ScanFold 2.0: a rapid approach for identifying potential structured RNA targets in genomes and transcriptomes

A major limiting factor in target discovery for both basic research and therapeutic intervention is the identification of structural and/or functional RNA elements in genomes and transcriptomes. This was the impetus for the original ScanFold algorithm, which provides maps of local RNA structural stability, evidence of sequence-ordered (potentially evolved) structure, and unique model structures comprised of recurring base pairs with the greatest structural bias. A key step in quantifying this propensity for ordered structure is the prediction of secondary structural stability for randomized sequences which, in the original implementation of ScanFold, is explicitly evaluated. This slow process has limited the rapid identification of ordered structures in large genomes/transcriptomes, which we seek to overcome in this current work introducing ScanFold 2.0. In this revised version of ScanFold, we no longer explicitly evaluate randomized sequence folding energy, but rather estimate it using a machine learning approach. For high randomization numbers, this can increase prediction speeds over 100-fold compared to ScanFold 1.0, allowing for the analysis of large sequences, as well as the use of additional folding algorithms that may be computationally expensive. In the testing of ScanFold 2.0, we re-evaluate the Zika, HIV, and SARS-CoV-2 genomes and compare both the consistency of results and the time of each run to ScanFold 1.0. We also re-evaluate the SARS-CoV-2 genome to assess the quality of ScanFold 2.0 predictions vs several biochemical structure probing datasets and compare the results to those of the original ScanFold program.

Expansion of the RNAStructuromeDB to include secondary structural data spanning the human protein-coding transcriptome

RNA plays vital functional roles in almost every component of biology, and these functional roles are often influenced by its folding into secondary and tertiary structures. An important role of RNA secondary structure is in maintaining proper gene regulation; therefore, making accurate predictions of the structures involved in these processes is important. In this study, we have expanded on our previous work that led to the creation of the RNAStructuromeDB. Unlike this previous study that analyzed the human genome at low resolution, we have now scanned the protein-coding human transcriptome at high (single nt) resolution. This provides more robust structure predictions for over 100,000 isoforms of known protein-coding genes. Notably, we also utilize the motif identification tool, ScanFold, to model structures with high propensity for ordered/evolved stability. All data have been uploaded to the RNAStructuromeDB, allowing for easy searching of transcripts, visualization of data tracks (via the Integrative Genomics Viewer or IGV), and download of ScanFold data—including unique highly-ordered motifs. Herein, we provide an example analysis of MAT2A to demonstrate the utility of ScanFold at finding known and novel secondary structures, highlighting regions of potential functionality, and guiding generation of functional hypotheses through use of the data.

Prediction and analysis of functional RNA structures within the integrative genomics viewer

In recent years, interest in RNA secondary structure has exploded due to its implications in almost all biological functions and its newly appreciated capacity as a therapeutic agent/target. This surge of interest has driven the development and adaptation of many computational and biochemical methods to discover novel, functional structures across the genome/transcriptome. To further enhance efforts to study RNA secondary structure, we have integrated the functional secondary structure prediction tool ScanFold, into IGV. This allows users to directly perform structure predictions and visualize results—in conjunction with probing data and other annotations—in one program. We illustrate the utility of this new tool by mapping the secondary structural landscape of the human MYC precursor mRNA. We leverage the power of vast ‘omics’ resources by comparing individually predicted structures with published data including: biochemical structure probing, RNA binding proteins, microRNA binding sites, RNA modifications, single nucleotide polymorphisms, and others that allow functional inferences to be made and aid in the discovery of potential drug targets. This new tool offers the RNA community an easy to use tool to find, analyze, and characterize RNA secondary structures in the context of all available data, in order to find those worthy of further analyses.

Complete Genome Sequencing and Targeted Mutagenesis Reveal Virulence Contributions of Tal2 and Tal4b of Xanthomonas translucens pv. undulosa ICMP11055 in Bacterial Leaf Streak of Wheat

