Plant-RRBS, a bisulfite and next-generation sequencing-based methylome profiling method enriching for coverage of cytosine positions.
ABSTRACT: Cytosine methylation in plant genomes is important for the regulation of gene transcription and transposon activity. Genome-wide methylomes are studied upon mutation of the DNA methyltransferases, adaptation to environmental stresses or during development. However, from basic biology to breeding programs, there is a need to monitor multiple samples to determine transgenerational methylation inheritance or differential cytosine methylation. Methylome data obtained by sodium hydrogen sulfite (bisulfite)-conversion and next-generation sequencing (NGS) provide genome-wide information on cytosine methylation. However, a profiling method that detects cytosine methylation state dispersed over the genome would allow high-throughput analysis of multiple plant samples with distinct epigenetic signatures. We use specific restriction endonucleases to enrich for cytosine coverage in a bisulfite and NGS-based profiling method, which was compared to whole-genome bisulfite sequencing of the same plant material.We established an effective methylome profiling method in plants, termed plant-reduced representation bisulfite sequencing (plant-RRBS), using optimized double restriction endonuclease digestion, fragment end repair, adapter ligation, followed by bisulfite conversion, PCR amplification and NGS. We report a performant laboratory protocol and a straightforward bioinformatics data analysis pipeline for plant-RRBS, applicable for any reference-sequenced plant species.As a proof of concept, methylome profiling was performed using an Oryza sativa ssp. indica pure breeding line and a derived epigenetically altered line (epiline). Plant-RRBS detects methylation levels at tens of millions of cytosine positions deduced from bisulfite conversion in multiple samples. To evaluate the method, the coverage of cytosine positions, the intra-line similarity and the differential cytosine methylation levels between the pure breeding line and the epiline were determined. Plant-RRBS reproducibly covers commonly up to one fourth of the cytosine positions in the rice genome when using MspI-DpnII within a group of five biological replicates of a line. The method predominantly detects cytosine methylation in putative promoter regions and not-annotated regions in rice.Plant-RRBS offers high-throughput and broad, genome-dispersed methylation detection by effective read number generation obtained from reproducibly covered genome fractions using optimized endonuclease combinations, facilitating comparative analyses of multi-sample studies for cytosine methylation and transgenerational stability in experimental material and plant breeding populations.
Project description:DNA methylation is a major epigenetic modification regulating several biological processes. A standard approach to measure DNA methylation is bisulfite sequencing (BS-Seq). BS-Seq couples bisulfite conversion of DNA with next-generation sequencing to profile genome-wide DNA methylation at single base resolution. The analysis of BS-Seq data involves the use of customized aligners for mapping bisulfite converted reads and the bioinformatic pipelines for downstream data analysis.Here we developed MethGo, a software tool designed for the analysis of data from whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS). MethGo provides both genomic and epigenomic analyses including: 1) coverage distribution of each cytosine; 2) global cytosine methylation level; 3) cytosine methylation level distribution; 4) cytosine methylation level of genomic elements; 5) chromosome-wide cytosine methylation level distribution; 6) Gene-centric cytosine methylation level; 7) cytosine methylation levels at transcription factor binding sites (TFBSs); 8) single nucleotide polymorphism (SNP) calling, and 9) copy number variation (CNV) calling.MethGo is a simple and effective tool for the analysis of BS-Seq data including both WGBS and RRBS. It contains 9 analyses in 5 major modules to profile (epi)genome. It profiles genome-wide DNA methylation in global and in gene level scale. It can also analyze the methylation pattern around the transcription factor binding sites, and assess genetic variations such as SNPs and CNVs. MethGo is coded in Python and is publically available at http://paoyangchen-laboratory.github.io/methgo/.
