Splice_sim: a nucleotide conversion-enabled RNA-seq simulation and evaluation framework

Nucleotide conversion RNA sequencing techniques interrogate chemical RNA modifications in cellular transcripts, resulting in mismatch-containing reads. Biases in mapping the resulting reads to reference genomes remain poorly understood. We present splice_sim, a splice-aware RNA-seq simulation and evaluation pipeline that introduces user-defined nucleotide conversions at set frequencies, creates mixture models of converted and unconverted reads, and calculates mapping accuracies per genomic annotation. By simulating nucleotide conversion RNA-seq datasets under realistic experimental conditions, including metabolic RNA labeling and RNA bisulfite sequencing, we measure mapping accuracies of state-of-the-art spliced-read mappers for mouse and human transcripts and derive strategies to prevent biases in the data interpretation.

Lambda3: homology search for protein, nucleotide, and bisulfite-converted sequences

MOTIVATION

Local alignments of query sequences in large databases represent a core part of metagenomic studies and facilitate homology search. Following the development of NCBI Blast, many applications aimed to provide faster and equally sensitive local alignment frameworks. Most applications focus on protein alignments, while only few also facilitate DNA-based searches. None of the established programs allow searching DNA sequences from bisulfite sequencing experiments commonly used for DNA methylation profiling, for which specific alignment strategies need to be implemented.

RESULTS

Here, we introduce Lambda3, a new version of the local alignment application Lambda. Lambda3 is the first solution that enables the search of protein, nucleotide as well as bisulfite-converted nucleotide query sequences. Its protein mode achieves comparable performance to that of the highly optimized protein alignment application Diamond, while the nucleotide mode consistently outperforms established local nucleotide aligners. Combined, Lambda3 presents a universal local alignment framework that enables fast and sensitive homology searches for a wide range of use-cases.

AVAILABILITY AND IMPLEMENTATION

Lambda3 is free and open-source software publicly available at https://github.com/seqan/lambda/.

MethScore as a new comprehensive DNA methylation-based value refining the prognosis in acute myeloid leukemia

BACKGROUND

Changes in DNA methylation are common events in the pathogenesis of acute myeloid leukemia (AML) and have been repeatedly reported as associated with prognosis. However, studies integrating these numerous and potentially prognostically relevant DNA methylation changes are lacking. Therefore, we aimed for an overall evaluation of these epigenetic aberrations to provide a comprehensive NGS-based approach of DNA methylation assessment for AML prognostication.

RESULTS

We designed a sequencing panel targeting 239 regions (approx. 573 kb of total size) described in the literature as having a prognostic impact or being associated with AML pathogenesis. Diagnostic whole-blood DNA samples of adult AML patients divided into a training (n = 128) and a testing cohort (n = 50) were examined. The libraries were prepared using SeqCap Epi Enrichments System (Roche) and sequenced on MiSeq instrument (Illumina). Altogether, 1935 CpGs affecting the survival (p < 0.05) were revealed in the training cohort. A summarizing value MethScore was then calculated from these significant CpGs. Patients with lower MethScore had markedly longer overall survival (OS) and event-free survival (EFS) than those with higher MethScore (p < 0.001). The predictive ability of MethScore was verified on the independent testing cohort for OS (p = 0.01). Moreover, the proof-of-principle validation was performed using the TCGA dataset.

CONCLUSIONS

We showed that comprehensive NGS-based approach of DNA methylation assessment revealed a robust epigenetic signature relevant to AML outcome. We called this signature MethScore and showed it might serve as a strong prognostic marker able to refine survival probability of AML patients.

An ecologist's guide for studying DNA methylation variation in wild vertebrates

The field of molecular biology is advancing fast with new powerful technologies, sequencing methods and analysis software being developed constantly. Commonly used tools originally developed for research on humans and model species are now regularly used in ecological and evolutionary research. There is also a growing interest in the causes and consequences of epigenetic variation in natural populations. Studying ecological epigenetics is currently challenging, especially for vertebrate systems, because of the required technical expertise, complications with analyses and interpretation, and limitations in acquiring sufficiently high sample sizes. Importantly, neglecting the limitations of the experimental setup, technology and analyses may affect the reliability and reproducibility, and the extent to which unbiased conclusions can be drawn from these studies. Here, we provide a practical guide for researchers aiming to study DNA methylation variation in wild vertebrates. We review the technical aspects of epigenetic research, concentrating on DNA methylation using bisulfite sequencing, discuss the limitations and possible pitfalls, and how to overcome them through rigid and reproducible data analysis. This review provides a solid foundation for the proper design of epigenetic studies, a clear roadmap on the best practices for correct data analysis and a realistic view on the limitations for studying ecological epigenetics in vertebrates. This review will help researchers studying the ecological and evolutionary implications of epigenetic variation in wild populations.

Efficiently quantifying DNA methylation for bulk- and single-cell bisulfite data

MOTIVATION

DNA CpG methylation (CpGm) has proven to be a crucial epigenetic factor in the mammalian gene regulatory system. Assessment of DNA CpG methylation values via whole-genome bisulfite sequencing (WGBS) is, however, computationally extremely demanding.

RESULTS

We present FAst MEthylation calling (FAME), the first approach to quantify CpGm values directly from bulk or single-cell WGBS reads without intermediate output files. FAME is very fast but as accurate as standard methods, which first produce BS alignment files before computing CpGm values. We present experiments on bulk and single-cell bisulfite datasets in which we show that data analysis can be significantly sped-up and help addressing the current WGBS analysis bottleneck for large-scale datasets without compromising accuracy.

AVAILABILITY AND IMPLEMENTATION

An implementation of FAME is open source and licensed under GPL-3.0 at https://github.com/FischerJo/FAME.