Bacterial leaf streak caused by Xanthomonas translucens pv. undulosa (Xtu) is an important disease of wheat (Triticum aestivum) and barley (Hordeum vulgare) worldwide. Transcription activator-like effectors (TALEs) play determinative roles in many of the plant diseases caused by the different species and pathovars of Xanthomonas, but their role in this disease has not been characterized. ICMP11055 is a highly virulent Xtu strain from Iran. The aim of this study was to better understand genetic diversity of Xtu and to assess the role of TALEs in bacterial leaf streak of wheat by comparing the genome of this strain to the recently completely sequenced genome of a U.S. Xtu strain, and to several other draft X. translucens genomes, and by carrying out mutational analyses of the TALE (tal) genes the Iranian strain might harbor. The ICMP11055 genome, including its repeat-rich tal genes, was completely sequenced using single molecule, real-time technology (Pacific Biosciences). It consists of a single circular chromosome of 4,561,583 bp, containing 3,953 genes. Whole genome alignment with the genome of the United States Xtu strain XT4699 showed two major re-arrangements, nine genomic regions unique to ICMP11055, and one region unique to XT4699. ICMP110055 harbors 26 non-TALE type III effector genes and seven tal genes, compared to 25 and eight for XT4699. The tal genes occur singly or in pairs across five scattered loci. Four are identical to tal genes in XT4699. In addition to common repeat-variable diresidues (RVDs), the tal genes of ICMP11055, like those of XT4699, encode several RVDs rarely observed in Xanthomonas, including KG, NF, Y^∗, YD, and YK. Insertion and deletion mutagenesis of ICMP11055 tal genes followed by genetic complementation analysis in wheat cv. Chinese Spring revealed that Tal2 and Tal4b of ICMP11055 each contribute individually to the extent of disease caused by this strain. A largely conserved ortholog of tal2 is present in XT4699, but for tal4b, only a gene with partial, fragmented RVD sequence similarity can be found. Our results lay the foundation for identification of important host genes activated by Xtu TALEs as targets for the development of disease resistant varieties.

TAL effector driven induction of a SWEET gene confers susceptibility to bacterial blight of cotton

Transcription activator-like (TAL) effectors from Xanthomonas citri subsp. malvacearum (Xcm) are essential for bacterial blight of cotton (BBC). Here, by combining transcriptome profiling with TAL effector-binding element (EBE) prediction, we show that GhSWEET10, encoding a functional sucrose transporter, is induced by Avrb6, a TAL effector determining Xcm pathogenicity. Activation of GhSWEET10 by designer TAL effectors (dTALEs) restores virulence of Xcm avrb6 deletion strains, whereas silencing of GhSWEET10 compromises cotton susceptibility to infections. A BBC-resistant line carrying an unknown recessive b6 gene bears the same EBE as the susceptible line, but Avrb6-mediated induction of GhSWEET10 is reduced, suggesting a unique mechanism underlying b6-mediated resistance. We show via an extensive survey of GhSWEET transcriptional responsiveness to different Xcm field isolates that additional GhSWEETs may also be involved in BBC. These findings advance our understanding of the disease and resistance in cotton and may facilitate the development cotton with improved resistance to BBC.

Transcription activator-like effectors contribute to virulence of the Xanthomonas strain responsible for bacterial blight in cotton. Here Cox et al. show that the Xanthomonas Avrb6 effector induces expression of the cotton SWEET10 sugar transporter and that this induction promotes disease.

Effector Diversification Contributes to Xanthomonas oryzae pv. oryzae Phenotypic Adaptation in a Semi-Isolated Environment

Understanding the processes that shaped contemporary pathogen populations in agricultural landscapes is quite important to define appropriate management strategies and to support crop improvement efforts. Here, we took advantage of an historical record to examine the adaptation pathway of the rice pathogen Xanthomonas oryzae pv. oryzae (Xoo) in a semi-isolated environment represented in the Philippine archipelago. By comparing genomes of key Xoo groups we showed that modern populations derived from three Asian lineages. We also showed that diversification of virulence factors occurred within each lineage, most likely driven by host adaptation, and it was essential to shape contemporary pathogen races. This finding is particularly important because it expands our understanding of pathogen adaptation to modern agriculture.

Single molecule real-time sequencing of Xanthomonas oryzae genomes reveals a dynamic structure and complex TAL (transcription activator-like) effector gene relationships

Pathogen-injected, direct transcriptional activators of host genes, TAL (transcription activator-like) effectors play determinative roles in plant diseases caused by Xanthomonas spp. A large domain of nearly identical, 33–35 aa repeats in each protein mediates DNA recognition. This modularity makes TAL effectors customizable and thus important also in biotechnology. However, the repeats render TAL effector (tal) genes nearly impossible to assemble using next-generation, short reads. Here, we demonstrate that long-read, single molecule real-time (SMRT) sequencing solves this problem. Taking an ensemble approach to first generate local, tal gene contigs, we correctly assembled de novo the genomes of two strains of the rice pathogen X. oryzae completed previously using the Sanger method and even identified errors in those references. Sequencing two more strains revealed a dynamic genome structure and a striking plasticity in tal gene content. Our results pave the way for population-level studies to inform resistance breeding, improve biotechnology and probe TAL effector evolution.

Online Tools for TALEN Design

Transcription activator-like effector nucleases (TALENs) can be exquisitely specific and highly effective genome editing reagents. Specificity and efficacy depend however on good design for minimal off-targeting and strong binding. Several online tools are accessible to aid in this process. Here, we tabulate those tools, noting their functions and key features.

