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Weinberger, D. R.

Publications and source records attributed to Weinberger, D. R..

At least 19 recordsLinked to original sources

Liquidity of gene co-expression trajectories across the lifespan highlights delayed maturation and the perinatal GABA switch in schizophrenia risk

Schizophrenia genetic and environmental risk factors play out largely in early life, biasing development toward a pathogenic trajectory that becomes clinically apparent in early adulthood, when the disorder typically onsets. Here, we convert snapshots of gene expression in postmortem brain at a moment in time into a dynamic lifetime series employing the "liquidity" metric, a novel tool to track the evolution of networks across time from a multi-systemic perspective. The landscape of normal prefrontal cortical development becomes increasingly "liquid" during the first two decades of post-natal life, with sharp discontinuities in known critical periods such as birth and adolescence. Neurotypical individuals free of apparent neuropathology with relatively elevated polygenic risk scores for schizophrenia exhibit a generalized delay in the dynamics of liquidity across these trajectories compared to below-average-risk individuals. Impacted biological processes strongly converge on delayed GABA-A receptor functional maturation, involved in establishing Excitatory/Inhibitory balance in brain during early development. Similar to patients with schizophrenia, neurotypical high-risk individuals show an increased expression ratio between the genes SLC12A2 (protein NKCC1) and SLC12A5 (protein KCC2) relative to low-risk, involved in the control of the equilibrium potential of chloride ions that regulates GABA-A function. These results provide evidence that genetic risk for schizophrenia is associated with a delayed maturational profile and delayed maturation of GABAergic signaling without detectable neuropathology and well before the age of clinical onset. Interestingly, the same effect is not observed in the hippocampus and is not observed with genetic risk for other neuropsychiatric and immune conditions. The dynamics of maturation of GABA-A signaling in the dorsolateral prefrontal cortex emerge as an early contributor to translating genetic risk into an altered developmental trajectory associated with schizophrenia.

genomics↗

Genetic Risk and Resilience for Schizophrenia Stratified by Perinatal Gene Expression Predict Adult Cognitive Performance

Genetic risk for schizophrenia (SCZ) has been linked to cognitive performance before the onset age. We examined how SCZ-related polygenic risk and resilience variants, and their co-expression patterns in the human brain, were associated with cognitive abilities across development in 16,520 non-psychiatric European and African ancestry children and adults. SCZ risk showed significant negative associations with spatial, verbal, and working memory across ancestries (all t<-2, pFDR<0.05). In Europeans, risk and resilience variants had opposing effects on attention, working and spatial memory ({Delta}t>4, pFDR<0.05). Polygenic scores filtered through perinatal co-expression networks showed stronger links with cognition than adult ({Delta}AIC>5.75, p=0.02) or juvenile ({Delta}AIC>5.8, p=0.03) networks. Cross-ancestry correlations (R=0.52, p<0.01) highlight replicability. These findings support the neurodevelopmental basis of SCZ, suggesting that risk and resilience variants influence cognition from early life, independent of symptoms and elucidate biological pathways through which SCZ risk may influence early cognitive development.

genomics↗

Genetic architecture of miRNA expression in human brain and its contribution to brain disorders

MicroRNAs (miRNAs) regulate nearly all protein-coding genes and play critical roles in gene regulation, yet the mechanisms governing miRNA regulation remain poorly understood. Here, we examined the genetic architecture of miRNA expression in 995 human brain tissues spanning four regions and two ancestries (African and European) from neurotypical controls and individuals with three psychiatric disorders (schizophrenia, major depressive disorder, and bipolar disorder). We found that miRNA expression is highly dynamic across brain regions, with region-specific differences exceeding those attributable to ancestry or psychiatric diagnosis. Through miRNA expression quantitative trait loci (miR-eQTL) analyses, we identified genetic variants associated with miRNA expression in a region- and ancestry-dependent manner. Overall, miRNAs exhibited heritability levels comparable to protein-coding genes and were positively co-regulated with their host transcripts. Notably, miRNA-regulating genetic variants were enriched in enhancers active in oligodendrocytes and in binding sites of the transcription factor OLIG2, suggesting miRNA-mediated gene regulation in oligodendrocyte lineage. Finally, we identified 15 miRNAs as likely causative factors for psychiatric and neurodegenerative disorders such as major depressive disorder and Alzheimers disease. Together, our results reveal the genetic underpinnings of miRNA regulation in the human brain and suggest that miRNAs serve as key intermediaries linking genetic variation to complex neuropsychiatric and neurological phenotypes.

genomics↗

Image-Based Profiling of Induced Trophoblast Stem Cells Identifies Signatures Associated with Sex, Schizophrenia Genomic Risk and Placental Stress

