Nature Reviews Genetics最新文献

Systems biology aims to achieve holistic insights into the molecular workings of cellular systems through iterative loops of measurement, analysis and perturbation. This framework has had remarkable success in unicellular model organisms, and recent experimental and computational advances — from single-cell and spatial profiling to CRISPR genome editing and machine learning — have raised the exciting possibility of leveraging such strategies to prevent, diagnose and treat human diseases. However, adapting systems-inspired approaches to dissect human disease complexity is challenging, given that discrepancies between the biological features of human tissues and the experimental models typically used to probe function (which we term ‘translational distance’) can confound insight. Here we review how samples, measurements and analyses can be contextualized within overall multiscale human disease processes to mitigate data and representation gaps. We then examine ways to bridge the translational distance between systems-inspired human discovery loops and model system validation loops to empower precision interventions in the era of single-cell genomics.

Deciphering metastatic processes is crucial for understanding cancer progression and potential treatment options. Genetic studies of model systems engineered to mimic metastatic disease, including organoids, genetically engineered mice and human cell lines, have had an important role in shaping our understanding of the metastatic cascade and how it can be manipulated. More recently, advances in high-throughput sequencing have enabled human metastases to be studied at single-cell and single-nucleotide resolution, providing insights into metastatic evolution and phenotypes of both cancer cells and immune cells. However, human tissue studies are often correlative and descriptive, whereas experimental models are reductionistic by nature, meaning that individual results should be interpreted with caution. Crucially, these seemingly disparate branches of metastasis research can and should complement each other to strengthen and validate findings. Here we explore the synergies between model systems and sequencing studies and outline key areas that must be explored to improve our understanding of the metastatic process.

The segmentation clock is a molecular oscillator that regulates the periodic formation of somites from the presomitic mesoderm during vertebrate embryogenesis. Synchronous oscillatory expression of a Hairy homologue or Hairy-related basic helix–loop–helix (bHLH) transcriptional repressor in presomitic mesoderm cells regulates periodic expression of downstream factors that control somite segmentation with a periodicity that varies across species. Although many of the key components of the clock have been identified and characterized, less is known about how the clock is synchronized across cells and how species-specific periodicity is achieved. Advances in live imaging, stem cell and organoid technologies, and synthetic approaches have started to uncover the detailed mechanisms underlying these aspects of somitogenesis, providing insight into how morphogenesis is coordinated in space and time during embryonic development.

Transcription factors (TFs) contribute to organismal development and function by regulating gene expression. Despite decades of research, the factors determining the specificity and speed at which eukaryotic TFs detect their target binding sites remain poorly understood. Recent studies have pointed to intrinsically disordered regions (IDRs) within TFs as key regulators of the process by which TFs find their target sites on DNA (the TF target search). However, IDRs are challenging to study because they can confer specificity despite low sequence complexity and can be functionally conserved despite rapid sequence divergence. Nevertheless, emerging computational and experimental approaches are beginning to elucidate the sequence–function relationship within the IDRs of TFs. Additional insights are informing potential mechanisms underlying the IDR-directed search for the DNA targets of TFs, including incorporation into biomolecular condensates, facilitating TF co-localization, and the hypothesis that IDRs recognize and directly interact with specific genomic regions.