Base-pair Resolution Research Articles

Deep neural networks identify sequence context features predictive of transcription factor binding.

Transcription factors (TFs) bind DNA by recognizing specific sequence motifs, typically of length 6–12bp. A motif can occur many thousands of times in the human genome, but only a subset of those sites are actually bound. Here we present a machine learning framework leveraging existing convolutional neural network architectures and model interpretation techniques to identify and interpret sequence context features most important for predicting whether a particular motif instance will be bound. We apply our framework to predict binding at motifs for 38 TFs in a lymphoblastoid cell line, score the importance of context sequences at base-pair resolution, and characterize context features most predictive of binding. We find that the choice of training data heavily influences classification accuracy and the relative importance of features such as open chromatin. Overall, our framework enables novel insights into features predictive of TF binding and is likely to inform future deep learning applications to interpret non-coding genetic variants.

A High-throughput Pipeline to Determine DNA and Nucleosome Conformations by AFM Imaging

Atomic force microscopy (AFM) is a powerful tool to image macromolecular complexes with nanometer resolution and exquisite single-molecule sensitivity. While AFM imaging is well-established to investigate DNA and nucleoprotein complexes, AFM studies are often limited by small datasets and manual image analysis that is slow and prone to user bias. Recently, we have shown that a combination of large scale AFM imaging and automated image analysis of nucleosomes can overcome these previous limitations of AFM nucleoprotein studies. Using our high-throughput imaging and analysis pipeline, we have resolved nucleosome wrapping intermediates with five base pair resolution and revealed how distinct nucleosome variants and environmental conditions affect the unwrapping pathways of nucleosomal DNA. Here, we provide a detailed protocol of our workflow to analyze DNA and nucleosome conformations focusing on practical aspects and experimental parameters. We expect our protocol to drastically enhance AFM analyses of DNA and nucleosomes and to be readily adaptable to a wide variety of other protein and protein-nucleic acid complexes.

Genome-Wide Functional Screen of 3’UTR Variants Uncovers Causal Variants for Human Disease and Evolution

3’ untranslated region (3’UTR) variants are strongly associated with human traits and diseases, yet few have been causally identified. We developed the Massively Parallel Reporter Assay for 3’UTRs (MPRAu) to sensitively assay 12,173 3’UTR variants. We applied MPRAu to six human cell lines, focusing on genetic variants associated with genome-wide association studies (GWAS) and human evolutionary adaptation. MPRAu expands our understanding of 3’UTR function, suggesting that low-complexity sequences predominately explain 3’UTR regulatory activity. We adapt MPRAu to uncover diverse molecular mechanisms at base-pair resolution, including an AU-rich element of LEPR linked to potential metabolic evolutionary adaptations in East Asians. We nominate hundreds of 3’UTR causal variants with genetically fine-mapped phenotype associations. Using endogenous allelic replacements, we characterize one variant that disrupts a miRNA site regulating the viral defense gene TRIM14, and one that alters PILRB abundance, nominating a causal variant underlying transcriptional changes in age-related macular degeneration.

Estimating Global Methylation and Erasure Using Low-Coverage Whole-Genome Bisulfite Sequencing (WGBS ).

Whole-genome bisulfite sequencing (WGBS) is a popular method for characterizing cytosine methylation because it is fully quantitative and has base-pair resolution. While WGBS is prohibitively expensive for experiments involving many samples, low-coverage WGBS can accurately determine global methylation and erasure at similar cost to high-performance liquid chromatography (HPLC) or enzyme-linked immunosorbent assays (ELISA). Moreover, low-coverage WGBS has the capacity to distinguish between methylation in different cytosine contexts (e.g., CG, CHH, and CHG), can tolerate low-input material (<100cells), and can detect the presence of overrepresented DNA originating from mitochondria or amplified ribosomal DNA. In addition to describing a WGBS library construction and quantitation approach, here we detail computational methods to predict the accuracy of low-coverage WGBS using empirical bootstrap samplers and theoretical estimators similar to those used in election polling. Using examples, we further demonstrate how non-independent sampling of cytosines can alter the precision of error calculation and provide methods to improve this.

