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

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.

Systematic and benchmarking studies of pipelines for mammal WGBS data in the novel NGS platform

BACKGROUND

Whole genome bisulfite sequencing (WGBS), possesses the aptitude to dissect methylation status at the nucleotide-level resolution of 5-methylcytosine (5-mC) on a genome-wide scale. It is a powerful technique for epigenome in various cell types, and tissues. As a recently established next-generation sequencing (NGS) platform, GenoLab M is a promising alternative platform. However, its comprehensive evaluation for WGBS has not been reported. We sequenced two bisulfite-converted mammal DNA in this research using our GenoLab M and NovaSeq 6000, respectively. Then, we systematically compared those data via four widely used WGBS tools (BSMAP, Bismark, BatMeth2, BS-Seeker2) and a new bisulfite-seq tool (BSBolt). We interrogated their computational time, genome depth and coverage, and evaluated their percentage of methylated Cs.

RESULT

Here, benchmarking a combination of pre- and post-processing methods, we found that trimming improved the performance of mapping efficiency in eight datasets. The data from two platforms uncovered ~ 80% of CpG sites genome-wide in the human cell line. Those data sequenced by GenoLab M achieved a far lower proportion of duplicates (~ 5.5%). Among pipelines, BSMAP provided an intriguing representation of 5-mC distribution at CpG sites with 5-mC levels > ~ 78% in datasets from human cell lines, especially in the GenoLab M. BSMAP performed more advantages in running time, uniquely mapped reads percentages, genomic coverage, and quantitative accuracy. Finally, compared with the previous methylation pattern of human cell line and mouse tissue, we confirmed that the data from GenoLab M performed similar consistency and accuracy in methylation levels of CpG sites with that from NovaSeq 6000.

CONCLUSION

Together we confirmed that GenoLab M was a qualified NGS platform for WGBS with high performance. Our results showed that BSMAP was the suitable pipeline that allowed for WGBS studies on the GenoLab M platform.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Benchmarking DNA Methylation Analysis of 14 Alignment Algorithms for Whole Genome Bisulfite Sequencing in Mammals

Whole genome bisulfite sequencing (WGBS) is an essential technique for methylome studies. Although a series of tools have been developed to overcome the mapping challenges caused by bisulfite treatment, the latest available tools have not been evaluated on the performance of reads mapping as well as on biological insights in multiple mammals. Herein, based on the real and simulated WGBS data of 14.77 billion reads, we undertook 936 mappings to benchmark and evaluate 14 wildly utilized alignment algorithms from reads mapping to biological interpretation in humans, cattle and pigs: Bwa-meth, BSBolt, BSMAP, Walt, Abismal, Batmeth2, Hisat_3n, Hisat_3n_repeat, Bismark-bwt2-e2e, Bismark-his2, BSSeeker2-bwt, BSSeeker2-soap2, BSSeeker2-bwt2-e2e and BSSeeker2-bwt2-local. Specifically, Bwa-meth, BSBolt, BSMAP, Bismark-bwt2-e2e and Walt exhibited higher uniquely mapped reads, mapped precision, recall and F1 score than other nine alignment algorithms, and the influences of distinct alignment algorithms on the methylomes varied considerably at the numbers and methylation levels of CpG sites, the calling of differentially methylated CpGs (DMCs) and regions (DMRs). Moreover, we reported that BSMAP showed the highest accuracy at the detection of CpG coordinates and methylation levels, the calling of DMCs, DMRs, DMR-related genes and signaling pathways. These results suggested that careful selection of algorithms to profile the genome-wide DNA methylation is required, and our works provided investigators with useful information on the choice of alignment algorithms to effectively improve the DNA methylation detection accuracy in mammals.

Analysis and Performance Assessment of the Whole Genome Bisulfite Sequencing Data Workflow: Currently Available Tools and a Practical Guide to Advance DNA Methylation Studies

DNA methylation is associated with transcriptional repression, genomic imprinting, stem cell differentiation, embryonic development, and inflammation. Aberrant DNA methylation can indicate disease states, including cancer and neurological disorders. Therefore, the prevalence and location of 5-methylcytosine in the human genome is a topic of interest. Whole-genome bisulfite sequencing (WGBS) is a high-throughput method for analyzing DNA methylation. This technique involves library preparation, alignment, and quality control. Advancements in epigenetic technology have led to an increase in DNA methylation studies. This review compares the detailed experimental methodology of WGBS using accessible and up-to-date analysis tools. Practical codes for WGBS data processing are included as a general guide to assist progress in DNA methylation studies through a comprehensive case study.

Low guanine content and biased nucleotide distribution in vertebrate mtDNA can cause overestimation of non-CpG methylation

Mitochondrial DNA (mtDNA) methylation in vertebrates has been hotly debated for over 40 years. Most contrasting results have been reported following bisulfite sequencing (BS-seq) analyses. We addressed whether BS-seq experimental and analysis conditions influenced the estimation of the levels of methylation in specific mtDNA sequences. We found false positive non-CpG methylation in the CHH context (fpCHH) using unmethylated Sus scrofa mtDNA BS-seq data. fpCHH methylation was detected on the top/plus strand of mtDNA within low guanine content regions. These top/plus strand sequences of fpCHH regions would become extremely AT-rich sequences after BS-conversion, whilst bottom/minus strand sequences remained almost unchanged. These unique sequences caused BS-seq aligners to falsely assign the origin of each strand in fpCHH regions, resulting in false methylation calls. fpCHH methylation detection was enhanced by short sequence reads, short library inserts, skewed top/bottom read ratios and non-directional read mapping modes. We confirmed no detectable CHH methylation in fpCHH regions by BS-amplicon sequencing. The fpCHH peaks were located in the D-loop, ATP6, ND2, ND4L, ND5 and ND6 regions and identified in our S. scrofa ovary and oocyte data and human BS-seq data sets. We conclude that non-CpG methylation could potentially be overestimated in specific sequence regions by BS-seq analysis.

