Developing Climate Resilient Wheat

Drought and heat stress can significantly reduce the yield of spring wheat by 40-60% compared to yield potential conditions. The research spans translational studies, modern pre-breeding methods, and genome-wide association studies to develop wheat varieties that can endure drought and heat stress. 

Key publications

• Reynolds, M.P., Lewis, J., Ammar, K., Basnet, B.R., Crespo Herrera, L.A., Crossa, J., Dhugga, K., Dreisigacker, S., Juliana, P., Karwat, H. Kishii, M., …, S. Sukumaran, et al 2021. Harnessing translational research in wheat for climate resilience. Journal of Experimental Botany,Volume 72, Issue 14, 10 July 2021, Pages 5134–5157 

• Sukumaran, S*., H. Krishna, K. Singh,Mottaleb, K., M. Reynolds. 2021. Progress and prospects for developing climate resilient wheat in South Asia using modern pre-breeding methods. Current Genomics, special issue: Genes, Genomics and Germplasm for Climate-Smart Agriculture. 

• Khodaee, S.M.M., M. Hashemi, A. Mirlohi, M.M. Majidi, S. Sukumaran, et al. 2021. Root characteristics of an elite spring wheat panel under contrasting water treatments and their genome-wide association study. Rhizosphere 19: 100413. 

• Jagadish, S.K., Pal, M., Sukumaran, S., Parani, M. and Siddique, K.H., 2020. Heat stress resilient crops for future hotter environments. Plant Physiology Reports, 1-4 

• Ramirez‐Villegas, J., Milan, A.M., Alexandrov, N., Asseng, S., Challinor, A.J., Crossa, J., van Eeuwijk, F., Ghanem, M.E., Grenier, C., Heinemann, A.B. and Wang, J., ...,Sukumaran, S. 2020. CGIAR modeling approaches for resource‐constrained scenarios: II. Accelerating crop breeding for a changing climate. Crop Science, pp1-21.

• Liu, C., S. Sukumaran*, E. Claverie, C. Sansaloni, S. Dreisigacker, M. Reynolds. 2019. Genetic dissection of heat and drought stress QTLs in a phenology controlled synthetic derived recombinant inbred lines in spring wheat. Molecular Breeding, 39(34)

• Sukumaran, S*., C. Sansaloni, M. Reynolds. 2018. Genome-wide association analyses identify QTL hotspots for yield and component traits in durum wheat grown under yield potential, drought, and heat stress environments. Frontiers in Plant Science, 9, 81. 

• Valluru, R., M. Reynolds, W. Davies, S. Sukumaran. 2017. Phenotypic and genome-wide association analysis of spike-ethylene in diverse wheat genotypes under heat stress. New Phytologist, 5 December 2016. 

• Reynolds, M., G. Molero, M. Tattaris, C.M. Cossani, P. Alderman and S. Sukumaran. 2015. Improving crop adaptation to climate change through strategic crossing of stress adaptive traits. Procedia Environmental Sciences, 29: 298-299. 

Developing High Yield Potential Wheat

High yield potential may come from optimizing trait and environmental combinations together with high yield potential germplasm. Several approaches from modelling, utilizing genetic resources, trait discovery, trait combinations, and high yielding environments are used to achieve this objective.

Key Publications

• Hu, P., Chapman, S.C., Sukumaran, S., Reynolds, M. and Zheng, B., 2022. Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environments. Journal of Experimental Botany. Volume 73, Issue 12, 24 June 2022, Pages 4236–4249. 

• Hu, P., Chapman, S.C., Dreisigacker, S., Sukumaran, S., Reynolds, M. and Zheng, B., 2021. Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments. Journal of Experimental Botany, 72(20), pp.7203-7218.

