Multi-trait modeling and machine learning discover new markers associated with stem traits in alfalfa DOI Open Access
Cesar Augusto Medina, D. Jo Heuschele, Dongyan Zhao

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 5, 2024

Abstract Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich highly digestible portion of for ruminant animals, while stems constitute high fiber less fraction, representing 50 to 70% the biomass. However, little attention has focused on stem-related traits, which are key aspect in improving nutritional value intake potential alfalfa. This study aimed identify molecular markers associated with four morphological traits panel five populations alfalfa generated over two cycles divergent selection based 16-h 96-h vitro neutral detergent digestibility stems. Phenotypic color, presence pith cells, winter standability, injury were modeled using univariate multivariate spatial mixed linear models (MLM), predicted values used as response variables genome-wide association studies (GWAS). The was genotyped 3K DArTag SNP evaluation genetic structure GWAS. Principal component population analyses revealed differentiations between selected high- low-digestibility. Thirteen significantly either or MLM. Additionally, support vector machine (SVM) random forest (RF) algorithms implemented determine marker importance scores validate GWAS results. top-ranked from SVM RF aligned findings solid pith, injury. identified additional variable Most located coding regions. These facilitate marker-assisted expedite breeding programs increase hardiness palatability. Author Summary constitutes significant forage yield, accounting influences various including plant height, digestibility. In our study, we thirteen parenchyma, populations. Multivariate trait modeling enhances correlation among thereby expanding number via Similarly, learning confidence initially by uncover new candidate regions that could serve markers. Genes harboring play roles growth, injury, tolerance cold, underscoring their utility enhancing such cold quality

Language: Английский

Genome-Wide Association and Genomic Prediction of Alfalfa (Medicago sativa L.) Biomass Yield Under Drought Stress DOI Open Access
Cesar Augusto Medina, Julie Hansen,

Jamie Crawford

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(2), P. 608 - 608

Published: Jan. 13, 2025

Developing drought-resistant alfalfa (Medicago sativa L.) that maintains high biomass yield is a key breeding goal to enhance productivity in water-limited areas. In this study, 424 families were analyzed identify molecular markers associated with under drought stress and predict high-merit plants. Biomass was measured from 18 harvests 2020 2023 field trial deficit irrigation. A total of 131 significant yield, 80 specifically linked stress; among these, 19 multiple harvests. Finally, genomic best linear unbiased prediction (GBLUP) employed obtain predictive accuracies (PAs) estimated values (GEBVs). Removing low-informative SNPs [SNPs p-values > 0.05 the additive Genome-Wide Association (GWAS) model] for GBLUP increased PA by 47.3%. The number highest (0.9) represent achievement improving alfalfa.

Language: Английский

Citations

1
Targeted genotyping‐by‐sequencing of potato and data analysis with R/polyBreedR DOI Creative Commons
Jeffrey B. Endelman, Moctar Kante, Hannele Lindqvist‐Kreuze

et al.

The Plant Genome, Journal Year: 2024, Volume and Issue: 17(3)

Published: June 17, 2024

Abstract Mid‐density targeted genotyping‐by‐sequencing (GBS) combines trait‐specific markers with thousands of genomic at an attractive price for linkage mapping and selection. A 2.5K GBS assay potato ( Solanum tuberosum L.) was developed using the DArTag technology later expanded to 4K targets. Genomic were selected from Infinium single nucleotide polymorphism (SNP) array maximize genome coverage rates. The SNP platforms produced equivalent dendrograms in a test set 298 tetraploid samples, 83% common showed good quantitative agreement, RMSE (root mean squared error) <0.5. is suited selection candidates clonal evaluation trial, coupled imputation higher density platform training population. Using software polyBreedR, R package manipulation analysis polyploid marker data, by 0.15 small half‐diallel population (N = 85), which significantly lower than 0.42 random forest method. Regarding high‐value traits, resistance virus Y, golden cyst nematode, wart appeared track their targets successfully, as did multi‐allelic maturity tuber shape. In summary, transformative publicly available breeding genetics.

Language: Английский

Citations

5
Pre-breeding in alfalfa germplasm develops highly differentiated populations, as revealed by genome-wide microhaplotype markers DOI Creative Commons
Cesar Augusto Medina, Dongyan Zhao, Meng Lin

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 8, 2025

Language: Английский

Citations

0
Molecular markers enhance substantially the distinctness of alfalfa varieties for registration and protection DOI Creative Commons
Paolo Annicchiarico,

Nicolò Franguelli,

Barbara Ferrari

et al.