From Methylome to Integrative Analysis of Tissue Specificity

DNA methylation is the most studied epigenetic mark in both plants and animals. The gold standard for assaying genome-wide DNA methylation at single-base resolution is whole-genome bisulfite sequencing (WGBS). Here, we describe an improved procedure for WGBS and original bioinformatic workflows applied to unravel tissue-specific variations of the methylome in relation to gene expression and accumulation of secondary metabolites in the medicinal plant Catharanthus roseus.

Rapid identification of methylase specificity (RIMS-seq) jointly identifies methylated motifs and generates shotgun sequencing of bacterial genomes

DNA methylation is widespread amongst eukaryotes and prokaryotes to modulate gene expression and confer viral resistance. 5-Methylcytosine (m5C) methylation has been described in genomes of a large fraction of bacterial species as part of restriction-modification systems, each composed of a methyltransferase and cognate restriction enzyme. Methylases are site-specific and target sequences vary across organisms. High-throughput methods, such as bisulfite-sequencing can identify m5C at base resolution but require specialized library preparations and single molecule, real-time (SMRT) sequencing usually misses m5C. Here, we present a new method called RIMS-seq (rapid identification of methylase specificity) to simultaneously sequence bacterial genomes and determine m5C methylase specificities using a simple experimental protocol that closely resembles the DNA-seq protocol for Illumina. Importantly, the resulting sequencing quality is identical to DNA-seq, enabling RIMS-seq to substitute standard sequencing of bacterial genomes. Applied to bacteria and synthetic mixed communities, RIMS-seq reveals new methylase specificities, supporting routine study of m5C methylation while sequencing new genomes.

Performance of methods to detect genetic variants from bisulphite sequencing data in a non-model species

The profiling of epigenetic marks like DNA methylation has become a central aspect of studies in evolution and ecology. Bisulphite sequencing is commonly used for assessing genome‐wide DNA methylation at single nucleotide resolution but these data can also provide information on genetic variants like single nucleotide polymorphisms (SNPs). However, bisulphite conversion causes unmethylated cytosines to appear as thymines, complicating the alignment and subsequent SNP calling. Several tools have been developed to overcome this challenge, but there is no independent evaluation of such tools for non‐model species, which often lack genomic references. Here, we used whole‐genome bisulphite sequencing (WGBS) data from four female great tits (Parus major) to evaluate the performance of seven tools for SNP calling from bisulphite sequencing data. We used SNPs from whole‐genome resequencing data of the same samples as baseline SNPs to assess common performance metrics like sensitivity, precision, and the number of true positive, false positive, and false negative SNPs for the full range of variant and genotype quality values. We found clear differences between the tools in either optimizing precision (bis‐snp), sensitivity (biscuit), or a compromise between both (all other tools). Overall, the choice of SNP caller strongly depends on which performance parameter should be maximized and whether ascertainment bias should be minimized to optimize downstream analysis, highlighting the need for studies that assess such differences.

Challenges and Perspectives in the Epigenetics of Climate Change-Induced Forests Decline

Forest tree species are highly vulnerable to the effects of climate change. As sessile organisms with long generation times, their adaptation to a local changing environment may rely on epigenetic modifications when allele frequencies are not able to shift fast enough. However, the current lack of knowledge on this field is remarkable, due to many challenges that researchers face when studying this issue. Huge genome sizes, absence of reference genomes and annotation, and having to analyze huge amounts of data are among these difficulties, which limit the current ability to understand how climate change drives tree species epigenetic modifications. In spite of this challenging framework, some insights on the relationships among climate change-induced stress and epigenomics are coming. Advances in DNA sequencing technologies and an increasing number of studies dealing with this topic must boost our knowledge on tree adaptive capacity to changing environmental conditions. Here, we discuss challenges and perspectives in the epigenetics of climate change-induced forests decline, aiming to provide a general overview of the state of the art.

Developmental Methylome of the Medicinal Plant Catharanthus roseus Unravels the Tissue-Specific Control of the Monoterpene Indole Alkaloid Pathway by DNA Methylation

Catharanthus roseus produces a wide spectrum of monoterpene indole alkaloids (MIAs). MIA biosynthesis requires a tightly coordinated pathway involving more than 30 enzymatic steps that are spatio-temporally and environmentally regulated so that some MIAs specifically accumulate in restricted plant parts. The first regulatory layer involves a complex network of transcription factors from the basic Helix Loop Helix (bHLH) or AP2 families. In the present manuscript, we investigated whether an additional epigenetic layer could control the organ-, developmental- and environmental-specificity of MIA accumulation. We used Whole-Genome Bisulfite Sequencing (WGBS) together with RNA-seq to identify differentially methylated and expressed genes among nine samples reflecting different plant organs and experimental conditions. Tissue specific gene expression was associated with specific methylation signatures depending on cytosine contexts and gene parts. Some genes encoding key enzymatic steps from the MIA pathway were found to be simultaneously differentially expressed and methylated in agreement with the corresponding MIA accumulation. In addition, we found that transcription factors were strikingly concerned by DNA methylation variations. Altogether, our integrative analysis supports an epigenetic regulation of specialized metabolisms in plants and more likely targeting transcription factors which in turn may control the expression of enzyme-encoding genes.