Cell lineage analysis with somatic mutations reveals late divergence of neuronal cell types and cortical areas in human cerebral cortex.

The mammalian cerebral cortex shows functional specialization into regions with distinct neuronal compositions, most strikingly in the human brain, but little is known in about how cellular lineages shape cortical regional variation and neuronal cell types during development. Here, we use somatic single nucleotide variants (sSNVs) to map lineages of neuronal sub-types and cortical regions. Early-occurring sSNVs rarely respect Brodmann area (BA) borders, while late-occurring sSNVs mark neuron-generating clones with modest regional restriction, though descendants often dispersed into neighboring BAs. Nevertheless, in visual cortex, BA17 contains 30-70% more sSNVs compared to the neighboring BA18, with clones across the BA17/18 border distributed asymmetrically and thus displaying different cortex-wide dispersion patterns. Moreover, we find that excitatory neuron-generating clones with modest regional restriction consistently share low-mosaic sSNVs with some inhibitory neurons, suggesting significant co-generation of excitatory and some inhibitory neurons in the dorsal cortex. Our analysis reveals human-specific cortical cell lineage patterns, with both regional inhomogeneities in progenitor proliferation and late divergence of excitatory/inhibitory lineages.

Landmarks of human embryonic development inscribed in somatic mutations.

Although cell lineage information is fundamental to understanding organismal development, very little direct information is available for humans. We performed high-depth (250×) whole-genome sequencing of multiple tissues from three individuals to identify hundreds of somatic single-nucleotide variants (sSNVs). Using these variants as "endogenous barcodes" in single cells, we reconstructed early embryonic cell divisions. Targeted sequencing of clonal sSNVs in different organs (about 25,000×) and in more than 1000 cortical single cells, as well as single-nucleus RNA sequencing and single-nucleus assay for transposase-accessible chromatin sequencing of ~100,000 cortical single cells, demonstrated asymmetric contributions of early progenitors to extraembryonic tissues, distinct germ layers, and organs. Our data suggest onset of gastrulation at an effective progenitor pool of about 170 cells and about 50 to 100 founders for the forebrain. Thus, mosaic mutations provide a permanent record of human embryonic development at very high resolution.

Comprehensive identification of somatic nucleotide variants in human brain tissue.

BACKGROUND: Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. RESULTS: Here, the Brain Somatic Mosaicism Network conducts a coordinated, multi-institutional study to examine the ability of existing methods to detect simulated somatic single-nucleotide variants (SNVs) in DNA mixing experiments, generate multiple replicates of whole-genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual, devise strategies to discover somatic SNVs, and apply various approaches to validate somatic SNVs. These efforts lead to the identification of 43 bona fide somatic SNVs that range in variant allele fractions from ~ 0.005 to ~ 0.28. Guided by these results, we devise best practices for calling mosaic SNVs from 250× whole-genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrate that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. CONCLUSIONS: This study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing.

We characterize the landscape of somatic mutations-mutations occurring after fertilization-in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Disease-related and Healthy Human Individuals.

Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variants, there is no collection of postzygotic mosaic variants in noncancer disease-related and healthy individuals. Here, we present MosaicBase, a comprehensive database that includes 6698 mosaic variants related to 266 noncancer diseases and 27,991 mosaic variants identified in 422 healthy individuals. Genomic and phenotypic information of each variant was manually extracted and curated from 383 publications. MosaicBase supports the query of variants with Online Mendelian Inheritance in Man (OMIM) entries, genomic coordinates, gene symbols, or Entrez IDs. We also provide an integrated genome browser for users to easily access mosaic variants and their related annotations for any genomic region. By analyzing the variants collected in MosaicBase, we find that mosaic variants that directly contribute to disease phenotype show features distinct from those of variants in individuals with mild or no phenotypes, in terms of their genomic distribution, mutation signatures, and fraction of mutant cells. MosaicBase will not only assist clinicians in genetic counseling and diagnosis but also provide a useful resource to understand the genomic baseline of postzygotic mutations in the general human population. MosaicBase is publicly available at http://mosaicbase.com/ or http://49.4.21.8:8000.

