Review Articles in 2020

The ability to reprogramme cellular translation and genomes to produce non-canonical biopolymers has wide-ranging applications, including in therapeutics, but has yet to be fully realized. In this Review, de la Torre and Chin discuss recent advances towards achieving this goal.

Haematopoietic stem and progenitor cell (HSPC) gene therapy using lentiviral or gammaretroviral vectors has now been approved for clinical use. In this Review, Ferrari, Thrasher and Aiuti discuss the history of HSPC gene therapy, the clinical promise of gene-editing HPSCs and the use of HSPC gene therapy to treat specific diseases.

Infectious diseases are an ever-present global threat. In this Review, Kwok, Mentzer and Knight discuss our latest understanding of how human genetics influence susceptibility to disease. Furthermore, they discuss emerging progress in the interplay between host and pathogen genetics, molecular responses to infection and vaccination, and opportunities to bring these aspects together for rapid responses to emerging diseases such as COVID-19.

In this Review, Hill et al. discuss how high-throughput methods for creating and characterizing mutations are providing insight into how regulatory variation is generated and evolves.

In this Review, Carter and Zhao discuss how single-cell sequencing technologies are being applied to investigate epigenetic heterogeneity among seemingly homogeneous populations of cells and how this epigenetic variability relates to cell–cell differences in gene expression.

RNA-binding proteins (RBPs) are critical effectors of gene expression, and their malfunction underlies many diseases. The authors review the role of RBPs in human genetic disorders, both Mendelian and somatic, discuss the molecular mechanisms of disease and highlight emerging therapeutic interventions that target RBPs.

In this Review, Oudelaar and Higgs discuss the relationship between genome structure and gene regulation, with a focus on whether genome organization has an instructive role or largely reflects the activity of regulatory elements.

Cell–cell interactions and communication can be inferred from RNA sequencing data of, for example, ligand–receptor pairs. The authors review insights gained and the methods and tools used in studies of cell–cell interactions based on transcriptomic data.

The effects of genetic variation on the adaptive potential of species depend on the frequencies of alleles at other loci in the individual or in the population, and the patterns of spatio-temporal co-occurrence between alleles in interacting species. This Review explores these population and community genomic contexts and their direct and indirect effects on biodiversity, ecosystems and people.

Deep resequencing has revealed extreme genetic variation in mitochondrial genomes at multiple levels. This heterogeneity has implications for the origins of human mitochondrial DNA mutations as well as their impact on rare and common human diseases, including cancer.

In this Review, Cenik and Shilatifard focus on two families of Trithorax group proteins: COMPASS histone H3 lysine 4 methyltransferase complexes and SWI/SNF chromatin remodelling complexes. They discuss the roles of these complexes in gene regulation, development and disease.

Various cellular metabolites provide the chemical moieties for DNA and histone modifications, resulting in a complex interplay between metabolism and epigenetics. In this Review, Dai, Ramesh and Locasale discuss the metabolic regulation of diverse types of chromatin modifications and the functional consequences of these modifications at the molecular, cellular and organismal levels, as well as influences from diet and microbiota.

Host–parasite co-evolution is expected to leave signatures of selection in the genome of both antagonists. Ebert and Fields discuss what is known about these signatures, how they relate to co-evolutionary processes and how they can help identify the genes underlying the co-evolving phenotypes.

In this Review, Suhre, McCarthy and Schwenk describe how combining genetics with plasma proteomics is providing notable insights into human disease. As changes in the circulating proteome are often an intermediate molecular readout between a genetic variant and its organismal effect, proteomics can enable a deeper understanding of disease mechanisms, clinical biomarkers and therapeutic opportunities.

Both genetic and non-genetic factors underlie the intratumoural heterogeneity that fuels cancer evolution. This Review discusses the application of single-cell multi-omics technologies to the study of cancer evolution, which capture and integrate the different layers of heritable information and reveal their complex interplay.

The growth and survival of cells within tissues can be influenced by competition between different cell clones. Genetic and cell biological studies suggest that cell competition may occur through the molecular recognition of ‘different’ cells, signalling imbalances between cell populations or the mechanical consequences of differential growth rates.

Genome instability can lead to a number of human diseases, including neurodegeneration and cancer. In this Review, Zong et al. discuss the various ways in which RNA can both promote genome instability and contribute to genome maintenance.

Gene expression is typically measured at the level of either mRNAs or proteins. In this Review, Buccitelli and Selbach discuss how large-scale comparative studies are characterizing the degree to which mRNA and protein levels correlate. They discuss technical and biological reasons why mRNA and protein levels may be particularly concordant or disconnected, as well as the different biological information provided by these non-redundant readouts of gene expression.

Data sharing can maximize the benefit and reach of genomics research. However, sharing must occur in a responsible manner, particularly when there are privacy risks to human participants. In this Review, the authors discuss the principles of data sharing, strategies for assessing and mitigating privacy risks, as well as practical guidelines for researchers and wider stakeholders.

Computational tools to analyse RNA sequencing data often disregard or even misinterpret reads derived from transposable elements. This Review highlights the main challenges associated with the detection of transposable element expression, including mappability, sequence polymorphisms and transcript diversity, and discusses the experimental and computational strategies to overcome them.