Project description:Here we used Illumina NGS for high-throughput profiling of the DNA methylome in two human colon cancer derived cell lines, two human normal bone marrow CD34+ controls and in five human Acutre Myeloid Leukeima patient samples. These data can be used to determine the CpG cytosine methylation pattern at base pair resolution in each sample and to determine differentially methylated cytosines and regions between samples Reduced Representation Bisulfite Sequencing (RRBS) and Extended Reduced Representation Bisulfite Sequencing (ERRBS) on genomic DNA. We used colon cancer cell lines (two) to establish reproducbility and range of assay sensitivity. We used Acute Myeloid Leukemia patient samples and CD34+ bone marrow cells as controls to determine the methylome pattern in the patient samples
Project description:Reduced representation bisulfite sequencing (RRBS) has been used to profile DNA methylation patterns in mammalian genomes such as human, mouse and rat. The methylome of the zebrafish, an important animal model, has not yet been characterized at base-pair resolution using RRBS. Therefore, we evaluated the technique of RRBS in this model organism by generating four single-nucleotide resolution DNA methylomes of adult zebrafish brain. We performed several simulations to show the distribution of fragments and enrichment of CpGs in different in silico reduced representation genomes of zebrafish. Four RRBS brain libraries generated 98 million sequenced reads and had higher frequencies of multiple mapping than equivalent human RRBS libraries. The zebrafish methylome indicates there is higher global DNA methylation in the zebrafish genome compared with its equivalent human methylome. This observation was confirmed by RRBS of zebrafish liver. High coverage CpG dinucleotides are enriched in CpG island shores more than in the CpG island core. We found that 45% of the mapped CpGs reside in gene bodies, and 7% in gene promoters. This analysis provides a roadmap for generating reproducible base-pair level methylomes for zebrafish using RRBS and our results provide the first evidence that RRBS is a suitable technique for global methylation analysis in zebrafish.
Project description:DNA methylation is an important epigenetic modification involved in many biological processes. Reduced representation bisulfite sequencing (RRBS) is a cost-effective method for studying DNA methylation at single base resolution. Although several tools are available for RRBS data processing and analysis, it is not clear which strategy performs the best and there has not been much attention to the contamination issue from artificial cytosines incorporated during the end repair step of library preparation. To address these issues, we describe a new method, Targeted Alignment and Artificial Cytosine Elimination for RRBS (TRACE-RRBS), which aligns bisulfite sequence reads to MSP1 digitally digested reference and specifically removes the end repair cytosines. We compared this approach on a simulated and a real dataset with 7 other RRBS analysis tools and Illumina 450 K microarray platform.TRACE-RRBS aligns sequence reads to a small fraction of the genome where RRBS protocol targets on and was demonstrated as the fastest, most sensitive and specific tool for the simulated dataset. For the real dataset, TRACE-RRBS took about the same time as RRBSMAP, a third to a sixth of time needed for BISMARK and NOVOALIGN. TRACE-RRBS aligned more reads uniquely than other tools and achieved the highest correlation with 450 k microarray data. The end repair artificial cytosine removal increased correlation between nearby CpGs and accuracy of methylation quantification.TRACE-RRBS is fast and more accurate tool for RRBS data analysis. It is freely available for academic use at http://bioinformaticstools.mayo.edu/.
Project description:Defects in epigenetic mechanisms are well-recognized in multiple neurodevelopmental disorders including Schizophrenia (SZ). In addition to aberrant epigenetic marks, dysregulated epigenetic machinery was also identified among the contributory factors in SZ patients. Among these, overexpression of DNA methyltransferase 1 (DNMT1) was the first to be identified. In this context, Dnmt1tet/tet (Tet/Tet), a mouse embryonic stem cell (ESC) line that overexpresses DNMT1 in ESCs and neurons, was developed to study abnormal neurogenesis. In an attempt to understand whether DNMT1 overexpression is associated with aberrant DNA methylation, we compared the genome-wide methylation levels of R1 (wild-type) and Tet/Tet ESCs and their neuronal derivatives by RRBS. The RRBS data (GSE152817) showed an average mappability of ?59% and an average coverage of 40X per locus. The data was processed to determine the methylation percentages of target genes and was visualized using the UCSC genome browser. The observed methylation differences were validated by Combined Bisulfite Restriction Analysis (COBRA). The methylome data described here can be used to study the relationship between DNMT1 overexpression, alterations in methylation levels and dysregulation of SZ-associated genes.
Project description:Reduced representation bisulfite sequencing (RRBS) is a powerful method of DNA methylome profiling that can be applied to single cells. However, no previous report has described how PCR-based duplication-induced artifacts affect the accuracy of this method when measuring DNA methylation levels. For quantifying the effects of duplication-induced artifacts on methylome profiling when using ultra-trace amounts of starting material, we developed a novel method, namely quantitative RRBS (Q-RRBS), in which PCR-induced duplication is excluded through the use of unique molecular identifiers (UMIs). By performing Q-RRBS on varying amounts of starting material, we determined that duplication-induced artifacts were more severe when small quantities of the starting material were used. However, through using the UMIs, we successfully eliminated these artifacts. In addition, Q-RRBS could accurately detect allele-specific methylation in absence of allele-specific genetic variants. Our results demonstrate that Q-RRBS is an optimal strategy for DNA methylation profiling of single cells or samples containing ultra-trace amounts of cells.
