Composite interval mapping and genomic prediction of nut quality traits in American and American–European interspecific hybrid hazelnuts

Crop Science · 2026-01-01

Abstract The native, perennial shrub American hazelnut ( Corylus americana ) is cultivated in the US Midwest for its significant ecological benefits, as well as its high‐value nut crop. Genetic improvement of perennial crops involves long‐term breeding efforts, and benefits from the use of genetic data in selection to reduce breeding cycle time. In addition, high‐throughput phenotyping methods are essential to the efficient and accurate screening of large breeding populations. This study reports novel advances in both of these domains, for American ( C. americana ) and interspecific hybrids between European ( Corylus avellana ) and American hazelnuts. Two populations of hazelnuts, one composed of C. americana and one composed of C. americana × C. avellana hybrids, were phenotyped over the course of 2 years in two locations using a digital imagery‐based method for quantifying morphological nut and kernel traits. These data were used to perform composite interval mapping using a recently released genetic map, and genomic prediction using a newly available chromosome‐scale reference genome for C. americana . Multiple quantitative trait loci were detected for all traits analyzed, with an average total R 2 of 52%. Genomic prediction exhibited high accuracy, with an average correlation coefficient between genotypic values and phenotypic observations of 0.78 across both environments. These results suggest that incorporating genetic data in selection is a tenable method for improving genetic gain for highly polygenic traits in hazelnut breeding programs.

Improving genomic prediction in wheat with random regression models with genotype‐specific phenology‐driven environmental covariates

The Plant Genome · 2026-05-08

Abstract Wheat ( Triticum aestivum L.), a crucial cereal crop for global food security, faces growing challenges from climate change. Future production requires varieties that are resilient to environmental extremes and fluctuations. The goal of this study was to assess strategies to increase selection response through genomic selection in wheat by integrating genotypic‐specific phenology‐derived environmental covariates (ECs) and random regression models (RRM) in multi‐environment trials. We analyzed phenotypic and genomic data from 1683 genotypes from 2010 to 2020 across 71 environments using 45 ECs derived from vegetative, reproductive, and grain‐filling phenological phases. Seven key ECs were selected via partial least squares regression to model genotype by environment interaction (GEI) and evaluate their integration in three different genomic prediction scenarios (CV0, CV1, and CV2). Genomic best linear unbiased prediction models (GBLUP), GBLUP models with GEI (GBLUP G × E ) modeled as a factor analytic (FA) model, and RRM were compared for their predictive ability performance. RRM with three ECs outperformed GBLUP achieving 50%–100% higher accuracy in CV1 and CV2. The FA exhibited the highest accuracy overall for CV2 but not for CV1. At least one RRM model improved predictions in >89% of environments when predicting new, un‐phenotyped environments. Integrating ECs into the RRM enhances genomic prediction by effectively capturing the GEI with a limited number of covariates.

Herbivory and Seed Banks Will Limit Regeneration and Restoration of an Endangered Subtropical Rainforest

Austral Ecology · 2025-04-01 · 1 citations

ABSTRACT Disturbances are an essential component of forest functionality and composition; however, when communities become disrupted, these disturbances may restrict the growth and productivity of species present. Illawarra subtropical rainforest (ISRF) is a threatened ecological community that is influenced by both native and exotic vertebrate herbivores and exotic plant pressures. The ability of ISRF to regenerate following the removal of large herbivores was assessed in fenced and unfenced sites within fragments of rainforest. To investigate the extent to which herbivory was limiting the restoration of ISRF, five native seedlings of each of eight species were planted at six sites, and growth and herbivore activity was compared between fenced and unfenced sites. We investigated seed bank capacity and composition to determine whether recruitment limitation is also preventing regeneration. Over 46 weeks, seedlings in unfenced sites experienced significantly lower growth, which varied amongst species and sites. High activity of feral deer and swamp wallabies caused significant reductions in seedling heights and the number of leaves. Herbivores reduced the growth of seedlings of Brachychiton acerifolius , Planchonella australis , and Breynia oblongifolia more than other species. Pittosporum multiflorum seedlings were not eaten. Only 297 seeds (10% of all seeds germinating) of 21 native species typical of ISRF communities germinated in the seed bank germination trial in the glasshouse. Most native species were missing, reflecting poor recruitment opportunities from a soil‐stored seed bank. Seed banks were dominated by 21 exotic species (2125 seedlings—74% of total), presenting a significant risk to the regeneration of the community. Our results indicated that ISRF communities are unlikely to regenerate naturally and require active planting coupled with effective protective measures from all herbivores to restore fragmented vegetation.

