Widespread effects of DNA methylation and intra-motif dependencies revealed by novel transcription factor binding models.

Several studies suggested that transcription factor (TF) binding to DNA may be impaired or enhanced by DNA methylation. We present MeDeMo, a toolbox for TF motif analysis that combines information about DNA methylation with models capturing intra-motif dependencies. In a large-scale study using ChIP-seq data for 335 TFs, we identify novel TFs that show a binding behaviour associated with DNA methylation. Overall, we find that the presence of CpG methylation decreases the likelihood of binding for the majority of methylation-associated TFs. For a considerable subset of TFs, we show that intra-motif dependencies are pivotal for accurately modelling the impact of DNA methylation on TF binding. We illustrate that the novel methylation-aware TF binding models allow to predict differential ChIP-seq peaks and improve the genome-wide analysis of TF binding. Our work indicates that simplistic models that neglect the effect of DNA methylation on DNA binding may lead to systematic underperformance for methylation-associated TFs.

Assembling highly repetitive Xanthomonas TALomes using Oxford Nanopore sequencing.

BACKGROUND: Most plant-pathogenic Xanthomonas bacteria harbor transcription activator-like effector (TALE) genes, which function as transcriptional activators of host plant genes and support infection. The entire repertoire of up to 29 TALE genes of a Xanthomonas strain is also referred to as TALome. The DNA-binding domain of TALEs is comprised of highly conserved repeats and TALE genes often occur in gene clusters, which precludes the assembly of TALE-carrying Xanthomonas genomes based on standard sequencing approaches. RESULTS: Here, we report the successful assembly of the 5 Mbp genomes of five Xanthomonas strains from Oxford Nanopore Technologies (ONT) sequencing data. For one of these strains, Xanthomonas oryzae pv. oryzae (Xoo) PXO35, we illustrate why Illumina short reads and longer PacBio reads are insufficient to fully resolve the genome. While ONT reads are perfectly suited to yield highly contiguous genomes, they suffer from a specific error profile within homopolymers. To still yield complete and correct TALomes from ONT assemblies, we present a computational correction pipeline specifically tailored to TALE genes, which yields at least comparable accuracy as Illumina-based polishing. We further systematically assess the ONT-based pipeline for its multiplexing capacity and find that, combined with computational correction, the complete TALome of Xoo PXO35 could have been reconstructed from less than 20,000 ONT reads. CONCLUSIONS: Our results indicate that multiplexed ONT sequencing combined with a computational correction of TALE genes constitutes a highly capable tool for characterizing the TALomes of huge collections of Xanthomonas strains in the future.

Importance of RpoD- and Non-RpoD-Dependent Expression of Horizontally Acquired Genes in Cupriavidus metallidurans.

The genome of the metal-resistant, hydrogen-oxidizing bacterium Cupriavidus metallidurans contains a large number of horizontally acquired plasmids and genomic islands that were integrated into its chromosome or chromid. For the C. metallidurans CH34 wild-type strain growing under nonchallenging conditions, 5,763 transcriptional starting sequences (TSSs) were determined. Using a custom-built motif discovery software based on hidden Markov models, patterns upstream of the TSSs were identified. The pattern TTGACA, -35.6 ± 1.6 bp upstream of the TSSs, in combination with a TATAAT sequence 15.8 ± 1.4 bp upstream occurred frequently, especially upstream of the TSSs for 48 housekeeping genes, and these were assigned to promoters used by RNA polymerase containing the main housekeeping sigma factor RpoD. From patterns upstream of the housekeeping genes, a score for RpoD-dependent promoters in C. metallidurans was derived and applied to all 5,763 TSSs. Among these, 2,572 TSSs could be associated with RpoD with high probability, 373 with low probability, and 2,818 with no probability. In a detailed analysis of horizontally acquired genes involved in metal resistance and not involved in this process, the TSSs responsible for the expression of these genes under nonchallenging conditions were assigned to RpoD- or non-RpoD-dependent promoters. RpoD-dependent promoters occurred frequently in horizontally acquired metal resistance and other determinants, which should allow their initial expression in a new host. However, other sigma factors and sense/antisense effects also contribute-maybe to mold in subsequent adaptation steps the assimilated gene into the regulatory network of the cell. IMPORTANCE In their natural environment, bacteria are constantly acquiring genes by horizontal gene transfer. To be of any benefit, these genes should be expressed. We show here that the main housekeeping sigma factor RpoD plays an important role in the expression of horizontally acquired genes in the metal-resistant hydrogen-oxidizing bacterium C. metallidurans. By conservation of the RpoD recognition consensus sequence, a newly arriving gene has a high probability to be expressed in the new host cell. In addition to integrons and genes travelling together with that for their sigma factor, conservation of the RpoD consensus sequence may be an important contributor to the overall evolutionary success of horizontal gene transfer in bacteria. Using C. metallidurans as an example, this publication sheds some light on the fate and function of horizontally acquired genes in bacteria.

