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ARS Home » Northeast Area » Ithaca, New York » Robert W. Holley Center for Agriculture & Health » Plant, Soil and Nutrition Research » Research » Publications at this Location » Publication #358243

Research Project: Improving Crop Efficiency Using Genomic Diversity and Computational Modeling

Location: Plant, Soil and Nutrition Research

Title: Leveraging mutational burden for complex trait prediction in sorghum

Author
item Valluru, Ravi - Cornell University - New York
item Gazave, Elodie - Cornell University - New York
item Fernandes, Samuel - University Of Illinois
item Ferguson, John - University Of Illinois
item Lozano, Roberto - Cornell University - New York
item Hirannaiah, Pradeep - University Of Illinois
item Zuo, Tao - Cornell University - New York
item Brown, Patrick - University Of California, Davis
item Leakey, Andrew - University Of Illinois
item Gore, Michael - Cornell University - New York
item Buckler, Edward - Ed
item Bandillo, Nonoy - Cornell University - New York

Submitted to: bioRxiv
Publication Type: Review Article
Publication Acceptance Date: 6/27/2018
Publication Date: 6/27/2018
Citation: Valluru, R., Gazave, E.E., Fernandes, S.B., Ferguson, J.N., Lozano, R., Hirannaiah, P., Zuo, T., Brown, P.J., Leakey, A.D., Gore, M., Buckler IV, E.S., Bandillo, N. 2018. Leveraging mutational burden for complex trait prediction in sorghum. bioRxiv. https://doi.org/10.1101/357418.
DOI: https://doi.org/10.1101/357418

Interpretive Summary: Plants normally accumulate new mutations in the genome. Although majority of them have no effect on the plant fitness, some are bad mutations affecting plant growth and yield. We identified bad mutations in sorghum genome and estimated their negative effects on several plant traits. Bad mutations affect negatively all traits studied where bad mutations explain half of the genetic variation of these traits. However, models with bad mutations only explain trait variation less than 10%, suggesting bad mutations are complex to explore in practical breeding. However, removing bad mutations through genome editing or selecting genotypes with fewer bad mutations could be useful in crop improvement.

Technical Abstract: Sorghum (Sorghum bicolor (L.) Moench) is a major staple food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. Though selection keeps deleterious mutations rare, their complete removal from the genome is impeded due to lack of recombination, drift, and their coupling with favorable loci. To study how deleterious mutations impact agronomic phenotypes, we identified putative deleterious mutations among ~5.5M segregating variants of 229 diverse sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that about 33% of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups; the caudatum shows higher mutation burden while the guinea has lower burden. Across racial groups, the mutation burden correlated negatively with biomass, plant height, Specific Leaf Area (SLA), and tissue starch content, suggesting deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (5.2%). There is no advantage in total heritable variance for SLA and starch. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, our results suggest that including putatively deleterious variants in models do not significantly improve breeding accuracy because of extensive linkage. However, knowledge of deleterious variants could be leveraged for sorghum breeding through genome editing.