Project description:Deep sequencing after bisulfite conversion (BS-Seq) is the method of choice to generate whole genome maps of cytosine methylation at single base-pair resolution. Its application to genomic DNA of Arabidopsis flower bud tissue resulted in the first complete methylome, determining a methylation rate of 6.7% in this tissue. BS-Seq reads were mapped onto an in silico converted reference genome, applying the so-called 3-letter genome method. Here, we present BiSS (Bisufite Sequencing Scorer), a new method applying Smith-Waterman alignment to map bisulfite-converted reads to a reference genome. In addition, we introduce a comprehensive adaptive error estimate that accounts for sequencing errors, erroneous bisulfite conversion and also wrongly mapped reads. The re-analysis of the Arabidopsis methylome data with BiSS mapped substantially more reads to the genome. As a result, it determines the methylation status of an extra 10% of cytosines and estimates the methylation rate to be 7.7%. We validated the results by individual traditional bisulfite sequencing for selected genomic regions. In addition to predicting the methylation status of each cytosine, BiSS also provides an estimate of the methylation degree at each genomic site. Thus, BiSS explores BS-Seq data more extensively and provides more information for downstream analysis.
Project description:DNA methylation is globally reprogrammed during mammalian preimplantation development, which is critical for normal development. Recent reduced representation bisulfite sequencing (RRBS) studies suggest that the methylome dynamics are essentially conserved between human and mouse early embryos. RRBS is known to cover 5-10% of all genomic CpGs, favoring those contained within CpG-rich regions. To obtain an unbiased and more complete representation of the methylome during early human development, we performed whole genome bisulfite sequencing of human gametes and blastocysts that covered>70% of all genomic CpGs. We found that the maternal genome was demethylated to a much lesser extent in human blastocysts than in mouse blastocysts, which could contribute to an increased number of imprinted differentially methylated regions in the human genome. Global demethylation of the paternal genome was confirmed, but SINE-VNTR-Alu elements and some other tandem repeat-containing regions were found to be specifically protected from this global demethylation. Furthermore, centromeric satellite repeats were hypermethylated in human oocytes but not in mouse oocytes, which might be explained by differential expression of de novo DNA methyltransferases. These data highlight both conserved and species-specific regulation of DNA methylation during early mammalian development. Our work provides further information critical for understanding the epigenetic processes underlying differentiation and pluripotency during early human development.
Project description:DNA methylation plays a central role in regulating many aspects of growth and development in mammals through regulating gene expression. The development of next generation sequencing technologies have paved the way for genome-wide, high resolution analysis of DNA methylation landscapes using methodology known as reduced representation bisulfite sequencing (RRBS). While RRBS has proven to be effective in understanding DNA methylation landscapes in humans, mice, and rats, to date, few studies have utilised this powerful method for investigating DNA methylation in agricultural animals. Here we describe the utilisation of RRBS to investigate DNA methylation in sheep Longissimus dorsi muscles. RRBS analysis of ?1% of the genome from Longissimus dorsi muscles provided data of suitably high precision and accuracy for DNA methylation analysis, at all levels of resolution from genome-wide to individual nucleotides. Combining RRBS data with mRNAseq data allowed the sheep Longissimus dorsi muscle methylome to be compared with methylomes from other species. While some species differences were identified, many similarities were observed between DNA methylation patterns in sheep and other more commonly studied species. The RRBS data presented here highlights the complexity of epigenetic regulation of genes. However, the similarities observed across species are promising, in that knowledge gained from epigenetic studies in human and mice may be applied, with caution, to agricultural species. The ability to accurately measure DNA methylation in agricultural animals will contribute an additional layer of information to the genetic analyses currently being used to maximise production gains in these species.
Project description:DNA methylation is a dynamic epigenetic mark regulating gene function and are implicated in the pathophysiology of schizophrenia and autism. Environmental exposures such as inflammation and diet modify the epigenome and may explain why prenatal exposure to inflammation increase risk of neurodevelopmental disorders. This manuscript presents genome-wide DNA methylation data (GSE102942) generated from adult offspring brain prenatally exposed to Maternal Immune Activation (MIA). Methylome of the adult brain supplemented with omega-3 polyunsaturated fatty acids (PUFA) is also described. DNA methylation across gene regulatory regions were measured using MSP-I digestion and Reduced Representation Bisulfite Sequencing (RRBS) method.