Epigenetic targets in B- and T-cell lymphomas: latest developments

Non-Hodgkin's lymphomas (NHLs) comprise a diverse group of diseases, either of mature B-cell or of T-cell derivation, characterized by heterogeneous molecular features and clinical manifestations. While most of the patients are responsive to standard chemotherapy, immunotherapy, radiation and/or stem cell transplantation, relapsed and/or refractory cases still have a dismal outcome. Deep sequencing analysis have pointed out that epigenetic dysregulations, including mutations in epigenetic enzymes, such as chromatin modifiers and DNA methyltransferases (DNMTs), are prevalent in both B- cell and T-cell lymphomas. Accordingly, over the past decade, a large number of epigenetic-modifying agents have been developed and introduced into the clinical management of these entities, and a few specific inhibitors have already been approved for clinical use. Here we summarize the main epigenetic alterations described in B- and T-NHL, that further supported the clinical development of a selected set of epidrugs in determined diseases, including inhibitors of DNMTs, histone deacetylases (HDACs), and extra-terminal domain proteins (bromodomain and extra-terminal motif; BETs). Finally, we highlight the most promising future directions of research in this area, explaining how bioinformatics approaches can help to identify new epigenetic targets in B- and T-cell lymphoid neoplasms.

An Association Study of DNA Methylation and Gene Expression in Angelman Syndrome: A Bioinformatics Approach

Angelman syndrome (AS) is a neurodevelopmental disorder caused by the loss of function of the E3-ligase UBE3A. Despite multiple studies, AS pathophysiology is still obscure and has mostly been explored in rodent models of the disease. In recent years, a growing body of studies has utilized omics datasets in the attempt to focus research regarding the pathophysiology of AS. Here, for the first time, we utilized a multi-omics approach at the epigenomic level and the transcriptome level, for human-derived neurons. Using publicly available datasets for DNA methylation and gene expression, we found genome regions in proximity to gene promoters and intersecting with gene-body regions that were differentially methylated and differentially expressed in AS. We found that overall, the genome in AS postmortem brain tissue was hypo-methylated compared to healthy controls. We also found more upregulated genes than downregulated genes in AS. Many of these dysregulated genes in neurons obtained from AS patients are known to be critical for neuronal development and synaptic functioning. Taken together, our results suggest a list of dysregulated genes that may be involved in AS development and its pathological features. Moreover, these genes might also have a role in neurodevelopmental disorders similar to AS.

A validation study of potential prognostic DNA methylation biomarkers in patients with acute myeloid leukemia using a custom DNA methylation sequencing panel

BACKGROUND

Multiple studies have reported the prognostic impact of DNA methylation changes in acute myeloid leukemia (AML). However, these epigenetic markers have not been thoroughly validated and therefore are still not considered in clinical practice. Hence, we aimed to independently verify results of selected studies describing the relationship between DNA methylation of specific genes and their prognostic potential in predicting overall survival (OS) and event-free survival (EFS).

RESULTS

Fourteen studies (published 2011-2019) comprising of 27 genes were subjected to validation by a custom NGS-based sequencing panel in 178 newly diagnosed non-M3 AML patients treated by 3 + 7 induction regimen. The results were considered as successfully validated, if both the log-rank test and multivariate Cox regression analysis had a p-value ≤ 0.05. The predictive role of DNA methylation was confirmed for three studies comprising of four genes: CEBPA (OS: p = 0.02; EFS: p = 0.03), PBX3 (EFS: p = 0.01), LZTS2 (OS: p = 0.05; EFS: p = 0.0003), and NR6A1 (OS: p = 0.004; EFS: p = 0.0003). For all of these genes, higher methylation was an indicator of longer survival. Concurrent higher methylation of both LZTS2 and NR6A1 was highly significant for survival in cytogenetically normal (CN) AML group (OS: p < 0.0001; EFS: p < 0.0001) as well as for the whole AML cohort (OS: p = 0.01; EFS < 0.0001). In contrast, for two studies reporting the poor prognostic effect of higher GPX3 and DLX4 methylation, we found the exact opposite, again linking higher GPX3 (OS: p = 0.006; EFS: p < 0.0001) and DLX4 (OS: p = 0.03; EFS = 0.03) methylation to a favorable treatment outcome. Individual gene significance levels refer to the outcomes of multivariate Cox regression analysis.

CONCLUSIONS

Out of twenty-seven genes subjected to DNA methylation validation, a prognostic role was observed for six genes. Therefore, independent validation studies are necessary to reveal truly prognostic DNA methylation changes and to enable the introduction of these promising epigenetic markers into clinical practice.

RLM: Fast and simplified extraction of Read-Level Methylation metrics from bisulfite sequencing data

 

Bisulfite sequencing data provide value beyond the straightforward methylation assessment by analyzing single-read patterns. Over the past years, various informative metrics have been established to explore this information. However, limited compatibility with alignment tools, reference genomes or the measurements they provide present a bottleneck for most groups to include this information as standard analysis. To address this, we developed RLM, a fast and scalable tool for the computation of frequently used Read-Level Methylation statistics. RLM supports several common alignment tools, works independently of the reference genome and handles all frequently used sequencing experiment designs. RLM can process large input files with a billion reads in just a few hours on common workstations.

AVAILABILITY

https://github.com/sarahet/RLM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RNA landscape of the emerging cancer-associated microbe Fusobacterium nucleatum

Fusobacterium nucleatum, long known as a constituent of the oral microflora, has recently garnered renewed attention for its association with several different human cancers. The growing interest in this emerging cancer-associated bacterium contrasts with a paucity of knowledge about its basic gene expression features and physiological responses. As fusobacteria lack all established small RNA-associated proteins, post-transcriptional networks in these bacteria are also unknown. In the present study, using differential RNA-sequencing, we generate high-resolution global RNA maps for five clinically relevant fusobacterial strains-F. nucleatum subspecies nucleatum, animalis, polymorphum and vincentii, as well as F. periodonticum-for early, mid-exponential growth and early stationary phase. These data are made available in an online browser, and we use these to uncover fundamental aspects of fusobacterial gene expression architecture and a suite of non-coding RNAs. Developing a vector for functional analysis of fusobacterial genes, we discover a conserved fusobacterial oxygen-induced small RNA, FoxI, which serves as a post-transcriptional repressor of the major outer membrane porin FomA. Our findings provide a crucial step towards delineating the regulatory networks enabling F. nucleatum adaptation to different environments, which may elucidate how these bacteria colonize different compartments of the human body.

