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Fabrication Methods and Additional Results Figures

Plants have the capacity to respond to conserved molecular features known as microbe-associated molecular patterns (MAMPs). The goal of this work was to assess variation in the MAMP response in sorghum, to map loci associated with this variation, and to investigate possible connections with variation in quantitative disease resistance. Using an assay that measures the production of reactive oxygen species, we assessed variation in the MAMP response in a sorghum association mapping population known as the sorghum conversion population (SCP). We identified consistent variation for the response to chitin and flg22-an epitope of flagellin. We identified two SNP loci associated with variation in the flg22 response and one with the chitin response. We also assessed resistance to Target Leaf Spot (TLS) disease caused by the necrotrophic fungus Bipolaris cookei in the SCP. We identified one strong association on chromosome 5 near a previously characterized disease resistance gene. A moderately significant correlation was observed between stronger flg22 response and lower TLS resistance. Possible reasons for this are discussed.

Genome-wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near-isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping-by-sequencing. Across traits, broad-sense heritability (0.4-0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping-by-sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies. NSF PGRP grantNational Science Foundation (NSF)NSF - Office of the Director (OD) [1127076] This work was partially funded by NSF PGRP grant #1127076. The authors thank Greg Marshall, Judith Kolkman and Molly Towne for technical and logistic support. The authors also thank Denise Costich and the CIMMYT Germplasm Bank for originally providing the nNIL seed. The authors also acknowledge the staff at the Central Crops Research Station in Clayton, NC for field trial management, the Cornell University Computational Biology Service Unit for providing computational resources, and Detlef Weigel and Hernan Burbano at the Max Planck Institute for Developmental Biology for desk space. Public domain – authored by a U.S. government employee

Summary Macroorganisms’ genotypes shape their phenotypes, which in turn shape the habitat available to potential microbial symbionts. This influence of host genotype on microbiome composition has been demonstrated in many systems; however, most previous studies have either compared unrelated genotypes or delved into molecular mechanisms. As a result, it is currently unclear whether the heritability of host-associated microbiomes follows similar patterns to the heritability of other complex traits. We take a new approach to this question by comparing the microbiomes of diverse maize inbred lines and their F1 hybrid offspring, which we quantified in both rhizosphere and leaves of field-grown plants using 16S-v4 and ITS1 amplicon sequencing. We show that inbred lines and hybrids differ consistently in composition of bacterial and fungal rhizosphere communities, as well as leaf-associated fungal communities. A wide range of microbiome features display heterosis within individual crosses, consistent with patterns for non-microbial maize phenotypes. For leaf microbiomes, these results were supported by the observation that broad-sense heritability in hybrids was substantially higher than narrow-sense heritability. Our results support our hypothesis that at least some heterotic host traits affect microbiome composition in maize.

The past few decades have seen major discoveries in the field of molecular plant-microbe interactions. As the result of technological and intellectual advances, we are now able to answer questions at a level of mechanistic detail that we could not have imagined possible 20 years ago. The MPMI Editorial Board felt it was time to take stock and reassess. What big questions remain unanswered? We knew that to identify the fundamental, overarching questions that drive our research, we needed to do this as a community. To reach a diverse audience of people with different backgrounds and perspectives, working in different areas of plant-microbe interactions, we queried the more than 1,400 participants at the 2019 International Congress on Molecular Plant-Microbe Interactions meeting in Glasgow. This group effort resulted in a list of ten, broad-reaching, fundamental questions that influence and inform our research. Here, we introduce these Top 10 unanswered questions, giving context and a brief description of the issues. Each of these questions will be the subject of a detailed review in the coming months. We hope that this process of reflecting on what is known and unknown and identifying the themes that underlie our research will provide a framework to use going forward, giving newcomers a sense of the mystery of the big questions and inspiring new avenues and novel insights.

Additional file 2. gRNA sequences used in this study.

Additional file 3. Dual luciferase assay components and preliminary results. (A) pGreenII-800-RNAI-PDS1-Luc dual luciferase construct, where Renilla luciferase provides an internal control for PDS1-driven Firefly luciferase. Dual luciferase assay using maize protoplasts co-transfected with indicated PDS1 gRNAs and dCas9-SRDX (B) or dCas9-VP64 (C). Data shown in B and C are from one biological replicate. An additional control construct was developed where GFP was expressed from the dual luciferase vector pGreenII-800-RNAI-Luc (D). Expression was detected by Western blot (E), which shows four separate maize protoplast transfection samples with this construct, compared to the no transfection, no DNA, and positive controls.

Additional file 1. Vector Maps. (A) pCXUN-HA-GFP used for testing protoplast transfection conditions. (B) Diagram of each pDA vector showing an ubiquitin-driven, Flag-tagged dCas9 with IV2 intron followed by transcription activators (VP64 and TAL-VP128) or suppressor (SRDX). A dual 35S promoter drives BAR for glufosinate resistance.