Schizophrenia (SCZ) is a neurodevelopmental disorder where both genetic and environmental risks converge during pregnancy. Recent studies have highlighted the importance of placental biology in influencing risk of developing SCZ. However, the pathways by which genetic risk factors for SCZ interact with environmental influences to alter placental development are poorly understood. Through image-based profiling using Cell Painting, we leveraged trophoblast cultures derived from human induced pluripotent stem cells (hiPSCs) from male and female SCZ and neurotypical donors with varying placental genomic risk scores (PlacGRS) to explore the developmental dynamics of placental cells under normal growth and hypoxic stress. We employed both classical (e.g., CellProfiler) and deep learning feature extraction combined with downstream supervised machine learning to analyze high-dimensional data obtained from this hiPSC-derived model system, highlighting that these approaches overcome the inherent line-to-line variability in phenotypic analysis. Our findings reveal a salient nucleus-localized SCZ risk signature across cell lines, along with clear sexual dimorphism. This research underscores the capability of hiPSC-derived placenta models to elucidate complex interactions between genetic risk and environmental factors implicated in the neurodevelopment of SCZ, paving the way for future studies aimed at developing targeted therapeutic and prevention strategies.

neuroscience↗

APOE E4 Alzheimer's Risk Converges on an Oligodendrocyte Subtype in the Human Entorhinal Cortex

The entorhinal cortex (ERC) is implicated in early progression of Alzheimers disease (AD). Here we investigated the impact of established biological risk factors for AD, including APOE genotype (E2 versus E4 alleles), sex, and ancestry, on gene expression in the human ERC. We generated paired spatially-resolved transcriptomics (SRT) and single-nucleus RNA sequencing data (snRNA-seq) in postmortem human ERC tissue from middle aged brain donors with no history of AD. APOE-dependent changes in gene expression predominantly mapped to a transcriptionally-defined oligodendrocyte subtype, which varied substantially with ancestry, and suggested differences in oligodendrocyte differentiation and myelination. Integration of SRT and snRNA-seq data identified a common gene expression signature associated with APOE genotype, which we localized to the same oligodendrocyte subtype and a white matter spatial domain. This suggests that AD risk in ERC may be associated with disrupted oligodendrocyte function, potentially contributing to future neurodegeneration. Lay SummaryAlzheimers disease (AD) is a neurodegenerative disorder that accounts for 60-80% dementia cases. Apolipoprotein E (APOE) genotype is the strongest genetic risk factor for AD, and the entorhinal cortex (ERC) is a brain region implicated in its earliest progression. Our study investigated how APOE genotype impacts gene expression in the ERC. We identified genotype-dependent effects on oligodendrocytes with different transcriptional profiles related to maturation that may help explain how APOE genotype mediates its effects on AD risk.

neuroscience↗

Impact of Alzheimer's disease risk factors and local neuromelanin content on the transcriptomic landscape of the human locus coeruleus

The locus coeruleus (LC) is a small noradrenergic nucleus in the dorsal pons that sends projections across the brain regulating sleep, arousal, attention, stress responses, and some forms of cognition. LC neurons show pathology in the earliest stages of Alzheimers disease (AD), including age-related accumulation of hyperphosphorylated tau (pTau) and accelerated loss of neuromelanin (NM) pigmentation. NM-sensitive neuroimaging of the LC predicts previous cognitive decline, clinical severity, and future AD progression. While these findings suggest that the LC plays an etiologic role in AD, the molecular landscape of the LC prior to clinical manifestation of sporadic AD remains largely uncharacterized. This information is critical for developing interventions that preserve LC integrity and function. We performed spatially-resolved transcriptomics on 85 sections of human postmortem LC from N=33 neurotypical middle-aged donors, balanced for epidemiologic AD risk factors including sex, African or European ancestry, and APOE genotype (carriers of the E4/risk or E2/protective alleles). Comparing across APOE genotypes, we find astrocytic gene expression differences proximal to LC neurons. Associating NM content with local gene expression, we show that higher overall APOE gene expression correlates with reduced NM content and an enrichment of NM-associated genes in aging pathways. Unexpectedly, we find enriched LC expression of cholesterol synthesis genes, alongside evidence for lipid synthesis gene regulatory network activity in NM-containing LC specifically, revealing a potential intersection between intrinsic lipid metabolism in LC neurons, NM, and the role of APOE-mediated lipid biology in AD. Together, these data illuminate the molecular features of the human LC at spatial resolution with unprecedented sampling depth, revealing how AD risk factors and NM content influence resilience and susceptibility of this critical brain nucleus to pathology accumulation and degeneration.

