Use of historical data improves early selection in a public rice breeding program

Crop Science · 2025-11-01

Abstract Increasing selection accuracy for parental lines in the early stages of a breeding program can significantly shorten the breeding cycle and accelerate genetic gain. Public breeding programs have limited resources, which in many cases implies not having enough funds for genomic selection. In this study, we propose a strategy that allows leveraging a data source that is often overlooked: the breeding program's historical data. We evaluated the impact of incorporating historical data through multi‐environment analysis for selection at early stages of evaluation in a public breeding program. Two distinct breeding goals were assessed: line advancement and parent selection. For the first objective we used available phenotypic data, and for the second objective we leveraged existing pedigree records in addition to the phenotypic data. The evaluation strategy employed replicated the breeding program's structure, accounting for the timing of data availability. We investigated five prediction strategies, starting from single trial analysis, incorporating one or 5 years of historical data, and including or not a genotype by environment interaction term. To compare the prediction strategies, we considered grain yield phenotypic variance partition and predictive ability. Joint analysis of multiple trials and environments led to more accurate estimations of variance components and higher predictive ability for early selection of parents and line advancement. Additionally, we found that modeling genotype by environment interaction did not consistently enhance predictive ability. This study highlights the benefits of joint analyses of multi‐environment trials for early selection of parents and lines in breeding programs.

Implementing marker covariates and multi‐trait genomic selection models to improve grain milling, appearance, cooking, and edible quality in rice ( <i>Oryza sativa</i> L.)

The Plant Genome · 2025-07-13 · 2 citations

Rice (Oryza sativa L.) is a staple food for over half of the world's population. With population growth, socioeconomic changes, and shifting consumer lifestyles, the demand for high-quality rice has surged. Understanding consumer preferences for rice quality traits is crucial for breeders to effectively address evolving market needs. Rice breeding programs assess various quality aspects, including grain shape, appearance, milling efficiency, and cooking and eating qualities. Molecular-based approaches like marker-assisted selection and genomic selection (GS) offer promising opportunities to enhance breeding efficiency. In this study, our goal was to build upon our previous findings and improve the predictive ability of GS for primary grain milling and cooking and eating quality traits by incorporating trait marker covariates and highly heritable, high-throughput secondary traits in multi-trait genomic selection strategies (MT-GS). By including amylose content and gelatinization temperature functional markers as covariates in GS models, we improved the predictive ability for primary cooking and eating traits from 21% to 44%. Additionally, integrating secondary traits into MT-GS increased the predictive ability for milling quality traits from 13.5% to 18% and for cooking and eating traits from 4.6% to 50%. Overall, our study demonstrates the feasibility of incorporating whole-genome markers, trait markers, and secondary trait information to enhance the predictive ability of GS for grain milling, cooking, and eating qualities in rice.

Oregon Wolfe barley genetic stocks – Research and teaching tools for next generation scientists

Journal of Plant Registrations · 2025-09-01

Abstract The Oregon Wolfe Barley (OWB) mapping population (Reg. no. MP‐4, NSL 554937 MAP) is a resource for genetics research and instruction. The OWBs are a set of doubled haploid barley ( Hordeum vulgare L.) lines developed at Oregon State University from the F 1 of a cross between Dr. Robert Wolfe's dominant and recessive marker stocks. Exhibiting a high level of genetic and phenotypic diversity, the OWBs are used throughout the world as a research tool for barley genetics. To date, these endeavors have led to 56 peer‐reviewed publications, as well as three reports in the Barley Genetics Newsletter. At the same time, the OWBs are widely used as an instructor resource at the K–12, undergraduate, graduate, and professional levels. They are currently used at universities and/or institutes in German, Italy, Norway, Spain, and the United States and are currently being developed further for educational use in other countries. Genotype and phenotype data, lesson plans, and seed availability information are available herein and online.

Global genomic population structure of wild and cultivated oat reveals signatures of chromosome rearrangements

Nature Communications · 2025-10-29 · 4 citations

The genus Avena consists of approximately 30 wild and cultivated oat species. Cultivated oat is an important food crop, yet the broader genetic diversity within the Avena gene pool remains underexplored and underexploited. Here, we characterize over 9000 wild and cultivated hexaploid oat accessions of global origin using genotyping-by-sequencing and explore population structure using multidimensional scaling and population-based clustering methods. We also conduct analyses to reveal chromosome regions associated with local adaptation, sometimes resulting from large-scale chromosome rearrangements. We report four distinct genetic populations within the wild species A. sterilis, a distinct population of cultivated A. byzantina, and multiple populations within cultivated A. sativa. Some chromosome regions associated with local adaptation are also associated with confirmed structural rearrangements on chromosomes 1A, 1C, 3C, 4C, and 7D. This work provides evidence suggesting multiple polyploid origins, multiple domestications, and/or reproductive barriers amongst Avena populations caused by differential chromosome structure.

Evaluation of strategies for early selection using historical data in a public rice breeding program

2025-11-19

Increasing selection accuracy for parental lines in the early stages of a breeding program can significantly shorten the breeding cycle and accelerate genetic gain. In this study, we evaluated the impact of incorporating historical data through multi-environment analysis for selection at the early stages of evaluation in a public breeding program. The evaluation strategy employed replicates the breeding program's structure, accounting for the timing of phenotypic data availability. We investigated five prediction strategies starting from single trial analysis, incorporation of one or 5-year historical data, varying levels of connectivity between lines, and the inclusion or exclusion of a genotype by environment interaction term. To compare the prediction strategies, we considered grain yield phenotypic variance partition and predictive ability. Joint analysis of multiple trials and environments led to more accurate estimations of variance components and higher predictive ability for early selection of parents and line advancement. Additionally, we found that modelling genotype by environment interaction did not consistently enhance predictive ability. This study highlights the benefits of joint analyses of multi-environment trials for early selection of parents and lines in breeding programs.