Progress and challenges in CRISPR-mediated therapeutic genome editing for monogenic diseases.

There are an estimated 10 000 monogenic diseases affecting tens of millions of individuals worldwide. The application of CRISPR/Cas genome editing tools to treat monogenic diseases is an emerging strategy with the potential to generate personalized treatment approaches for these patients. CRISPR/Cas-based systems are programmable and sequence-specific genome editing tools with the capacity to generate base pair resolution manipulations to DNA or RNA. The complexity of genomic insults resulting in heritable disease requires patient-specific genome editing strategies with consideration of DNA repair pathways, and CRISPR/Cas systems of different types, species, and those with additional enzymatic capacity and/or delivery methods. In this review we aim to discuss broad and multifaceted therapeutic applications of CRISPR/Cas gene editing systems including in harnessing of homology directed repair, non-homologous end joining, microhomology-mediated end joining, and base editing to permanently correct diverse monogenic diseases.

Methrix: an R/Bioconductor package for systematic aggregation and analysis of bisulfite sequencing data.

Whole-genome bisulfite sequencing (WGBS) measures DNA methylation at base pair resolution resulting in large bedGraph like coverage files. Current options for processing such files are hindered by discrepancies in file format specification, speed, and memory requirements. We developed methrix, an R package, which provides a toolset for systematic analysis of large datasets. Core functionality of the package includes a comprehensive bedGraph or similar tab-separated text file reader-which summarizes methylation calls based on annotated reference indices, infers and collapses strands and handles uncovered reference CpG sites while facilitating a flexible input file format specification. Additional optimized functions for quality control filtering, subsetting and visualization allow user-friendly and effective processing of WGBS results. Easy integration with tools for differentially methylated region (DMR) calling and annotation further eases the analysis of genome-wide methylation data. Overall, methrix enriches established WGBS workflows by bringing together computational efficiency and versatile functionality. Methrix is implemented as an R package, made available under MIT license at https://github.com/CompEpigen/methrix and can be installed from the Bioconductor repository. Supplementary data are available at Bioinformatics online.

Employing the CRISPR-Cas System for Clonal Hematopoiesis Research.

Clonal hematopoiesis is a state in which substantial fraction of hematopoietic stem cells acquire mutations in specific driver genes and expand in the absence of an overt hematological malignancy. Recent clinical studies have shown that clonal hematopoiesis increases likelihood of hematological malignancy and cardiovascular disease. While clinical studies have identified countless candidate driver genes associated with clonal hematopoiesis, experimental studies are required to evaluate causal and mechanistic relationships with disease processes. This task is technically difficult and expensive to achieve with traditional genetically engineered mice. The versatility and programmability of CRISPR-Cas system enables investigators to evaluate the pathogenesis of each mutation in experimental systems. Technical refinements have enabled gene editing in a cell type specific manner and at a single base pair resolution. Here, we summarize strategies to apply CRISPR-Cas system to experimental studies of clonal hematopoiesis and concerns that should be addressed.

Diabetes changes gene expression but not DNA methylation in cardiac cells

BackgroundDiabetes mellitus is a worldwide epidemic that causes high mortality due to cardiovascular complications, in particular heart failure. Diabetes is associated with profound pathophysiological changes in the heart. The aim of this study was to investigate the impact of diabetes on gene expression and DNA methylation in cardiac cells. Methods and resultsTranscriptome analysis of heart tissue from mice with streptozotocin-induced diabetes revealed only 39 genes regulated, whereas cell type-specific analysis of the diabetic heart was more sensitive and more specific than heart tissue analysis and revealed a total of 3205 differentially regulated genes in five cell types. Whole genome DNA methylation analysis with basepair resolution of distinct cardiac cell types identified highly specific DNA methylation signatures of genic and regulatory regions. Interestingly, despite marked changes in gene expression, DNA methylation remained stable in streptozotocin-induced diabetes. Integrated analysis of cell type-specific gene expression enabled us to assign the particular contribution of single cell types to the pathophysiology of the diabetic heart. Finally, analysis of gene regulation revealed ligand-receptor pairs as potential mediators of heterocellular interaction in the diabetic heart, with fibroblasts and monocytes showing the highest degree of interaction. ConclusionIn summary, cell type-specific analysis reveals differentially regulated gene programs that are associated with distinct biological processes in diabetes. Interestingly, despite these changes in gene expression, cell type-specific DNA methylation signatures of genic and regulatory regions remain stable in diabetes. Analysis of heterocellular interactions in the diabetic heart suggest that the interplay between fibroblasts and monocytes is of pivotal importance.