Flexible TALEs for an expanded use in gene activation, virulence and scaffold engineering.

Transcription activator-like effectors (TALEs) are bacterial proteins with a programmable DNA-binding domain, which turned them into exceptional tools for biotechnology. TALEs contain a central array of consecutive 34 amino acid long repeats to bind DNA in a simple one-repeat-to-one-nucleotide manner. However, a few naturally occurring aberrant repeat variants break this strict binding mechanism, allowing for the recognition of an additional sequence with a -1 nucleotide frameshift. The limits and implications of this extended TALE binding mode are largely unexplored. Here, we analyse the complete diversity of natural and artificially engineered aberrant repeats for their impact on the DNA binding of TALEs. Surprisingly, TALEs with several aberrant repeats can loop out multiple repeats simultaneously without losing DNA-binding capacity. We also characterized members of the only natural TALE class harbouring two aberrant repeats and confirmed that their target is the major virulence factor OsSWEET13 from rice. In an aberrant TALE repeat, the position and nature of the amino acid sequence strongly influence its function. We explored the tolerance of TALE repeats towards alterations further and demonstrate that inserts as large as GFP can be tolerated without disrupting DNA binding. This illustrates the extraordinary DNA-binding capacity of TALEs and opens new uses in biotechnology.

Epigenetic features improve TALE target prediction.

BACKGROUND: The yield of many crop plants can be substantially reduced by plant-pathogenic Xanthomonas bacteria. The infection strategy of many Xanthomonas strains is based on transcription activator-like effectors (TALEs), which are secreted into the host cells and act as transcriptional activators of plant genes that are beneficial for the bacteria.The modular DNA binding domain of TALEs contains tandem repeats, each comprising two hyper-variable amino acids. These repeat-variable diresidues (RVDs) bind to their target box and determine the specificity of a TALE.All available tools for the prediction of TALE targets within the host plant suffer from many false positives. In this paper we propose a strategy to improve prediction accuracy by considering the epigenetic state of the host plant genome in the region of the target box. RESULTS: To this end, we extend our previously published tool PrediTALE by considering two epigenetic features: (i) chromatin accessibility of potentially bound regions and (ii) DNA methylation of cytosines within target boxes. Here, we determine the epigenetic features from publicly available DNase-seq, ATAC-seq, and WGBS data in rice.We benchmark the utility of both epigenetic features separately and in combination, deriving ground-truth from RNA-seq data of infections studies in rice. We find an improvement for each individual epigenetic feature, but especially the combination of both.Having established an advantage in TALE target predicting considering epigenetic features, we use these data for promoterome and genome-wide scans by our new tool EpiTALE, leading to several novel putative virulence targets. CONCLUSIONS: Our results suggest that it would be worthwhile to collect condition-specific chromatin accessibility data and methylation information when studying putative virulence targets of Xanthomonas TALEs.

Insights gained from a comprehensive all-against-all transcription factor binding motif benchmarking study.

BACKGROUND: Positional weight matrix (PWM) is a de facto standard model to describe transcription factor (TF) DNA binding specificities. PWMs inferred from in vivo or in vitro data are stored in many databases and used in a plethora of biological applications. This calls for comprehensive benchmarking of public PWM models with large experimental reference sets. RESULTS: Here we report results from all-against-all benchmarking of PWM models for DNA binding sites of human TFs on a large compilation of in vitro (HT-SELEX, PBM) and in vivo (ChIP-seq) binding data. We observe that the best performing PWM for a given TF often belongs to another TF, usually from the same family. Occasionally, binding specificity is correlated with the structural class of the DNA binding domain, indicated by good cross-family performance measures. Benchmarking-based selection of family-representative motifs is more effective than motif clustering-based approaches. Overall, there is good agreement between in vitro and in vivo performance measures. However, for some in vivo experiments, the best performing PWM is assigned to an unrelated TF, indicating a binding mode involving protein-protein cooperativity. CONCLUSIONS: In an all-against-all setting, we compute more than 18 million performance measure values for different PWM-experiment combinations and offer these results as a public resource to the research community. The benchmarking protocols are provided via a web interface and as docker images. The methods and results from this study may help others make better use of public TF specificity models, as well as public TF binding data sets.

