate the development of climate-resilient cultivars.

plant biology↗

bioRxiv2026

Environment and plant genetics shape barley rhizosphere microbiome structure across contrasting locations

AbstractSoil microorganisms are crucial for plant survival and productivity, but factors governing rhizosphere recruitment across diverse regions remain unclear. This study investigated the rhizosphere microbiome of barley, using elite cultivars across seven location-year trials to evaluate the effects of environmental factors and crop genotype on bacterial and fungal community composition. Three locations were in the US northern Great Plains, and Hawaii was used as a contrasting environment. A greenhouse reciprocal transplant study determined the relative contributions of soil physicochemical factors and soil inoculum to rhizosphere community structure. Using 16S and ITS2 amplicon sequencing, the study characterized bacterial and fungal microbiomes and assessed the contribution of environment, soil chemistry, and barley genetics to microbial community assembly. In locations within the adapted range of barley, Actinobacteriota was the dominant phylum, while Proteobacteria was dominant in Hawaii. Variance partitioning showed that 73% of bacterial and 80% of fungal genera were associated with location-year effects while 53% of bacterial and 36% of fungal genera were responsive to soil factors. Enrichment analysis found 21.6% of bacterial and 51.4% of fungal ASVs were unique to specific barley genetic subpopulations. Results from the reciprocal transplant study validated field observations by demonstrating that 20.7% of the variation in community structure was explained by soil while 18.2% was explained by inoculum source. These findings demonstrate that environmental variation is the dominant constraint on rhizosphere community composition but within these constraints, barley genotype drives recruitment of distinct bacterial and fungal taxa. ImportanceThese findings underscore the complex interplay between plant genotype, environment, and microbial community assembly, providing insights into how barley recruits distinct microbial communities in the rhizosphere across different environments. These insights have the potential to be leveraged for management and plant breeding strategies to optimize plant-microbe interactions for enhancing agricultural sustainability.

microbiology↗

bioRxiv2026

Unlocking the potential of Capsicum Germplasm Collections for Climate Resilience and Fruit Quality

Climate change increasingly threatens global Capsicum (pepper) production. Accelerating the deployment of climate-resilient cultivars requires effective use of genetic diversity conserved in genebanks. We implement a "turbocharging" strategy in Capsicum by integrating genome-wide association studies and genomic prediction in a core collection (n = 423), followed by genomic prediction across the global collection (n = 10,250) using the core as a training population. We generated genomic estimated breeding values (GEBVs) for 31 high-accuracy traits (r > 0.5) encompassing hyperspectral phenotypes (heat/control), agronomic performance (heat/control) and fruit quality. To enhance accessibility and decision-making, we developed a large language model (LLM) integrated application that enables flexible, preference-based selection of candidates. By narrowing the parental decision space, this framework streamlines screening of large germplasm collections while balancing climate resilience, quality attributes and market demands. Our approach provides a scalable decision-support system to accelerate climate-resilient Capsicum breeding and maximize global genetic resources.

plant biology↗

bioRxiv2026

Ancestry and Environmental Adaptation in North American Feral Cannabis

Understanding how different populations respond to environmental variation is fundamental to breeding climate resilient crops. In this study, we integrate three diverse georeferenced Cannabis datasets comprising North American feral populations and Eurasian samples (n=909) to resolve population structure, infer evolutionary relationships and quantify adaptive responses to climate across a broad environmental gradient. Phylogenetic analysis rooted to Humulus lupulus shows North American feral populations are more closely related to basal and hemp-type lineages than to drug-type or Iranian populations, a pattern supported by ancestry and PCA analyses. By combining these datasets, we capture a wider range of climatic variation and gain new insight into the adaptive potential of cannabis germplasm. Using environmental genomic selection (EGS), we identified nine bioclimatic traits with prediction accuracies exceeding 0.5 across the combined datasets (12,030 SNPs; 909 samples; training = 191). When analyzing the North American dataset alone, EGS revealed 14 traits with prediction accuracies greater than 0.85 (22,852 SNPs; 760 samples; training = 310). Genomic estimated adaptive values (GEAVs) revealed population specific climatic responses, particularly for precipitation related traits, with northeastern North American populations (Indiana and New York) showing signatures consistent with adaptation to wetter and cooler environments. Climate projections under a high emission scenario (SSP585) indicate that [~]34 % of sampled locations are expected to transition to different Koppen-Geiger climate classes by 2050, with distinct shifts observed among North American and Iranian populations. Genome environment association (GEA) analysis identified replicated temperature and precipitation associated loci across multiple chromosomes. Using genotype-phenotype data, genomic selection for cannabinoid traits revealed that only CBD achieved prediction accuracies exceeding 0.5, consistent with a polygenic architecture extending beyond the CBDAS locus. Collectively, these results demonstrate that feral and landrace Cannabis populations harbor substantial adaptive variation and represent an underutilized reservoir for climate resilient breeding and allele discovery, with relevance for pre-breeding efforts under future climate scenarios.