SnxPy Monolayers: a New Type of Two-Dimensional Materials with High Stability, Carrier Mobility, and Magnetic Properties.

Searching for two-dimensional (2D) group V materials with ferromagnetism, elastic anisotropy, and carrier mobility and tunable band structure is one key to developing constantly developing nanodevices. The 2D monolayers SnxPy with x/y (1/1, 1/2, 1/3, and so on) coordination number are studied based on the particle-swarm optimization technique combined with the density functional theory optimization. Its thermal stability can be confirmed by molecular dynamics at 70K and 300K, indicating that the novel 2D materials have a stable existence. The electronic band structures of four stable structures suggest that all the monolayers of SnxPy are fully adjustable and flexible tunable band gaps semiconductors under the biaxial strain. The monolayer of P[Formula: see text]m-SnP2 with unique valence band structure can go from nonmagnetic to ferromagnetic by the hole doping because of the "Stoner criterion," and Pmc21-SnP2 is a direct-like gap semiconductor with in-plane elastic anisotropy to possess a high electron mobility as high as 800 cm2V-1 s-1 along the kb direction, which is much higher than that of MoS2 (∼ 200 cm2V-1 s-1). The optical absorption peak of the material is in the ultraviolet region. These discoveries expand the potential applications of the emerging field of 2D SnxPy structures in nanoelectronics.

Parallel RNA and DNA analysis after deep sequencing (PRDD-seq) reveals cell type-specific lineage patterns in human brain.

Elucidating the lineage relationships among different cell types is key to understanding human brain development. Here we developed parallel RNA and DNA analysis after deep sequencing (PRDD-seq), which combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single-cell and bulk DNA sequencing by single-cell MosaicHunter (scMH). PRDD-seq enables simultaneous reconstruction of neuronal cell type, cell lineage, and sequential neuronal formation ("birthdate") in postmortem human cerebral cortex. Analysis of two human brains showed remarkable quantitative details that relate mutation mosaic frequency to clonal patterns, confirming an early divergence of precursors for excitatory and inhibitory neurons, and an "inside-out" layer formation of excitatory neurons as seen in other species. In addition our analysis allows an estimate of excitatory neuron-restricted precursors (about 10) that generate the excitatory neurons within a cortical column. Inhibitory neurons showed complex, subtype-specific patterns of neurogenesis, including some patterns of development conserved relative to mouse, but also some aspects of primate cortical interneuron development not seen in mouse. PRDD-seq can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition.

Accurate detection of mosaic variants in sequencing data without matched controls.

Detection of mosaic mutations that arise in normal development is challenging, as such mutations are typically present in only a minute fraction of cells and there is no clear matched control for removing germline variants and systematic artifacts. We present MosaicForecast, a machine-learning method that leverages read-based phasing and read-level features to accurately detect mosaic single-nucleotide variants and indels, achieving a multifold increase in specificity compared with existing algorithms. Using single-cell sequencing and targeted sequencing, we validated 80-90% of the mosaic single-nucleotide variants and 60-80% of indels detected in human brain whole-genome sequencing data. Our method should help elucidate the contribution of mosaic somatic mutations to the origin and development of disease.

Novel graphene-like two-dimensional bilayer germanene dioxide: electronic structure and optical properties.

