Mark E. Sorrells

Genome-wide association analysis of resistance to scald in an adapted multiparent winter malting barley population

This study identifies genetic factors controlling scald resistance in winter malting barley using GWAS and finds that Rrs1 contributes 29% of the variation, with other QTLs and agronomic traits also influencing resistance.

Environmentally-mediated yield effects of vernalization and photoperiod alleles in historic winter wheat trials

The paper analyzes historic wheat trials to show how vrn1 and Ppd1 alleles affect yield through environmental interactions, finding that vrn1 effects are more variable than Ppd1 effects.

Whole-Genome Sequencing of the Wild Barley Diversity Collection: A Resource for Identifying and Exploiting Genetic Variation for Cultivated Barley Improvement

The paper sequenced wild barley to identify genetic markers linked to agronomic traits and found novel loci for stem rust resistance and days to heading.

Generalizable approaches for genomic prediction of metabolites in plants

The paper develops genomic prediction methods for plant metabolites using metabolite GWAS and kernel models, improving accuracy for LC-MS metabolites but not GC-MS.

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

The paper develops a wheat haplotype graph database for efficient genotype storage and imputation, showing improved accuracy over existing methods.

Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations

This study evaluates multi-omics prediction models for oat traits across environments and populations, showing improved accuracy over genomic prediction with SNP data.

Aerial High-Throughput Phenotyping Enabling Indirect Selection for Grain Yield at the Early-generation Seed-limited Stages in Breeding Programs

This study evaluates aerial high-throughput phenotyping for indirect selection of grain yield in wheat breeding programs, finding vegetation indices predictive of yield and more effective than visual selection.

Translating insights from the seed metabolome into improved prediction for healthful compounds in oat

This study uses metabolomics and genomic approaches to improve prediction of healthful compounds in oat seeds by identifying latent factors associated with lipid metabolism.

Heritable temporal gene expression patterns correlate with metabolomic seed content in developing hexaploid oat seed

This study identifies heritable temporal gene expression patterns in oat seeds and links them to metabolomic seed content, providing insights for breeding improved oat varieties.

Multivariate Genome-wide Association Analyses Reveal the Genetic Basis of Seed Fatty Acid Composition in Oat (Avena sativa L.)

The paper identifies genetic loci associated with seed fatty acid composition in oat using multivariate GWAS approaches, finding more significant SNPs than univariate analyses.

Use of Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat

This study uses hyperspectral reflectance-derived relationship matrices in genomic selection to predict grain yield in wheat, showing improved accuracy when combined with marker and pedigree data.

A subfunctionalization epistasis model to evaluate homeologous gene interactions in allopolyploid wheat

The paper develops a subfunctionalization epistasis model to assess homeologous gene interactions in allopolyploid wheat and evaluates their contribution to genetic variation.

A low resolution epistasis mapping approach to identify chromosome arm interactions in allohexaploid wheat

The paper introduces a low-resolution epistasis mapping method to detect chromosome arm interactions in allohexaploid wheat, finding significant epistatic interactions for 2% of tested pairs.

Prediction of subgenome additive and interaction effects in allohexaploid wheat

The paper presents a statistical framework to predict subgenome additive and interaction effects in allohexaploid wheat, showing reliable variance estimation and comparable predictive ability to existing methods.