Assessment of Efficiency of Breeding Methods in Accelerating Genetic Gain in Rice

Agronomy · 2024-03-12 · 5 citations

The pedigree, bulk, and single-seed descent-based rapid generation advance methods are commonly practiced breeding methods in rice. But the efficiency of these breeding methods in enhancing genetic gain has not been investigated yet. In this study, we compared the pedigree and bulk method-derived breeding lines of five crosses with RGA-derived lines. The RGA method was found to be almost two times more efficient in capturing high-yielding lines with a high breeding value and thus accelerated genetic gain much more than the bulk and pedigree methods. The RGA method is not only more efficient but also significantly cheaper (~24%) compared to pedigree methods. The cost per kilogram of genetic gain in yield for the RGA lines is almost 3 times lower than the bulk method and 4.5 times lower than the pedigree method, and it can be achieved in half the time required for line development with either the bulk or pedigree method.

Global genomic population structure of wild and cultivated oat reveals signatures of chromosome rearrangements

Research Square · 2024-12-31 · 1 citations

Registration of ‘FL12034‐10’ oat: A new dual‐purpose disease resistant cultivar for Florida and southern United States

Journal of Plant Registrations · 2024-04-01 · 1 citations

Abstract ‘FL12034‐10’ (Reg. no. CV‐389, PI 704483), a facultative oat ( Avena sativa L.) cultivar, co‐developed by the University of Florida and Louisiana State University Agricultural Center, was released in October 2022. FL12034‐10 was derived from a three‐way cross LA06055SBSBSB‐79/FL11048 F 1 . It is well adapted across the southern United States and provides producers with a medium‐tall, mid‐season, awnless, white‐glumed, dual‐purpose oat that has high yield potential, good straw strength, and good forage yield. FL12034‐10 was observed to be uniform and stable across environments in the southern United States from 2017 to present. The line possesses a semi‐prostrate growth habit, vigorous growth, and high tillering capacity, and has large leaves that are dark green in color. It expresses moderate‐to‐high levels of resistance to most oat diseases prevalent in the southern United States. The crown and stem rust and Barley yellow dwarf virus ratings (0–9 scale) of FL12034‐10 were 1.7, 0.7, and 1.5, respectively, across different environments. The disease ratings were better than most of the checks. The grain yield average of FL12034‐10 from 41 environments during 2018–2021 was 6437 kg ha −1 , which is competitive with check cultivars that are widely used in the southern part of the United States. The forage yield of FL12034‐10 ranged from 2358 to 6617 kg ha −1 (20 environments), which was higher than most of the checks. FL12034‐10 demonstrated better lodging and disease resistance, higher grain yield potential, and higher mid‐winter to late spring season forage yield potential than Horizon 720 and Legend 567 oats released by University of Florida.

Implementing multi‐trait genomic selection to improve grain milling quality in oats ( <i>Avena sativa</i> L.)

The Plant Genome · 2024-05-19 · 10 citations

Oats (Avena sativa L.) provide unique nutritional benefits and contribute to sustainable agricultural systems. Breeding high-value oat varieties that meet milling industry standards is crucial for satisfying the demand for oat-based food products. Test weight, thins, and groat percentage are primary traits that define oat milling quality and the final price of food-grade oats. Conventional selection for milling quality is costly and burdensome. Multi-trait genomic selection (MTGS) combines information from genome-wide markers and secondary traits genetically correlated with primary traits to predict breeding values of primary traits on candidate breeding lines. MTGS can improve prediction accuracy and significantly accelerate the rate of genetic gain. In this study, we evaluated different MTGS models that used morphometric grain traits to improve prediction accuracy for primary grain quality traits within the constraints of a breeding program. We evaluated 558 breeding lines from the University of Illinois Oat Breeding Program across 2 years for primary milling traits, test weight, thins, and groat percentage, and secondary grain morphometric traits derived from kernel and groat images. Kernel morphometric traits were genetically correlated with test weight and thins percentage but were uncorrelated with groat percentage. For test weight and thins percentage, the MTGS model that included the kernel morphometric traits in both training and candidate sets outperformed single-trait models by 52% and 59%, respectively. In contrast, MTGS models for groat percentage were not significantly better than the single-trait model. We found that incorporating kernel morphometric traits can improve the genomic selection for test weight and thins percentage.

Convergence of autism proteins at the cilium

bioRxiv (Cold Spring Harbor Laboratory) · 2024-12-05 · 16 citations

Hundreds of high-confidence autism genes have been identified, yet the relevant etiological mechanisms remain unclear. Gene ontology analyses have repeatedly identified enrichment of proteins with annotated functions in gene expression regulation and neuronal communication. However, proteins are often pleiotropic and these annotations are inherently incomplete. Our recent autism functional genetics work has suggested that these genes may share a common mechanism at the cilium, a membrane-bound organelle critical for neurogenesis, brain patterning, and neuronal activity-all processes strongly implicated in autism. Moreover, autism commonly co-occurs with conditions that are known to involve ciliary-related pathologies, including congenital heart disease, hydrocephalus, and blindness. However, the role of autism genes at the cilium has not been systematically investigated. Here we demonstrate that autism proteins spanning disparate functional annotations converge in expression, localization, and function at cilia, and that patients with pathogenic variants in these genes have cilia-related co-occurring conditions and biomarkers of disrupted ciliary function. This degree of convergence among genes spanning diverse functional annotations strongly suggests that cilia are relevant to autism, as well as to commonly co-occurring conditions, and that this organelle should be explored further for therapeutic potential.