Using ab initio calculations, we present a two-dimensional (2D) α-2D-germanene dioxide material with an ideal sp3 bonding network which possesses a large band gap up to 2.50 eV. The phonon dispersion curves and molecular dynamics (MD) simulation under the chosen parameters suggest that the novel 2D structure is stable. The dielectric function and absorption spectrum also show the consistent band gap within the electronic structure diagram, suggesting possible application as an ultraviolet light optical detector. The calculated carrier mobility of 4.09 × 103 cm2 V-1 s-1 can be observed along the x direction, which is much higher than that of MoS2 (∼3.0 cm2 V-1 s-1). Finally, we found that α-2D-germanene dioxide could potentially act as an ideal monolayer insulator in so-called van der Waals (vdW) heterostructure devices. These findings expand the potential applications of the emerging field of 2D α-2D-germanene dioxide materials in nanoelectronics.

AutismKB 2.0: a knowledgebase for the genetic evidence of autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with strong genetic contributions. To provide a comprehensive resource for the genetic evidence of ASD, we have updated the Autism KnowledgeBase (AutismKB) to version 2.0. AutismKB 2.0 integrates multiscale genetic data on 1379 genes, 5420 copy number variations and structural variations, 11 669 single-nucleotide variations or small insertions/deletions (SNVs/indels) and 172 linkage regions. In particular, AutismKB 2.0 highlights 5669 de novo SNVs/indels due to their significant contribution to ASD genetics and includes 789 mosaic variants due to their recently discovered contributions to ASD pathogenesis. The genes and variants are annotated extensively with genetic evidence and clinical evidence. To help users fully understand the functional consequences of SNVs and small indels, we provided comprehensive predictions of pathogenicity with iFish, SIFT, Polyphen etc. To improve user experiences, the new version incorporates multiple query methods, including simple query, advanced query and batch query. It also functionally integrates two analytical tools to help users perform downstream analyses, including a gene ranking tool and an enrichment analysis tool, KOBAS. AutismKB 2.0 is freely available and can be a valuable resource for researchers.

A model for postzygotic mosaicisms quantifies the allele fraction drift, mutation rate, and contribution to de novo mutations.

The allele fraction (AF) distribution, occurrence rate, and evolutionary contribution of postzygotic single-nucleotide mosaicisms (pSNMs) remain largely unknown. In this study, we developed a mathematical model to describe the accumulation and AF drift of pSNMs during the development of multicellular organisms. By applying the model, we quantitatively analyzed two large-scale data sets of pSNMs identified from human genomes. We found that the postzygotic mutation rate per cell division during early embryogenesis, especially during the first cell division, was higher than the average mutation rate in either male or female gametes. We estimated that the stochastic cell death rate per cell cleavage during human embryogenesis was ∼5%, and parental pSNMs occurring during the first three cell divisions contributed to ∼10% of the de novo mutations observed in children. We further demonstrated that the genomic profiles of pSNMs could be used to measure the divergence distance between tissues. Our results highlight the importance of pSNMs in estimating recurrence risk and clarified the quantitative relationship between postzygotic and de novo mutations.

Detecting Somatic Mutations in Normal Cells.

Somatic mutations have been studied extensively in the context of cancer. Recent studies have demonstrated that high-throughput sequencing data can be used to detect somatic mutations in non-tumor cells. Analysis of such mutations allows us to better understand the mutational processes in normal cells, explore cell lineages in development, and examine potential associations with age-related disease. We describe here approaches for characterizing somatic mutations in normal and non-tumor disease tissues. We discuss several experimental designs and common pitfalls in somatic mutation detection, as well as more recent developments such as phasing and linked-read technology. With the dramatically increasing numbers of samples undergoing genome sequencing, bioinformatic analysis will enable the characterization of somatic mutations and their impact on non-cancer tissues.

Postzygotic single-nucleotide mosaicisms contribute to the etiology of autism spectrum disorder and autistic traits and the origin of mutations.

