Estimating DNA methylation potential energy landscapes from nanopore sequencing data.

High-throughput third-generation nanopore sequencing devices have enormous potential for simultaneously observing epigenetic modifications in human cells over large regions of the genome. However, signals generated by these devices are subject to considerable noise that can lead to unsatisfactory detection performance and hamper downstream analysis. Here we develop a statistical method, CpelNano, for the quantification and analysis of 5mC methylation landscapes using nanopore data.

Converging genetic and epigenetic drivers of paediatric acute lymphoblastic leukaemia identified by an information-theoretic analysis.

In cancer, linking epigenetic alterations to drivers of transformation has been difficult, in part because DNA methylation analyses must capture epigenetic variability, which is central to tumour heterogeneity and tumour plasticity. Here, by conducting a comprehensive analysis, based on information theory, of differences in methylation stochasticity in samples from patients with paediatric acute lymphoblastic leukaemia (ALL), we show that ALL epigenomes are stochastic and marked by increased methylation entropy at specific regulatory regions and genes. By integrating DNA methylation and single-cell gene-expression data, we arrived at a relationship between methylation entropy and gene-expression variability, and found that epigenetic changes in ALL converge on a shared set of genes that overlap with genetic drivers involved in chromosomal translocations across the disease spectrum.

Detection of haplotype-dependent allele-specific DNA methylation in WGBS data.

In heterozygous genomes, allele-specific measurements can reveal biologically significant differences in DNA methylation between homologous alleles associated with local changes in genetic sequence. Current approaches for detecting such events from whole-genome bisulfite sequencing (WGBS) data perform statistically independent marginal analysis at individual cytosine-phosphate-guanine (CpG) sites, thus ignoring correlations in the methylation state, or carry-out a joint statistical analysis of methylation patterns at four CpG sites producing unreliable statistical evidence. Here, we employ the one-dimensional Ising model of statistical physics and develop a method for detecting allele-specific methylation (ASM) events within segments of DNA containing clusters of linked single-nucleotide polymorphisms (SNPs), called haplotypes.

The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight.

To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress-related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted.