Alternaria TeA toxin activates a chloroplast retrograde signaling pathway to facilitate JA-dependent pathogenicity.

The chloroplast is a critical battleground in the arms race between plants and pathogens. Among microbe-secreted mycotoxins, tenuazonic acid (TeA), produced by the genus Alternaria and other phytopathogenic fungi, inhibits photosynthesis, leading to a burst of photosynthetic singlet oxygen (1O2) that is implicated in damage and chloroplast-to-nucleus retrograde signaling. Despite the significant crop damage caused by Alternaria pathogens, our understanding of the molecular mechanism by which TeA promotes pathogenicity and cognate plant defense responses remains fragmentary. We now reveal that A. alternata induces necrotrophic foliar lesions by harnessing EXECUTER1 (EX1)/EX2-mediated chloroplast-to-nucleus retrograde signaling activated by TeA toxin-derived photosynthetic 1O2 in Arabidopsis thaliana. Mutation of the 1O2-sensitive EX1-W643 residue or complete deletion of the EX1 singlet oxygen sensor domain compromises expression of 1O2-responsive nuclear genes and foliar lesions. We also found that TeA toxin rapidly induces nuclear genes implicated in jasmonic acid (JA) synthesis and signaling, and EX1-mediated retrograde signaling appears to be critical for establishing a signaling cascade from 1O2 to JA. The present study sheds new light on the foliar pathogenicity of A. alternata, during which EX1-dependent 1O2 signaling induces JA-dependent foliar cell death.

Comparative Genome Analyses of Plant Rust Pathogen Genomes Reveal a Confluence of Pathogenicity Factors to Quell Host Plant Defense Responses.

Switchgrass rust caused by Puccinia novopanici (P. novopanici) has the ability to significantly affect the biomass yield of switchgrass, an important biofuel crop in the United States. A comparative genome analysis of P. novopanici with rust pathogen genomes infecting monocot cereal crops wheat, barley, oats, maize and sorghum revealed the presence of larger structural variations contributing to their genome sizes. A comparative alignment of the rust pathogen genomes resulted in the identification of collinear and syntenic relationships between P. novopanici and P. sorghi; P. graminis tritici 21-0 (Pgt 21) and P. graminis tritici Ug99 (Pgt Ug99) and between Pgt 21 and P. triticina (Pt). Repeat element analysis indicated a strong presence of retro elements among different Puccinia genomes, contributing to the genome size variation between ~1 and 3%. A comparative look at the enriched protein families of Puccinia spp. revealed a predominant role of restriction of telomere capping proteins (RTC), disulfide isomerases, polysaccharide deacetylases, glycoside hydrolases, superoxide dismutases and multi-copper oxidases (MCOs). All the proteomes of Puccinia spp. share in common a repertoire of 75 secretory and 24 effector proteins, including glycoside hydrolases cellobiohydrolases, peptidyl-propyl isomerases, polysaccharide deacetylases and protein disulfide-isomerases, that remain central to their pathogenicity. Comparison of the predicted effector proteins from Puccinia spp. genomes to the validated proteins from the Pathogen-Host Interactions database (PHI-base) resulted in the identification of validated effector proteins PgtSR1 (PGTG_09586) from P. graminis and Mlp124478 from Melampsora laricis across all the rust pathogen genomes.

PIP-SNP: a pipeline for processing SNP data featured as linkage disequilibrium bin mapping, genotype imputing and marker synthesizing.

