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DNA sequencing analysis typically involves mapping reads to just one reference genome.  Mapping against multiple genomes is necessary, however, when the genome of origin requires confirmation. Mapping against multiple genomes is also advisable for detecting contamination or for identifying sample swaps which, if left undetected, may lead to incorrect experimental conclusions.  Consequently, we present FastQ Screen, a tool to validate the origin of DNA samples by quantifying the proportion of reads that map to a panel of reference genomes. FastQ Screen is intended to be used routinely as a quality control measure and for analysing samples in which the origin of the DNA is uncertain or has multiple sources.

Sequencing reads overlapping polymorphic sites in diploid mammalian genomes may be assigned to one allele or the other. This holds the potential to detect gene expression, chromatin modifications, DNA methylation or nuclear interactions in an allele-specific fashion. SNPsplit is an allele-specific alignment sorter designed to read files in SAM/BAM format and determine the allelic origin of reads or read-pairs that cover known single nucleotide polymorphic (SNP) positions. For this to work libraries must have been aligned to a genome in which all known SNP positions were masked with the ambiguity base 'N' and aligned using a suitable mapping program such as Bowtie2, TopHat, STAR, HISAT2, HiCUP or Bismark. SNPsplit also provides an automated solution to generate N-masked reference genomes for hybrid mouse strains based on the variant call information provided by the Mouse Genomes Project. The unique ability of SNPsplit to work with various different kinds of sequencing data including RNA-Seq, ChIP-Seq, Bisulfite-Seq or Hi-C opens new avenues for the integrative exploration of allele-specific data.

In this Review, the authors take the reader through the steps needed to analyze bisulfite-treated DNA, pointing out different considerations for data in base or color space, to ensure high-quality methylome analysis. Bisulfite conversion of genomic DNA combined with next-generation sequencing (BS-seq) is widely used to measure the methylation state of a whole genome, the methylome, at single-base resolution. However, analysis of BS-seq data still poses a considerable challenge. Here we summarize the challenges of BS-seq mapping as they apply to both base and color-space data. We also explore the effect of sequencing errors and contaminants on inferred methylation levels and recommend the most appropriate way to analyze this type of data.

Single-cell bisulfite sequencing (scBS-seq) allows robust DNA methylation analysis in rare cells and heterogeneous populations. We report a single-cell bisulfite sequencing (scBS-seq) method that can be used to accurately measure DNA methylation at up to 48.4% of CpG sites. Embryonic stem cells grown in serum or in 2i medium displayed epigenetic heterogeneity, with '2i-like' cells present in serum culture. Integration of 12 individual mouse oocyte datasets largely recapitulated the whole DNA methylome, which makes scBS-seq a versatile tool to explore DNA methylation in rare cells and heterogeneous populations.

Background Whole-genome bisulfite sequencing (WGBS) is becoming an increasingly accessible technique, used widely for both fundamental and disease-oriented research. Library preparation methods benefit from a variety of available kits, polymerases and bisulfite conversion protocols. Although some steps in the procedure, such as PCR amplification, are known to introduce biases, a systematic evaluation of biases in WGBS strategies is missing. Results We perform a comparative analysis of several commonly used pre- and post-bisulfite WGBS library preparation protocols for their performance and quality of sequencing outputs. Our results show that bisulfite conversion per se is the main trigger of pronounced sequencing biases, and PCR amplification builds on these underlying artefacts. The majority of standard library preparation methods yield a significantly biased sequence output and overestimate global methylation. Importantly, both absolute and relative methylation levels at specific genomic regions vary substantially between methods, with clear implications for DNA methylation studies. Conclusions We show that amplification-free library preparation is the least biased approach for WGBS. In protocols with amplification, the choice of bisulfite conversion protocol or polymerase can significantly minimize artefacts. To aid with the quality assessment of existing WGBS datasets, we have integrated a bias diagnostic tool in the Bismark package and offer several approaches for consideration during the preparation and analysis of WGBS datasets.

DNA methylation is a repressive epigenetic modification that is essential for development, exemplified by the embryonic and perinatal lethality observed in mice lacking de novo DNA methyltransferases (DNMTs). Here we characterise the role for DNMT3A, 3B and 3L in gene regulation and development of the mouse placenta. We find that each DNMT establishes unique aspects of the placental methylome through targeting to distinct chromatin features. Loss of Dnmt3b results in de-repression of germline genes in trophoblast lineages and impaired formation of the maternal-foetal interface in the placental labyrinth. Using Sox2 -Cre to delete Dnmt3b in the embryo, leaving expression intact in placental cells, the placental phenotype was rescued and, consequently, the embryonic lethality, as Dnmt3b null embryos could now survive to birth. We conclude that de novo DNA methylation by DNMT3B during embryogenesis is principally required to regulate placental development and function, which in turn is critical for embryo survival. DNA methylation is a repressive modification that is essential for development. Here the authors reveal a critical role for DNA methylation in placental development during pregnancy. Failure to properly establish placental DNA methylation patterns compromises not only placental function, but embryo survival.

