A single-cell time-lapse of mouse prenatal development from gastrula to birth.

The house mouse (Mus musculus) is an exceptional model system, combining genetic tractability with close evolutionary affinity to humans1,2. Mouse gestation lasts only 3 weeks, during which the genome orchestrates the astonishing transformation of a single-cell zygote into a free-living pup composed of more than 500 million cells. Here, to establish a global framework for exploring mammalian development, we applied optimized single-cell combinatorial indexing3 to profile the transcriptional states of 12.4 million nuclei from 83 embryos, precisely staged at 2- to 6-hour intervals spanning late gastrulation (embryonic day 8) to birth (postnatal day 0). From these data, we annotate hundreds of cell types and explore the ontogenesis of the posterior embryo during somitogenesis and of kidney, mesenchyme, retina and early neurons. We leverage the temporal resolution and sampling depth of these whole-embryo snapshots, together with published data4-8 from earlier timepoints, to construct a rooted tree of cell-type relationships that spans the entirety of prenatal development, from zygote to birth. Throughout this tree, we systematically nominate genes encoding transcription factors and other proteins as candidate drivers of the in vivo differentiation of hundreds of cell types. Remarkably, the most marked temporal shifts in cell states are observed within one hour of birth and presumably underlie the massive physiological adaptations that must accompany the successful transition of a mammalian fetus to life outside the womb.

Mutations in LAMA1 cause cerebellar dysplasia and cysts with and without retinal dystrophy.

Cerebellar dysplasia with cysts (CDC) is an imaging finding typically seen in combination with cobblestone cortex and congenital muscular dystrophy in individuals with dystroglycanopathies. More recently, CDC was reported in seven children without neuromuscular involvement (Poretti-Boltshauser syndrome). Using a combination of homozygosity mapping and whole-exome sequencing, we identified biallelic mutations in LAMA1 as the cause of CDC in seven affected individuals (from five families) independent from those included in the phenotypic description of Poretti-Boltshauser syndrome. Most of these individuals also have high myopia, and some have retinal dystrophy and patchy increased T2-weighted fluid-attenuated inversion recovery (T2/FLAIR) signal in cortical white matter. In one additional family, we identified two siblings who have truncating LAMA1 mutations in combination with retinal dystrophy and mild cerebellar dysplasia without cysts, indicating that cysts are not an obligate feature associated with loss of LAMA1 function. This work expands the phenotypic spectrum associated with the lamininopathy disorders and highlights the tissue-specific roles played by different laminin-encoding genes.

Mutations in CSPP1 cause primary cilia abnormalities and Joubert syndrome with or without Jeune asphyxiating thoracic dystrophy.

Joubert syndrome (JBTS) is a recessive ciliopathy in which a subset of affected individuals also have the skeletal dysplasia Jeune asphyxiating thoracic dystrophy (JATD). Here, we have identified biallelic truncating CSPP1 (centrosome and spindle pole associated protein 1) mutations in 19 JBTS-affected individuals, four of whom also have features of JATD. CSPP1 mutations explain ∼5% of JBTS in our cohort, and despite truncating mutations in all affected individuals, the range of phenotypic severity is broad. Morpholino knockdown of cspp1 in zebrafish caused phenotypes reported in other zebrafish models of JBTS (curved body shape, pronephric cysts, and cerebellar abnormalities) and reduced ciliary localization of Arl13b, further supporting loss of CSPP1 function as a cause of JBTS. Fibroblasts from affected individuals with CSPP1 mutations showed reduced numbers of primary cilia and/or short primary cilia, as well as reduced axonemal localization of ciliary proteins ARL13B and adenylyl cyclase III. In summary, CSPP1 mutations are a major cause of the Joubert-Jeune phenotype in humans; however, the mechanism by which these mutations lead to both JBTS and JATD remains unknown.

Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart.