PrediTALE: A novel model learned from quantitative data allows for new perspectives on TALE targeting.

Plant-pathogenic Xanthomonas bacteria secrete transcription activator-like effectors (TALEs) into host cells, where they act as transcriptional activators on plant target genes to support bacterial virulence. TALEs have a unique modular DNA-binding domain composed of tandem repeats. Two amino acids within each tandem repeat, termed repeat-variable diresidues, bind to contiguous nucleotides on the DNA sequence and determine target specificity. In this paper, we propose a novel approach for TALE target prediction to identify potential virulence targets. Our approach accounts for recent findings concerning TALE targeting, including frame-shift binding by repeats of aberrant lengths, and the flexible strand orientation of target boxes relative to the transcription start of the downstream target gene. The computational model can account for dependencies between adjacent RVD positions. Model parameters are learned from the wealth of quantitative data that have been generated over the last years. We benchmark the novel approach, termed PrediTALE, using RNA-seq data after Xanthomonas infection in rice, and find an overall improvement of prediction performance compared with previous approaches. Using PrediTALE, we are able to predict several novel putative virulence targets. However, we also observe that no target genes are predicted by any prediction tool for several TALEs, which we term orphan TALEs for this reason. We postulate that one explanation for orphan TALEs are incomplete gene annotations and, hence, propose to replace promoterome-wide by genome-wide scans for target boxes. We demonstrate that known targets from promoterome-wide scans may be recovered by genome-wide scans, whereas the latter, combined with RNA-seq data, are able to detect putative targets independent of existing gene annotations.

DepLogo: visualizing sequence dependencies in R.

SUMMARY: Statistical dependencies are present in a variety of sequence data, but are not discernible from traditional sequence logos. Here, we present the R package DepLogo for visualizing inter-position dependencies in aligned sequence data as dependency logos. Dependency logos make dependency structures, which correspond to regular co-occurrences of symbols at dependent positions, visually perceptible. To this end, sequences are partitioned based on their symbols at highly dependent positions as measured by mutual information, and each partition obtains its own visual representation. We illustrate the utility of the DepLogo package in several use cases generating dependency logos from DNA, RNA and protein sequences. AVAILABILITY AND IMPLEMENTATION: The DepLogo R package is available from CRAN and its source code is available at https://github.com/Jstacs/DepLogo. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data.

GeMoMa is a homology-based gene prediction program that predicts gene models in target species based on gene models in evolutionary related reference species. GeMoMa utilizes amino acid sequence conservation, intron position conservation, and RNA-seq data to accurately predict protein-coding transcripts. Furthermore, GeMoMa supports the combination of predictions based on several reference species allowing to transfer high-quality annotation of different reference species to a target species. Here, we present a detailed description of GeMoMa modules and the GeMoMa pipeline and how they can be used on the command line to address particular biological problems.

Transcriptional Reprogramming of Rice Cells by Xanthomonas oryzae TALEs.

Rice-pathogenic Xanthomonas oryzae bacteria cause severe harvest loss and challenge a stable food supply. The pathogen virulence relies strongly on bacterial TALE (transcription activator-like effector) proteins that function as transcriptional activators inside the plant cell. To understand the plant targets of TALEs, we determined the genome sequences of the Indian X. oryzae pv. oryzae (Xoo) type strain ICMP 3125T and the strain PXO142 from the Philippines. Their complete TALE repertoire was analyzed and genome-wide TALE targets in rice were characterized. Integrating computational target predictions and rice transcriptomics data, we were able to verify 12 specifically induced target rice genes. The TALEs of the Xoo strains were reconstructed and expressed in a TALE-free Xoo strain to attribute specific induced genes to individual TALEs. Using reporter assays, we could show that individual TALEs act directly on their target promoters. In particular, we show that TALE classes assigned by AnnoTALE reflect common target genes, and that TALE classes of Xoo and the related pathogen X. oryzae pv. oryzicola share more common target genes than previously believed. Taken together, we establish a detailed picture of TALE-induced plant processes that significantly expands our understanding of X. oryzae virulence strategies and will facilitate the development of novel resistances to overcome this important rice disease.

Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases.

Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.

