The mitochondrial genome is co-localized with DNA replication machinery, which maintains and propagates it in cells, and gene expression machinery, which synthesizes essential mtDNA-encoded components of the respiratory chain required for energy conversion
Mammalian mitochondria produce a minimalistic complement of 11 mRNAs, 22 tRNAs, and two rRNAs, however, their metabolism is predominantly regulated post-transcriptionally by nuclear-encoded RNA-binding proteins during RNA processing, maturation, translation and decay
Advances in high-throughput sequencing technologies and cryoelectron microscopy have shed light on the structure and organization of the mitochondrial genome and revealed unique mechanisms of mitochondrial gene regulation
New animal models of impaired mitochondrial protein synthesis have shown how the coordinated regulation of the cytoplasmic and mitochondrial translation machineries ensures the correct assembly of the respiratory chain complexes
Defects in mitochondrial genome regulation and expression are responsible for mitochondrial diseases, and also contribute to common diseases such as cardiovascular, metabolic and neurodegenerative diseases, cancer and ageing
Here, Rackham and Filipovska review our current understanding of mitochondrial genome organization and expression and showcase studies that dissect how mitochondrial signals are communicated to the rest of the cell to trigger responses to altered mitochondrial gene expression
A fundamental goal of developmental and stem cell biology is to map the developmental history (ontogeny) of differentiated cell types
Recent advances in high-throughput single-cell sequencing technologies have enabled the construction of comprehensive transcriptional atlases of adult tissues and of developing embryos from measurements of up to millions of individual cells
Recent technologies use large-scale genetic and evolutionary datasets to model the structures of proteins and their complexes
Coevolution-based methods model protein structures by identifying pairs of amino acid residues that are likely to be close in space because they evolve together
Computational tools to analyse RNA-seq data often discard reads derived from transposable elements (TE) but measuring TE expression helps to understand when and where TE mobilization occurs and how it alters gene expression, chromatin accessibility or cellular signalling pathways
Measuring TE expression is not straightforward; not only are TEs highly repeated in their host genome but insertional polymorphisms (presence/absence) and internal sequence polymorphisms between individuals complicate their identification
This Review discusses the evolving definitions of transcriptional enhancers and the modern experimental tools to identify, characterize and validate them.
The authors discuss how diverse perspectives and methods provide differing but complementary insights into enhancers, each with notable strengths and caveats, and how they might be combined in a comprehensive catalogue of functional enhancers.