Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA
Department of Botany, University of Wisconsin, Madison, Wisconsin 53706, USA
Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853, USA, Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, New York 14853, USA
Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA, Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA, Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61901, USA
Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.
Ferguson, John N., et al. "Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions." Plant Physiology (Bethesda), vol. 187, no. 3, Jul. 2021. https://doi.org/10.1093/plphys/kiab346
Ferguson, John N., Fernandes, Samuel B., Monier, Brandon, Miller, Nathan D., Allen, Dylan, Dmitrieva, Anna, Schmuker, Peter, Lozano, Roberto, Valluru, Ravi, Buckler, Edward S., Gore, Michael A., Brown, Patrick J., Spalding, Edgar P., & Leakey, Andrew D. B. (2021). Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions. Plant Physiology (Bethesda), 187(3). https://doi.org/10.1093/plphys/kiab346
Ferguson, John N., Fernandes, Samuel B., Monier, Brandon, et al., "Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions," Plant Physiology (Bethesda) 187, no. 3 (2021), https://doi.org/10.1093/plphys/kiab346
@article{osti_1828986,
author = {Ferguson, John N. and Fernandes, Samuel B. and Monier, Brandon and Miller, Nathan D. and Allen, Dylan and Dmitrieva, Anna and Schmuker, Peter and Lozano, Roberto and Valluru, Ravi and Buckler, Edward S. and others},
title = {Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions},
annote = {Abstract Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.},
doi = {10.1093/plphys/kiab346},
url = {https://www.osti.gov/biblio/1828986},
journal = {Plant Physiology (Bethesda)},
issn = {ISSN 0032-0889},
number = {3},
volume = {187},
place = {United States},
publisher = {Oxford University Press},
year = {2021},
month = {07}}