plant biology↗

bioRxiv2025

Dissecting Genotype-Environment interactions with functional implications for parental selection in Cannabis Breeding

As climate variability continues to impact agricultural systems, identifying genetic factors that contribute to environmental adaptation will be essential for optimizing breeding strategies for the development of climate resilient varieties. Through human cultivation and naturalization, Cannabis sativa has dispersed globally, adapting to a range of environmental conditions across various climates and latitudes. We combined raw data from multiple public sources to conduct an Environmental Genomic Selection (EGS) analysis on 149 Cannabis sativa samples, to assess how different populations of Cannabis relate to their environmental conditions. Exploring Genomic Estimated Adaptive Values (GEAVs) across bioclimatic variables can facilitate the selection of parental material adapted for a specific condition. We further explore potential mechanisms of local adaptation by characterizing the individual marker effects which underlie these GEAV scores. To facilitate interpretation, we used previously described genetic groupings (Basal, Hemp-type, Drug-type feral, Drug-type). Distinct patterns emerged across population groups with the drug-type (Type I) group showing consistently narrow GEAV ranges, whereas the drug-type feral group showed a broader distribution, often having high GEAVs for precipitation variables. A key climate variable difference was seen in monthly average values, revealing a seasonal response to precipitation in drug-type feral samples. Exploring marker-effect differences between seasonal GEAVs indicated a response to seasonal precipitation in drug-type feral samples. As this samples are sourced from geographic regions that have seasonal monsoons, they may have traits conferring flood tolerance (water logging) that could be introgressed into other backgrounds. The basal group also exhibited broad GEAV ranges across several bioclimatic traits, indicating they may be a valuable genetic resource for introgression to enhance environmental resilience. These findings underscore the importance of incorporating diverse germplasm into breeding programs to improve Cannabis resilience to changing environmental conditions. EGS provides a fast method to enable climate-conscious parental selection while gaining mechanistic information. Ultimately, we hope that such a strategy could support the development of climate-resilient Cannabis varieties tailored to both current and future environmental challenges.

plant biology↗

bioRxiv2024

Uncovering genetic linkages in the rhizosphere contributing to adaptation

Microorganisms recruited to the rhizosphere from the surrounding soil can benefit the fitness of their host. Variation in plant genetics is associated with variation in rhizosphere microbial community composition leading to changes in fitness and crop productivity. However, what impact the abiotic environment has on connections between microbes and host genetics, and whether those connections in turn impact crop performance in realistic agricultural scenarios remains unclear. We assessed agronomic performance and 16S and ITS amplicon-based rhizosphere bacterial and fungal community composition on a large diverse barley population grown in seven field trials across four locations and two years. Within adapted regions, we observed consistent rhizosphere compositions across diverse soils, whereas in an unadapted environment, distinct microbial communities were recruited, indicating environmental specificity in microbial assembly. A Genome-wide association study (GWAS) identified 864 associations of barley genetic markers with bacterial or fungal taxa abundance. A total of 108 microbe-associated quantitative trait loci (QTL) co-localized with agronomic traits, suggesting pleiotropy or genetic linkage. Associated taxa varied considerably across field trial environments, whereas the mapped host QTL were more consistent. Members of the nitrogen cycling bacterial phylum, Nitrospirota were the most extensively associated. This phylum had 25 marker associations across five of the field trial location-years in the GWAS. These included a locus on chromosome 2H that associated with Nitrospirota bacteria and grain protein in two location-years, and the Leohumicola fungal genus and grain protein in a third trial. These findings support the genetic manipulation of rhizosphere microbiomes to enhance crop adaptation, whether with consistent or environment-specific microbial taxa. Such breeding advances will support phenotyping and selection strategies to improve crop resilience and productivity across variable environments.

