Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions.

John N Ferguson,Ravi Valluru,Patrick J Brown,Dylan Allen,Roberto Lozano,Nathan D Miller,Michael A Gore,Andrew D B Leakey,Peter Schmuker,Edgar P Spalding,Anna Dmitrieva,Samuel B Fernandes,Brandon Monier,Edward S Buckler

doi:10.1093/plphys/kiab346

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.

Highlights

Global climatic change is subjecting agricultural regions to elevated atmospheric vapor pressure deficits (Yuan et al, 2019) and patterns of precipitation that lead to greater or more frequent drought stress (IPCC, 2014, 2018)
This study aimed to address key knowledge gaps regarding natural variation in intrinsic Water use efficiency (WUE) (iWUE) and related traits across diverse biomass sorghum accessions, including evaluation of heritability, environmental effects, trait correlations, and associations between DNA sequence variation or RNA transcript abundance and trait values. iWUE was studied alongside its component traits (AN and gs) plus stomatal density (SD) and specific leaf area (SLA) since these anatomical and allometric traits are known to influence leaf physiology
High-throughput phenotyping metrics A high-throughput approach for measurement of photosynthetic gas exchange, along with tissue sampling for SLA and SD, was performed on $220 leaves per day, allowing two leaves per replicate plot of every genotype in the population to be sampled through 9–10 d of work for each replicate field in a given year

Summary

Introduction

Global climatic change is subjecting agricultural regions to elevated atmospheric vapor pressure deficits (Yuan et al, 2019) and patterns of precipitation that lead to greater or more frequent drought stress (IPCC, 2014, 2018). Water use efficiency (WUE; the ratio of carbon gain to water loss) is a key target trait for crop improvement to improve production and sustainable water use (Bailey-Serres et al, 2019; Leakey et al, 2019). Mechanistic modeling suggests that enhancing intrinsic WUE (iWUE) by reducing stomatal conductance (gs) while maintaining rates of net CO2 assimilation (AN) can increase biomass production in C4 as well as C3 species across a broad range of environmental conditions (Truong et al, 2017; Leakey et al, 2019). These benefits will become greater as atmospheric [CO2] continues to rise. Compiling surveys of natural variation in C4 species, including grain sorghum (Kapanigowda et al, 2013), demonstrated that gs could explain substantially more variation in iWUE than AN (Leakey et al, 2019)

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