Single molecule real-time sequencing of Xanthomonas oryzae genomes reveals a dynamic structure and complex TAL (transcription activator-like) effector gene relationships

Pathogen-injected, direct transcriptional activators of host genes, TAL (transcription activator-like) effectors play determinative roles in plant diseases caused by Xanthomonas spp. A large domain of nearly identical, 33-35 aa repeats in each protein mediates DNA recognition. This modularity makes TAL effectors customizable and thus important also in biotechnology. However, the repeats render TAL effector (tal) genes nearly impossible to assemble using next-generation, short reads. Here, we demonstrate that long-read, single molecule real-time (SMRT) sequencing solves this problem. Taking an ensemble approach to first generate local, tal gene contigs, we correctly assembled de novo the genomes of two strains of the rice pathogen X. oryzae completed previously using the Sanger method and even identified errors in those references. Sequencing two more strains revealed a dynamic genome structure and a striking plasticity in tal gene content. Our results pave the way for population-level studies to inform resistance breeding, improve biotechnology and probe TAL effector evolution.

TAL effectors and activation of predicted host targets distinguish Asian from African strains of the rice pathogen Xanthomonas oryzae pv. oryzicola while strict conservation suggests universal importance of five TAL effectors

Xanthomonas oryzae pv. oryzicola (Xoc) causes the increasingly important disease bacterial leaf streak of rice (BLS) in part by type III delivery of repeat-rich transcription activator-like (TAL) effectors to upregulate host susceptibility genes. By pathogen whole genome, single molecule, real-time sequencing and host RNA sequencing, we compared TAL effector content and rice transcriptional responses across 10 geographically diverse Xoc strains. TAL effector content is surprisingly conserved overall, yet distinguishes Asian from African isolates. Five TAL effectors are conserved across all strains. In a prior laboratory assay in rice cv. Nipponbare, only two contributed to virulence in strain BLS256 but the strict conservation indicates all five may be important, in different rice genotypes or in the field. Concatenated and aligned, TAL effector content across strains largely reflects relationships based on housekeeping genes, suggesting predominantly vertical transmission. Rice transcriptional responses did not reflect these relationships, and on average, only 28% of genes upregulated and 22% of genes downregulated by a strain are up- and down- regulated (respectively) by all strains. However, when only known TAL effector targets were considered, the relationships resembled those of the TAL effectors. Toward identifying new targets, we used the TAL effector-DNA recognition code to predict effector binding elements in promoters of genes upregulated by each strain, but found that for every strain, all upregulated genes had at least one. Filtering with a classifier we developed previously decreases the number of predicted binding elements across the genome, suggesting that it may reduce false positives among upregulated genes. Applying this filter and eliminating genes for which upregulation did not strictly correlate with presence of the corresponding TAL effector, we generated testable numbers of candidate targets for four of the five strictly conserved TAL effectors.

Tools for TAL effector design and target prediction

TAL effectors are transcription factors injected into plant cells by pathogenic bacteria during infection. They find their specific DNA targets via a string of contiguous, structural repeats that individually recognize single nucleotides (with some degeneracy) by virtue of polymorphisms at residue 13. The number of repeats and sequence of the amino acids at position 13 determine the nucleotide sequence of the DNA target. Due to this modularity, TAL effectors are readily engineered and have been used alone or as molecular fusions for targeted gene activation, gene repression, chromatin modification, chromatin tagging, and most broadly, for genome editing as TAL effector nucleases (TALENs). Several moderate and high-throughput cloning methods are in place for assembling TAL effector-based genetic constructs. Targeting is complicated to an extent by a general requirement for thymine to precede the DNA target, a requirement of TALENs to bind paired opposing sites separated by a defined range of distances, differential contributions of different repeat types to overall affinity, and a polarity to mismatch tolerance. Several computational tools are available online to aid in design and the identification of candidate off-target binding sites, as well as assembly and implementation. These tools vary in their approaches, capabilities, and relative utility for different types of TAL effector applications. Accuracy of off-target prediction is not well characterized yet for any of the tools and will require a better understanding of the qualitative and quantitative variation in the nucleotide preferences of individual repeats.

TAL Effector-Nucleotide Targeter (TALE-NT) 2.0: tools for TAL effector design and target prediction

Transcription activator-like (TAL) effectors are repeat-containing proteins used by plant pathogenic bacteria to manipulate host gene expression. Repeats are polymorphic and individually specify single nucleotides in the DNA target, with some degeneracy. A TAL effector-nucleotide binding code that links repeat type to specified nucleotide enables prediction of genomic binding sites for TAL effectors and customization of TAL effectors for use in DNA targeting, in particular as custom transcription factors for engineered gene regulation and as site-specific nucleases for genome editing. We have developed a suite of web-based tools called TAL Effector-Nucleotide Targeter 2.0 (TALE-NT 2.0; https://boglab.plp.iastate.edu/) that enables design of custom TAL effector repeat arrays for desired targets and prediction of TAL effector binding sites, ranked by likelihood, in a genome, promoterome or other sequence of interest. Search parameters can be set by the user to work with any TAL effector or TAL effector nuclease architecture. Applications range from designing highly specific DNA targeting tools and identifying potential off-target sites to predicting effector targets important in plant disease.