Genome-wide association study data analyses often face two significant challenges: (i) high dimensionality of single-nucleotide polymorphism (SNP) genotypes and (ii) imputation of missing values. SNPs are not independent due to physical linkage and natural selection. The correlation of nearby SNPs is known as linkage disequilibrium (LD), which can be used for LD conceptual SNP bin mapping, missing genotype inferencing and SNP dimension reduction. We used a stochastic process to describe the SNP signals and proposed two types of autocorrelations to measure nearby SNPs' information redundancy. Based on the calculated autocorrelation coefficients, we constructed LD bins. We adopted a k-nearest neighbors algorithm (kNN) to impute the missing genotypes. We proposed several novel methods to find the optimal synthetic marker to represent the SNP bin. We also proposed methods to evaluate the information loss or information conservation between using the original genome-wide markers and using dimension-reduced synthetic markers. Our performance assessments on the real-life SNP data from a rice recombinant inbred line (RIL) population and a rice HapMap project show that the new methods produce satisfactory results. We implemented these functional modules in C/C++ and streamlined them into a web-based pipeline named PIP-SNP (https://bioinfo.noble.org/PIP_SNP/) for processing SNP data.

LegumeIP V3: from models to crops-an integrative gene discovery platform for translational genomics in legumes.

Legumes have contributed to human health, sustainable food and feed production worldwide for centuries. The study of model legumes has played vital roles in deciphering key genes, pathways, and networks regulating biological mechanisms and agronomic traits. Along with emerging breeding technology such as genome editing, translation of the knowledge gained from model plants to crops is in high demand. The updated database (V3) was redesigned for translational genomics targeting the discovery of novel key genes in less-studied non-model legume crops by referring to the knowledge gained in model legumes. The database contains genomic data for all 22 included species, and transcriptomic data covering thousands of RNA-seq samples mostly from model species. The rich biological data and analytic tools for gene expression and pathway analyses can be used to decipher critical genes, pathways, and networks in model legumes. The integrated comparative genomic functions further facilitate the translation of this knowledge to legume crops. Therefore, the database will be a valuable resource to identify important genes regulating specific biological mechanisms or agronomic traits in the non-model yet economically significant legume crops. LegumeIP V3 is available free to the public at https://plantgrn.noble.org/LegumeIP. Access to the database does not require login, registration, or password.

pssRNAit: A Web Server for Designing Effective and Specific Plant siRNAs with Genome-Wide Off-Target Assessment.

We report an advanced web server, the plant-specific small noncoding RNA interference tool pssRNAit, which can be used to design a pool of small interfering RNAs (siRNAs) for highly effective, specific, and nontoxic gene silencing in plants. In developing this tool, we integrated the transcript dataset of plants, several rules governing gene silencing, and a series of computational models of the biological mechanism of the RNA interference (RNAi) pathway. The designed pool of siRNAs can be used to construct a long double-strand RNA and expressed through virus-induced gene silencing (VIGS) or synthetic transacting siRNA vectors for gene silencing. We demonstrated the performance of pssRNAit by designing and expressing the VIGS constructs to silence Phytoene desaturase (PDS) or a ribosomal protein-encoding gene, RPL10 (QM), in Nicotiana benthamiana We analyzed the expression levels of predicted intended-target and off-target genes using reverse transcription quantitative PCR. We further conducted an RNA-sequencing-based transcriptome analysis to assess genome-wide off-target gene silencing triggered by the fragments that were designed by pssRNAit, targeting different homologous regions of the PDS gene. Our analyses confirmed the high accuracy of siRNA constructs designed using pssRNAit The pssRNAit server, freely available at https://plantgrn.noble.org/pssRNAit/, supports the design of highly effective and specific RNAi, VIGS, or synthetic transacting siRNA constructs for high-throughput functional genomics and trait improvement in >160 plant species.

A novel methodology of the myeloid-derived suppressor cells (MDSCs) generation with splenic stroma feeder cells.