Comprehensive benchmarking of software for mapping whole genome bisulfite data: from read alignment to DNA methylation analysis

Whole genome bisulfite sequencing is currently at the forefront of epigenetic analysis, facilitating the nucleotide-level resolution of 5-methylcytosine (5mC) on a genome-wide scale. Specialized software have been developed to accommodate the unique difficulties in aligning such sequencing reads to a given reference, building on the knowledge acquired from model organisms such as human, or Arabidopsis thaliana. As the field of epigenetics expands its purview to non-model plant species, new challenges arise which bring into question the suitability of previously established tools. Herein, nine short-read aligners are evaluated: Bismark, BS-Seeker2, BSMAP, BWA-meth, ERNE-BS5, GEM3, GSNAP, Last and segemehl. Precision-recall of simulated alignments, in comparison to real sequencing data obtained from three natural accessions, reveals on-balance that BWA-meth and BSMAP are able to make the best use of the data during mapping. The influence of difficult-to-map regions, characterized by deviations in sequencing depth over repeat annotations, is evaluated in terms of the mean absolute deviation of the resulting methylation calls in comparison to a realistic methylome. Downstream methylation analysis is responsive to the handling of multi-mapping reads relative to mapping quality (MAPQ), and potentially susceptible to bias arising from the increased sequence complexity of densely methylated reads.

Increased prostaglandin-D2 in male STAT3-deficient hearts shifts cardiac progenitor cells from endothelial to white adipocyte differentiation

Cardiac levels of the signal transducer and activator of transcription factor-3 (STAT3) decline with age, and male but not female mice with a cardiomyocyte-specific STAT3 deficiency conditional knockout (CKO) display premature age-related heart failure associated with reduced cardiac capillary density. In the present study, isolated male and female CKO-cardiomyocytes exhibit increased prostaglandin (PG)-generating cyclooxygenase-2 (COX-2) expression. The PG-degrading hydroxyprostaglandin-dehydrogenase-15 (HPGD) expression is only reduced in male cardiomyocytes, which is associated with increased prostaglandin D₂ (PGD₂) secretion from isolated male but not female CKO-cardiomyocytes. Reduced HPGD expression in male cardiomyocytes derive from impaired androgen receptor (AR)–signaling due to loss of its cofactor STAT3. Elevated PGD₂ secretion in males is associated with increased white adipocyte accumulation in aged male but not female hearts. Adipocyte differentiation is enhanced in isolated stem cell antigen-1 (SCA-1)⁺ cardiac progenitor cells (CPC) from young male CKO-mice compared with the adipocyte differentiation of male wild-type (WT)-CPC and CPC isolated from female mice. Epigenetic analysis in freshly isolated male CKO-CPC display hypermethylation in pro-angiogenic genes (Fgfr2, Epas1) and hypomethylation in the white adipocyte differentiation gene Zfp423 associated with up-regulated ZFP423 expression and a shift from endothelial to white adipocyte differentiation compared with WT-CPC. The expression of the histone-methyltransferase EZH2 is reduced in male CKO-CPC compared with male WT-CPC, whereas no differences in the EZH2 expression in female CPC were observed. Clonally expanded CPC can differentiate into endothelial cells or into adipocytes depending on the differentiation conditions. ZFP423 overexpression is sufficient to induce white adipocyte differentiation of clonal CPC. In isolated WT-CPC, PGD₂ stimulation reduces the expression of EZH2, thereby up-regulating ZFP423 expression and promoting white adipocyte differentiation. The treatment of young male CKO mice with the COX inhibitor Ibuprofen or the PGD₂ receptor (DP)2 receptor antagonist BAY-u 3405 in vivo increased EZH2 expression and reduced ZFP423 expression and adipocyte differentiation in CKO-CPC. Thus, cardiomyocyte STAT3 deficiency leads to age-related and sex-specific cardiac remodeling and failure in part due to sex-specific alterations in PGD₂ secretion and subsequent epigenetic impairment of the differentiation potential of CPC. Causally involved is the impaired AR signaling in absence of STAT3, which reduces the expression of the PG-degrading enzyme HPGD.

Impaired androgen-receptor-signaling due to STAT3-deficiency promotes increased prostaglandin-D2-secretion from male but not female cardiomyocytes; this induces an epigenetic switch in cardiac progenitor cells from endothelial to white adipocyte differentiation, associated with reduced cardiac capillary density, increased cardiac white fat deposits and heart failure in aged male but not female mice.

Minor DNA methylation changes are observed in spermatozoa prepared using different protocols

BACKGROUND

DNA methylation patterns can show transgenerational inheritance and are influenced by lifestyle and environmental factors. It is suggested that these patterns can be changed by assisted reproductive technology.

OBJECTIVES

To evaluate the impact of two different sperm preparation methods, conventional density gradient centrifugation (DGC) vs. density gradient centrifugation followed by magnetic-activated cell sorting (MACS) of non-apoptotic spermatozoa, on sperm DNA methylation profile.

MATERIALS AND METHODS

We analyzed semen of patients included in our IVF treatment program. Half of the semen from each included patient was prepared for ICSI using the DGC method and the other half with DGC followed by MACS. The remaining samples were processed for DNA methylation analysis with reduced representation bisulfite sequencing (RRBS). In addition to the DNA methylation profile, we assessed the morphology and DNA fragmentation of spermatozoa.