Composite interval mapping and genomic prediction of nut quality traits in American and American-European interspecific hybrid hazelnutss

bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-20

ABSTRACT The native, perennial shrub American hazelnut ( Corylus americana ) is cultivated in the Midwestern U.S. for its significant ecological benefits, as well as its high-value nut crop. Genetic improvement of perennial crops involves long-term breeding efforts, and benefits from the use of genetic data in selection to reduce breeding cycle time. In addition, high-throughput phenotyping methods are essential to the efficient and accurate screening of large breeding populations. This study reports novel advances in both of these domains, for American ( C. americana ) and interspecific hybrids between European ( C. avellana ) and American hazelnuts. Two populations of hazelnuts, one composed of C. americana and one composed of C. americana x C. avellana hybrids, were phenotyped over the course of two years in two locations using a digital imagery-based method for quantifying morphological nut and kernel traits. This data was used to perform composite interval mapping (CIM) using a recently released genetic map, and genomic prediction using a newly-available chromosome-scale reference genome for C. americana . Multiple QTL were detected for all traits analyzed, with an average total R 2 of 52%. Genomic prediction exhibited high accuracy, with an average correlation coefficient between genotypic values and phenotypic observations of 0.78 across both environments. These results suggest that incorporating genetic data in selection is a tenable method for improving genetic gain for highly-polygenic traits in hazelnut breeding programs. Core ideas Morphological nut characteristics are under polygenic control in American and American- European interspecific hazelnuts. Best linear unbiased predictors allow for accurate prediction of morphological nut characteristics. Marker density and training population design must be tailored to the sample population for which predictions are being made.

Combining genome‐wide association and genomic prediction to unravel the genetic architecture of carotenoid accumulation in carrot

The Plant Genome · 2025-01-30 · 6 citations

Carrots (Daucus carota L.) are a rich source of provitamin A, namely, α- and β-carotene. Breeding programs prioritize increasing β-carotene content for improved color and nutrition. Understanding the genetic basis of carotenoid accumulation is crucial for implementing genomic-assisted selection to develop high-carotenoid lines. While previous studies identified loci (Y2, Y, Or, and REC) associated with carrot color and carotenoid content, this study employed genome-wide association (GWA) in a diverse panel of 738 carrot accessions. We discovered a novel locus with a candidate gene encoding phytoene synthase, a key enzyme in carotenoid biosynthesis. The Y2, Y, Or, and REC loci are mostly fixed in orange varieties, yet considerable variation in carotenoid concentration persists. This suggests a multigenic trait influenced by the environment. GWA of carotenoid concentration identified a quantitative trait locus for total carotenoids and α-carotene. We explored the accuracy of genomic prediction (GP) models to predict carotenoid concentration. We determined the optimal number of plants and plots required for accurate carotenoid phenotyping, finding ≥5 plants per plot and three plots per site as the minimum effective sample per accession. GP models achieved accuracies ranging from 0.06 to 0.40 depending on the carotenoid measured and environment the carrots were assayed. Additional studies in breeding programs will clarify the potential of genomic-assisted selection for high-carotenoid carrots.