Myeloid-derived suppressor cells (MDSCs) are a significant obstacle for immunotherapy of cancer. It is of great clinical relevance to study the mechanism of MDSCs accumulation in mouse spleens and establish a stable method to obtain high-purity MDSCs in vitro for further research. Here, we established a new method for amplifying a large number of highly pure MDSCs in vitro. To mimic the microenvironment of MDSCs development in vivo, mouse splenic stroma feeder cells and serum-free medium containing granulocyte-macrophage colony stimulating factor (GM-CSF) were used to induce myeloid precursors in mouse bone marrow cells, which differentiate into MDSCs. Development and immunological functions of the cells were monitored both in vivo and in vitro. A total of 4 × 108 MDSCs could be obtained from the bone marrow from one mouse, the ratio of CD11b+Gr-1+ MDSCs could reach 93.8% ± 3.3% after nine days of culture in vitro. Cultured MDSCs maintained a similar immunophenotype with MDSCs found in tumor-bearing mice. Colony forming assay in vitro and in vivo demonstrated that these were myeloid precursor cells. These cells generated high levels of reactive oxygen species and arginase 1 to prevent proliferation of CD8+ T cells in vitro. These also increased regulatory T (Treg) cells in blood while promoting the growth of lymphoma in vivo. In addition, cultured MDSCs effectively inhibited acute graft-versus-host disease (aGVHD). Our findings suggest that mouse splenic stroma plays an important role in the generation of MDSCs and represent a preliminary mechanism for the accumulation of MDSCs in spleens, and thereby lay the foundation for basic research and the clinical application of MDSCs.

Insertional mutagenesis of Brachypodium distachyon using the Tnt1 retrotransposable element.

Brachypodium distachyon is an annual C3 grass used as a monocot model system in functional genomics research. Insertional mutagenesis is a powerful tool for both forward and reverse genetics studies. In this study, we explored the possibility of using the tobacco retrotransposon Tnt1 to create a transposon-based insertion mutant population in B. distachyon. We developed transgenic B. distachyon plants expressing Tnt1 (R0) and in the subsequent regenerants (R1) we observed that Tnt1 actively transposed during somatic embryogenesis, generating an average of 6.37 insertions per line in a population of 19 independent R1 regenerant plants analyzed. In seed-derived progeny of R1 plants, Tnt1 segregated in a Mendelian ratio of 3:1 and no new Tnt1 transposition was observed. A total of 126 flanking sequence tags (FSTs) were recovered from the analyzed R0 and R1 lines. Analysis of the FSTs showed a uniform pattern of insertion in all the chromosomes (1-5) without any preference for a particular chromosome region. Considering the average length of a gene transcript to be 3.37 kb, we estimated that 29 613 lines are required to achieve a 90% possibility of tagging a given gene in the B. distachyon genome using the Tnt1-based mutagenesis approach. Our results show the possibility of using Tnt1 to achieve near-saturation mutagenesis in B. distachyon, which will aid in functional genomics studies of other C3 grasses.

The CLE53-SUNN genetic pathway negatively regulates arbuscular mycorrhiza root colonization in Medicago truncatula.

Plants and arbuscular mycorrhizal fungi (AMF) engage in mutually beneficial symbioses based on a reciprocal exchange of nutrients. The beneficial character of the symbiosis is maintained through a mechanism called autoregulation of mycorrhization (AOM). AOM includes root-to-shoot-to-root signaling; however, the molecular details of AOM are poorly understood. AOM shares many features of autoregulation of nodulation (AON) where several genes are known, including the receptor-like kinase SUPER NUMERIC NODULES (SUNN), root-to-shoot mobile CLAVATA3/ENDOSPERM SURROUNDING REGION (ESR)-RELATED (CLE) peptides, and the hydroxyproline O-arabinosyltransferase ROOT DETERMINED NODULATION1 (RDN1) required for post-translational peptide modification. In this work, CLE53 was identified to negatively regulate AMF symbiosis in a SUNN- and RDN1-dependent manner. CLE53 expression was repressed at low phosphorus, while it was induced by AMF colonization and high phosphorus. CLE53 overexpression reduced AMF colonization in a SUNN- and RDN1 dependent manner, while cle53, rdn1, and sunn mutants were more colonized than the wild type. RNA-sequencing identified 700 genes with SUNN-dependent regulation in AMF-colonized plants, providing a resource for future identification of additional AOM genes. Disruption of AOM genes in crops potentially constitutes a novel route for improving AMF-derived phosphorus uptake in agricultural systems with high phosphorus levels.

