Integrating phylogenies into single-cell RNA sequencing analysis allows comparisons across species, genes, and cells.

Comparisons of single-cell RNA sequencing (scRNA-seq) data across species can reveal links between cellular gene expression and the evolution of cell functions, features, and phenotypes. These comparisons evoke evolutionary histories, as depicted by phylogenetic trees, that define relationships between species, genes, and cells. This Essay considers each of these in turn, laying out challenges and solutions derived from a phylogenetic comparative approach and relating these solutions to previously proposed methods for the pairwise alignment of cellular dimensional maps. This Essay contends that species trees, gene trees, cell phylogenies, and cell lineages can all be reconciled as descriptions of the same concept-the tree of cellular life. By integrating phylogenetic approaches into scRNA-seq analyses, challenges for building informed comparisons across species can be overcome, and hypotheses about gene and cell evolution can be robustly tested.

Cell type evolution reconstruction across species through cell phylogenies of single-cell RNA sequencing data.

The origin and evolution of cell types has emerged as a key topic in evolutionary biology. Driven by rapidly accumulating single-cell datasets, recent attempts to infer cell type evolution have largely been limited to pairwise comparisons because we lack approaches to build cell phylogenies using model-based approaches. Here we approach the challenges of applying explicit phylogenetic methods to single-cell data by using principal components as phylogenetic characters. We infer a cell phylogeny from a large, comparative single-cell dataset of eye cells from five distantly related mammals. Robust cell type clades enable us to provide a phylogenetic, rather than phenetic, definition of cell type, allowing us to forgo marker genes and phylogenetically classify cells by topology. We further observe evolutionary relationships between diverse vessel endothelia and identify the myelinating and non-myelinating Schwann cells as sister cell types. Finally, we examine principal component loadings and describe the gene expression dynamics underlying the function and identity of cell type clades that have been conserved across the five species. A cell phylogeny provides a rigorous framework towards investigating the evolutionary history of cells and will be critical to interpret comparative single-cell datasets that aim to ask fundamental evolutionary questions.

Normalizing need not be the norm: count-based math for analyzing single-cell data.

Counting transcripts of mRNA are a key method of observation in modern biology. With advances in counting transcripts in single cells (single-cell RNA sequencing or scRNA-seq), these data are routinely used to identify cells by their transcriptional profile, and to identify genes with differential cellular expression. Because the total number of transcripts counted per cell can vary for technical reasons, the first step of many commonly used scRNA-seq workflows is to normalize by sequencing depth, transforming counts into proportional abundances. The primary objective of this step is to reshape the data such that cells with similar biological proportions of transcripts end up with similar transformed measurements. But there is growing concern that normalization and other transformations result in unintended distortions that hinder both analyses and the interpretation of results. This has led to an intense focus on optimizing methods for normalization and transformation of scRNA-seq data. Here, we take an alternative approach, by avoiding normalization and transformation altogether. We abandon the use of distances to compare cells, and instead use a restricted algebra, motivated by measurement theory and abstract algebra, that preserves the count nature of the data. We demonstrate that this restricted algebra is sufficient to draw meaningful and practical comparisons of gene expression through the use of the dot product and other elementary operations. This approach sidesteps many of the problems with common transformations, and has the added benefit of being simpler and more intuitive. We implement our approach in the package countland, available in python and R.

The genome of the reef-building glass sponge Aphrocallistes vastus provides insights into silica biomineralization.

Well-annotated and contiguous genomes are an indispensable resource for understanding the evolution, development, and metabolic capacities of organisms. Sponges, an ecologically important non-bilaterian group of primarily filter-feeding sessile aquatic organisms, are underrepresented with respect to available genomic resources. Here we provide a high-quality and well-annotated genome of Aphrocallistes vastus, a glass sponge (Porifera: Hexactinellida) that forms large reef structures off the coast of British Columbia (Canada). We show that its genome is approximately 80 Mb, small compared to most other metazoans, and contains nearly 2500 nested genes, more than other genomes. Hexactinellida is characterized by a unique skeletal architecture made of amorphous silicon dioxide (SiO2), and we identified 419 differentially expressed genes between the osculum, i.e. the vertical growth zone of the sponge, and the main body. Among the upregulated ones, mineralization-related genes such as glassin, as well as collagens and actins, dominate the expression profile during growth. Silicateins, suggested being involved in silica mineralization, especially in demosponges, were not found at all in the A. vastus genome and suggests that the underlying mechanisms of SiO2 deposition in the Silicea sensu stricto (Hexactinellida + Demospongiae) may not be homologous.