Bayesian joint-regression analysis of unbalanced series of on-farm trials

Peer Community Journal · 2025-01-06 · 3 citations

Participatory plant breeding (PPB) is aimed at developing varieties adapted to agroecologically-based systems. In PPB, selection is decentralized in the target environments, and relies on collaboration between farmers, farmers' organisations and researchers. By doing so, evaluation of new genotypes takes genotype x environment (GxE) interactions into account to select for specific adaptation. In many cases, there is little overlap among genotypes assessed from farm to farm because the farmers participating in a PPB project choose which ones to assess on their farm. In addition, on-farm trials can often generate more extreme observations than trials carried out on research stations. These features make the estimation of genotype, environment and interaction effects more difficult. This challenge is not unique to PPB, as many breeding programs use sparse testing or incomplete block designs to evaluate more genotypes, however in PPB genotypes are not always assigned randomly to environments. To explore methods of overcoming these challenges, this article tests various data analysis scenarios using a Bayesian approach with different models and a real wheat PPB dataset over 11 years. Four morpho-agronomic traits were studied, representing over 1000 GxE combinations from 189 on-farm trials. This dataset was severely unbalanced with more than 90% of GxE combinations missing. We compared various Bayesian Finlay-Wilkinson models and found that placing hierarchical distributions on model parameters and modelling residuals using a Student's t distribution jointly improved the estimates of main effects and interactions. Environment effects were the most important and explained more than 50% of the variance of observations. This statistical framework allowed us to estimate two indicators of genotype stability (one static and one dynamic) despite the high disequilibrium of the data. We found differences in mean and stability between genotype categories, with registred varieties consistently shorter (-30 cm) and containing less protein (-0.3%) than other types of varieties. The methods developed could be used for evaluation and/or selection within networks of various stakeholders such as farmers, gardeners, plant breeders or managers of genetic resource centres.

Influence of Organic and Conventional Management Systems on Carrot Performance and Implications for Organic Plant Breeding

Journal of the American Society for Horticultural Science · 2025-03-01 · 2 citations

In this study, 36 carrot breeding lines and cultivars widely used for organic production were grown for 4 years in two locations under organic and conventionally managed trials. Highly significant genotypic main effects and genotype × year and, to a lesser extent, genotype × location interactions were observed for all traits, including harvest root and top weight as well as top height and width measured at early season, midseason, and the time of harvest. In contrast, management systems and most management system interactions were not significant. Broad sense heritability (repeatability) for most responses was relatively high (≥0.75), suggesting a high potential for genetic gains through selection, although early-season top height and width heritability were somewhat lower. High rank correlations were found for all traits when comparing genotypes grown under organic and conventional management in both locations when evaluated across all years for each location ( P ≤ 0.001) or with few exceptions when evaluated by individual years ( P ≤ 0.05). An analysis of F1 hybrid cultivars and comparison of the performance of production systems showed no rank correlations for most traits and years. In contrast to the results observed for F1 hybrid cultivars, open-pollinated breeding lines presented more instances of correlation between management systems in given locations and years. The stability analysis provided insights into the relative stability or adaptability of 36 carrot genotypes (cultivars) across environments. Considering all traits evaluated, several open-pollinated and hybrid cultivars demonstrated consistent performance along the environmental index, whereas other cultivars and the more inbred breeding lines did not. An additive main effects and multiplicative interactions analysis did not present any clear patterns for management system or location, but it did reflect the highly significant effect of year in genotype × environment interactions. The first and second principal components explain a range of total variance from 41.8% for early top height to 55.2% for harvest top weight. The results of the current study contribute to the body of knowledge regarding genotype X management system interactions and provide insights into implications for organic crop improvement in carrot. The results further aid in understanding the influence of organic management in horticultural crops, which may differ with the results of grain crops.

Root exudation and rhizosphere microbial assembly are influenced by novel plant trait diversity in carrot genotypes

Soil Biology and Biochemistry · 2024-07-08 · 37 citations

Recent advances in characterizing the carrot genome

Acta Horticulturae · 2024-04-01

The carrot SCRI project taps into carrot diversity to develop genetic and genomic resources, evaluate nutrient bioavailability, and assess factors influencing grower and consumer decisions

Acta Horticulturae · 2024-04-01

ISHS III International Symposium on Carrot and Other Apiaceae The carrot SCRI project taps into carrot diversity to develop genetic and genomic resources, evaluate nutrient bioavailability, and assess factors influencing grower and consumer decisions