MtSSPdb: The Medicago truncatula Small Secreted Peptide Database.

A growing number of small secreted peptides (SSPs) in plants are recognized as important regulatory molecules with roles in processes such as growth, development, reproduction, stress tolerance, and pathogen defense. Recent discoveries further implicate SSPs in regulating root nodule development, which is of particular significance for legumes. SSP-coding genes are frequently overlooked, because genome annotation pipelines generally ignore small open reading frames, which are those most likely to encode SSPs. Also, SSP-coding small open reading frames are often expressed at low levels or only under specific conditions, and thus are underrepresented in non-tissue-targeted or non-condition-optimized RNA-sequencing projects. We previously identified 4,439 SSP-encoding genes in the model legume Medicago truncatula To support systematic characterization and annotation of these putative SSP-encoding genes, we developed the M. truncatula Small Secreted Peptide Database (MtSSPdb; https://mtsspdb.noble.org/). MtSSPdb currently hosts (1) a compendium of M. truncatula SSP candidates with putative function and family annotations; (2) a large-scale M. truncatula RNA-sequencing-based gene expression atlas integrated with various analytical tools, including differential expression, coexpression, and pathway enrichment analyses; (3) an online plant SSP prediction tool capable of analyzing protein sequences at the genome scale using the same protocol as for the identification of SSP genes; and (4) information about a library of synthetic peptides and root and nodule phenotyping data from synthetic peptide screens in planta. These datasets and analytical tools make MtSSPdb a unique and valuable resource for the plant research community. MtSSPdb also has the potential to become the most complete database of SSPs in plants.

GPU empowered pipelines for calculating genome-wide kinship matrices with ultra-high dimensional genetic variants and facilitating 1D and 2D GWAS.

Genome-wide association study (GWAS) is a powerful approach that has revolutionized the field of quantitative genetics. Two-dimensional GWAS that accounts for epistatic genetic effects needs to consider the effects of marker pairs, thus quadratic genetic variants, compared to one-dimensional GWAS that accounts for individual genetic variants. Calculating genome-wide kinship matrices in GWAS that account for relationships among individuals represented by ultra-high dimensional genetic variants is computationally challenging. Fortunately, kinship matrix calculation involves pure matrix operations and the algorithms can be parallelized, particular on graphics processing unit (GPU)-empowered high-performance computing (HPC) architectures. We have devised a new method and two pipelines: KMC1D and KMC2D for kinship matrix calculation with high-dimensional genetic variants, respectively, facilitating 1D and 2D GWAS analyses. We first divide the ultra-high-dimensional markers and marker pairs into successive blocks. We then calculate the kinship matrix for each block and merge together the block-wise kinship matrices to form the genome-wide kinship matrix. All the matrix operations have been parallelized using GPU kernels on our NVIDIA GPU-accelerated server platform. The performance analyses show that the calculation speed of KMC1D and KMC2D can be accelerated by 100-400 times over the conventional CPU-based computing.

Identification and Functional Investigation of Genome-Encoded, Small, Secreted Peptides in Plants.

Hundreds to thousands of small secreted peptides (SSPs) are encoded in plant genomes but have been overlooked, and most remain unannotated and unstudied. Despite their low profile, they have been found to confer dramatic effects on growth and development of plants. With the growing appreciation of their significance, the development of appropriate methods to identify and functionally assess the myriad SSPs encoded in plant genomes has become critical. Here, we provide protocols for the computational and physiological analysis of SSPs in plant genomes. We first describe our methodology successfully used for genome-wide identification and annotation of SSP-coding genes in the model legume Medicago truncatula, which can be readily adapted for other plant species. We then provide protocols for the functional analysis of SSPs using various synthetic peptide screens. Considerations for the design and handling of peptides are included. © 2019 by John Wiley & Sons, Inc.

