Biology subjects

Guttieri, M.

Publications and source records attributed to Guttieri, M..

3 recordsLinked to original sources

bioRxiv2026

Mapping of Stripe Rust and Leaf Rust Resistance Genes in the Hard Red Winter Wheat Population Green Hammer/Lonerider

Stripe rust and leaf rust, caused by Puccinia striiformis f. sp. tritici and P. triticina, respectively, are the most destructive wheat diseases in the southern Great Plains. Green Hammer is a hard red winter wheat (HRWW) cultivar released by Oklahoma State University in 2018 and has demonstrated a stable adult plant resistance to stripe rust and race-specific seedling resistance to leaf rust. To identify and map rust resistance loci, 109 doubled haploid (DH) lines derived from the cross between Green Hammer and another HRWW cultivar, Lonerider, were developed. Lonerider showed adult plant resistance to stripe rust but was susceptible to multiple P. triticina races. The DH lines were evaluated for stripe rust at the adult plant stage in greenhouse and field environments across Oklahoma, Kansas, and Washington, and for leaf rust at the seedling stage against seven U.S. P. triticina races and at the adult plant stage in Oklahoma and Texas. Genotyping-by-sequencing generated 6,078 polymorphic single-nucleotide polymorphisms used for genetic mapping. Quantitative trait loci (QTL) analysis identified 14 stripe rust and 8 leaf rust resistance QTL. For stripe rust, a major QTL in Green Hammer, QYr.osughln-2AS, was identified in the proximity of the 2NvS translocation. Three other major stripe rust resistance QTL were identified in Lonerider on chromosomes 2AL (two QTL) and 2BS (one QTL). For leaf rust, QLr.osughln-1DS and QLr.osughln-2DS.1 were the two major QTL identified in Green Hammer and most likely correspond to the all-stage resistance genes Lr21 and Lr39, respectively. In this study, we identified previously characterized genes as well as unknown genes that can be utilized in wheat breeding programs to enhance resistance to leaf rust and stripe rust.

genetics↗

bioRxiv2025

Identification of stripe rust adult plant resistance genes in the hard winter wheat cultivar Bakers Ann

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is among the most destructive wheat diseases. Identifying resistance genes is crucial for the development of resistant cultivars. "Bakers Ann", a hard winter wheat cultivar developed by Oklahoma State University, has shown durable adult plant resistance to stripe rust. To dissect the genetic basis underlying stripe rust resistance in Bakers Ann, 125 doubled haploid lines, derived from the cross OK12D22004-016 x Bakers Ann, were evaluated at the adult plant stage in the greenhouse and in field environments in Oklahoma, Kansas, and Washington. This population was genotyped using genotyping-by-sequencing, which produced 7,268 single-nucleotide polymorphisms for genetic mapping. Quantitative trait loci (QTL) analysis identified six loci, four from Bakers Ann on chromosomes 2DL, 4BS, 4BL, and 7BL, and two from OK12D22004-016 on chromosomes 2AS and 2AL. Although OK12D22004-016 is susceptible in the US Great Plains, it was found to carry QYr.osu-2AS, which was linked to Yr17 on the 2NvS translocation and explained up to 30% of the phenotypic variation, but was effective in a single location in Washington. Two major QTL were identified in Bakers Ann, QYr.osu-2DL on chromosome 2DL that explained up to 57% of the phenotypic variation and mapped close to Yr54, and QYr.osu-4BL on chromosome 4BL that explained up to 15% of the phenotypic variation and mapped close to Yr62. Resistance in Bakers Ann resulted from additive effects of the four QTL. Two kompetitive allele-specific PCR markers were developed for QYr.osu-2DL to facilitate marker-assisted selection for stripe rust resistance.

genetics↗

bioRxiv2021

Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

genomics↗