Mark Sorrells

Our research program utilizes appropriate technologies encompassing molecular genetics, physiology, pathology, and breeding to research strategies that contribute to the development of superior crop varieties. We collaborate with plant breeders and geneticists around the world including international centers on projects that involve the use of molecular markers to assess genetic relationship, construct linkage maps, and clone genes. The focus of our basic work involves comparative genomics, association mapping, allele characterization and particularly genomic selection methods. Characterization of allelic diversity and allelic value in both wild and cultivated germplasm is fundamental to crop improvement and efficient strategies are a major focus. Current research projects include mapping, cloning and characterization of candidate genes underlying QTL for preharvest sprouting resistance, milling and baking quality, kernel size and shape, mapping novel stem rust resistance genes, and nutritional quality. We also recently completed a large project on evaluating ancient and specialty grains under organic management.

Selected journal articles:

Google Scholar profile and publications.

• Taagen, E., K. Jordan, E. Akhunov, M.E. Sorrells, J-L. Jannink. 2022. If it ain't broke, don't fix it: evaluating the effect of increased recombination on response to selection for wheat breeding, G3 Genes|Genomes|Genetics, Volume 12, Issue 12, jkac291, https://doi.org/10.1093/g3journal/jkac291
• Brzozowski, L.J., H. Hu, M.T. Campbell, C.D. Broeckling, M. Caffe, L. Gutiérrez, K.P. Smith, M.E. Sorrells, M.A. Gore, J-L. Jannink. 2023. Genomic prediction of seed nutritional traits in biparental families of oat (Avena sativa). The Plant Genome. 16:e20370. https://doi.org/10.1002/tpg2.20370
• Sun, J., Rutkoski, J. E., Poland, J. A., Crossa, J., J-L Jannink,, & Sorrells, M. E. (2017). Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield. The Plant Genome.
• Yu, L., Barbier, H., Rouse, M. N., Singh, S., Singh, R. P., Bhavani, S., Huerta-Espinosa, J., & Sorrells, M. E. (2014). A consensus map for Ug99 stem rust resistance loci in wheat. Theoretical and Applied Genetics. 127:1561Ð1581.
• Rutkoski, J. E., Poland, J. A., Singh, R. P., Huerta-Espino, J., Bhavani, S., Barbier, H., Rouse, M. N., Jannink, J., & Sorrells, M. E. (2014). Genomic selection for quantitative adult plant stem rust resistance in wheat. The Plant Genome.
• Heslot, N., Akdemir, D., Sorrells, M. E., & Jannink, J. (2014). Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions. Theoretical and Applied Genetics. 127:463-480.
• Endelman, J. B., Atlin, G. N., Beyene, Y., Semagn, K., Zhang, X., Sorrells, M. E., & Jannink, J. (2014). Optimal design of preliminary yield trials with genome-wide markers. Crop Science. 54:48-59.
• Heslot, N., Jannink, J., & Sorrells, M. E. (2014). Perspectives for genomic selection applications and research in plants. Crop Science. 55:105-126.
• Isidro, J., Jannink, J., Akdemir, D., Poland, J., Heslot, N., & Sorrells, M. E. (2014). Training set optimization under population structure in genomic selection. Theoretical and Applied Genetics.
• Cavanagh, C. R., Chao, S., Wang, S., Huang, B. E., Stephen, S., Kiani, S., Forrest, K., Saintenac, C., Brown-Guedira, G. L., Akhunova, A., See, D., Bai, G., Pumphrey, M., Tomar, L., Wong, D., Kong, S., Reynolds, M., Lopez da Silva, M., Bockelman, H., Talbert, L., Anderson, J. A., Dreisigacker, S., Baenziger, S., Carter, A., Korzun, V., Morrell, P. L., Dubcovsky, J., Morrell, M. K., Sorrells, M. E., Hayden, M. J., & Akhunov, E. (2013). Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars. PNAS: Proceedings of the National Academy of Sciences of the United States of America. 110:8057-8062.
• Riedelsheimer, C., Endelman, J. B., Stange, M., Sorrells, M. E., Jannink, J., & Melchinger, A. E. (2013). Genomic Predictability of Interconnected Bi-parental Maize Populations. Genetics. 194:493-503.

Outreach and Extension Focus

We deliver information on performance of small grains varieties to the public through field days, extension publications, workshops, and web sites.

• Elected Board Representative Board Representative, Crop Science Society of America C1 Crop Breeding and Genetics (2019) Crop Science Society of America
• Named to a list of the world’s most influential scientific minds based on citations in the top 1% (2017) Reuters and Clarivate Analytics
• Ron Phillips Plant Genetics Lectureship (2017) Crop Science Society of America
• Outstanding Research Award (2016) Crop Science Society of America
• Board Representative of C7 Genomics, Molecular Genetics, and Biotechnology (2015) Crop Science Society of America

The objectives of my courses are to: i) stimulate original thought, ii) teach critical thinking and writing, iii) expose students to decisions and problems encountered in plant breeding research programs, and iv) bring together plant breeding methods and principles to form logical, innovative crop improvement programs.

• PLBR 4080: Methods of Plant Breeding Laboratory
• PLBR 7160: Perspectives in Plant Breeding Strategies