Draft Genome Sequence Resource of Switchgrass Rust Pathogen, Puccinia novopanici Isolate Ard-01.

Puccinia novopanici is an important biotrophic fungal pathogen that causes rust disease in switchgrass. Lack of genomic resources for P. novopanici has hampered the progress toward developing effective disease resistance against this pathogen. Therefore, we have sequenced the whole genome of P. novopanici and generated a framework to understand pathogenicity mechanisms and identify effectors, repeat element invasion, genome evolution, and comparative genomics among Puccinia spp. in the future. Long- and short-read sequences were generated from P. novopanici genomic DNA by PacBio and Illumina technologies, respectively, and assembled a 99.9-Mb genome. Transcripts of P. novopanici were predicted from assembled genome using MAKER and were further validated by RNAseq data. The genome sequence information of P. novopanici will be a valuable resource for researchers working on monocot rusts and plant disease resistance in general.

A microRNA biogenesis-like pathway for producing phased small interfering RNA from a long non-coding RNA in rice.

Phased small interfering RNAs (phasiRNAs) are a class of non-coding RNAs that perform essential functions in plants. Unlike microRNA biogenesis from a hairpin structure, the production of phasiRNAs usually requires a phase initiator and an RNA-dependent RNA polymerase (RDR) to form double-strand RNAs. By using full-length rice cDNA (KL-cDNA) to identify phasiRNA loci, we found that a putative non-coding sequence with a long hairpin structure generates the phasiRNAs, which we name Long Hairpin-structure containing non-coding RNA (LHR). The biogenesis of LHR-derived phasiRNAs was dependent on rice DCL4, but not on RDR2/6, DCL1, or DCL3. Since all of the LHR-phasiRNAs (-5p from the forward strand and -3p from the reverse strand of the dsRNAs) are mapped to the forward strand of LHR, LHR-phasiRNAs should be derived from its hairpin structure, similar to a microRNA precursor. A degradome-based validation suggested that several thylakoid-related genes were targeted by LHR-phasiRNAs. In addition, the production of LHR-phasiRNAs was completely abolished in the lhr mutant, which also exhibited decreased plant height, leaf size, and grain weight, probably through the regulation of photosynthesis. Based on our results, we propose a microRNA biogenesis-like pathway for producing phased siRNAs that expands our understanding of the current model of phased siRNA biogenesis in plants.

GWASpro: a high-performance genome-wide association analysis server.

SUMMARY: We present GWASpro, a high-performance web server for the analyses of large-scale genome-wide association studies (GWAS). GWASpro was developed to provide data analyses for large-scale molecular genetic data, coupled with complex replicated experimental designs such as found in plant science investigations and to overcome the steep learning curves of existing GWAS software tools. GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model. GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10 000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators. AVAILABILITY AND IMPLEMENTATION: GWASpro is freely available at https://bioinfo.noble.org/GWASPRO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

2D association and integrative omics analysis in rice provides systems biology view in trait analysis.

The interactions among genes and between genes and environment contribute significantly to the phenotypic variation of complex traits and may be possible explanations for missing heritability. However, to our knowledge no existing tool can address the two kinds of interactions. Here we propose a novel linear mixed model that considers not only the additive effects of biological markers but also the interaction effects of marker pairs. Interaction effect is demonstrated as a 2D association. Based on this linear mixed model, we developed a pipeline, namely PATOWAS. PATOWAS can be used to study transcriptome-wide and metabolome-wide associations in addition to genome-wide associations. Our case analysis with real rice recombinant inbred lines (RILs) at three omics levels demonstrates that 2D association mapping and integrative omics are able to provide a systems biology view into the analyzed traits, leading toward an answer about how genes, transcripts, proteins, and metabolites work together to produce an observable phenotype.

psRNATarget: a plant small RNA target analysis server (2017 release).

