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Although cancer genome sequencing is becoming routine in cancer research, cancer transcriptome profiling through methods such as RNA sequencing (RNA-seq) provides information not only on mutations but also on their functional cellular consequences. This Review discusses how technical and analytical advances in cancer transcriptomics have provided various clinically valuable insights into gene expression signatures, driver gene prioritization, cancer microenvironments, immuno-oncology and prognostic biomarkers.
Genomic technologies are providing a clearer picture of how nuclear receptors (NRs) regulate complex transcriptional networks and contribute to the development and progression of cancer. This deeper understanding of NRs will hopefully lead to improved prognostic tools and new therapeutic targets.
Genetic architecture describes the characteristics of genetic variation that are responsible for phenotypic variability. This Review discusses the types of genetic architecture that have been observed, how they can be measured and how genetic architecture informs the scientific and clinical goals of human genetics.
In this Review, Kanieckiet al. discuss how the use of single-molecule optical microscopy and super-resolution optical microscopy methods has benefited our understanding of homologous recombination by generating detailed insights into the molecules and processes involved.
The rapid development of CRISPR-based gene manipulation has enabled various approaches for high-throughput functional genomics. This Review guides users through the practicalities of CRISPR-based functional genomics screens, including study design options, best-practice approaches, pitfalls to avoid and data analysis strategies.
Including diverse populations in genomic studies has the potential to improve the use of genomic data in the clinic. Here, members of the National Human Genome Research Institute review the benefits of increasing diversity, the challenges to overcome and key recommendations for how to achieve this goal.
The wealth of DNA methylation data continues to grow rapidly, including from epigenome-wide association studies (EWAS). However, extracting meaningful biological and clinical information requires diverse computational approaches for data analysis. This Review discusses the range of statistical tools available, including for cell-type deconvolution, identification of important methylation data features, causation and system-level integration with other types of omic data.
Next-generation sequencing has the potential to support public health surveillance systems to improve the early detection of emerging infectious diseases. This Review delineates the role of genomics in rapid outbreak response and the challenges that need to be tackled for genomics-informed pathogen surveillance to become a global reality.