Sponge Behavior and the Chemical Basis of Responses: A Post-Genomic View.

Sponges perceive and respond to a range of stimuli. How they do this is still difficult to pin down despite now having transcriptomes and genomes of an array of species. Here we evaluate the current understanding of sponge behavior and present new observations on sponge activity in situ. We also explore biosynthesis pathways available to sponges from data in genomes/transcriptomes of sponges and other non-bilaterians with a focus on exploring the role of chemical signaling pathways mediating sponge behavior and how such chemical signal pathways may have evolved. Sponge larvae respond to light but opsins are not used, nor is there a common photoreceptor molecule or mechanism used across sponge groups. Other cues are gravity and chemicals. In situ recordings of behavior show that both shallow and deep-water sponges move a lot over minutes and hours, and correlation of behavior with temperature, pressure, oxygen, and water movement suggests that at least one sponge responds to changes in atmospheric pressure. The sensors for these cues as far as we know are individual cells and, except in the case of electrical signaling in Hexactinellida, these most likely act as independent effectors, generating a whole-body reaction by the global reach of the stimulus to all parts of the animal. We found no evidence for use of conventional neurotransmitters such as serotonin and dopamine. Intriguingly, some chemicals synthesized by symbiont microbes could mean other more complex signaling occurs, but how that interplay might happen is not understood. Our review suggests chemical signaling pathways found in sponges do not reflect loss of a more complex set.

Think like a sponge: The genetic signal of sensory cells in sponges.

A complex genetic repertoire underlies the apparently simple body plan of sponges. Among the genes present in poriferans are those fundamental to the sensory and nervous systems of other animals. Sponges are dynamic and sensitive animals and it is intuitive to link these genes to behaviour. The proposal that ctenophores are the earliest diverging metazoan has led to the question of whether sponges possess a 'pre-nervous' system or have undergone nervous system loss. Both lines of thought generally assume that the last common ancestor of sponges and eumetazoans possessed the genetic modules that underlie sensory abilities. By corollary extant sponges may possess a sensory cell homologous to one present in the last common ancestor, a hypothesis that has been studied by gene expression. We have performed a meta-analysis of all gene expression studies published to date to explore whether gene expression is indicative of a feature's sensory function. In sponges we find that eumetazoan sensory-neural markers are not particularly expressed in structures with known sensory functions. Instead it is common for these genes to be expressed in cells with no known or uncharacterized sensory function. Indeed, many sensory-neural markers so far studied are expressed during development, perhaps because many are transcription factors. This suggests that the genetic signal of a sponge sensory cell is dissimilar enough to be unrecognizable when compared to a bilaterian sensory or neural cell. It is possible that sensory-neural markers have as yet unknown functions in sponge cells, such as assembling an immunological synapse in the larval globular cell. Furthermore, the expression of sensory-neural markers in non-sensory cells, such as adult and larval epithelial cells, suggest that these cells may have uncharacterized sensory functions. While this does not rule out the co-option of ancestral sensory modules in later evolving groups, a distinct genetic foundation may underlie the sponge sensory system.

Choanoflagellate and choanocyte collar-flagellar systems and the assumption of homology.

The similarities between the choanoflagellates and the choanocytes of sponges have been discussed for more than a century yet few studies allow a direct comparison of the two. We reviewed current knowledge of the collar and flagellum and compared their structure and function in the choanoflagellate Monosiga brevicollis and the sponge Spongilla lacustris. Collar microvilli were of similar length and number, but the shape of the collar differed between the two cells. In Monosiga, collars were flared and microvilli were joined by a single band of glycocalyx mid-way along their length; in Spongilla, collars formed a tube and microvilli were joined by a mesh of glycocalyx. Monosiga flagella beat at least four times faster than those in Spongilla. Flagellar vanes were found in both cell types. In both cells, the flagella and so probably also the vanes maintained moving points of contact with the microvilli, which suggested that collars and flagella were integrated systems rather than independent units. There were fundamental differences in how the collar and flagella interacted, however. In Spongilla, the flagellum bent upon contact with the collar; the flagellar amplitude was fitted to the collar diameter. In Monosiga, the flagellar amplitude was unaffected by the collar; instead the collar diameter appeared fitted to the flagellum. These differences suggest that though choanocytes and choanoflagellates are similar, homology cannot be taken for granted. Similarities in collar-flagellum systems separated by 600 million years of evolution, whether maintained or convergent, suggest that these form important adaptations for optimizing fluid flow through micro-scale filters.