RESULTS

RRBS analysis revealed that the average genome-wide methylation level was similar between both groups (DGC vs. MACS group) and ranged from 0.53 to 0.56. Furthermore, RRBS analysis identified 99 differentially methylated regions (DMRs) and 800 differentially methylated positions (DMPs). In the DGC group, 43 DMRs and 392 DMPs were hypermethylated whereas 56 DMRs and 408 DMPs were hypomethylated compared with those in the MACS group. When DMRs and DMPs were annotated to genes, 3 genes associated with imprinting were found: IGF2, PRDM16, and CLF4/BRUNOL4. The percentage of morphologically normal spermatozoa (MACS vs. DGC; 14.0 ± 10.8 vs. 13.2 ± 10.0; P = .335) and of spermatozoa with fragmented DNA of patients with RRBS analysis (22.9 ± 21.1% vs. 34.4 ± 21.2; P = .529) were also similar between groups.

DISCUSSION AND CONCLUSION

Although the average genome-wide level of sperm DNA methylation was similar in both sample groups, a distinctive number of methylation changes were observed in DMR and DMP levels. A larger number of samples should be analyzed and additional sperm preparation methods should be tested to confirm our findings.

Performance of Mapping Approaches for Whole-Genome Bisulfite Sequencing Data in Crop Plants

DNA methylation is involved in many different biological processes in the development and well-being of crop plants such as transposon activation, heterosis, environment-dependent transcriptome plasticity, aging, and many diseases. Whole-genome bisulfite sequencing is an excellent technology for detecting and quantifying DNA methylation patterns in a wide variety of species, but optimized data analysis pipelines exist only for a small number of species and are missing for many important crop plants. This is especially important as most existing benchmark studies have been performed on mammals with hardly any repetitive elements and without CHG and CHH methylation. Pipelines for the analysis of whole-genome bisulfite sequencing data usually consists of four steps: read trimming, read mapping, quantification of methylation levels, and prediction of differentially methylated regions (DMRs). Here we focus on read mapping, which is challenging because un-methylated cytosines are transformed to uracil during bisulfite treatment and to thymine during the subsequent polymerase chain reaction, and read mappers must be capable of dealing with this cytosine/thymine polymorphism. Several read mappers have been developed over the last years, with different strengths and weaknesses, but their performances have not been critically evaluated. Here, we compare eight read mappers: Bismark, BismarkBwt2, BSMAP, BS-Seeker2, Bwameth, GEM3, Segemehl, and GSNAP to assess the impact of the read-mapping results on the prediction of DMRs. We used simulated data generated from the genomes of Arabidopsis thaliana, Brassica napus, Glycine max, Solanum tuberosum, and Zea mays, monitored the effects of the bisulfite conversion rate, the sequencing error rate, the maximum number of allowed mismatches, as well as the genome structure and size, and calculated precision, number of uniquely mapped reads, distribution of the mapped reads, run time, and memory consumption as features for benchmarking the eight read mappers mentioned above. Furthermore, we validated our findings using real-world data of Glycine max and showed the influence of the mapping step on DMR calling in WGBS pipelines. We found that the conversion rate had only a minor impact on the mapping quality and the number of uniquely mapped reads, whereas the error rate and the maximum number of allowed mismatches had a strong impact and leads to differences of the performance of the eight read mappers. In conclusion, we recommend BSMAP which needs the shortest run time and yields the highest precision, and Bismark which requires the smallest amount of memory and yields precision and high numbers of uniquely mapped reads.

Arioc: GPU-accelerated alignment of short bisulfite-treated reads

Motivation

The alignment of bisulfite-treated DNA sequences (BS-seq reads) to a large genome involves a significant computational burden beyond that required to align non-bisulfite-treated reads. In the analysis of BS-seq data, this can present an important performance bottleneck that can be mitigated by appropriate algorithmic and software-engineering improvements. One strategy is to modify the read-alignment algorithms by integrating the logic related to BS-seq alignment, with the goal of making the software implementation amenable to optimizations that lead to higher speed and greater sensitivity than might otherwise be attainable.

Results

We evaluated this strategy using Arioc, a short-read aligner that uses GPU (general-purpose graphics processing unit) hardware to accelerate computationally-expensive programming logic. We integrated the BS-seq computational logic into both GPU and CPU code throughout the Arioc implementation. We then carried out a read-by-read comparison of Arioc's reported alignments with the alignments reported by well-known CPU-based BS-seq read aligners. With simulated reads, Arioc's accuracy is equal to or better than the other read aligners we evaluated. With human sequencing reads, Arioc's throughput is at least 10 times faster than existing BS-seq aligners across a wide range of sensitivity settings.

Availability and implementation

The Arioc software is available for download at https://github.com/RWilton/Arioc. It is released under a BSD open-source license.

Supplementary information

Supplementary data are available at Bioinformatics online.

How to Design a Whole-Genome Bisulfite Sequencing Experiment

Aside from post-translational histone modifications and small RNA populations, the epigenome of an organism is defined by the level and spectrum of DNA methylation. Methyl groups can be covalently bound to the carbon-5 of cytosines or the carbon-6 of adenine bases. DNA methylation can be found in both prokaryotes and eukaryotes. In the latter, dynamic variation is shown across species, along development, and by cell type. DNA methylation usually leads to a lower binding affinity of DNA-interacting proteins and often results in a lower expression rate of the subsequent genome region, a process also referred to as transcriptional gene silencing. We give an overview of the current state of research facilitating the planning and implementation of whole-genome bisulfite-sequencing (WGBS) experiments. We refrain from discussing alternative methods for DNA methylation analysis, such as reduced representation bisulfite sequencing (rrBS) and methylated DNA immunoprecipitation sequencing (MeDIPSeq), which have value in specific experimental contexts but are generally disadvantageous compared to WGBS.