Accurate prediction of cell type-specific transcription factor binding.

Prediction of cell type-specific, in vivo transcription factor binding sites is one of the central challenges in regulatory genomics. Here, we present our approach that earned a shared first rank in the "ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge" in 2017. In post-challenge analyses, we benchmark the influence of different feature sets and find that chromatin accessibility and binding motifs are sufficient to yield state-of-the-art performance. Finally, we provide 682 lists of predicted peaks for a total of 31 transcription factors in 22 primary cell types and tissues and a user-friendly version of our approach, Catchitt, for download.

A conserved motif promotes HpaB-regulated export of type III effectors from Xanthomonas.

The type III secretion (T3S) system, an essential pathogenicity factor in most Gram-negative plant-pathogenic bacteria, injects bacterial effector proteins directly into the plant cell cytosol. Here, the type III effectors (T3Es) manipulate host cell processes to suppress defence and establish appropriate conditions for bacterial multiplication in the intercellular spaces of the plant tissue. T3E export depends on a secretion signal which is also present in 'non-effectors'. The latter are secreted extracellular components of the T3S apparatus, but are not translocated into the plant cell. How the T3S system discriminates between T3Es and non-effectors is still enigmatic. Previously, we have identified a putative translocation motif (TrM) in several T3Es from Xanthomonas campestris pv. vesicatoria (Xcv). Here, we analysed the TrM of the Xcv effector XopB in detail. Mutation studies showed that the proline/arginine-rich motif is required for efficient type III-dependent secretion and translocation of XopB and determines the dependence of XopB transport on the general T3S chaperone HpaB. Similar results were obtained for other effectors from Xcv. As the arginine residues of the TrM mediate specific binding of XopB to cardiolipin, one of the major lipid components in Xanthomonas membranes, we assume that the association of T3Es to the bacterial membrane prior to secretion supports type III-dependent export.

Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi.

BACKGROUND: Genome annotation is of key importance in many research questions. The identification of protein-coding genes is often based on transcriptome sequencing data, ab-initio or homology-based prediction. Recently, it was demonstrated that intron position conservation improves homology-based gene prediction, and that experimental data improves ab-initio gene prediction. RESULTS: Here, we present an extension of the gene prediction program GeMoMa that utilizes amino acid sequence conservation, intron position conservation and optionally RNA-seq data for homology-based gene prediction. We show on published benchmark data for plants, animals and fungi that GeMoMa performs better than the gene prediction programs BRAKER1, MAKER2, and CodingQuarry, and purely RNA-seq-based pipelines for transcript identification. In addition, we demonstrate that using multiple reference organisms may help to further improve the performance of GeMoMa. Finally, we apply GeMoMa to four nematode species and to the recently published barley reference genome indicating that current annotations of protein-coding genes may be refined using GeMoMa predictions. CONCLUSIONS: GeMoMa might be of great utility for annotating newly sequenced genomes but also for finding homologs of a specific gene or gene family. GeMoMa has been published under GNU GPL3 and is freely available at http://www.jstacs.de/index.php/GeMoMa .

Evolution of Transcription Activator-Like Effectors in Xanthomonas oryzae.

Transcription activator-like effectors (TALEs) are secreted by plant-pathogenic Xanthomonas bacteria into plant cells where they act as transcriptional activators and, hence, are major drivers in reprogramming the plant for the benefit of the pathogen. TALEs possess a highly repetitive DNA-binding domain of typically 34 amino acid (AA) tandem repeats, where AA 12 and 13, termed repeat variable di-residue (RVD), determine target specificity. Different Xanthomonas strains possess different repertoires of TALEs. Here, we study the evolution of TALEs from the level of RVDs determining target specificity down to the level of DNA sequence with focus on rice-pathogenic Xanthomonas oryzae pv. oryzae (Xoo) and Xanthomonas oryzae pv. oryzicola (Xoc) strains. We observe that codon pairs coding for individual RVDs are conserved to a similar degree as the flanking repeat sequence. We find strong indications that TALEs may evolve 1) by base substitutions in codon pairs coding for RVDs, 2) by recombination of N-terminal or C-terminal regions of existing TALEs, or 3) by deletion of individual TALE repeats, and we propose possible mechanisms. We find indications that the reassortment of TALE genes in clusters is mediated by an integron-like mechanism in Xoc. We finally study the effect of the presence/absence and evolutionary modifications of TALEs on transcriptional activation of putative target genes in rice, and find that even single RVD swaps may lead to considerable differences in activation. This correlation allowed a refined prediction of TALE targets, which is the crucial step to decipher their virulence activity.

