Spatial Single-cell Analysis Decodes Cortical Layer and Area Specification.

The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas1,2. The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization3,4. While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation5,6,7,8. Here, we utilized multiplexed error-robust fluorescence in situ hybridization (MERFISH)9, augmented with deep-learning-based cell segmentation, to examine the molecular, cellular, and cytoarchitectural development of human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing 16 million single cells, spans eight cortical areas across four time points in the second and third trimesters. We uncovered an early establishment of the six-layer structure, identifiable in the laminar distribution of excitatory neuronal subtypes by mid-gestation, long before the emergence of cytoarchitectural layers. Notably, while anterior-posterior gradients of neuronal subtypes were generally observed in most cortical areas, a striking exception was the sharp molecular border between primary (V1) and secondary visual cortices (V2) at gestational week 20. Here we discovered an abrupt binary shift in neuronal subtype specification at the earliest stages, challenging the notion that continuous morphogen gradients dictate mid-gestation cortical arealization6,10. Moreover, integrating single-nuclei RNA-sequencing and in situ whole transcriptomics revealed an early upregulation of synaptogenesis in V1-specific Layer 4 neurons, suggesting a role of synaptogenesis in this discrete border formation. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This work not only provides a valuable resource for the field, but also establishes a spatially resolved single-cell analysis paradigm that paves the way for a comprehensive developmental atlas of the human brain.

Exome copy number variant detection, analysis, and classification in a large cohort of families with undiagnosed rare genetic disease.

Copy number variants (CNVs) are significant contributors to the pathogenicity of rare genetic diseases and, with new innovative methods, can now reliably be identified from exome sequencing. Challenges still remain in accurate classification of CNV pathogenicity. CNV calling using GATK-gCNV was performed on exomes from a cohort of 6,633 families (15,759 individuals) with heterogeneous phenotypes and variable prior genetic testing collected at the Broad Institute Center for Mendelian Genomics of the Genomics Research to Elucidate the Genetics of Rare Diseases consortium and analyzed using the seqr platform. The addition of CNV detection to exome analysis identified causal CNVs for 171 families (2.6%). The estimated sizes of CNVs ranged from 293 bp to 80 Mb. The causal CNVs consisted of 140 deletions, 15 duplications, 3 suspected complex structural variants (SVs), 3 insertions, and 10 complex SVs, the latter two groups being identified by orthogonal confirmation methods. To classify CNV variant pathogenicity, we used the 2020 American College of Medical Genetics and Genomics/ClinGen CNV interpretation standards and developed additional criteria to evaluate allelic and functional data as well as variants on the X chromosome to further advance the framework. We interpreted 151 CNVs as likely pathogenic/pathogenic and 20 CNVs as high-interest variants of uncertain significance. Calling CNVs from existing exome data increases the diagnostic yield for individuals undiagnosed after standard testing approaches, providing a higher-resolution alternative to arrays at a fraction of the cost of genome sequencing. Our improvements to the classification approach advances the systematic framework to assess the pathogenicity of CNVs.

Neurodevelopmental disorders associated variants in ADAT3 disrupt the activity of the ADAT2/ADAT3 tRNA deaminase complex and impair neuronal migration.

The ADAT2/ADAT3 complex catalyzes the adenosine to inosine modification at the wobble position of eukaryotic tRNAs. Mutations in ADAT3 , the catalytically inactive subunit of the ADAT2/ADAT3 complex, have been identified in patients presenting with severe neurodevelopmental disorders (NDDs). Yet, the physiological function of ADAT2/ADAT3 complex during brain development remains totally unknown. Here we showed that maintaining a proper level of ADAT2/ADAT3 catalytic activity is required for correct radial migration of projection neurons in the developing mouse cortex. In addition, we not only reported 7 new NDD patients carrying biallelic variants in ADAT3 but also deeply characterize the impact of those variants on ADAT2/ADAT3 structure, biochemical properties, enzymatic activity and tRNAs editing and abundance. We demonstrated that all the identified variants alter both the expression and the activity of the complex leading to a significant decrease of I 34 with direct consequence on their steady-state. Using in vivo complementation assays, we correlated the severity of the migration phenotype with the degree of the loss of function caused by the variants. Altogether, our results indicate a critical role of ADAT2/ADAT3 during cortical development and provide cellular and molecular insights into the pathogenicity of ADAT3-related neurodevelopmental disorder.