The Plant Genome, Journal Year: 2025, Volume and Issue: 18(1)

Published: Feb. 5, 2025

Abstract Plant varieties must satisfy distinctness, uniformity, and stability (DUS) requirements for registration. Morphophysiological trait‐based distinctness may be challenging cultivars of major perennial forages. Our study focused on alfalfa ( Medicago sativa L. subsp. ) with the aims (a) comparing morphophysiological molecular based genotyping‐by‐sequencing (GBS) or DArTag panel, envisaging different statistical criteria (b) assessing consistency cultivar diversity. The 18 most grown Italian were jointly reevaluated morphophysiologically characterized molecularly using three bulked DNA samples 200 independent genotypes per cultivar. was limited by correlations between traits resulted in 39 non‐distinct 153 paired comparisons distinct from any other. Best configurations featured about 10‐fold more polymorphic markers lower average read depth marker GBS compared to DArTag. allowed somewhat better variety distinction than GBS. They reduced 11 increased completely cultivars, a principal components analysis allele frequencies followed analyses variance component scores. This criterion achieved greater cluster bootstrap values, discriminant analysis, variance. Morphophysiologically generally molecularly, but not reverse. Mantel's test revealed modest across r = 0.39) GBS‐based 0.46) measures Euclidean distance. results other considerations strongly encourage adoption DUS.

Language: Английский

Citations

0
Targeted genotyping-by-sequencing of potato and data analysis with R/polyBreedR DOI Creative Commons
Jeffrey B. Endelman, Moctar Kante, Hannele Lindqvist‐Kreuze

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 14, 2024

ABSTRACT Mid-density targeted genotyping-by-sequencing (GBS) combines trait-specific markers with thousands of genomic at an attractive price for linkage mapping and selection. A 2.5K GBS assay potato was developed using the DArTag TM technology later expanded to 4K targets. Genomic were selected from Infinium SNP array maximize genome coverage polymorphism rates. The platforms produced equivalent dendrograms in a test set 298 tetraploid samples, 83% common showed good quantitative agreement, RMSE (root-mean-squared-error) less than 0.5. is suited selection candidates clonal evaluation trial, coupled imputation higher density platform training population. Using software polyBreedR, R package manipulation analysis polyploid marker data, by 0.15 small half-diallel population (N=85), which significantly lower 0.42 Random Forest method. Regarding high-value traits, resistance virus Y, golden cyst nematode, wart appeared track their targets successfully, as did multi-allelic maturity tuber shape. In summary, transformative publicly available breeding genetics. Core Ideas mid-density, potato. includes wart. polyBreedR has functions manipulating imputing data Variant Call Format. Linkage Analysis more accurate method when 2K 10K markers.

Language: Английский

Citations

3
Systems management strategies for increasing alfalfa use in warm‐humid regions DOI Creative Commons
Jennifer J Tucker, Mary K Mullenix, Esteban F. Rios

et al.

Grassland Research, Journal Year: 2024, Volume and Issue: 3(2), P. 187 - 198

Published: May 16, 2024

Abstract Alfalfa use ( Medicago sativa L.; “lucerne”) in warm, humid regions of the world represents a potential area expansion for alfalfa industry. The objective this review paper is to demonstrate how forage breeding and systems research efforts have identified opportunities increasing contributions these regions, along with pathways seed industry farming operations increase adoption. Our draws primarily on reports from Southeast United States Argentina. Significant technological advancements plant screening selection populations that are more adapted growing conditions experienced which often characterized by mild temperature, long seasons, multiple other abiotic biotic stressors. Management conducted Argentina has demonstrated conserved forage, grazing, or dual‐purpose monoculture mixtures warm‐season grasses such as bermudagrass Cynodon spp.). These trials report increased production, nutritive value, ecosystem services alfalfa–grass when compared traditionally N‐fertilized grass‐based systems. Grazing‐based methods utilizing part beef, dairy, finishing Some approaches expanding production region include targeted marketing varieties demonstrating applications within existing frameworks. This includes educational programming on‐farm demonstrations promote component livestock diets, integration into systems, crop rotations, wildlife use. Continued emphasis approach inclusion an opportunity improved world.

