Genetic architecture of source-sink-regulated senescence in maize.

Source and sink interactions play a critical but mechanistically poorly understood role in the regulation of senescence. To disentangle the genetic and molecular mechanisms underlying source-sink-regulated senescence (SSRS), we performed a phenotypic, transcriptomic, and systems genetics analysis of senescence induced by the lack of a strong sink in maize (Zea mays). Comparative analysis of genotypes with contrasting SSRS phenotypes revealed that feedback inhibition of photosynthesis, a surge in reactive oxygen species, and the resulting endoplasmic reticulum (ER) stress were the earliest outcomes of weakened sink demand. Multienvironmental evaluation of a biparental population and a diversity panel identified 12 quantitative trait loci and 24 candidate genes, respectively, underlying SSRS. Combining the natural diversity and coexpression networks analyses identified 7 high-confidence candidate genes involved in proteolysis, photosynthesis, stress response, and protein folding. The role of a cathepsin B like protease 4 (ccp4), a candidate gene supported by systems genetic analysis, was validated by analysis of natural alleles in maize and heterologous analyses in Arabidopsis (Arabidopsis thaliana). Analysis of natural alleles suggested that a 700-bp polymorphic promoter region harboring multiple ABA-responsive elements is responsible for differential transcriptional regulation of ccp4 by ABA and the resulting variation in SSRS phenotype. We propose a model for SSRS wherein feedback inhibition of photosynthesis, ABA signaling, and oxidative stress converge to induce ER stress manifested as programed cell death and senescence. These findings provide a deeper understanding of signals emerging from loss of sink strength and offer opportunities to modify these signals to alter senescence program and enhance crop productivity.

Host Determinants of Fungal Species Composition and Symptom Manifestation in the Sorghum Grain Mold Disease Complex.

Sorghum grain mold (SGM) is an important multifungal disease complex affecting sorghum (Sorghum bicolor) production systems worldwide. SGM-affected sorghum grain can be contaminated with potent fumonisin mycotoxins produced by Fusarium verticillioides, a prevalent SGM-associated taxon. Historically, efforts to improve resistance to SGM have achieved only limited success. Classical approaches to evaluating SGM resistance are based solely on disease severity, which offers little insight regarding the distinct symptom manifestations within the disease complex. In this study, three novel phenotypes were developed to facilitate assessment of SGM symptom manifestation. A sorghum diversity panel composed of 390 accessions was inoculated with endogenous strains of F. verticillioides and evaluated for these phenotypes, as well as for the conventional panicle grain mold severity rating phenotype, in South Carolina, U.S.A., in 2017 and 2019. Distributions of phenotype values were examined, broad-sense heritability was estimated, and relationships to botanical race were explored. A typology of SGM symptom manifestations was developed to classify accessions using principal component analysis and k-means clustering, constituting a novel option for basing breeding decisions on SGM outcomes more nuanced than disease severity. Genome-wide association studies were performed using SGM trait data, resulting in the identification of 19 significant single nucleotide polymorphisms in linkage disequilibrium with a total of 86 gene models. Our findings provide a basis of exploratory evidence regarding the genetic architecture of SGM symptom manifestation and indicate that traits other than disease severity could be tractable targets for SGM resistance breeding.

Genomic prediction of hybrid performance for agronomic traits in sorghum.

Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic-nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time-consuming, genomic prediction of parental lines and hybrids is based on genetic data genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency > 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76-0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12-90%, with plant height showing the greatest decline. Mean accuracies for predicting the general combining ability of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.

The Sorghum Grain Mold Disease Complex: Pathogens, Host Responses, and the Bioactive Metabolites at Play.

Grain mold is a major concern in sorghum [Sorghum bicolor (L.) Moench] production systems, threatening grain quality, safety, and nutritional value as both human food and livestock feed. The crop's nutritional value, environmental resilience, and economic promise poise sorghum for increased acreage, especially in light of the growing pressures of climate change on global food systems. In order to fully take advantage of this potential, sorghum improvement efforts and production systems must be proactive in managing the sorghum grain mold disease complex, which not only jeopardizes agricultural productivity and profitability, but is also the culprit of harmful mycotoxins that warrant substantial public health concern. The robust scholarly literature from the 1980s to the early 2000s yielded valuable insights and key comprehensive reviews of the grain mold disease complex. Nevertheless, there remains a substantial gap in understanding the complex multi-organismal dynamics that underpin the plant-pathogen interactions involved - a gap that must be filled in order to deliver improved germplasm that is not only capable of withstanding the pressures of climate change, but also wields robust resistance to disease and mycotoxin accumulation. The present review seeks to provide an updated perspective of the sorghum grain mold disease complex, bolstered by recent advances in the understanding of the genetic and the biochemical interactions among the fungal pathogens, their corresponding mycotoxins, and the sorghum host. Critical components of the sorghum grain mold disease complex are summarized in narrative format to consolidate a collection of important concepts: (1) the current state of sorghum grain mold in research and production systems; (2) overview of the individual pathogens that contribute to the grain mold complex; (3) the mycotoxin-producing potential of these pathogens on sorghum and other substrates; and (4) a systems biology approach to the understanding of host responses.

Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize.

Premature senescence in annual crops reduces yield, while delayed senescence, termed stay-green, imposes positive and negative impacts on yield and nutrition quality. Despite its importance, scant information is available on the genetic architecture of senescence in maize (Zea mays) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and coexpression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by genome-wide association study (GWAS), and 14 of these genes are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a coexpression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding Cys protease in stay-green in Arabidopsis (Arabidopsis thaliana), and analysis of natural alleles suggests a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals.