Despite intense interest in discovering drugs that cause G-protein-coupled receptors (GPCRs) to selectively stimulate or block arrestin signalling, the structural mechanism of receptor-mediated arrestin activation remains unclear. Here we reveal this mechanism through extensive atomic-level simulations of arrestin. We find that the receptor's transmembrane core and cytoplasmic tail-which bind distinct surfaces on arrestin-can each independently stimulate arrestin activation. We confirm this unanticipated role of the receptor core, and the allosteric coupling between these distant surfaces of arrestin, using site-directed fluorescence spectroscopy. The effect of the receptor core on arrestin conformation is mediated primarily by interactions of the intracellular loops of the receptor with the arrestin body, rather than the marked finger-loop rearrangement that is observed upon receptor binding. In the absence of a receptor, arrestin frequently adopts active conformations when its own C-terminal tail is disengaged, which may explain why certain arrestins remain active long after receptor dissociation. Our results, which suggest that diverse receptor binding modes can activate arrestin, provide a structural foundation for the design of functionally selective ('biased') GPCR-targeted ligands with desired effects on arrestin signalling.

Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type–specific RNA splicing was discovered and analyzed across tissues within an individual.

Studies of the macroevolutionary legacy of polyploidy are limited by an incomplete sampling of these events across the tree of life. To better locate and understand these events, we need comprehensive taxonomic sampling as well as homology inference methods that accurately reconstruct the frequency and location of gene duplications. We assembled a data set of transcriptomes and genomes from 168 species in Caryophyllales, of which 43 transcriptomes were newly generated for this study, representing one of the most densely sampled genomic-scale data sets available. We carried out phylogenomic analyses using a modified phylome strategy to reconstruct the species tree. We mapped the phylogenetic distribution of polyploidy events by both tree-based and distance-based methods, and explicitly tested scenarios for allopolyploidy. We identified 26 ancient and more recent polyploidy events distributed throughout Caryophyllales. Two of these events were inferred to be allopolyploidy. Through dense phylogenomic sampling, we show the propensity of polyploidy throughout the evolutionary history of Caryophyllales. We also provide a framework for utilizing transcriptome data to detect allopolyploidy, which is important as it may have different macroevolutionary implications compared with autopolyploidy.

Transcriptomes are useful both for species-tree inference and for uncovering evolutionary complexity within lineages. Through analyses of gene-tree conflict and multiple methods of species-tree inference, we demonstrate that phylogenomic data can provide unparalleled insight into the evolutionary history of Caryophyllales. We also discuss a method for overcoming computational challenges associated with homolog clustering in large data sets.