• Dreisigacker, S., J. Burgueño, A. Pacheco, G. Molero, S. Sukumaran, C. Rivera-Amado, M. Reynolds, S. Griffiths. 2021. Effect of Flowering Time-Related Genes on Biomass, Harvest Index, and Grain Yield in CIMMYT Elite Spring Bread Wheat. 2021. Biology, 10(9), 855

• Reynolds, M., A. Pask, W. Hoppitt, K. Sonder, S. Sukumaran, et al. 2017. Strategic crossing of biomass and harvest index—source and sink—achieves genetic gains in wheat. Euphytica, 214 (1).

• Sukumaran, S., M. Reynolds, M. Lopes, J. Crossa. 2015. Genome-wide association study for Adaptation to density: A component high yield potential in spring wheat. Crop Science, 55, 1-11. 

• Sukumaran, S*., M. Lopes, S. Dreisigacker, P. Chavez, M. Reynolds. 2015. Genome-wide association study for yield and related traits in an elite spring wheat population grown at temperate irrigated environments. Theoretical and Applied Genetics, 128 (2), 353-363. 

• Piñera‐Chavez, F.J., Berry, P.M., Foulkes, M.J., Sukumaran, S. and Reynolds, M.P., 2021. Identifying quantitative trait loci for lodging‐associated traits in the wheat doubled‐haploid population Avalon× Cadenza. Crop Science, 61(4), pp.2371-2386.

• Basavaraddi, P.A., Savin, R., Sukumaran, S., Reynolds, M.P., Griffiths, S. and Slafer, G.A., 2021. Genotypic differences in wheat yield determinants within a NAM population based on elite parents. European Journal of Agronomy, 123, p.126223.

• Sukumaran, S., M. Reynolds, M. Lopes, J. Crossa. 2015. Genome-wide association study for Adaptation to density: A component high yield potential in spring wheat. Crop Science, 55, 1-11. 

Complex Trait Dissection 

Complex trait dissection is the process of analyzing and identifying the genetic factors that contribute to traits influenced by multiple genes and environmental factors. The dissection involves using various genetic approaches, to pinpoint specific genomic regions associated with the trait. This process helps researchers understand the underlying genetic architecture and interactions that drive these important traits. 

Key publications

• Li, X., T. Guo, J. Wang, W. Bekele, S. Sukumaran, A. E. Vanous, J. P. McNellie, L. Cortes, M. Lopes, K. Lamkey, M. Westgate, J. McKay, S. Archontoulis, M. Reynolds, N. Tinker, P. Schnable, J. Yu. Reinstating the Environmental Dimension for Genome-Wide Association Studies and Genomic Selection for Current and Future Environments. Molecular Plant, 14(6), pp.874-887. Cell press

• Liu, C., S. Sukumaran*, D. Jarquin, J. Crossa, S. Dreisigacker, C. Sansaloni, M. Reynolds. 2020. Comparison of Array- and Sequencing-based Markers for Genome Wide Association Mapping and Genomic Prediction in Spring Wheat. Crop Science, 60, 211-225

• Sukumaran, S., W. Xiang, S. R. Bean, J. F. Pederson, S. Kresovich, M. R. Tuinstra, T. T. Tesso, M. T. Hamblin, and J. Yu. 2012. Association mapping for grain quality in diverse sorghum collection. The Plant Genome, 5:126–135.

• Wang, M.L., S. Sukumaran, N. A. Barkley, Z. Chen, C. Y. Chen, B. Z. Guo, R. N. Pittman, G. A. Pederson, and J. Yu. 2009. Population Structure and marker-trait Association analysis of the U.S. peanut (Arachis hypogea L.) mini-core collection. Theoretical and Applied Genetics, 102:13-23. 

• Liu, C., Guo, W., Zhang, Q., Fu, B., Yang, Z., Sukumaran, S., Cai, J., Liu, Y., Zhai, W., Wu, X. and Wu, J., 2020. Genetic Dissection of Adult Plant Resistance to Sharp Eyespot Using an Updated Genetic Map of Niavt14× Xuzhou25 Winter Wheat Recombinant Inbred Line Population. Plant Disease, 105(4) pp.997-1005.