Bisulfite treatment and single-molecule real-time sequencing reveal D-loop length, position, and distribution.

Displacement loops (D-loops) are signature intermediates formed during homologous recombination. Numerous factors regulate D-loop formation and disruption, thereby influencing crucial aspects of DNA repair, including donor choice and the possibility of crossover outcome. While D-loop detection methods exist, it is currently unfeasible to assess the relationship between D-loop editors and D-loop characteristics such as length and position. Here, we developed a novel in vitro assay to characterize the length and position of individual D-loops with near base-pair resolution and deep coverage, while also revealing their distribution in a population. Non-denaturing bisulfite treatment modifies the cytosines on the displaced strand of the D-loop to uracil, leaving a permanent signature for the displaced strand. Subsequent single-molecule real-time sequencing uncovers the cytosine conversion patch as a D-loop footprint. The D-loop Mapping Assay is widely applicable with different substrates and donor types and can be used to study factors that influence D-loop properties.

Abstract IA06: Molecular classification of diffuse large B-cell lymphoma

Abstract Key PointsSequencing-based approaches are readily used for molecular classifications of diffuse large B-cell lymphomaGenetically distinct diffuse large B-cell lymphoma provides insights into unique lymphomagenesis, prognosis prediction, and combination of targeted treatmentsGenetic classifiers identify novel vulnerabilities and inform clinical trial designs Heterogeneity of Diffuse Large B-Cell Lymphoma. Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive B-cell non-Hodgkin lymphoma and is thought to arise from antigen-exposed B cells. Although the majority of patients with DLBCL are curable with combination immunochemotherapy consisting of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP), a substantial fraction of patients develop recurrent or progressive disease that is often fatal. The clinical heterogeneity of these tumors prompted the development of various classification schemes and included molecular classifiers that i.) improved the accuracy of diagnosis, ii.) identified relevant molecular subtypes with distinct biology, iii.) developed prognostic models for relevant clinical endpoints, and iv.) stratified patients for disease management. The heterogeneity of DLBCL is partially captured in clinically and/or transcriptionally defined subtypes that provide insights into disease pathogenesis and candidate treatment targets. However, patient stratification for treatment-based transcriptional subtypes, including the activated B-cell type (ABC) and the germinal center B-cell type (GCB), has been largely unsuccessful thus far and suggested that additional heterogeneity had not been fully captured. Technical advantages paved the way for next-generation sequencing (NGS)-based techniques to be included in clinical and/or low-throughput-based molecular classifiers. These technologies allowed detection and prioritization of all genetic alteration types—recurrent mutations, somatic copy number alterations (SCNAs), and structural variants (SVs) —followed by an integration and assessment of their temporal ordering and associated transcriptional profiles. Genetic Heterogeneity of DLBCL. Recently, two independent comprehensive genomic efforts at base-pair resolution of hundreds of patients diagnosed with primary DLBCL have captured the complex intrinsic genetic heterogeneity of these lymphomas and have shed light on the genomic architecture of DLBCL. Integration of significant genetic alterations composed of recurrent somatic mutations, SCNAs and SVs, resulted in the discovery of at least 5 genetically distinct DLBCL subsets that predicted outcome to state-of-the-art frontline treatment, suggesting new insights into the lymphomagenesis of DLBCLs and rational combination treatments. These 5 subsets included: 1) a high-risk ABC DLBCLs