Conflicts of CpG density and DNA methylation are proximally and distally involved in gene regulation in human and mouse tissues

The relationship between CpG content and DNA methylation has attracted considerable interest in recent years. Direct or indirect methods have been developed to investigate their regulatory functions based on various hypotheses, large cohort studies, and meta-analyses. However, all of these analyses were performed at units of CpG blocks and, thus, the influence of finer genome structure has been neglected. Herein, we present a novel algorithm of base-pair resolution to systematically investigate the relationship between CpG contents and DNA methylation. By introducing the concept of 'complementary index' we examined the methylomes of 34 adult and 7 embryonic tissues and successfully fitted the relationship of DNA methylation and CpG density into a nonlinear mathematical model. A further algorithm was developed to locate the regions where CpG density does not match expectations from the model, termed 'conflict of gap' (COG) regions. Interestingly, COGs are highly concordant in human and mouse and their distributions display a tissue-specific pattern. Based on COG methylation patterns we correctly classified tissues according to their function or origin. We demonstrate that COGs based on our method can reveal more and deeper information than traditional differential methylation region (DMR) approaches. We also found that when COGs are located near to transcription start site (TSS), these regions can determine which promoters will be utilized for initiating gene transcription. Furthermore, COGs located far from the TSS perform as enhancers in terms of histone modification, sequence conservation, transcription factor binding, and DNase I-hypersensitivity.

Hepatocyte Ploidy Is a Diversity Factor for Liver Homeostasis

Polyploidy, the existence of cells containing more than one pair of chromosomes, is a well-known feature of mammalian hepatocytes. Polyploid hepatocytes are found either as cells with a single polyploid nucleus or as multinucleated cells with diploid or even polyploid nuclei. In this study, we evaluate the degree of polyploidy in the murine liver by accounting both DNA content and number of nuclei per cell. We demonstrate that mouse hepatocytes with diploid nuclei have distinct metabolic characteristics compared to cells with polyploid nuclei. In addition to strong differential gene expression, comprising metabolic as well as signaling compounds, we found a strongly decreased insulin binding of nuclear polyploid cells. Our observations were associated with nuclear ploidy but not with total ploidy within a cell. We therefore suggest ploidy of the nuclei as an new diversity factor of hepatocytes and hypothesize that hepatocytes with polyploid nuclei may have distinct biological functions than mono-nuclear ones. This diversity is independent from the well-known heterogeneity related to the cells' position along the porto-central liver-axis.

Keeping it complicated: Mitochondrial genome plasticity across diplonemids

Chromosome rearrangements are important drivers in genome and gene evolution, with implications ranging from speciation to development to disease. In the flagellate Diplonema papillatum (Euglenozoa), mitochondrial genome rearrangements have resulted in nearly hundred chromosomes and a systematic dispersal of gene fragments across the multipartite genome. Maturation into functional RNAs involves separate transcription of gene pieces, joining of precursor RNAs via trans-splicing, and RNA editing by substitution and uridine additions both reconstituting crucial coding sequence. How widespread these unusual features are across diplonemids is unclear. We have analyzed the mitochondrial genomes and transcriptomes of four species from the Diplonema/Rhynchopus clade, revealing a considerable genomic plasticity. Although gene breakpoints, and thus the total number of gene pieces (~80), are essentially conserved across this group, the number of distinct chromosomes varies by a factor of two, with certain chromosomes combining up to eight unrelated gene fragments. Several internal protein-coding gene pieces overlap substantially, resulting, for example, in a stretch of 22 identical amino acids in cytochrome c oxidase subunit 1 and NADH dehydrogenase subunit 5. Finally, the variation of post-transcriptional editing patterns across diplonemids indicates compensation of two adverse trends: rapid sequence evolution and loss of genetic information through unequal chromosome segregation.

Bioinformatics Tools for Genome-Wide Epigenetic Research

Epigenetics play a central role in the regulation of many important cellular processes, and dysregulations at the epigenetic level could be the source of serious pathologies, such as neurological disorders affecting brain development, neurodegeneration, and intellectual disability. Despite significant technological advances for epigenetic profiling, there is still a need for a systematic understanding of how epigenetics shapes cellular circuitry, and disease pathogenesis. The development of accurate computational approaches for analyzing complex epigenetic profiles is essential for disentangling the mechanisms underlying cellular development, and the intricate interaction networks determining and sensing chromatin modifications and DNA methylation to control gene expression. In this chapter, we review the recent advances in the field of "computational epigenetics," including computational methods for processing different types of epigenetic data, prediction of chromatin states, and study of protein dynamics. We also discuss how "computational epigenetics" has complemented the fast growth in the generation of epigenetic data for uncovering the main differences and similarities at the epigenetic level between individuals and the mechanisms underlying disease onset and progression.

Tissue-, sex-, and age-specific DNA methylation of rat glucocorticoid receptor gene promoter and insulin-like growth factor 2 imprinting control region

Tissue-, sex-, and age-specific epigenetic modifications such as DNA methylation are largely unknown. Changes in DNA methylation of the glucocorticoid receptor gene (NR3C1) and imprinting control region (ICR) of IGF2 and H19 genes during the lifespan are particularly interesting since these genes are susceptible to epigenetic modifications by prenatal stress or malnutrition. They are important regulators of development and aging. Methylation changes of NR3C1 affect glucocorticoid receptor expression, which is associated with stress sensitivity and stress-related diseases predominantly occurring during aging. Methylation changes of IGF2/H19 affect growth trajectory and nutrient use with risk of metabolic syndrome. Using a locus-specific approach, we characterized DNA methylation patterns of different Nr3c1 promoters and Igf2/H19 ICR in seven tissues of rats at 3, 9, and 24 mo of age. We found a complex pattern of locus-, tissue-, sex-, and age-specific DNA methylation. Tissue-specific methylation was most prominent at the shores of the Nr3c1 CpG island (CGI). Sex-specific differences in methylation peaked at 9 mo. During aging, Nr3c1 predominantly displayed hypomethylation mainly in females and at shores, whereas hypermethylation occurred within the CGI. Igf2/H19 ICR exhibited age-related hypomethylation occurring mainly in males. Methylation patterns of Nr3c1 in the skin correlated with those in the cortex, hippocampus, and hypothalamus. Skin may serve as proxy for methylation changes in central parts of the hypothalamic-pituitary-adrenal axis and hence for vulnerability to stress- and age-associated diseases. Thus, we provide in-depth insight into the complex DNA methylation changes of rat Nr3c1 and Igf2/H19 during aging that are tissue and sex specific.