The roles and characteristics of postzygotic single-nucleotide mosaicisms (pSNMs) in autism spectrum disorders (ASDs) remain unclear. In this study of the whole exomes of 2,361 families in the Simons Simplex Collection, we identified 1,248 putative pSNMs in children and 285 de novo SNPs in children with detectable parental mosaicism. Ultra-deep amplicon resequencing suggested a validation rate of 51%. Analyses of validated pSNMs revealed that missense/loss-of-function (LoF) pSNMs with a high mutant allele fraction (MAF≥ 0.2) contributed to ASD diagnoses (P = 0.022, odds ratio [OR] = 5.25), whereas missense/LoF pSNMs with a low MAF (MAF<0.2) contributed to autistic traits in male non-ASD siblings (P = 0.033). LoF pSNMs in parents were less likely to be transmitted to offspring than neutral pSNMs (P = 0.037), and missense/LoF pSNMs in parents with a low MAF were transmitted more to probands than to siblings (P = 0.016, OR = 1.45). We estimated that pSNMs in probands or de novo mutations inherited from parental pSNMs increased the risk of ASD by approximately 6%. Adding pSNMs into the transmission and de novo association test model revealed 13 new ASD risk genes. These results expand the existing repertoire of genes involved in ASD and shed new light on the contribution of genomic mosaicisms to ASD diagnoses and autistic traits.

MosaicHunter: accurate detection of postzygotic single-nucleotide mosaicism through next-generation sequencing of unpaired, trio, and paired samples.

Genomic mosaicism arising from postzygotic mutations has long been associated with cancer and more recently with non-cancer diseases. It has also been detected in healthy individuals including healthy parents of children affected with genetic disorders, highlighting its critical role in the origin of genetic mutations. However, most existing software for the genome-wide identification of single-nucleotide mosaicisms (SNMs) requires a paired control tissue obtained from the same individual which is often unavailable for non-cancer individuals and sometimes missing in cancer studies. Here, we present MosaicHunter (http://mosaichunter.cbi.pku.edu.cn), a bioinformatics tool that can identify SNMs in whole-genome and whole-exome sequencing data of unpaired samples without matched controls using Bayesian genotypers. We evaluate the accuracy of MosaicHunter on both simulated and real data and demonstrate that it has improved performance compared with other somatic mutation callers. We further demonstrate that incorporating sequencing data of the parents can be an effective approach to significantly improve the accuracy of detecting SNMs in an individual when a matched control sample is unavailable. Finally, MosaicHunter also has a paired mode that can take advantage of matched control samples when available, making it a useful tool for detecting SNMs in both non-cancer and cancer studies.

Profiling the RNA editomes of wild-type C. elegans and ADAR mutants.

RNA editing increases transcriptome diversity through post-transcriptional modifications of RNA. Adenosine deaminases that act on RNA (ADARs) catalyze the adenosine-to-inosine (A-to-I) conversion, the most common type of RNA editing in higher eukaryotes. Caenorhabditis elegans has two ADARs, ADR-1 and ADR-2, but their functions remain unclear. Here, we profiled the RNA editomes of C. elegans at different developmental stages of wild-type and ADAR mutants. We developed a new computational pipeline with a "bisulfite-seq-mapping-like" step and achieved a threefold increase in identification sensitivity. A total of 99.5% of the 47,660 A-to-I editing sites were found in clusters. Of the 3080 editing clusters, 65.7% overlapped with DNA transposons in noncoding regions and 73.7% could form hairpin structures. The numbers of editing sites and clusters were highest at the L1 and embryonic stages. The editing frequency of a cluster positively correlated with the number of editing sites within it. Intriguingly, for 80% of the clusters with 10 or more editing sites, almost all expressed transcripts were edited. Deletion of adr-1 reduced the editing frequency but not the number of editing clusters, whereas deletion of adr-2 nearly abolished RNA editing, indicating a modulating role of ADR-1 and an essential role of ADR-2 in A-to-I editing. Quantitative proteomics analysis showed that adr-2 mutant worms altered the abundance of proteins involved in aging and lifespan regulation. Consistent with this finding, we observed that worms lacking RNA editing were short-lived. Taken together, our results reveal a sophisticated landscape of RNA editing and distinct modes of action of different ADARs.