neuroscience↗

Comparative molecular landscapes of immature neurons in the mammalian dentate gyrus across species reveal special features in humans

Immature dentate granule cells (imGCs) arising from adult hippocampal neurogenesis contribute to plasticity, learning and memory, but their evolutionary changes across species and specialized features in humans remain poorly understood. Here we performed machine learning-augmented analysis of published single-cell RNA-sequencing datasets and identified macaque imGCs with transcriptome-wide immature neuronal characteristics. Our cross-species comparisons among humans, monkeys, pigs, and mice showed few shared (such as DPYSL5), but mostly species-specific gene expression in imGCs that converged onto common biological processes regulating neuronal development. We further identified human-specific transcriptomic features of imGCs and demonstrated functional roles of human imGC-enriched expression of a family of proton-transporting vacuolar-type ATPase subtypes in development of imGCs derived from human pluripotent stem cells. Our study reveals divergent gene expression patterns but convergent biological processes in the molecular characteristics of imGCs across species, highlighting the importance of conducting independent molecular and functional analyses for adult neurogenesis in different species.

neuroscience↗

Transcriptomics and proteomics of projection neurons in a circuit linking hippocampus with dorsolateral prefrontal cortex in human brain

Transcriptome and proteome sequencing of brain tissue homogenate has helped unravel processes underlying schizophrenia (SCZ). However, most studies have lacked granularity at the cell type level and have focused on individual brain regions, rather than examining expression dynamics across multiple regions or illness-relevant circuitries. We used laser capture microdissection to collect excitatory neuron-enriched samples from hippocampal subregions CA1 and presubiculum (SUB), and from dorsolateral prefrontal cortex (DLPFC), a circuit prominently implicated in schizophrenia. Using RNA sequencing and quantitative proteomics, we show significantly superior discrimination of brain regional identity in the transcriptomic (>90% accuracy) and proteomic data (>97% accuracy) compared with gene-level expression data (<70% in bulk). Patients with SCZ show hippocampal-specific differential protein phosphorylation. SCZ risk co-expression gene-sets that replicate across transcript and protein networks are enriched for transmembrane transporters in the DLPFC and CA1 and postsynaptic processes in the SUB. We demonstrate a strong directional connectivity effect of SCZ risk in that excitatory synaptic genes in CA1 unidirectionally predict gene expression in SUB. Finally, parallel CA1 snRNA-seq results suggest that in SCZ excitatory efferents in CA1 are affected by interactions with glia and by downregulation of inhibitory neuropeptide inputs. Our study proposes molecular mechanisms by which hippocampal communication, previously associated with SCZ at the macroscopic level, may be altered at the inter-field and interregional circuit level.

neuroscience↗

Transcriptomic analysis of the human habenula in schizophrenia

Pathophysiology of many neuropsychiatric disorders, including schizophrenia (SCZD), is linked to habenula (Hb) function. While pharmacotherapies and deep brain stimulation targeting the Hb are emerging as promising therapeutic treatments, little is known about the cell type-specific transcriptomic organization of the human Hb or how it is altered in SCZD. Here we define the molecular neuroanatomy of the human Hb and identify transcriptomic changes in individuals with SCZD compared to neurotypical controls. Utilizing Hb-enriched postmortem human brain tissue, we performed single nucleus RNA-sequencing (snRNA-seq; n=7 neurotypical donors) and identified 17 molecularly defined Hb cell types across 16,437 nuclei, including 3 medial and 7 lateral Hb populations, several of which were conserved between rodents and humans. Single molecule fluorescent in situ hybridization (smFISH; n=3 neurotypical donors) validated snRNA-seq Hb cell types and mapped their spatial locations. Bulk RNA-sequencing and cell type deconvolution in Hb-enriched tissue from 35 individuals with SCZD and 33 neurotypical controls yielded 45 SCZD-associated differentially expressed genes (DEGs, FDR < 0.05), with 32 (71%) unique to Hb-enriched tissue. eQTL analysis identified 717 independent SNP-gene pairs (FDR < 0.05), where either the SNP is a SCZD risk variant (16 pairs) or the gene is a SCZD DEG (7 pairs). eQTL and SCZD risk colocalization analysis identified 16 colocalized genes. These results identify topographically organized cell types with distinct molecular signatures in the human Hb and demonstrate unique genetic changes associated with SCZD, thereby providing novel molecular insights into the role of Hb in neuropsychiatric disorders. One Sentence SummaryTranscriptomic analysis of the human habenula and identification of molecular changes associated with schizophrenia risk and illness state.

neuroscience↗

Genetic and environmental contributions to ancestry differences in gene expression in the human brain