Correction: Dissection of TALE-dependent gene activation reveals that they induce transcription cooperatively and in both orientations.

[This corrects the article DOI: 10.1371/journal.pone.0173580.].

Dissection of TALE-dependent gene activation reveals that they induce transcription cooperatively and in both orientations.

Plant-pathogenic Xanthomonas bacteria inject transcription activator-like effector proteins (TALEs) into host cells to specifically induce transcription of plant genes and enhance susceptibility. Although the DNA-binding mode is well-understood it is still ambiguous how TALEs initiate transcription and whether additional promoter elements are needed to support this. To systematically dissect prerequisites for transcriptional initiation the activity of one TALE was compared on different synthetic Bs4 promoter fragments. In addition, a large collection of artificial TALEs spanning the OsSWEET14 promoter was compared. We show that the presence of a TALE alone is not sufficient to initiate transcription suggesting the requirement of additional supporting promoter elements. At the OsSWEET14 promoter TALEs can initiate transcription from various positions, in a synergistic manner of multiple TALEs binding in parallel to the promoter, and even by binding in reverse orientation. TALEs are known to shift the transcriptional start site, but our data show that this shift depends on the individual position of a TALE within a promoter context. Our results implicate that TALEs function like classical enhancer-binding proteins and initiate transcription in both orientations which has consequences for in planta target gene prediction and design of artificial activators.

InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites.

Summary: Recent studies have shown that the traditional position weight matrix model is often insufficient for modeling transcription factor binding sites, as intra-motif dependencies play a significant role for an accurate description of binding motifs. Here, we present the Java application InMoDe, a collection of tools for learning, leveraging and visualizing such dependencies of putative higher order. The distinguishing feature of InMoDe is a robust model selection from a class of parsimonious models, taking into account dependencies only if justified by the data while choosing for simplicity otherwise. Availability and Implementation: InMoDe is implemented in Java and is available as command line application, as application with a graphical user-interface, and as an integration into Galaxy on the project website at http://www.jstacs.de/index.php/InMoDe . Contact: ralf.eggeling@cs.helsinki.fi.

Auxin-induced expression divergence between Arabidopsis species may originate within the TIR1/AFB-AUX/IAA-ARF module.

Auxin is an essential regulator of plant growth and development, and auxin signaling components are conserved among land plants. Yet, a remarkable degree of natural variation in physiological and transcriptional auxin responses has been described among Arabidopsis thaliana accessions. As intraspecies comparisons offer only limited genetic variation, we here inspect the variation of auxin responses between A. thaliana and A. lyrata. This approach allowed the identification of conserved auxin response genes including novel genes with potential relevance for auxin biology. Furthermore, promoter divergences were analyzed for putative sources of variation. De novo motif discovery identified novel and variants of known elements with potential relevance for auxin responses, emphasizing the complex, and yet elusive, code of element combinations accounting for the diversity in transcriptional auxin responses. Furthermore, network analysis revealed correlations of interspecies differences in the expression of AUX/IAA gene clusters and classic auxin-related genes. We conclude that variation in general transcriptional and physiological auxin responses may originate substantially from functional or transcriptional variations in the TIR1/AFB, AUX/IAA, and ARF signaling network. In that respect, AUX/IAA gene expression divergence potentially reflects differences in the manner in which different species transduce identical auxin signals into gene expression responses.

Using intron position conservation for homology-based gene prediction.

Annotation of protein-coding genes is very important in bioinformatics and biology and has a decisive influence on many downstream analyses. Homology-based gene prediction programs allow for transferring knowledge about protein-coding genes from an annotated organism to an organism of interest.Here, we present a homology-based gene prediction program called GeMoMa. GeMoMa utilizes the conservation of intron positions within genes to predict related genes in other organisms. We assess the performance of GeMoMa and compare it with state-of-the-art competitors on plant and animal genomes using an extended best reciprocal hit approach. We find that GeMoMa often makes more precise predictions than its competitors yielding a substantially increased number of correct transcripts. Subsequently, we exemplarily validate GeMoMa predictions using Sanger sequencing. Finally, we use RNA-seq data to compare the predictions of homology-based gene prediction programs, and find again that GeMoMa performs well.Hence, we conclude that exploiting intron position conservation improves homology-based gene prediction, and we make GeMoMa freely available as command-line tool and Galaxy integration.