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Transposable elements (TEs) need to be tightly regulated in genomes to prevent the detrimental consequences of transposition. In this Review, Deniz, Frost and Branco discuss how DNA methylation dynamics play a central role in the multilayered epigenetic mechanisms regulating TEs. Beyond roles for 5-methylcytosine (5mC), they discuss TET-mediated oxidation products of 5mC, as well as ongoing debates about the functional relevance of adenine methylation.
Chromosomal inversions that relocate a limb enhancer establish patterns of asymmetric chromatin contacts, so-called architectural stripes, that result in ectopic gene expression and congenital limb phenotypes, according to a study in Nature Cell Biology.
A new technique named ChIA-Drop combines chromatin interaction analysis (ChIA) with droplet-based and barcode-linked high-throughput sequencing to capture multiplex chromatin interactions at the single-molecule level.
In this Timeline article, Shay and Wright provide a historical account of progress in our understanding of telomeres (the ends of linear chromosomes) and telomerase (the primary enzyme that maintains and extends telomere lengths). Their perspective covers seminal moments from the early discoveries through to our latest understanding of the roles of telomeres and telomerase in ageing, diverse human diseases and gene regulation.
A study published in Nature reports the functional and structural characterization of CasX, an RNA-guided DNA endonuclease with potential for use as a new genome editing platform.
Enthusiasm for patient-specific therapies based on induced pluripotent stem cells (iPSCs) has risen in parallel with rapid advances in genome editing. This Review summarizes the progress in iPSC-based disease modelling over the past decade, with a focus on 3D organoid systems and chimeric models being exploited for new therapeutic approaches.
The functional interpretation of single-cell RNA sequencing (scRNA-seq) data can be enhanced by integrating additional data types beyond RNA-based gene expression. In this Review, Stuart and Satija discuss diverse approaches for integrative single-cell analysis, including experimental methods for profiling multiple omics types from the same cells, analytical approaches for extracting additional layers of information directly from scRNA-seq data and computational integration of omics data collected across different cell samples.
A new study uses deep learning to predict genetic variants that generate cryptic splice sites and to investigate the role of these non-coding cryptic splice mutations in rare genetic disorders.
Two studies in Developmental Cell report the generation of mice with longer and shorter than normal tails, respectively, giving insight into developmental programmes and key genes involved in mouse tail development.
Chromatin accessibility comprises the positions, compaction and dynamics of nucleosomes, as well as the occupancy of DNA by other proteins such as transcription factors. In this Review, the authors discuss diverse methods for characterizing chromatin accessibility, how accessibility is determined and remodelled in cells and the regulatory roles of accessibility in gene expression and development.
A new study published in Cell uses bacterial genetic screens to identify mutagenic proteins. Overexpression of homologues of these proteins in human cells has similar mutagenic effects and potential prognostic value in cancer.
The BabySeq project, a pilot randomized clinical trial exploring the value of routine genomic sequencing of neonates compared with standard newborn screening, now reports initial results in the American Journal of Human Genetics.
Disruption of genomic imprinting can lead to disease. Recent studies suggest that interactions between the genome, the epigenome and the environment in germ cells and early embryos have an impact on developmental outcomes and on the heritability of imprinting disorders.
Comparing the microbiomes of great apes enables an evolutionary perspective on microbial communities. This approach is revealing not only new insights about humans and what differentiates us from our closest relatives but also the factors that influence microbiome composition and the ways in which microbiomes diverge.
Single-cell RNA sequencing (scRNA-seq) enables transcriptome-based characterization of the constituent cell types within a heterogeneous sample. However, reliable analysis and biological interpretation typically require optimal use of clustering algorithms. This Review discusses the multiple algorithmic options for clustering scRNA-seq data, including various technical, biological and computational considerations.