with near-uniform BCL2 copy gain, frequent activating MYD88 and CD79B mutations, and extranodal tropism (C5 DLBCLs); 2) favorable-risk ABC-DLBCLs with genetic features of an extrafollicular, possibly marginal zone origin (C1 DLBCLs); 3) poor-risk GCB-DLBCLs with BCL2 SVs, inactivating mutations, and/or copy loss of PTEN and alterations of epigenetic enzymes (C3 DLBCLs); 4) a good-risk GCB-DLBCLs with distinct alterations in BCR/PI3K, JAK/STAT, and BRAF pathway components and multiple histones (C4 DLBCLs); and 5) an ABC/GCB-independent group of tumors with biallelic inactivation of TP53, 9p21.3/CDKN2A, and associated genomic instability (C2 DLBCLs). The biology of these 5 DLBCL subsets was largely confirmed by an independent non-overlapping large-scale study that followed a completely different analytical approach and discovered similar groups with shared pathogenetic mechanisms. In particular, C1 DLBCLs were similar to BN2 (BCL6/NOTCH2), C3 DLBCLs were similar to EZB (EZH2/BCL2), and C5 DLBCLs were similar to MCD (MYD88/CD79B). In subsequent work, the biology of the remaining DLBCL subtypes (C2 and C4 DLBLCs) was recently independently validated by two other groups (C4 ~ ST2; C2 ~ A53 | C4 ~ SGK1; C2 ~ TP53). These studies underscore that DLBCL is a genetically heterogenous disease with at least 5-7 different molecular subtypes. At the same time, they also highlight that despite having several hundreds of sequenced tumors, we still do not capture the full spectrum of DLBCL subsets, and for low-frequency subtypes in particular larger sample sizes are needed. More work is needed, to link genetically defined subtypes to actionable vulnerabilities, and eventually build molecular classifiers that link genetics to dependencies with the hope of using them for precision medical trials. Citation Format: Bjoern Chapuy. Molecular classification of diffuse large B-cell lymphoma [abstract]. In: Proceedings of the AACR Virtual Meeting: Advances in Malignant Lymphoma; 2020 Aug 17-19. Philadelphia (PA): AACR; Blood Cancer Discov 2020;1(3_Suppl):Abstract nr IA06.

Deciphering the regulatory genome of Escherichia coli, one hundred promoters at a time.

Advances in DNA sequencing have revolutionized our ability to read genomes. However, even in the most well-studied of organisms, the bacterium Escherichia coli, for ≈65% of promoters we remain ignorant of their regulation. Until we crack this regulatory Rosetta Stone, efforts to read and write genomes will remain haphazard. We introduce a new method, Reg-Seq, that links massively parallel reporter assays with mass spectrometry to produce a base pair resolution dissection of more than a E. coli promoters in 12 growth conditions. We demonstrate that the method recapitulates known regulatory information. Then, we examine regulatory architectures for more than 80 promoters which previously had no known regulatory information. In many cases, we also identify which transcription factors mediate their regulation. This method clears a path for highly multiplexed investigations of the regulatory genome of model organisms, with the potential of moving to an array of microbes of ecological and medical relevance.

Studying DNA Methylation Genome-Wide by Bisulfite Sequencing from Low Amounts of DNA in Mammals.

DNA methylation is extensively reprogrammed during mammalian embryogenesis and germ cell development. Protocols for genome-wide bisulfite sequencing enable the quantification of DNA methylation with high precision and single base-pair resolution; however they can be limited by the necessity for high amounts of DNA. Here we describe optimized reduced representation bisulfite sequencing (RRBS) and whole genome bisulfite sequencing (WGBS) protocols for low amounts of DNA, which include steps to estimate the minimal number of PCR cycles needed for the final library preparation to minimize PCR biases. These protocols require no more than 5ng DNA and can easily be applied to mammalian cells available in small quantities such as early embryos or primordial germ cells.