Plant regulatory small RNAs (sRNAs), which include most microRNAs (miRNAs) and a subset of small interfering RNAs (siRNAs), such as the phased siRNAs (phasiRNAs), play important roles in regulating gene expression. Although generated from genetically distinct biogenesis pathways, these regulatory sRNAs share the same mechanisms for post-translational gene silencing and translational inhibition. psRNATarget was developed to identify plant sRNA targets by (i) analyzing complementary matching between the sRNA sequence and target mRNA sequence using a predefined scoring schema and (ii) by evaluating target site accessibility. This update enhances its analytical performance by developing a new scoring schema that is capable of discovering miRNA-mRNA interactions at higher 'recall rates' without significantly increasing total prediction output. The scoring procedure is customizable for the users to search both canonical and non-canonical targets. This update also enables transmitting and analyzing 'big' data empowered by (a) the implementation of multi-threading chunked file uploading, which can be paused and resumed, using HTML5 APIs and (b) the allocation of significantly more computing nodes to its back-end Linux cluster. The updated psRNATarget server has clear, compelling and user-friendly interfaces that enhance user experiences and present data clearly and concisely. The psRNATarget is freely available at http://plantgrn.noble.org/psRNATarget/.

Genome-Wide Identification of Medicago Peptides Involved in Macronutrient Responses and Nodulation.

Growing evidence indicates that small, secreted peptides (SSPs) play critical roles in legume growth and development, yet the annotation of SSP-coding genes is far from complete. Systematic reannotation of the Medicago truncatula genome identified 1,970 homologs of established SSP gene families and an additional 2,455 genes that are potentially novel SSPs, previously unreported in the literature. The expression patterns of known and putative SSP genes based on 144 RNA sequencing data sets covering various stages of macronutrient deficiencies and symbiotic interactions with rhizobia and mycorrhiza were investigated. Focusing on those known or suspected to act via receptor-mediated signaling, 240 nutrient-responsive and 365 nodulation-responsive Signaling-SSPs were identified, greatly expanding the number of SSP gene families potentially involved in acclimation to nutrient deficiencies and nodulation. Synthetic peptide applications were shown to alter root growth and nodulation phenotypes, revealing additional regulators of legume nutrient acquisition. Our results constitute a powerful resource enabling further investigations of specific SSP functions via peptide treatment and reverse genetics.

PEPIS: A Pipeline for Estimating Epistatic Effects in Quantitative Trait Locus Mapping and Genome-Wide Association Studies.

The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.

LegumeIP 2.0--a platform for the study of gene function and genome evolution in legumes.

The LegumeIP 2.0 database hosts large-scale genomics and transcriptomics data and provides integrative bioinformatics tools for the study of gene function and evolution in legumes. Our recent updates in LegumeIP 2.0 include gene and protein sequences, gene models and annotations, syntenic regions, protein families and phylogenetic trees for six legume species: Medicago truncatula, Glycine max (soybean), Lotus japonicus, Phaseolus vulgaris (common bean), Cicer arietinum (chickpea) and Cajanus cajan (pigeon pea) and two outgroup reference species: Arabidopsis thaliana and Poplar trichocarpa. Moreover, the LegumeIP 2.0 features the following new data resources and bioinformatics tools: (i) an integrative gene expression atlas for four model legumes that include 550 array hybridizations from M. truncatula, 962 gene expression profiles of G. max, 276 array hybridizations from L. japonicas and 56 RNA-Seq-based gene expression profiles for C. arietinum. These datasets were manually curated and hierarchically organized based on Experimental Ontology and Plant Ontology so that users can browse, search, and retrieve data for their selected experiments. (ii) New functions/analytical tools to query, mine and visualize large-scale gene sequences, annotations and transcriptome profiles. Users may select a subset of expression experiments and visualize and compare expression profiles for multiple genes. The LegumeIP 2.0 database is freely available to the public at http://plantgrn.noble.org/LegumeIP/.