plant biology↗

bioRxiv2024

Back to the Future: Environmental genomic selection to take advantage of polygenic local adaptation

The genetic basis of adaptation is a fundamental question in evolutionary genetics. Environmental association analysis (EAA) and various allele frequency comparisons in genomic environmental association (GEA) have become standard approaches for investigating the genetic basis of adaptation to natural environments. While these analyses provide insight into local adaptation, they have not been widely adopted in breeding or conservation programs. This may be attributable to the difficulty in identifying the best individuals for transplantation/relocation in conservation efforts or identification of the best parents in breeding programs. To explore the use of EAA and GEA for future breeding programs, we used a cereal crop - barley (Hordeum vulgare L.) as our case-study species due to its wide adaptability to different environments and agro-ecologies, ranging from marginal and low input fields to high-productive farms. Here, we use publicly available data to conduct environmental genomic selection (EGS) on 753 landrace barley accessions using a mini-core of 31 landrace accessions and a de-novo core of 100 as the training populations. Environmental genomic selection is to environmental association analysis (EAA) what genomic selection is to genome-wide association studies (GWAS). Since local adaptation to the environment is polygenic, a whole-genome approach is likely to be more accurate for selecting for environmental adaptation. Here we show distinct genetic background and population differences and how an integrative approach coupling environmental genomic selection and species distribution modelling can help identify key parents for breeding for adaptation to specific environmental variables and geographies to minimize linkage drag.

plant biology↗

bioRxiv2024

Species Distribution of Cannabis sativa: Past, Present and future

Cannabis sativa L. is an annual flowering herb of Eurasian origin that has long been associated with humans. Domesticated independently at multiple locations at different times for different purposes (food, fiber, and medicine), these long-standing human associations have influenced its distribution. However, changing environmental conditions and climatic fluctuations have also contributed to the distribution of the species and define where it is optimally cultivated. Here we explore the shifts in distribution that C. sativa may have experienced in the past and explore the likely shifts in the future. Modeling under paleoclimatic scenarios shows niche expansion and contraction in Eurasia through the timepoints examined. Temperature and precipitation variables and soil variable data were combined for species distribution modeling in the present day and showed high and improved predictive ability together as opposed to when examined in isolation. The five most important variables explaining [~]65% of the total variation were soil organic carbon content (ORCDRC), pH index measured in water solution (PHIHOX), annual mean temperature (BIO-1), mean temperature of the coldest quarter (BIO-11) and soil organic carbon density (OCDENS) (AUC = 0.934). Climate model projections where efforts are made to curb emissions (RCP45/SSP245) and the business as usual (RCP85/SSP585) models were evaluated. Under projected future climate scenarios, shifts worldwide are predicted with a loss of [~]43% in suitability areas with scores above 0.4 observed by 2050 and continued but reduced rates of loss by 2070. Changes in habitat range have large implications for the conservation of wild relatives as well as for the cultivation of Cannabis as the industry moves toward outdoor cultivation practices.

plant biology↗

bioRxiv2022

Phylogenetic resolution of the Cannabis genus reveals extensive admixture

Population structure of Cannabis sativa L. was explored across nine independent collections that each contained a unique sampling of varieties. Hierarchical Clustering of Principal Components (HCPC) identified a range of three to seven genetic clusters across datasets with inconsistent structure based on use type indicating the importance of sampling particularly when there is limited passport data. There was broader genetic diversity in modern cultivars relative to landraces. Further, in a subset of geo-referenced landrace accessions, population structure was observed based on geography. The inconsistent structure across different collections shows the complexity within Cannabis, and the importance of understanding any particular collection which could then be leveraged in breeding programs for future crop improvement.

genomics↗