Gavin Kelsey and colleagues report methylation landscapes in mouse oocytes, sperm and blastocysts. They find that the majority of methylated CpG islands in oocytes display incomplete demethylation in preimplantation embryos. Elucidating how and to what extent CpG islands (CGIs) are methylated in germ cells is essential to understand genomic imprinting and epigenetic reprogramming 1 , 2 , 3 . Here we present, to our knowledge, the first integrated epigenomic analysis of mammalian oocytes, identifying over a thousand CGIs methylated in mature oocytes. We show that these CGIs depend on DNMT3A and DNMT3L 4 , 5 but are not distinct at the sequence level, including in CpG periodicity 6 . They are preferentially located within active transcription units and are relatively depleted in H3K4me3, supporting a general transcription-dependent mechanism of methylation. Very few methylated CGIs are fully protected from post-fertilization reprogramming but, notably, the majority show incomplete demethylation in embryonic day (E) 3.5 blastocysts. Our study shows that CGI methylation in gametes is not entirely related to genomic imprinting but is a strong factor in determining methylation status in preimplantation embryos, suggesting a need to reassess mechanisms of post-fertilization demethylation.

Age-related tissue alterations have been associated with a decline in stem cell number and function. Although increased cell-to-cell variability in transcription or epigenetic marks has been proposed to be a major hallmark of ageing, little is known about the molecular diversity of stem cells during ageing. Here we present a single cell multi-omics study of mouse muscle stem cells, combining single-cell transcriptome and DNA methylome profiling. Aged cells show a global increase of uncoordinated transcriptional heterogeneity biased towards genes regulating cell-niche interactions. We find context-dependent alterations of DNA methylation in aged stem cells. Importantly, promoters with increased methylation heterogeneity are associated with increased transcriptional heterogeneity of the genes they drive. These results indicate that epigenetic drift, by accumulation of stochastic DNA methylation changes in promoters, is associated with the degradation of coherent transcriptional networks during stem cell ageing. Furthermore, our observations also shed light on the mechanisms underlying the DNA methylation clock. Age-related tissue alterations have been associated with a decline in stem cell number and function. Here the authors report a single cell multi-omics study of mouse muscle stem cells, combining single cell transcriptome and DNA methylome profiling and find that aged cells have a global increase of uncoordinated transcriptional heterogeneity biased towards genes regulating cell-niche interactions.

The occurrence of repetitive genomic changes that provide a selective growth advantage in pluripotent stem cells is of concern for their clinical application. However, the effect of different culture conditions on the underlying mutation rate is unknown. Here we show that the mutation rate in two human embryonic stem cell lines derived and banked for clinical application is low and not substantially affected by culture with Rho Kinase inhibitor, commonly used in their routine maintenance. However, the mutation rate is reduced by >50% in cells cultured under 5% oxygen, when we also found alterations in imprint methylation and reversible DNA hypomethylation. Mutations are evenly distributed across the chromosomes, except for a slight increase on the X-chromosome, and an elevation in intergenic regions suggesting that chromatin structure may affect mutation rate. Overall the results suggest that pluripotent stem cells are not subject to unusually high rates of genetic or epigenetic alterations. Mutations in human pluripotent stem cells (PSC) and whether any form during culture prior to use in a human clinical context are a concern. Here, the authors use hPSCs derived to cGMP standards and show they have low mutation rates after culture, noting this decreases on culturing in low (5%) oxygen conditions.

Massively parallel DNA sequencing is capable of sequencing tens of millions of DNA fragments at the same time. However, sequence bias in the initial cycles, which are used to determine the coordinates of individual clusters, causes a loss of fidelity in cluster identification on Illumina Genome Analysers. This can result in a significant reduction in the numbers of clusters that can be analysed. Such low sample diversity is an intrinsic problem of sequencing libraries that are generated by restriction enzyme digestion, such as e4C-seq or reduced-representation libraries. Similarly, this problem can also arise through the combined sequencing of barcoded, multiplexed libraries. We describe a procedure to defer the mapping of cluster coordinates until low-diversity sequences have been passed. This simple procedure can recover substantial amounts of next generation sequencing data that would otherwise be lost.