Nature Reviews Genetics最新文献

DNA sequencing from bulk or clonal human tissues has shown that genetic mosaicism is common and contributes to both cancer and non-cancerous disorders. However, single-cell resolution is required to understand the full genetic heterogeneity that exists within a tissue and the mechanisms that lead to somatic mosaicism. Single-cell DNA-sequencing technologies have traditionally trailed behind those of single-cell transcriptomics and epigenomics, largely because most applications require whole-genome amplification before costly whole-genome sequencing. Now, recent technological and computational advances are enabling the use of single-cell DNA sequencing to tackle previously intractable problems, such as delineating the genetic landscape of tissues with complex clonal patterns, of samples where cellular material is scarce and of non-cycling, postmitotic cells. Single-cell genomes are also revealing the mutational patterns that arise from biological processes or disease states, and have made it possible to track cell lineage in human tissues. These advances in our understanding of tissue biology and our ability to identify disease mechanisms will ultimately transform how disease is diagnosed and monitored.

Transcription factors relay information from the external environment to gene regulatory networks that control cell physiology. To confer signalling specificity, robustness and coordination, these signalling networks use temporal communication codes, such as the amplitude, duration or frequency of signals. Although much is known about how temporal information is encoded, a mechanistic understanding of how gene regulatory networks decode signalling dynamics is lacking. Recent advances in our understanding of phase separation of transcriptional condensates provide new biophysical frameworks for both temporal encoding and decoding mechanisms. In this Perspective, we summarize the mechanisms by which transcriptional condensates could enable temporal decoding through signal adaptation, memory and persistence. We further outline methods to probe and manipulate dynamic communication codes of transcription factors and condensates to rationally control gene activation.

Endogenous, long double-stranded RNA (dsRNA) can resemble viral dsRNA and be recognized by cytosolic dsRNA sensors, triggering autoimmunity. Genetic studies of rare, inherited human diseases and experiments using mouse models have established the importance of adenosine-to-inosine RNA editing by the enzyme adenosine deaminase acting on RNA 1 (ADAR1) as a critical safeguard against autoinflammatory responses to cellular dsRNA. More recently, human genetic studies have revealed that dsRNA editing and sensing mechanisms are involved in common inflammatory diseases, emphasizing the broader role of dsRNA in modulating immune responses and disease pathogenesis. These findings have highlighted the therapeutic potential of targeting dsRNA editing and sensing, as exemplified by the emergence of ADAR1 inhibition in cancer therapy.

Eukaryotic RNA transcripts undergo extensive processing before becoming functional messenger RNAs, with splicing being a critical and highly regulated step that occurs both co-transcriptionally and post-transcriptionally. Recent analyses have revealed, with unprecedented spatial and temporal resolution, that up to 40% of mammalian introns are retained after transcription termination and are subsequently removed largely while transcripts remain chromatin-associated. Post-transcriptional splicing has emerged as a key layer of gene expression regulation during development, stress response and disease progression. The control of post-transcriptional splicing regulates protein production through delayed splicing and nuclear export, or nuclear retention and degradation of specific transcript isoforms. Here, we review current methodologies for detecting post-transcriptional splicing, discuss the mechanisms controlling the timing of splicing and examine how this temporal regulation affects gene expression programmes in healthy cells and in disease states.

Human height is a model polygenic trait — additive effects of many individual variants create continuous, genetically determined variation in this phenotype. Height can also be severely affected by single-gene variants in monogenic disorders, often causing severe alterations in stature relative to population averages. Deciphering the genetic basis of height provides understanding into the biology of growth and is also of relevance to disease, as increased or decreased height relative to population averages has been epidemiologically and genetically associated with an altered risk of cancer or cardiometabolic diseases. With recent large-scale genome-wide association studies of human height reaching saturation, its genetic architecture has become clearer. Genes implicated by both monogenic and polygenic studies converge on common developmental or cellular pathways that affect stature, including at the growth plate, a key site of skeletal growth. In this Review, we summarize the genetic contributors to height, from ultra-rare monogenic disorders that severely affect growth to common alleles that act across multiple pathways.

During early embryonic development in mammals, the totipotency of the zygote — which is reprogrammed from the differentiated gametes — transitions to pluripotency by the blastocyst stage, coincident with the first cell fate decision. These changes in cellular potency are accompanied by large-scale alterations in the nucleus, including major transcriptional, epigenetic and architectural remodelling, and the establishment of the DNA replication programme. Advances in low-input genomics and loss-of-function methodologies tailored to the pre-implantation embryo now enable these processes to be studied at an unprecedented level of molecular detail in vivo. Such studies have provided new insights into the genome-wide landscape of epigenetic reprogramming and chromatin dynamics during this fundamental period of pre-implantation development.

Retrotransposable elements (RTEs) are interspersed repetitive sequences that represent a large portion of eukaryotic genomes. Ancestral expansions of RTEs directly contributed to the shaping of these genomes and to the evolution of different species, particularly mammals. RTE activity is tightly regulated by different epigenetic mechanisms but this control becomes compromised as cells age and RTEs are reactivated. This dysregulation of RTEs leads to perturbation of cell function and organ and organismal homeostasis, which drives ageing and age-related disease. Environmental stress is associated with both ageing-related characteristics and the epigenetic mechanisms that control RTE activity, with accumulating evidence indicating that RTE reactivation mediates the effects of environmental stressors on ageing onset and progression. A better understanding of how RTEs are reactivated and their subsequent biological roles may help the development of therapies against ageing-related phenotypes and diseases.

DNA methylation is a critical epigenetic mechanism in numerous biological processes, including gene regulation, development, ageing and the onset of various diseases such as cancer. Studies of methylation are increasingly using single-molecule long-read sequencing technologies to simultaneously measure epigenetic states such as DNA methylation with genomic variation. These long-read data sets have spurred the continuous development of advanced computational methods to gain insights into the roles of methylation in regulating chromatin structure and gene regulation. In this Review, we discuss the computational methods for calling methylation signals, contrasting methylation between samples, analysing cell-type diversity and gaining additional genomic insights, and then further discuss the challenges and future perspectives of tool development for DNA methylation research.