Assessment of tumor suppressor promoter methylation in healthy individuals

BackgroundThe number of tumor suppressor genes for which germline mutations have been linked to cancer risk is steadily increasing. However, while recent reports have linked constitutional normal tissue promoter methylation of BRCA1 and MLH1 to ovarian and colon cancer risk, the role of epigenetic alterations as cancer risk factors remains largely unknown, presenting an important area for future research. Currently, we lack fast and sensitive methods for assessment of promoter methylation status across known tumor suppressor genes.ResultsIn this paper, we present a novel NGS-based approach assessing promoter methylation status across a large panel of defined tumor suppressor genes to base-pair resolution. The method omits the limitations related to commonly used array-approaches. Our panel includes 565 target regions covering the promoters of 283 defined tumor suppressors, selected by pre-specified criteria, and was applied for rapid targeted methylation-specific NGS. The feasibility of the method was assessed by analyzing normal tissue DNA (white blood cells, WBC) samples from 34 healthy postmenopausal women and by performing preliminary assessment of the methylation landscape of tumor suppressors in these individuals. The mean target coverage was 189.6x providing a sensitivity of 0.53%, sufficient for promoter methylation assessment of low-level methylated genes like BRCA1. Within this limited test-set, we detected 206 regions located in the promoters of 149 genes to be differentially methylated (hyper- or hypo-) at > 99% confidence level. Seven target regions in gene promoters (CIITA, RASSF1, CHN1, PDCD1LG2, GSTP1, XPA, and ZNF668) were found to be hyper-methylated in a minority of individuals, with a > 20 percent point difference in mean methylation across the region between individuals. In an exploratory hierarchical clustering analysis, we found that the individuals analyzed may be grouped into two main groups based on their WBC methylation profile across the 283 tumor suppressor gene promoters.ConclusionsMethylation-specific NGS of our tumor suppressor panel, with detailed assessment of differential methylation in healthy individuals, presents a feasible method for identification of novel epigenetic risk factors for cancer.

Abstract 158: Custom primer design pipeline and analysis workflow for targeted methylation sequencing using NGS Ion AmpliSeq technology

Abstract Changes in DNA methylation, causing chromosome instability and altered gene expression, have been strongly associated with carcinogenesis. Due to the involvement of methylation in cancer, methylation profiles have been heralded as promising cancer biomarkers. Here, we present a primer design pipeline and an analysis workflow that we have developed to design and analyze custom methylation panels and detect methylation status. An automated primer design pipeline for methylation sequencing has been developed, consisting of genome conversion, primer selection, amplicon tiling, and generation of optimal amplicons. Custom methylation panels can be designed using pre-converted genomes or reference genome sequences for any other organism which can then be converted. The pipeline has the capability to create custom targeted panels specific to any methylation sites of interest. The pipeline designs Ion AmpliSeq primers to enable high multiplexing and robust amplification of low abundance or degraded DNA. Following the creation of a custom panel, a complete 3-day workflow has been developed, comprising bisulfite conversion, library construction, template preparation, sequencing and data analysis. This 3-day protocol offers manual or automated library options, low input (10-20ng DNA) and a flexible multiplexed approach with quantitative information at single base pair resolution. Sequencing is performed on the Ion GeneStudio S5 system. The bioinformatics analysis has been streamlined into a downloadable plugin performing alignment and DNA methylation calling for amplicons on both the Watson and Crick strands. To evaluate the in silico performance of the primer design pipeline for targeted bisulfite sequencing, a custom methylation panel was created using a set of 48 oncology markers from the BLUEPRINT consortium. These markers were also used for the Ion AmpliSeq Methylation Panel for Cancer Research, which was compared to the custom methylation panel to evaluate the performance of the pipeline. Key metrics from in silico design such as total number of degenerate oligos, mean amplicon length and average Tm spread for the custom methylation panel are equal to or better than Ion AmpliSeq Methylation Panel for Cancer Research. To assess the sequencing performance of the panel, two control gDNA samples were used. The expected average methylation status across all CpGs were &amp;gt;98% and &amp;lt;5% for the first sample and the second sample, respectively. The evaluation was also carried out with an equal mixture of these two samples. The wet lab testing of the custom methylation panel generated comparable results to the Ion AmpliSeq Methylation Panel for Cancer Research. The primer design pipeline and 3-day workflow provide custom design of targeted methylation panels along with quantitative analysis of relevant oncology markers from low DNA input. Citation Format: Zunping Luo, Loni Pickle, Andrew Hatch, Aren Ewing, Fiona Hyland, David Berman, Palak Patel, Mark Andersen. Custom primer design pipeline and analysis workflow for targeted methylation sequencing using NGS Ion AmpliSeq technology [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 158.