BAT: Bisulfite Analysis Toolkit: BAT is a toolkit to analyze DNA methylation sequencing data accurately and reproducibly. It covers standard processing and analysis steps from raw read mapping up to annotation data integration and calculation of correlating DMRs

Here, we present BAT, a modular bisulfite analysis toolkit, that facilitates the analysis of bisulfite sequencing data. It covers the essential analysis steps of read alignment, quality control, extraction of methylation information, and calling of differentially methylated regions, as well as biologically relevant downstream analyses, such as data integration with gene expression, histone modification data, or transcription factor binding site annotation.

EpiTEome: Simultaneous detection of transposable element insertion sites and their DNA methylation levels

The genome-wide investigation of DNA methylation levels has been limited to reference transposable element positions. The methylation analysis of non-reference and mobile transposable elements has only recently been performed, but required both genome resequencing and MethylC-seq datasets. We have created epiTEome, a program that detects both new transposable element insertion sites and their methylation states from a single MethylC-seq dataset. EpiTEome outperforms other split-read insertion site detection programs, even while functioning on bisulfite-converted reads. EpiTEome characterizes the previously discarded fraction of DNA methylation at sites of new insertions, enabling future investigation into the epigenetic regulation of non-reference and transposed elements.

Integrating Epigenomics into the Understanding of Biomedical Insight

Epigenetics is one of the most rapidly expanding fields in biomedical research, and the popularity of the high-throughput next-generation sequencing (NGS) highlights the accelerating speed of epigenomics discovery over the past decade. Epigenetics studies the heritable phenotypes resulting from chromatin changes but without alteration on DNA sequence. Epigenetic factors and their interactive network regulate almost all of the fundamental biological procedures, and incorrect epigenetic information may lead to complex diseases. A comprehensive understanding of epigenetic mechanisms, their interactions, and alterations in health and diseases genome widely has become a priority in biological research. Bioinformatics is expected to make a remarkable contribution for this purpose, especially in processing and interpreting the large-scale NGS datasets. In this review, we introduce the epigenetics pioneering achievements in health status and complex diseases; next, we give a systematic review of the epigenomics data generation, summarize public resources and integrative analysis approaches, and finally outline the challenges and future directions in computational epigenomics.

Evaluation of preprocessing, mapping and postprocessing algorithms for analyzing whole genome bisulfite sequencing data

Cytosine methylation regulates many biological processes such as gene expression, chromatin structure and chromosome stability. The whole genome bisulfite sequencing (WGBS) technique measures the methylation level at each cytosine throughout the genome. There are an increasing number of publicly available pipelines for analyzing WGBS data, reflecting many choices of read mapping algorithms as well as preprocessing and postprocessing methods. We simulated single-end and paired-end reads based on three experimental data sets, and comprehensively evaluated 192 combinations of three preprocessing, five postprocessing and five widely used read mapping algorithms. We also compared paired-end data with single-end data at the same sequencing depth for performance of read mapping and methylation level estimation. Bismark and LAST were the most robust mapping algorithms. We found that Mott trimming and quality filtering individually improved the performance of both read mapping and methylation level estimation, but combining them did not lead to further improvement. Furthermore, we confirmed that paired-end sequencing reduced error rate and enhanced sensitivity for both read mapping and methylation level estimation, especially for short reads and in repetitive regions of the human genome.

Post-transcriptional mending of gene sequences: Looking under the hood of mitochondrial gene expression in diplonemids

The instructions to make proteins and structural RNAs are laid down in gene sequences. Yet, in certain instances, these primary instructions need to be modified considerably during gene expression, most often at the transcript level. Here we review a case of massive post-transcriptional revisions via trans-splicing and RNA editing, a phenomenon occurring in mitochondria of a recently recognized protist group, the diplonemids. As of now, the various post-transcriptional steps have been cataloged in detail, but how these processes function is still unknown. Since genetic manipulation techniques such as gene replacement and RNA interference have not yet been established for these organisms, alternative strategies have to be deployed. Here, we discuss the experimental and bioinformatics approaches that promise to unravel the molecular machineries of trans-splicing and RNA editing in Diplonema mitochondria.

Detection of differentially methylated regions in whole genome bisulfite sequencing data using local Getis-Ord statistics

MOTIVATION

DNA methylation is an important epigenetic modification that has essential role in gene regulation, cell differentiation and cancer development. Bisulfite sequencing is a widely used technique to obtain genome-wide DNA methylation profiles, and one of the key tasks of analyzing bisulfite sequencing data is to detect differentially methylated regions (DMRs) among samples under different treatment conditions. Although numerous tools have been proposed to detect differentially methylated single CpG site (DMC) between samples, methods for direct DMR detection, especially for complex study designs, are largely limited.

RESULTS

We present a new software, GetisDMR, for direct DMR detection. We use beta-binomial regression to model the whole-genome bisulfite sequencing data, where variations in methylation levels and confounding effects have been accounted for. We employ a region-wise test statistic, which is derived from local Getis-Ord statistics and considers the spatial correlation between nearby CpG sites, to detect DMRs. Unlike existing methods, that attempt to infer DMRs from DMCs based on empirical criteria, we provide statistical inference for direct DMR detection. Through extensive simulations and an application to two mouse datasets, we demonstrate that GetisDMR achieves better sensitivities, positive predictive values, more exact locations and better agreement of DMRs with current biological knowledge.

