Multi-trait modeling and machine learning discover new markers associated with stem traits in alfalfa.

Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich and highly digestible portion of biomass for ruminant animals, while stems constitute a high fiber and less digestible fraction, representing 50 to 70% of the biomass. However, little attention has focused on stem-related traits, which are a key aspect in improving the nutritional value and intake potential of alfalfa. This study aimed to identify molecular markers associated with four morphological traits in a panel of five populations of alfalfa generated over two cycles of divergent selection based on 16-h and 96-h in vitro neutral detergent fiber digestibility in stems. Phenotypic traits of stem color, presence of stem pith cells, winter standability, and winter injury were modeled using univariate and multivariate spatial mixed linear models (MLM), and the predicted values were used as response variables in genome-wide association studies (GWAS). The alfalfa panel was genotyped using a 3K DArTag SNP markers for the evaluation of the genetic structure and GWAS. Principal component and population structure analyses revealed differentiations between populations selected for high- and low-digestibility. Thirteen molecular markers were significantly associated with stem traits using either univariate or multivariate MLM. Additionally, support vector machine (SVM) and random forest (RF) algorithms were implemented to determine marker importance scores for stem traits and validate the GWAS results. The top-ranked markers from SVM and RF aligned with GWAS findings for solid stem pith, winter standability, and winter injury. Additionally, SVM identified additional markers with high variable importance for solid stem pith and winter injury. Most molecular markers were located in coding regions. These markers can facilitate marker-assisted selection to expedite breeding programs to increase winter hardiness or stem palatability.

A Public Mid-Density Genotyping Platform for Hexaploid Sweetpotato (Ipomoea batatas [L.] Lam).

Small public breeding programs focused on specialty crops have many barriers to adopting technology, particularly creating and using genetic marker panels for genomic-based decisions in selection. Here, we report the creation of a DArTag panel of 3120 loci distributed across the sweetpotato (Ipomoea batatas [L.] Lam) genome for molecular-marker-assisted breeding and genomic prediction. The creation of this marker panel has the potential to bring cost-effective and rapid genotyping capabilities to sweetpotato breeding programs worldwide. The open access provided by this platform will allow the genetic datasets generated on the marker panel to be compared and joined across projects, institutions, and countries. This genotyping resource has the power to make routine genotyping a reality for any breeder of sweetpotato.

Genetic diversity, population structure, and taxonomic confirmation in annual medic (Medicago spp.) collections from Crimea, Ukraine.

Annual medic (Medicago spp.) germplasm was collected from the Crimean Peninsula of Ukraine in 2008 to fill gaps in geographic coverage in the United States department of Agriculture, Agricultural Research Service, National Plant Germplasm System (NPGS) temperate-adapted forage legume collection. A total of 102 accessions across 10 Medicago species were collected. To assess genetic diversity, population structure, and to confirm taxonomic identities, the collections were phenotypically and genetically characterized. Phenotyping included the use of 24 descriptor traits while genetic characterization was accomplished using a 3K Diversity Array Technologies (DArTag) panel developed for alfalfa (Medicago sativa L.). For both field and molecular characterizations, a reference set of 92 geographically diverse and species-representative accessions were obtained from the NPGS collection. Phenotypic descriptors showed consistency among replicated plants within accessions, some variation across accessions within species, and evident distinctions between species. Because the DArTag panel was developed for cultivated alfalfa, the transferability of markers to the species being evaluated was limited, resulting in an average of ~1,500 marker loci detected per species. From these loci, 448 markers were present in 95% of the samples. Principal component and phylogenetic analysis based on a larger set of 2,396 selected markers clustered accessions by species and predicted evolutionary relationships among species. Additionally, the markers aided in the taxonomic identity of a few accessions that were likely mislabeled. The genotyping results also showed that sampling individual plants for these mostly self-pollinating species is sufficient due to high reproducibility between single (n=3) and pooled (n=7) biological replicate leaf samples. The phenotyping and the 2,396 Single Nucleotide Polymorphism (SNP) marker set were useful in estimating population structure in the Crimean and reference accessions, highlighting novel and unique genetic diversity captured in the Crimean accessions. This research not only demonstrated the utility of the DArTag marker panel in evaluating the Crimean germplasm but also highlighted its broader application in assessing genetic resources within the Medicago genus. Furthermore, we anticipate that our findings will underscore the importance of leveraging genetic resources and advanced genotyping tools for sustainable crop improvement and biodiversity conservation in annual medic species.

Development and characterization of mutant winter wheat (Triticum aestivum L.) accessions resistant to the herbicide quizalofop.

KEY MESSAGE: New herbicide resistance traits in wheat were produced through the use of induced mutagenesis. While herbicide-resistant crops have become common in many agricultural systems, wheat has seen few introductions of herbicide resistance traits. A population of Hatcher winter wheat treated with ethyl methanesulfonate was screened with quizalofop to identify herbicide-resistant plants. Initial testing identified plants that survived multiple quizalofop applications. A series of experiments were designed to characterize this trait. In greenhouse studies the mutants exhibited high levels of quizalofop resistance compared to non-mutant wheat. Sequencing ACC1 revealed a novel missense mutation causing an alanine to valine change at position 2004 (Alopecurus myosuroides reference sequence). Plants carrying single mutations in wheat's three genomes (A, B, D) were identified. Acetyl co-enzyme A carboxylase in resistant plants was 4- to 10-fold more tolerant to quizalofop. Populations of segregating backcross progenies were developed by crossing each of the three individual mutants with wild-type wheat. Experiments conducted with these populations confirmed largely normal segregation, with each mutant allele conferring an additive level of resistance. Further tests showed that the A genome mutation conferred the greatest resistance and the B genome mutation conferred the least resistance to quizalofop. The non-transgenic herbicide resistance trait identified will enhance weed control strategies in wheat.