ChIA-PIPE: A fully automated pipeline for comprehensive ChIA-PET data analysis and visualization.

ChIA-PET (chromatin interaction analysis with paired-end tags) enables genome-wide discovery of chromatin interactions involving specific protein factors, with base pair resolution. Interpretation of ChIA-PET data requires a robust analytic pipeline. Here, we introduce ChIA-PIPE, a fully automated pipeline for ChIA-PET data processing, quality assessment, visualization, and analysis. ChIA-PIPE performs linker filtering, read mapping, peak calling, and loop calling and automates quality control assessment for each dataset. To enable visualization, ChIA-PIPE generates input files for two-dimensional contact map viewing with Juicebox and HiGlass and provides a new dockerized visualization tool for high-resolution, browser-based exploration of peaks and loops. To enable structural interpretation, ChIA-PIPE calls chromatin contact domains, resolves allele-specific peaks and loops, and annotates enhancer-promoter loops. ChIA-PIPE also supports the analysis of other related chromatin-mapping data types.

IMPLICON: an ultra-deep sequencing method to uncover DNA methylation at imprinted regions.

Genomic imprinting is an epigenetic phenomenon leading to parental allele-specific expression. Dosage of imprinted genes is crucial for normal development and its dysregulation accounts for several human disorders. This unusual expression pattern is mostly dictated by differences in DNA methylation between parental alleles at specific regulatory elements known as imprinting control regions (ICRs). Although several approaches can be used for methylation inspection, we lack an easy and cost-effective method to simultaneously measure DNA methylation at multiple imprinted regions. Here, we present IMPLICON, a high-throughput method measuring DNA methylation levels at imprinted regions with base-pair resolution and over 1000-fold coverage. We adapted amplicon bisulfite-sequencing protocols to design IMPLICON for ICRs in adult tissues of inbred mice, validating it in hybrid mice from reciprocal crosses for which we could discriminate methylation profiles in the two parental alleles. Lastly, we developed a human version of IMPLICON and detected imprinting errors in embryonic and induced pluripotent stem cells. We also provide rules and guidelines to adapt this method for investigating the DNA methylation landscape of any set of genomic regions. In summary, IMPLICON is a rapid, cost-effective and scalable method, which could become the gold standard in both imprinting research and diagnostics.

Xdrop: Targeted sequencing of long DNA molecules from low input samples using droplet sorting.

Long‐read sequencing can resolve regions of the genome that are inaccessible to short reads, and therefore are ideal for genome‐gap closure, solving structural rearrangements and sequencing through repetitive elements. Here we introduce the Xdrop technology: a novel microfluidic‐based system that allows for targeted enrichment of long DNA molecules starting from only a few nanograms of DNA. Xdrop is based on the isolation of long DNA fragments in millions of droplets, where the droplets containing a target sequence of interest are fluorescently labeled and sorted using flow cytometry. The final product from the Xdrop procedure is an enriched population of long DNA molecules that can be investigated by sequencing. To demonstrate the capability of Xdrop, we performed enrichment of the human papilloma virus 18 integrated into the genome of human HeLa cells. Analysis of the sequencing reads resolved three HPV18‐chr8 integrations at base‐pair resolution, and the captured fragments extended up to 30 kb into the human genome at the integration sites. Further, we enriched the complete TP53 locus in a leukemia cell line and could successfully phase coexisting mutations using PacBio sequencing. In summary, our results show that Xdrop is an efficient enrichment technology for studying complex genomic regions.