• Lozada, D., E. Mason, S. Sukumaran, S. Dreisigacker. 2018. Validation of grain yield QTL from soft winter wheat using a CIMMYT spring wheat panel. Crop Science, 58 (5): 1964-1971. 

• Sukumaran, S*., M. Lopes, S. Dreisigacker, M. Zhikali, L. Dixon, S. Griffiths, B. Zheng, S. Chapman, M. Reynolds. 2016. Validation of earliness per se flowering time locus in spring wheat through a genome-wide association study. Crop Science, 56 (6): 2962-2672. 

• Sukumaran, S*., M. Lopes, S. Dreisigacker, M. Reynolds. 2018. Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus specific trade-offs for grain weight and grain number. Theoretical and Applied Genetics, 1-14. 

• Lopes, M.S., S. Dreisigacker, R.J. Pena, S. Sukumaran, M. Reynolds. 2015. Genetic characterization of a wheat association mapping initiative (WAMI) panel for dissection of complex traits in spring wheat. Theoretical and Applied Genetics, 128 (3), 453-464. 

• Liu, C., Khodaee, M., Lopes, M.S., Sansaloni, C., Dreisigacker, S., Sukumaran, S*. and Reynolds, M., 2019. Multi-environment QTL analysis using an updated genetic map of a widely distributed Seri× Babax spring wheat population. Molecular Breeding, 39(9), p.134. doi:10.1007/s11032-019-1040-1

• Sukumaran, S., X. Li, Xin Li, C. Zhu, G. Bai, R. Perumal, M.R. Tuinstra, P.V.V. Prasad, S.E. Mitchell, T.T. Tesso, J. Yu. 2016. QTL mapping for grain yield, flowering time, and stay-green traits in sorghum with genotyping-by-sequencing markers. Crop science, 56(4), pp.1429-1442. 

Genomic Prediction

Genomic prediction, also known as genomic selection, is a method used in plant and animal breeding to predict the genetic value of an individual based on its DNA profile. This approach utilizes a model built from data on thousands of genetic markers spread across the genome and the known performance of related individuals. By applying this model, breeders can estimate the breeding value of individuals without the need for extensive phenotypic testing, allowing for more efficient selection of individuals with desirable traits. Genomic prediction is particularly valuable for accelerating the breeding of complex traits that are difficult or time-consuming to measure. 

Key publications

• Sukumaran, S., D. Jarquin, J. Crossa, M. Reynolds. 2018. Genomic enabled prediction accuracies increased by incorporating genotype by environment interaction in durum wheat. The Plant Genome, July:11(2). 

• Sukumaran, S., J. Crossa, D. Jarquin, M. Reynolds. 2017. Pedigree based prediction of grain yield by modelling genotype by environment interactions in multi-environment trials of CIMMYT wheat nurseries. Crop Science, 57 (4), 1-16. 

• Sukumaran, S., J. Crossa, D. Jarquin, M. Lopes, M. Reynolds. 2017. Genomic Prediction with Pedigree and Genotype × Environment Interaction in Spring Wheat Grown in Soutand West Asia, North Africa, and Mexico. G3:Genes, Genomes, Genetics, 7 (2), 481-495. 

Genomics

Key collabative publications

• He, F., Wang, W., Rutter, W.B., Jordan, K.W., Ren, J., Taagen, E., DeWitt, N., Sehgal, D., Sukumaran, S., Dreisigacker, S. and Reynolds, M., 2022. Genomic variants affecting homoeologous gene expression dosage contribute to agronomic trait variation in allopolyploid wheat. Nature communications, 13(1), pp.1-15.

• Hussain, B., Akpınar, B.A., Alaux, M., Algharib, A.M., Sehgal, D., Ali, Z., Aradottir, G.I., Batley, J., Bellec, A., Bentley, A.R. and Cagirici, H.B., Sukumaran, S., …, H., Budak. 2022. Capturing Wheat Phenotypes at the Genome Level. Frontiers in Plant Science, 13.