Southern Leaf Blight, Northern Leaf Blight, and Gray Leaf Spot, caused by ascomycete fungi, are among the most important foliar diseases of maize worldwide. Previously, disease resistance quantitative trait loci (QTL) for all three diseases were identified in a connected set of chromosome segment substitution line (CSSL) populations designed for the identification of disease resistance QTL. Some QTL for different diseases co-localized, indicating the presence of multiple disease resistance (MDR) QTL. The goal of this study was to perform an independent test of several of the MDR QTL identified to confirm their existence and derive a more precise estimate of allele additive and dominance effects. Twelve F-2:3 family populations were produced, in which selected QTL were segregating in an otherwise uniform genetic background. The populations were assessed for each of the three diseases in replicated trials and genotyped with markers previously associated with disease resistance. Pairwise phenotypic correlations across all the populations for resistance to the three diseases ranged from 0.2 to 0.3 and were all significant at the alpha level of 0.01. Of the 44 QTL tested, 16 were validated (identified at the same genomic location for the same disease or diseases) and several novel QTL/disease associations were found. Two MDR QTL were associated with resistance to all three diseases. This study identifies several potentially important MDR QTL and demonstrates the importance of independently evaluating QTL effects following their initial identification. USDA-ARSUnited States Department of Agriculture (USDA); Corn Growers' Association of North Carolina; NSFNational Science Foundation (NSF) [1127076]; NCSU Crop; Soil Science Department and Monsanto Funding for the work was provided by USDA-ARS, the Corn Growers' Association of North Carolina and by NSF grant #1127076 to RJW, JBH and PBK. LBM was funded by a fellowship from the NCSU Crop and Soil Science Department and Monsanto. Pioneer and Monsanto both provided space for GLS field trials for this study. We thank Cathy Herring and the staff at Central Crops Research Station for excellent field support, Shannon Sermons, Greg Marshall and Teclemariam Weldekidan for their technical support. We thank Susana Milla-Lewis and Luis Lopez-Zuniga for helpful discussion.

Table S1. PCR primers used in this study (PDF 213 kb)

In this study we mapped the QTL Qgls8 for gray leaf spot (GLS) resistance in maize to a similar to 130 kb region on chromosome 8 including five predicted genes. In previous work, using near isogenic line (NIL) populations in which segments of the teosinte (Zea mays ssp. parviglumis) genome had been introgressed into the background of the maize line B73, we had identified a QTL on chromosome 8, here called Qgls8, for gray leaf spot (GLS) resistance. We identified alternate teosinte alleles at this QTL, one conferring increased GLS resistance and one increased susceptibility relative to the B73 allele. Using segregating populations derived from NIL parents carrying these contrasting alleles, we were able to delimit the QTL region to a similar to 130 kb (based on the B73 genome) which encompassed five predicted genes. NSFNational Science Foundation (NSF) [1127076]; China Scholarship Council FellowshipChina Scholarship Council QY is supported by NSF Grant #1127076, "Genetic and Histological Dissection of Phenotypic Variation in Quantitative Resistance to Maize Diseases"; XY is supported by a China Scholarship Council Fellowship. We are very grateful to Jose Santa-Cruz Hidalgo, Julie Taylor, and Monsanto Inc. for planting and managing our experiments in Andrews NC. Public domain – authored by a U.S. government employee

Disease resistance (R) genes encode nucleotide binding Leu-rich-repeat (NLR) proteins that confer resistance to specific pathogens. Upon pathogen recognition they trigger a defense response that usually includes a so-called hypersensitive response (HR), a rapid localized cell death at the site of pathogen infection. Intragenic recombination between two maize (Zea mays) NLRs, Rp1-D and Rp1-dp2, resulted in the formation of a hybrid NLR, Rp1-D21, which confers an autoactive HR in the absence of pathogen infection. From a previous quantitative trait loci and genome-wide association study, we identified genes encoding two key enzymes in lignin biosynthesis, hydroxycinnamoyltransferase (HCT) and caffeoyl CoA O-methyltransferase (CCoAOMT), adjacent to the nucleotide polymorphisms that were highly associated with variation in the severity of Rp1-D21-induced HR We have previously shown that the two maize HCT homologs suppress the HR conferred by Rp1-D21 in a heterologous system, very likely through physical interaction. Here, we show, similarly, that CCoAOMT2 suppresses the HR induced by either the full-length or by the N-terminal coiled-coil domain of Rp1-D21 also likely via physical interaction and that the metabolic activity of CCoAOMT2 is unlikely to be necessary for its role in suppressing HR. We also demonstrate that CCoAOMT2, HCTs, and Rp1 proteins can form in the same complexes. A model is derived to explain the roles of CCoAOMT and HCT in Rp1-mediated defense resistance.

Figure S1. Chemical-Induced Cell Death Assay. This assay has been described previously [21]. A. The middle portion of individual emergent but not yet fully-expanded 4th leaves (indicated by yellow circle) are separately treated with two 10 μl droplets of 10-OPEA (1 mM or 2 mM, dissolved in 5% DMSO and 0.1% Tween 20) or salicylic acid (10 mM or 20 mM, dissolved in 1% or 2% ethanol and 0.1% Tween 20). B. At 24 h (10-OPEA)/72 h (SA) post treatment, lesion areas are photographed and digitally measured using ImageJ software (Image J 1.36b; Wyne Raband, NIH, Bethesda, MD, USA). (PPTX 1201 kb)

Figure S1. Chemical-Induced Cell Death Assay. This assay has been described previously [21]. A. The middle portion of individual emergent but not yet fully-expanded 4th leaves (indicated by yellow circle) are separately treated with two 10 μl droplets of 10-OPEA (1 mM or 2 mM, dissolved in 5% DMSO and 0.1% Tween 20) or salicylic acid (10 mM or 20 mM, dissolved in 1% or 2% ethanol and 0.1% Tween 20). B. At 24 h (10-OPEA)/72 h (SA) post treatment, lesion areas are photographed and digitally measured using ImageJ software (Image J 1.36b; Wyne Raband, NIH, Bethesda, MD, USA). (PPTX 1201 kb)