Disruption of PCDH10 and TNRC18 Genes due to a Balanced Translocation

Balanced chromosomal rearrangements are usually associated with a normal phenotype, although in some individuals, phenotypic alterations are observed. In these patients, molecular characterization of the breakpoints can reveal the pathogenic mechanism, providing the annotation of disease-associated loci and a better genotype-phenotype correlation. In this study, we describe a patient with a balanced reciprocal translocation between 4q27 and 7p22 associated with neurodevelopmental delay. We performed cytogenetic evaluation, next-generation sequencing of microdissected derivative chromosomes, and Sanger sequencing of the junction points to define the translocation's breakpoints at base pair resolution. We found that the PCDH10 and TNRC18 genes were disrupted by the breakpoints at chromosomes 4 and 7, respectively, with the formation of chimeric genes at the junction points. Gene expression studies in the patient's peripheral blood showed reduced expression of TNRC18, a gene with unknown function and clinical significance. PCDH10 plays a role in the development of the nervous system and might be involved with the patient's neurodevelopmental delay. In this study, the full molecular characterization of the junction points was shown as an efficient tool for fine breakpoint mapping in balanced translocations in order to unmask gene disruptions and investigate the potential pathogenic role of the disrupted genes.

Genome-wide DNA methylation analysis of paulownia with phytoplasma infection.

DNA methylation, an important epigenetic modification, regulates a wide range of biological processes. Previous MSAP results showed that the occurrence of PaWB related to changes of DNA methylation level; however, the relationship between DNA methylation and gene expression remains obscure in paulownia. Therefore, in the present study, we applied WGBS and RNA-seq techniques to investigate the DNA methylation and gene expression changes between healthy Paulownia fortunei seedlings and the phytoplasma-infected ones. A map of methylated cytosines at the single base pair resolution of paulownia was constructed. Compared to the healthy seedlings, the DNA methylation level increased after phytoplasma infection, and the change of mCHH was the main methylation pattern. DMR analysis showed that 422,662 DMRs in the genome were identified, in which, 27,871 DMR-associated genes were differentially expressed. Finally, 436 genes with significant differences in their methylation levels and mRNA expression profiles were identified through integrated analysis of the DNA methylomic and transcriptomic. KEGG pathway analysis revealed that these genes are mainly involved in plant hormone signal transduction, carbon metabolism, and starch and sucrose metabolism pathways. Two of DMR-associated genes were verified by BS- PCR. Finally, we selected TRP 1 and R2R3-MYB protein were closely related to the occurrence of PaWB. Our findings provide valuable insight into the mechanism of PaWB at the epigenetic level.

CopomuS-Ranking Compensatory Mutations to Guide RNA-RNA Interaction Verification Experiments.

In silico RNA-RNA interaction prediction is widely applied to identify putative interaction partners and to assess interaction details in base pair resolution. To verify specific interactions, in vitro evidence can be obtained via compensatory mutation experiments. Unfortunately, the selection of compensatory mutations is non-trivial and typically based on subjective ad hoc decisions. To support the decision process, we introduce our COmPensatOry MUtation Selector CopomuS. CopomuS evaluates the effects of mutations on RNA-RNA interaction formation using a set of objective criteria, and outputs a reliable ranking of compensatory mutation candidates. For RNA-RNA interaction assessment, the state-of-the-art IntaRNA prediction tool is applied. We investigate characteristics of successfully verified RNA-RNA interactions from the literature, which guided the design of CopomuS. Finally, we evaluate its performance based on experimentally validated compensatory mutations of prokaryotic sRNAs and their target mRNAs. CopomuS predictions highly agree with known results, making it a valuable tool to support the design of verification experiments for RNA-RNA interactions. It is part of the IntaRNA package and available as stand-alone webserver for ad hoc application.