Sex differences and age-related changes in the human heart at the tissue, cell, and molecular level have been well-documented and many may be relevant for cardiovascular disease. However, how molecular programs within individual cell types vary across individuals by age and sex remains poorly characterized. To better understand this variation, we performed single-nucleus combinatorial indexing (sci) ATAC- and RNA-Seq in human heart samples from nine donors. We identify hundreds of differentially expressed genes by age and sex and find epigenetic signatures of variation in ATAC-Seq data in this discovery cohort. We then scale up our single-cell RNA-Seq analysis by combining our data with five recently published single nucleus RNA-Seq datasets of healthy adult hearts. We find variation such as metabolic alterations by sex and immune changes by age in differential expression tests, as well as alterations in abundance of cardiomyocytes by sex and neurons with age. In addition, we compare our adult-derived ATAC-Seq profiles to analogous fetal cell types to identify putative developmental-stage-specific regulatory factors. Finally, we train predictive models of cell-type-specific RNA expression levels utilizing ATAC-Seq profiles to link distal regulatory sequences to promoters, quantifying the predictive value of a simple TF-to-expression regulatory grammar and identifying cell-type-specific TFs. Our analysis represents the largest single-cell analysis of cardiac variation by age and sex to date and provides a resource for further study of healthy cardiac variation and transcriptional regulation at single-cell resolution.

Genotype-phenotype correlation in CC2D2A-related Joubert syndrome reveals an association with ventriculomegaly and seizures.

BACKGROUND: Joubert syndrome (JS) is a ciliopathy characterised by a distinctive brain malformation (the 'molar tooth sign'), developmental delay, abnormal eye movements and abnormal breathing pattern. Retinal dystrophy, cystic kidney disease, liver fibrosis and polydactyly are variably present, resulting in significant phenotypic heterogeneity and overlap with other ciliopathies. JS is also genetically heterogeneous, resulting from mutations in 13 genes. These factors render clinical/molecular diagnosis and management challenging. CC2D2A mutations are a relatively common cause of JS and also cause Meckel syndrome. The clinical consequences of CC2D2A mutations in patients with JS have been incompletely reported. METHODS: Subjects with JS from 209 families were evaluated to identify mutations in CC2D2A. Clinical and imaging features in subjects with CC2D2A mutations were compared with those in subjects without CC2D2A mutations and reports in the literature. RESULTS: 10 novel CC2D2A mutations in 20 subjects were identified; a summary is provided of all published CC2D2A mutations. Subjects with CC2D2A-related JS were more likely to have ventriculomegaly (p<0.0001) and seizures (p=0.024) than subjects without CC2D2A mutations. No mutation-specific genotype-phenotype correlations could be identified, but the findings confirm the observation that mutations that cause CC2D2A-related JS are predicted to be less deleterious than mutations that cause CC2D2A-related Meckel syndrome. Missense variants in the coiled-coil and C2 domains, as well as the C-terminal region, identify these regions as important for the biological mechanisms underlying JS. CONCLUSIONS: CC2D2A testing should be prioritised in patients with JS and ventriculomegaly and/or seizures. Patients with CC2D2A-related JS should be monitored for hydrocephalus and seizures.

Cross-species imputation and comparison of single-cell transcriptomic profiles.

Cross-species comparison and prediction of gene expression profiles are important to understand regulatory changes during evolution and to transfer knowledge learned from model organisms to humans. Single-cell RNA-seq (scRNA-seq) profiles enable us to capture gene expression profiles with respect to variations among individual cells; however, cross-species comparison of scRNA-seq profiles is challenging because of data sparsity, batch effects, and the lack of one-to-one cell matching across species. Moreover, single-cell profiles are challenging to obtain in certain biological contexts, limiting the scope of hypothesis generation. Here we developed Icebear, a neural network framework that decomposes single-cell measurements into factors representing cell identity, species, and batch factors. Icebear enables accurate prediction of single-cell gene expression profiles across species, thereby providing high-resolution cell type and disease profiles in under-characterized contexts. Icebear also facilitates direct cross-species comparison of single-cell expression profiles for conserved genes that are located on the X chromosome in eutherian mammals but on autosomes in chicken. This comparison, for the first time, revealed evolutionary and diverse adaptations of X-chromosome upregulation in mammals.

A single-cell multi-omic atlas spanning the adult rhesus macaque brain.