AVAILABILITY AND IMPLEMENTATION

It is available at https://github.com/DMU-lilab/GetisDMR CONTACTS: y.wen@auckland.ac.nz or zhiguangli@dlmedu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control

Although Burkitt lymphomas and follicular lymphomas both have features of germinal center B cells, they are biologically and clinically quite distinct. Here we performed whole-genome bisulfite, genome and transcriptome sequencing in 13 IG-MYC translocation-positive Burkitt lymphoma, nine BCL2 translocation-positive follicular lymphoma and four normal germinal center B cell samples. Comparison of Burkitt and follicular lymphoma samples showed differential methylation of intragenic regions that strongly correlated with expression of associated genes, for example, genes active in germinal center dark-zone and light-zone B cells. Integrative pathway analyses of regions differentially methylated in Burkitt and follicular lymphomas implicated DNA methylation as cooperating with somatic mutation of sphingosine phosphate signaling, as well as the TCF3-ID3 and SWI/SNF complexes, in a large fraction of Burkitt lymphomas. Taken together, our results demonstrate a tight connection between somatic mutation, DNA methylation and transcriptional control in key B cell pathways deregulated differentially in Burkitt lymphoma and other germinal center B cell lymphomas.

Distinct roles of DNMT1-dependent and DNMT1-independent methylation patterns in the genome of mouse embryonic stem cells

BACKGROUND

DNA methylation patterns are initiated by de novo DNA methyltransferases DNMT3a/3b adding methyl groups to CG dinucleotides in the hypomethylated genome of early embryos. These patterns are faithfully maintained by DNMT1 during DNA replication to ensure epigenetic inheritance across generations. However, this two-step model is based on limited data.

RESULTS

We generated base-resolution DNA methylomes for a series of DNMT knockout embryonic stem cells, with deep coverage at highly repetitive elements. We show that DNMT1 and DNMT3a/3b activities work complementarily and simultaneously to establish symmetric CG methylation and CHH (H = A, T or C) methylation. DNMT3a/3b can add methyl groups to daughter strands after each cycle of DNA replication. We also observe an unexpected division of labor between DNMT1 and DNMT3a/3b in suppressing retrotransposon long terminal repeats and long interspersed elements, respectively. Our data suggest that mammalian cells use a specific CG density threshold to predetermine methylation levels in wild-type cells and the magnitude of methylation reduction in DNMT knockout cells. Only genes with low CG density can be induced or, surprisingly, suppressed in the hypomethylated genome. Lastly, we do not find any association between gene body methylation and transcriptional activity.

CONCLUSIONS

We show the concerted actions of DNMT enzymes in the establishment and maintenance of methylation patterns. The finding of distinct roles of DNMT1-dependent and -independent methylation patterns in genome stability and regulation of transcription provides new insights for understanding germ cell development, neuronal diversity, and transgenerational epigenetic inheritance and will help to develop next-generation DNMT inhibitors.

Facilitated sequence counting and assembly by template mutagenesis

Presently, inferring the long-range structure of the DNA templates is limited by short read lengths. Accurate template counts suffer from distortions occurring during PCR amplification. We explore the utility of introducing random mutations in identical or nearly identical templates to create distinguishable patterns that are inherited during subsequent copying. We simulate the applications of this process under assumptions of error-free sequencing and perfect mapping, using cytosine deamination as a model for mutation. The simulations demonstrate that within readily achievable conditions of nucleotide conversion and sequence coverage, we can accurately count the number of otherwise identical molecules as well as connect variants separated by long spans of identical sequence. We discuss many potential applications, such as transcript profiling, isoform assembly, haplotype phasing, and de novo genome assembly.

GPU-BSM: a GPU-based tool to map bisulfite-treated reads

Cytosine DNA methylation is an epigenetic mark implicated in several biological processes. Bisulfite treatment of DNA is acknowledged as the gold standard technique to study methylation. This technique introduces changes in the genomic DNA by converting cytosines to uracils while 5-methylcytosines remain nonreactive. During PCR amplification 5-methylcytosines are amplified as cytosine, whereas uracils and thymines as thymine. To detect the methylation levels, reads treated with the bisulfite must be aligned against a reference genome. Mapping these reads to a reference genome represents a significant computational challenge mainly due to the increased search space and the loss of information introduced by the treatment. To deal with this computational challenge we devised GPU-BSM, a tool based on modern Graphics Processing Units. Graphics Processing Units are hardware accelerators that are increasingly being used successfully to accelerate general-purpose scientific applications. GPU-BSM is a tool able to map bisulfite-treated reads from whole genome bisulfite sequencing and reduced representation bisulfite sequencing, and to estimate methylation levels, with the goal of detecting methylation. Due to the massive parallelization obtained by exploiting graphics cards, GPU-BSM aligns bisulfite-treated reads faster than other cutting-edge solutions, while outperforming most of them in terms of unique mapped reads.

Lacking alignments? The next-generation sequencing mapper segemehl revisited

MOTIVATION

Next-generation sequencing has become an important tool in molecular biology. Various protocols to investigate genomic, transcriptomic and epigenomic features across virtually all species and tissues have been devised. For most of these experiments, one of the first crucial steps of bioinformatic analysis is the mapping of reads to reference genomes.

RESULTS

Here, we present thorough benchmarks of our read aligner segemehl in comparison with other state-of-the-art methods. Furthermore, we introduce the tool lack to rescue unmapped RNA-seq reads which works in conjunction with segemehl and many other frequently used split-read aligners.

AVAILABILITY

lack is distributed together with segemehl and freely available at www.bioinf.uni-leipzig.de/Software/segemehl/.

