A new approach to decode DNA methylome and genomic variants simultaneously from double strand bisulfite sequencing

Simultaneous assessment of human genome and methylome data in a single experiment using limited deamination of methylated cytosine

Multiomics require concerted recording of independent information, ideally from a single experiment. In this study, we introduce RIMS-seq2, a high-throughput technique to simultaneously sequence genomes and overlay methylation information while requiring only a small modification of the experimental protocol for high-throughput DNA sequencing to include a controlled deamination step. Importantly, the rate of deamination of 5-methylcytosine is negligible and thus does not interfere with standard DNA sequencing and data processing. Thus, RIMS-seq2 libraries from whole- or targeted-genome sequencing show the same germline variation calling accuracy and sensitivity compared with standard DNA-seq. Additionally, regional methylation levels provide an accurate map of the human methylome.

bsgenova: an accurate, robust, and fast genotype caller for bisulfite-sequencing data

BACKGROUND

Bisulfite sequencing (BS-Seq) is a fundamental technique for characterizing DNA methylation profiles. Genotype calling from bisulfite-converted BS-Seq data allows allele-specific methylation analysis and the concurrent exploration of genetic and epigenetic profiles. Despite various methods have been proposed, single nucleotide polymorphisms (SNPs) calling from BS-Seq data, particularly for SNPs on chromosome X and in the presence of contaminative data, poses ongoing challenges.

RESULTS

We introduce bsgenova, a novel SNP caller tailored for bisulfite sequencing data, employing a Bayesian multinomial model. The performance of bsgenova is assessed by comparing SNPs called from real-world BS-Seq data with those from corresponding whole-genome sequencing (WGS) data across three human cell lines. bsgenova is both sensitive and precise, especially for chromosome X, compared with three existing methods. Moreover, in the presence of low-quality reads, bsgenova outperforms other methods notably. In addition, bsgenova is meticulously implemented, leveraging matrix imputation and multi-process parallelization. Compared to existing methods, bsgenova stands out for its speed and efficiency in memory and disk usage. Furthermore, bsgenova integrates bsextractor, a methylation extractor, enhancing its flexibility and expanding its utility.

CONCLUSIONS

We introduce bsgenova for SNP calling from bisulfite-sequencing data. The source code is available at https://github.com/hippo-yf/bsgenova under license GPL-3.0.

Methylation Array Signals are Predictive of Chronological Age Without Bisulfite Conversion

DNA methylation data has been used to make "epigenetic clocks" which attempt to measure chronological and biological aging. These models rely on data derived from bisulfite-based measurements, which exploit a semi-selective deamination and a genomic reference to determine methylation states. Here, we demonstrate how another hallmark of aging, genomic instability, influences methylation measurements in both bisulfite sequencing and methylation arrays. We found that non-methylation factors lead to "pseudomethylation" signals that are both confounding of epigenetic clocks and uniquely age predictive. Quantifying these covariates in aging studies will be critical to building better clocks and designing appropriate studies of epigenetic aging.

Genome-wide DNA methylation landscape of four Chinese populations and epigenetic variation linked to Tibetan high-altitude adaptation

DNA methylation (DNAm) is one of the major epigenetic mechanisms in humans and is important in diverse cellular processes. The variation of DNAm in the human population is related to both genetic and environmental factors. However, the DNAm profiles have not been investigated in the Chinese population of diverse ethnicities. Here, we performed double-strand bisulfite sequencing (DSBS) for 32 Chinese individuals representing four major ethnic groups including Han Chinese, Tibetan, Zhuang, and Mongolian. We identified a total of 604,649 SNPs and quantified DNAm at more than 14 million CpGs in the population. We found global DNAm-based epigenetic structure is different from the genetic structure of the population, and ethnic difference only partially explains the variation of DNAm. Surprisingly, non-ethnic-specific DNAm variations showed stronger correlation with the global genetic divergence than these ethnic-specific DNAm. Differentially methylated regions (DMRs) among these ethnic groups were found around genes in diverse biological processes. Especially, these DMR-genes between Tibetan and non-Tibetans were enriched around high-altitude genes including EPAS1 and EGLN1, suggesting DNAm alteration plays an important role in high-altitude adaptation. Our results provide the first batch of epigenetic maps for Chinese populations and the first evidence of the association of epigenetic changes with Tibetans' high-altitude adaptation.

Methyl-SNP-seq reveals dual readouts of methylome and variome at molecule resolution while enabling target enrichment

Covalent modifications of genomic DNA are crucial for most organisms to survive. Amplicon-based high-throughput sequencing technologies erase all DNA modifications to retain only sequence information for the four canonical nucleobases, necessitating specialized technologies for ascertaining epigenetic information. To also capture base modification information, we developed Methyl-SNP-seq, a technology that takes advantage of the complementarity of the double helix to extract the methylation and original sequence information from a single DNA molecule. More specifically, Methyl-SNP-seq uses bisulfite conversion of one of the strands to identify cytosine methylation while retaining the original four-bases sequence information on the other strand. As both strands are locked together to link the dual readouts on a single paired-end read, Methyl-SNP-seq allows detecting the methylation status of any DNA even without a reference genome. Because one of the strands retains the original four nucleotide composition, Methyl-SNP-seq can also be used in conjunction with standard sequence-specific probes for targeted enrichment and amplification. We show the usefulness of this technology in a broad spectrum of applications ranging from allele-specific methylation analysis in humans to identification of methyltransferase specificity in complex bacterial communities.