Plant waxes and staygreen are distinct phenotypic traits that have been independently implicated in heat and drought tolerance among grasses. The association between these two traits has not been fully explored, which makes the exploitation of synergy between them difficult. This study assessed the association between QTL regulating the staygreen (Stg) trait in sorghum and those regulating epicuticular wax load (WL) and associated canopy temperature depression (TD). Using a recombinant inbred line (RIL) population derived from Tx642 and Tx7000, phenotypic data were collected in three replicated field trials and one greenhouse trial. High absolute TD generally corresponded to high WL. The r 2 of TD against WL was highest under non-stress conditions in the greenhouse while it was much larger in the cooler and irrigated field conditions compared to hotter, drier field trials. The genetic correlations between the two traits also followed this pattern. Composite interval mapping identified a total of 28 QTL, 15 of which had significant overlaps between different traits. Most of the wax QTL were associated with pre-anthesis drought tolerant Tx7000. However, one QTL for WL overlapped with a QTL for staygreen (Stg2) and was represented by a single, isolated marker near the centromeric region on the short arm of SBI-01. The marker is identified by a Cis-acting regulatory module and is part of a 2-kb multifunctional motif-rich region which includes core promoter and enhancer regions and transcription elements, including a droughtresponsive MYB binding site. We suggest that this QTL may be pleiotropic for important stress tolerance mechanisms regulating both staygreen and leaf wax in sorghum.

The Plant Genome S pinach, a member of the Amaranthaceae family, is an economically important leafy green crop that is widely grown in the United States. Although the spinach production area has grown steadily during the past 7 yr (

The efficient acquisition and transport of nutrients by plants largely depend on the root architecture. Due to the absence of complex microbial network interactions and soil heterogeneity in a restricted soilless medium, the architecture of roots is a function of genetics defined by the soilless matrix and exogenously supplied nutrients such as nitrogen (N). The knowledge of root trait combinations that offer the optimal nitrogen use efficiency (NUE) is far from being conclusive. The objective of this study was to define the root trait(s) that best predicts and correlates with vegetative biomass under differed N treatments. We used eight image-derived root architectural traits of 202 diverse spinach lines grown in two N concentrations (high N, HN, and low N, LN) in randomized complete blocks design. Supervised random forest (RF) machine learning augmented by ranger hyperparameter grid search was used to predict the variable importance of the root traits. We also determined the broad-sense heritability (H) and genetic (rg) and phenotypic (rp) correlations between root traits and the vegetative biomass (shoot weight, SWt). Each root trait was assigned a predicted importance rank based on the trait’s contribution to the cumulative reduction in the mean square error (MSE) in the RF tree regression models for SWt. The root traits were further prioritized for potential selection based on the rg and SWt correlated response (CR). The predicted importance of the eight root traits showed that the number of root tips (Tips) and root length (RLength) under HN and crossings (Xsings) and root average diameter (RAvdiam) under LN were the most relevant. SWt had a highly antagonistic rg (− 0.83) to RAvdiam, but a high predicted indirect selection efficiency (− 112.8%) with RAvdiam under LN; RAvdiam showed no significant rg or rp to SWt under HN. In limited N availability, we suggest that selecting against larger RAvdiam as a secondary trait might improve biomass and, hence, NUE with no apparent yield penalty under HN.

Minor alleles (MA) have been associated with disease incidence in human studies, enabling the identification of diagnostic risk factors for various diseases. However, allelic mapping has rarely been performed in plant systems. The goal of this study was to determine whether a difference in MA prevalence is a strong enough risk factor to indicate a likely significant difference in disease resistance against white rust (WR; Albugo occidentalis) in spinach (Spinacia oleracea). We used WR disease severity ratings (WR-DSRs) in a diversity panel of 267 spinach accessions to define resistant- and susceptibility-associated groups within the distribution scores and then tested the single-nucleotide polymorphism (SNP) variants to interrogate the MA prevalence in the most susceptible (MS) vs. most resistant (MR) individuals using permutation-based allelic association tests. A total of 448 minor alleles associated with WR severity were identified in the comparison between the 25% MS and the 25% MR accessions, while the MA were generally similar between the two halves of the interquartile range. The minor alleles in the MS group were distributed across all six chromosomes and made up ~71% of the markers that were also strongly associated with WR in parallel performed genome-wide association study. These results indicate that susceptibility may be highly determined by the disproportionate overrepresentation of minor alleles, which could be used to select for resistant plants. Furthermore, by focusing on the distribution tails, allelic mapping could be used to identify plant markers associated with quantitative traits on the most informative segments of the phenotypic distribution.

Anthracnose (Colletotrichum dematium) is an important disease in spinach (Spinacia oleracea). Sources of resistance must be identified, and molecular tools must be developed to expedite cultivar development. In this study, a diverse collection of 276 spinach accessions was scored for anthracnose disease severity. We then evaluated marker identification approaches by testing how well haplotype‐based trait modelling compares to single markers in identifying strong association signals. Alleles in linkage disequilibrium were tagged in haplotype blocks, and anthracnose‐associated molecular markers were identified using single‐SNP (sSNP), pairwise haplotype (htP) and multi‐marker haplotype (htM) SNP tagging approaches. We identified 49 significantly associated markers distributed on several spinach chromosomes using all methods. The sSNP approach identified 13 markers, while htP identified 24 (~63% more) and htM 34 (~162% more). Of these markers, four were uniquely identified by the sSNP approach, nine by htP and nineteen by htM. The results indicate that resistance to anthracnose is polygenic and that haplotype‐based analysis may have more power than sSNP. Using a combination of these methods can improve the identification of molecular markers for spinach breeding.