Cataloging the diverse cellular architecture of the primate brain is crucial for understanding cognition, behavior, and disease in humans. Here, we generated a brain-wide single-cell multimodal molecular atlas of the rhesus macaque brain. Together, we profiled 2.58 M transcriptomes and 1.59 M epigenomes from single nuclei sampled from 30 regions across the adult brain. Cell composition differed extensively across the brain, revealing cellular signatures of region-specific functions. We also identified 1.19 M candidate regulatory elements, many previously unidentified, allowing us to explore the landscape of cis-regulatory grammar and neurological disease risk in a cell type-specific manner. Altogether, this multi-omic atlas provides an open resource for investigating the evolution of the human brain and identifying novel targets for disease interventions.

Single-cell census of human tooth development enables generation of human enamel.

Tooth enamel secreted by ameloblasts (AMs) is the hardest material in the human body, acting as a shield to protect the teeth. However, the enamel is gradually damaged or partially lost in over 90% of adults and cannot be regenerated due to a lack of ameloblasts in erupted teeth. Here, we use single-cell combinatorial indexing RNA sequencing (sci-RNA-seq) to establish a spatiotemporal single-cell census for the developing human tooth and identify regulatory mechanisms controlling the differentiation process of human ameloblasts. We identify key signaling pathways involved between the support cells and ameloblasts during fetal development and recapitulate those findings in human ameloblast in vitro differentiation from induced pluripotent stem cells (iPSCs). We furthermore develop a disease model of amelogenesis imperfecta in a three-dimensional (3D) organoid system and show AM maturation to mineralized structure in vivo. These studies pave the way for future regenerative dentistry.

A single-cell transcriptional timelapse of mouse embryonic development, from gastrula to pup.

The house mouse, Mus musculus, is an exceptional model system, combining genetic tractability with close homology to human biology. Gestation in mouse development lasts just under three weeks, a period during which its genome orchestrates the astonishing transformation of a single cell zygote into a free-living pup composed of >500 million cells. Towards a global framework for exploring mammalian development, we applied single cell combinatorial indexing (sci-*) to profile the transcriptional states of 12.4 million nuclei from 83 precisely staged embryos spanning late gastrulation (embryonic day 8 or E8) to birth (postnatal day 0 or P0), with 2-hr temporal resolution during somitogenesis, 6-hr resolution through to birth, and 20-min resolution during the immediate postpartum period. From these data (E8 to P0), we annotate dozens of trajectories and hundreds of cell types and perform deeper analyses of the unfolding of the posterior embryo during somitogenesis as well as the ontogenesis of the kidney, mesenchyme, retina, and early neurons. Finally, we leverage the depth and temporal resolution of these whole embryo snapshots, together with other published data, to construct and curate a rooted tree of cell type relationships that spans mouse development from zygote to pup. Throughout this tree, we systematically nominate sets of transcription factors (TFs) and other genes as candidate drivers of the in vivo differentiation of hundreds of mammalian cell types. Remarkably, the most dramatic shifts in transcriptional state are observed in a restricted set of cell types in the hours immediately following birth, and presumably underlie the massive changes in physiology that must accompany the successful transition of a placental mammal to extrauterine life.

Spatial and cell type transcriptional landscape of human cerebellar development.

The human neonatal cerebellum is one-fourth of its adult size yet contains the blueprint required to integrate environmental cues with developing motor, cognitive and emotional skills into adulthood. Although mature cerebellar neuroanatomy is well studied, understanding of its developmental origins is limited. In this study, we systematically mapped the molecular, cellular and spatial composition of human fetal cerebellum by combining laser capture microscopy and SPLiT-seq single-nucleus transcriptomics. We profiled functionally distinct regions and gene expression dynamics within cell types and across development. The resulting cell atlas demonstrates that the molecular organization of the cerebellar anlage recapitulates cytoarchitecturally distinct regions and developmentally transient cell types that are distinct from the mouse cerebellum. By mapping genes dominant for pediatric and adult neurological disorders onto our dataset, we identify relevant cell types underlying disease mechanisms. These data provide a resource for probing the cellular basis of human cerebellar development and disease.