Cerebral organoids-3D cultures of human cerebral tissue derived from pluripotent stem cells-have emerged as models of human cortical development. However, the extent to which in vitro organoid systems recapitulate neural progenitor cell proliferation and neuronal differentiation programs observed in vivo remains unclear.Here we use single-cell RNA sequencing (scRNA-seq) to dissect and compare cell composition and progenitor-to-neuron lineage relationships in human cerebral organoids and fetal neocortex. Covariation network analysis using the fetal neocortex data reveals known and previously unidentified interactions among genes central to neural progenitor proliferation and neuronal differentiation. In the organoid, we detect diverse progenitors and differentiated cell types of neuronal and mesenchymal lineages and identify cells that derived from regions resembling the fetal neocortex. We find that these organoid cortical cells use gene expression programs remarkably similar to those of the fetal tissue to organize into cerebral cortex-like regions. Our comparison of in vivo and in vitro cortical single-cell transcriptomes illuminates the genetic features underlying human cortical development that can be studied in organoid cultures.

Evolutionary expansion of the human neocortex reflects increased amplification of basal progenitors in the subventricular zone, producing more neurons during fetal corticogenesis. In this work, we analyze the transcriptomes of distinct progenitor subpopulations isolated by a cell polarity-based approach from developing mouse and human neocortex. We identify 56 genes preferentially expressed in human apical and basal radial glia that lack mouse orthologs. Among these, ARHGAP11B has the highest degree of radial glia-specific expression. ARHGAP11B arose from partial duplication of ARHGAP11A (which encodes a Rho guanosine triphosphatase-activating protein) on the human lineage after separation from the chimpanzee lineage. Expression of ARHGAP11B in embryonic mouse neocortex promotes basal progenitor generation and self-renewal and can increase cortical plate area and induce gyrification. Hence, ARHGAP11B may have contributed to evolutionary expansion of human neocortex.

Summary1. A number of approaches for studying macroevolution using phylogenetic trees have been developed in the last few years. Here, we present RPANDA, an R package that implements model-free and model-based phylogenetic comparative methods for macroevolutionary analyses. 2. The model-free approaches implemented in RPANDA are recently developed approaches stemming from graph theory that allow summarizing the information contained in phylogenetic trees, computing distances between trees, and clustering them accordingly. They also allow identifying distinct branching patterns within single trees. 3. RPANDA also implements likelihood-based models for fitting various diversification models to phylogenetic trees. It includes birth-death models with i) constant, ii) time-dependent and iii) environmental-dependent speciation and extinction rates. It also includes models with equilibrium diversity derived from the coalescent process, as well as a likelihood-based inference framework to fit the individual-based model of Speciation by Genetic Differentiation, which is an extension of Hubbell's neutral theory of biodiversity. 4. RPANDA can be used to (i) characterize trees by plotting their spectral density profiles (ii) compare trees and cluster them according to their similarities, (iii) identify and plot distinct branching patterns within trees, (iv) compare the fit of alternative diversification models to phylogenetic trees, (v) estimate rates of speciation and extinction, (vi) estimate and plot how these rates have varied with time and environmental variables and (vii) deduce and plot estimates of species richness through geological time. 5. RPANDA provides investigators with a set of tools for exploring patterns in phylogenetic trees and fitting various models to these trees, thereby contributing to the ongoing development of phylogenetics in the life sciences.

The magnitude of the COVID-19 pandemic underscores the urgency for a safe and effective vaccine. Many vaccine candidates focus on the Spike protein, as it is targeted by neutralizing antibodies and plays a key role in viral entry. Here we investigate the diversity seen in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences and compare it to the sequence on which most vaccine candidates are based. Using 18,514 sequences, we perform phylogenetic, population genetics, and structural bioinformatics analyses. We find limited diversity across SARS-CoV-2 genomes: Only 11 sites show polymorphisms in >5% of sequences; yet two mutations, including the D614G mutation in Spike, have already become consensus. Because SARS-CoV-2 is being transmitted more rapidly than it evolves, the viral population is becoming more homogeneous, with a median of seven nucleotide substitutions between genomes. There is evidence of purifying selection but little evidence of diversifying selection, with substitution rates comparable across structural versus nonstructural genes. Finally, the Wuhan-Hu-1 reference sequence for the Spike protein, which is the basis for different vaccine candidates, matches optimized vaccine inserts, being identical to an ancestral sequence and one mutation away from the consensus. While the rapid spread of the D614G mutation warrants further study, our results indicate that drift and bottleneck events can explain the minimal diversity found among SARS-CoV-2 sequences. These findings suggest that a single vaccine candidate should be efficacious against currently circulating lineages.