Comparison and quantitative verification of mapping algorithms for whole-genome bisulfite sequencing

Coupling bisulfite conversion with next-generation sequencing (Bisulfite-seq) enables genome-wide measurement of DNA methylation, but poses unique challenges for mapping. However, despite a proliferation of Bisulfite-seq mapping tools, no systematic comparison of their genomic coverage and quantitative accuracy has been reported. We sequenced bisulfite-converted DNA from two tissues from each of two healthy human adults and systematically compared five widely used Bisulfite-seq mapping algorithms: Bismark, BSMAP, Pash, BatMeth and BS Seeker. We evaluated their computational speed and genomic coverage and verified their percentage methylation estimates. With the exception of BatMeth, all mappers covered >70% of CpG sites genome-wide and yielded highly concordant estimates of percentage methylation (r² ≥ 0.95). Fourfold variation in mapping time was found between BSMAP (fastest) and Pash (slowest). In each library, 8–12% of genomic regions covered by Bismark and Pash were not covered by BSMAP. An experiment using simulated reads confirmed that Pash has an exceptional ability to uniquely map reads in genomic regions of structural variation. Independent verification by bisulfite pyrosequencing generally confirmed the percentage methylation estimates by the mappers. Of these algorithms, Bismark provides an attractive combination of processing speed, genomic coverage and quantitative accuracy, whereas Pash offers considerably higher genomic coverage.

Estimating absolute methylation levels at single-CpG resolution from methylation enrichment and restriction enzyme sequencing methods

Recent advancements in sequencing-based DNA methylation profiling methods provide an unprecedented opportunity to map complete DNA methylomes. These include whole-genome bisulfite sequencing (WGBS, MethylC-seq, or BS-seq), reduced-representation bisulfite sequencing (RRBS), and enrichment-based methods such as MeDIP-seq, MBD-seq, and MRE-seq. These methods yield largely comparable results but differ significantly in extent of genomic CpG coverage, resolution, quantitative accuracy, and cost, at least while using current algorithms to interrogate the data. None of these existing methods provides single-CpG resolution, comprehensive genome-wide coverage, and cost feasibility for a typical laboratory. We introduce methylCRF, a novel conditional random fields–based algorithm that integrates methylated DNA immunoprecipitation (MeDIP-seq) and methylation-sensitive restriction enzyme (MRE-seq) sequencing data to predict DNA methylation levels at single-CpG resolution. Our method is a combined computational and experimental strategy to produce DNA methylomes of all 28 million CpGs in the human genome for a fraction (<10%) of the cost of whole-genome bisulfite sequencing methods. methylCRF was benchmarked for accuracy against Infinium arrays, RRBS, WGBS sequencing, and locus-specific bisulfite sequencing performed on the same human embryonic stem cell line. methylCRF transformation of MeDIP-seq/MRE-seq was equivalent to a biological replicate of WGBS in quantification, coverage, and resolution. We used conventional bisulfite conversion, PCR, cloning, and sequencing to validate loci where our predictions do not agree with whole-genome bisulfite data, and in 11 out of 12 cases, methylCRF predictions of methylation level agree better with validated results than does whole-genome bisulfite sequencing. Therefore, methylCRF transformation of MeDIP-seq/MRE-seq data provides an accurate, inexpensive, and widely accessible strategy to create full DNA methylomes.

An integrated workflow for DNA methylation analysis

The analysis of cytosine methylation provides a new way to assess and describe epigenetic regulation at a whole-genome level in many eukaryotes. DNA methylation has a demonstrated role in the genome stability and protection, regulation of gene expression and many other aspects of genome function and maintenance. BS-seq is a relatively unbiased method for profiling the DNA methylation, with a resolution capable of measuring methylation at individual cytosines. Here we describe, as an example, a workflow to handle DNA methylation analysis, from BS-seq library preparation to the data visualization. We describe some applications for the analysis and interpretation of these data. Our laboratory provides public access to plant DNA methylation data via visualization tools available at our "Next-Gen Sequence" websites (http://mpss.udel.edu), along with small RNA, RNA-seq and other data types.

The Arabidopsis elongator complex subunit2 epigenetically regulates plant immune responses

The Arabidopsis thaliana Elongator complex subunit2 (ELP2) genetically interacts with NONEXPRESSOR OF PATHOGENESIS-RELATED GENES1 (NPR1), a key transcription coactivator of plant immunity, and regulates the induction kinetics of defense genes. However, the mechanistic relationship between ELP2 and NPR1 and how ELP2 regulates the kinetics of defense gene induction are unclear. Here, we demonstrate that ELP2 is an epigenetic regulator required for pathogen-induced rapid transcriptome reprogramming. We show that ELP2 functions in a transcriptional feed-forward loop regulating both NPR1 and its target genes. An elp2 mutation increases the total methylcytosine number, reduces the average methylation levels of methylcytosines, and alters (increases or decreases) methylation levels of specific methylcytosines. Interestingly, infection of plants with the avirulent bacterial pathogen Pseudomonas syringae pv tomato DC3000/avrRpt2 induces biphasic changes in DNA methylation levels of NPR1 and PHYTOALEXIN DEFICIENT4 (PAD4), which encodes another key regulator of plant immunity. These dynamic changes are blocked by the elp2 mutation, which is correlated with delayed induction of NPR1 and PAD4. The elp2 mutation also reduces basal histone acetylation levels in the coding regions of several defense genes. Together, our data demonstrate a new role for Elongator in somatic DNA demethylation/methylation and suggest a function for Elongator-mediated chromatin regulation in pathogen-induced transcriptome reprogramming.

Analysing and interpreting DNA methylation data

DNA methylation is an epigenetic mark that has suspected regulatory roles in a broad range of biological processes and diseases. The technology is now available for studying DNA methylation genome-wide, at a high resolution and in a large number of samples. This Review discusses relevant concepts, computational methods and software tools for analysing and interpreting DNA methylation data. It focuses not only on the bioinformatic challenges of large epigenome-mapping projects and epigenome-wide association studies but also highlights software tools that make genome-wide DNA methylation mapping more accessible for laboratories with limited bioinformatics experience.