Language: Английский

Citations

2
Multi-trait modeling and machine learning discover new markers associated with stem traits in alfalfa DOI Creative Commons
Cesar Augusto Medina, D. Jo Heuschele, Dongyan Zhao

et al.

Frontiers in Plant Science, Journal Year: 2024, Volume and Issue: 15

Published: Sept. 9, 2024

Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich highly digestible portion of for ruminant animals, while stems constitute high fiber less fraction, representing 50 to 70% the biomass. However, little attention has focused on stem-related traits, which are key aspect in improving nutritional value intake potential alfalfa. This study aimed identify molecular markers associated with four morphological traits panel five populations alfalfa generated over two cycles divergent selection based 16-h 96-h

Language: Английский

Citations

2
Optimization of high‐throughput marker systems for genomic prediction in alfalfa family bulks DOI Creative Commons

Pablo Sipowicz,

Mário Henrique Murad Leite Andrade, Cláudio Carlos Fernandes Filho

et al.

The Plant Genome, Journal Year: 2024, Volume and Issue: 18(1)

Published: Dec. 5, 2024

Abstract Alfalfa ( Medicago sativa L.) is a perennial forage legume esteemed for its exceptional quality and dry matter yield (DMY); however, alfalfa has historically exhibited low genetic gain DMY. Advances in genotyping platforms paved the way cost‐effective application of genomic prediction family bulks. In this context, optimization marker density holds potential to reallocate resources within pipelines. This study aimed (i) test two population structure discrimination predictive ability (PA) models (G‐BLUP) DMY, (ii) explore optimal levels predict DMY For this, 160 nondormant families were phenotyped across 11 harvests genotyped via targeted sequencing using Capture‐seq with 17K probes DArTag 3K panel. Both discriminated similarly against resulted comparable PA optimization, different randomly extracted from each platform. both cases, plateau was achieved around 500 markers, yielding similar as full set markers. phenotyping markers built data five compared Altogether, efforts optimized terms number harvests. yielded results have flexibility adjust their panels meet breeders’ needs density.

Language: Английский

Citations

2
A public mid-density genotyping platform for cultivated blueberry (Vaccinium spp.) DOI Creative Commons
Dongyan Zhao, Manoj Sapkota, Jeffrey Glaubitz

et al.

Genetic Resources, Journal Year: 2024, Volume and Issue: 5(9), P. 36 - 44

Published: April 11, 2024

Small public breeding programmes 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 3,000 loci distributed across tetraploid genome blueberry (Vaccinium corymbosum) use molecular genomic prediction. The this brings cost-effective rapid genotyping capabilities private programmes. open access provided by platform will allow data sets generated on be compared joined projects, institutions countries. This resource has power make routine reality any breeder blueberry.

Language: Английский

Citations

1
Pre-breeding in alfalfa germplasm develops highly differentiated populations, as revealed by genome-wide microhaplotype markers DOI
Cesar Augusto Medina, Dongyan Zhao, Meng Lin

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: April 30, 2024

Abstract Plant genebanks contain large numbers of accessions that likely harbor useful alleles or genes absent in commercial plant breeding programs. Broadening the genetic base alfalfa germplasm with these variations can be accomplished by screening extensive diversity collections and enabling maximal recombination among selected genotypes. In this study we surveyed differentiation pools northern US latitudes (USDA Hardiness Zone seven less) originating from Eurasian germplasm. The evaluated here included four BASE populations (C0) different geographical origins (CASIA, EURO, OTTM, SYBR), 20 cycle-one (C1) generated each five locations USA Canada, cultivars. A panel 3,000 SNP Diversity Array Technologies (DArTag) markers harboring ~ 12,000 microhaplotypes were used to quantify population structure. Principal Component Analysis Discriminant Components identified substantial structure based on their origin, while check cultivars formed a central cluster. Inbreeding coefficients (FIS) ranged − 0.1 0.006, 27 out 28 had negative FIS values, indicating an excess heterozygotes. Interpopulation distances calculated using Rho analysis molecular variance (AMOVA) parameters. Pairwise values 0.007 0.336. All lowest compared C1 AMOVA found high individuals within low between populations. Variation was highest at 10.6% 7.3% total variation, respectively. This shows have gene diversity, interpopulation distances, minimal inbreeding which is required for base-broadening selection.

Language: Английский

Citations

1