Population-level gene expression can repeatedly link genes to functions in maize.

Transcriptome-wide association studies (TWAS) can provide single gene resolution for candidate genes in plants, complementing genome-wide association studies (GWAS) but efforts in plants have been met with, at best, mixed success. We generated expression data from 693 maize genotypes, measured in a common field experiment, sampled over a 2-h period to minimize diurnal and environmental effects, using full-length RNA-seq to maximize the accurate estimation of transcript abundance. TWAS could identify roughly 10 times as many genes likely to play a role in flowering time regulation as GWAS conducted data from the same experiment. TWAS using mature leaf tissue identified known true-positive flowering time genes known to act in the shoot apical meristem, and trait data from a new environment enabled the identification of additional flowering time genes without the need for new expression data. eQTL analysis of TWAS-tagged genes identified at least one additional known maize flowering time gene through trans-eQTL interactions. Collectively these results suggest the gene expression resource described here can link genes to functions across different plant phenotypes expressed in a range of tissues and scored in different experiments.

A common resequencing-based genetic marker data set for global maize diversity.

Maize (Zea mays ssp. mays) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole-genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high-confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering-time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

Development of the Wheat Practical Haplotype Graph database as a resource for genotyping data storage and genotype imputation.

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The Wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the Wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 92% imputation accuracy with 0.01× sequence coverage, which was slightly lower than the accuracy obtained using the 0.5× sequence coverage (96.6%). Compared to Beagle, on average, PHG imputation was ∼3.5% (P-value < 2 × 10-14) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. We found reduced accuracy of imputation with independent 2× GBS data (88.6%), which increases to 89.2% with the inclusion of parental haplotypes in the database. The accuracy reduction with GBS is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequilibrium and proportion of identity-by-descent regions among accessions in the PHG database. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

Quantitative Resistance Loci to Southern Rust Mapped in a Temperate Maize Diversity Panel.

Southern rust is a severe foliar disease of maize (Zea mays) resulting from infection with the obligate biotrophic fungus Puccinia polysora. This disease reduces photosynthetic productivity, which in turn reduces yields, with the greatest yield losses (up to 50%) associated with earlier onset infections. P. polysora urediniospores overwinter only in tropical and subtropical regions but cause outbreaks when environmental conditions favor initial infection. Increased temperatures and humidity during the growing season combined with an increased frequency of moderate winters are likely to increase the frequency of severe southern rust outbreaks in the U.S. Corn Belt. In summer 2020, a severe outbreak of southern rust was observed in eastern Nebraska, United States. We scored a replicated maize association panel planted in Lincoln, NE for disease severity and found that disease incidence and severity showed significant variation among maize genotypes. Genome-wide association studies identified four loci associated with significant quantitative variation in disease severity. These loci were associated with candidate genes with plausible links to quantitative disease resistance. A transcriptome-wide association study identified additional genes associated with disease severity. Together, these results indicate that substantial diversity in resistance to southern rust exists among current temperate-adapted maize germplasm, including several candidate loci that may explain the observed variation in resistance to southern rust.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Synergistic Cytotoxicity from Drugs and Cytokines In Vitro as an Approach to Classify Drugs According to Their Potential to Cause Idiosyncratic Hepatotoxicity: A Proof-of-Concept Study.

Idiosyncratic drug-induced liver injury (IDILI) typically occurs in a small fraction of patients and has resulted in removal of otherwise efficacious drugs from the market. Current preclinical testing methods are ineffective in predicting which drug candidates have IDILI liability. Recent results suggest that immune mediators such as tumor necrosis factor-α (TNF) and interferon-γ (IFN) interact with drugs that cause IDILI to kill hepatocytes. This proof-of-concept study was designed to test the hypothesis that drugs can be classified according to their ability to cause IDILI in humans using classification modeling with covariates derived from concentration-response relationships that describe cytotoxic interaction with cytokines. Human hepatoma (HepG2) cells were treated with drugs associated with IDILI or with drugs lacking IDILI liability and cotreated with TNF and/or IFN. Detailed concentration-response relationships were determined for calculation of parameters such as the maximal cytotoxic effect, slope, and EC50 for use as covariates for classification modeling using logistic regression. These parameters were incorporated into multiple classification models to identify combinations of covariates that most accurately classified the drugs according to their association with human IDILI. Of 14 drugs associated with IDILI, almost all synergized with TNF to kill HepG2 cells and were successfully classified by statistical modeling. IFN enhanced the toxicity mediated by some IDILI-associated drugs in the presence of TNF. In contrast, of 10 drugs with little or no IDILI liability, none synergized with inflammatory cytokines to kill HepG2 cells and were classified accordingly. The resulting optimal model classified the drugs with extraordinary selectivity and specificity.

Calcium Contributes to the Cytotoxic Interaction Between Diclofenac and Cytokines.

Diclofenac (DCLF) is a widely used non-steroidal anti-inflammatory drug that is associated with idiosyncratic, drug-induced liver injury (IDILI) in humans. The mechanisms of DCLF-induced liver injury are unknown; however, patients with certain inflammatory diseases have an increased risk of developing IDILI, which raises the possibility that immune mediators play a role in the pathogenesis. DCLF synergizes with the cytokines tumor necrosis factor-alpha (TNF) and interferon-gamma (IFN) to cause hepatocellular apoptosis in vitro by a mechanism that involves activation of the endoplasmic reticulum (ER) stress response pathway and of the mitogen-activated protein kinases, c-Jun N-terminal kinase (JNK), and extracellular signal-regulated kinase (ERK). DCLF also causes an increase in intracellular calcium (Ca(++)) in hepatocytes, but the role of this in the cytotoxic synergy between DCLF and cytokines is unknown. We tested the hypothesis that Ca(++) contributes to DCLF/cytokine-induced cytotoxic synergy. Treatment of HepG2 cells with DCLF led to an increase in intracellular Ca(++) at 6 and 12 h, and this response was augmented in the presence of TNF and IFN at 12 h. The intracellular Ca(++) chelator BAPTA/AM reduced cytotoxicity and caspase-3 activation caused by DCLF/cytokine cotreatment. BAPTA/AM also significantly reduced DCLF-induced activation of the ER stress sensor, protein kinase RNA-like ER kinase (PERK), as well as activation of JNK and ERK. Treatment of cells with an inositol trisphosphate receptor antagonist almost completely eliminated DCLF/cytokine-induced cytotoxicity and decreased DCLF-induced activation of PERK, JNK, and ERK. These findings indicate that Ca(++) contributes to DCLF/cytokine-induced cytotoxic synergy by promoting activation of the ER stress-response pathway and JNK and ERK.