Ancestral differences in genomic variation are determining factors in gene regulation; however, most gene expression studies have been limited to European ancestry samples or adjusted for ancestry to identify ancestry-independent associations. We instead examined the impact of genetic ancestry on gene expression and DNA methylation (DNAm) in admixed African/Black American neurotypical individuals to untangle effects of genetic and environmental factors. Ancestry-associated differentially expressed genes (DEGs), transcripts, and gene networks, while notably not implicating neurons, are enriched for genes related to immune response and vascular tissue and explain up to 26% of heritability for ischemic stroke, 27% of heritability for Parkinsons disease, and 30% of heritability for Alzhemiers disease. Ancestry-associated DEGs also show general enrichment for heritability of diverse immune-related traits but depletion for psychiatric-related traits. The cell-type enrichments and direction of effects vary by brain region. These DEGs are less evolutionarily constrained and are largely explained by genetic variations; roughly 15% are predicted by DNAm variation implicating environmental exposures. We also compared Black and White Americans, confirming most of these ancestry-associated DEGs. Our results highlight how environment and genetic background affect genetic ancestry differences in gene expression in the human brain and affect risk for brain illness. SummaryWe examine the impact of genetic ancestry on gene expression and DNA methylation of admixed African/Black Americans, highlighting how genetic and environmental background affect risk for brain illness.

genetics↗

Mapping the Complex Genetic Landscape of Human Neurons

When somatic cells acquire complex karyotypes, they are removed by the immune system. Mutant somatic cells that evade immune surveillance can lead to cancer. Neurons with complex karyotypes arise during neurotypical brain development, but neurons are almost never the origin of brain cancers. Instead, somatic mutations in neurons can bring about neurodevelopmental disorders, and contribute to the polygenic landscape of neuropsychiatric and neurodegenerative disease. A subset of human neurons harbors idiosyncratic copy number variants (CNVs, "CNV neurons"), but previous analyses of CNV neurons have been limited by relatively small sample sizes. Here, we developed an allele-based validation approach, SCOVAL, to corroborate or reject read-depth based CNV calls in single human neurons. We applied this approach to 2,125 frontal cortical neurons from a neurotypical human brain. This approach identified 226 CNV neurons, as well as a class of CNV neurons with complex karyotypes containing whole or substantial losses on multiple chromosomes. Moreover, we found that CNV location appears to be nonrandom. Recurrent regions of neuronal genome rearrangement contained fewer, but longer, genes.

neuroscience↗

KIBRA-PKCγ signaling pathway modulates memory performance in mice and humans

Human memory is a polygenic cognitive trait that is fundamental to individual competence. Genome-wide association studies (GWAS) have identified KIBRA as a novel gene associated with human memory performance. KIBRA interacts with AMPA receptors (AMPARs) and proteins essential for synaptic plasticity. The deletion of Kibra in mice impairs synaptic plasticity and learning and memory. However, the molecular basis through which KIBRA regulates dynamic AMPAR trafficking underlying synaptic plasticity is still unknown. Here we report that KIBRA interacts with the neuronal specific kinase PKC{gamma} to modulate AMPAR trafficking upon learning, and KIBRA-PKC{gamma} signaling pathway also associates with human memory performance. We find PKC{gamma} is an essential kinase that phosphorylates AMPARs upon learning, and the loss of KIBRA in mouse brain impedes PKC{gamma}-AMPAR interaction. Activation of PKC{gamma} enables KIBRA to recruit phosphorylated AMPARs to the synapse to promote LTP and learning. We further performed transcriptomic and genetic analyses in human postmortem brain samples, and behavioral and fMRI evaluations in living human subjects, to demonstrate the genetic interactions between KIBRA and PRKCG on memory performance and memory associated physiological engagement of the hippocampal memory system. Overall, our results support that the KIBRA-PKC{gamma} signaling pathway is crucial for modulating memory performance in mice and humans.

neuroscience↗

A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Neuroimaging Phenotypes of Disease

AO_SCPLOWBSTRACTC_SCPLOWWe propose a novel end-to-end framework for whole-brain and whole-genome imaging-genetics. Our genetics network uses hierarchical graph convolution and pooling operations to embed subject-level data onto a low-dimensional latent space. The hierarchical network implicitly tracks the convergence of genetic risk across well-established biological pathways, while an attention mechanism automatically identifies the salient edges of this network at the subject level. In parallel, our imaging network projects multimodal data onto a set of latent embeddings. For interpretability, we implement a Bayesian feature selection strategy to extract the discriminative imaging biomarkers; these feature weights are optimized alongside the other model parameters. We couple the imaging and genetic embeddings with a predictor network, to ensure that the learned representations are linked to phenotype. We evaluate our framework on a schizophrenia dataset that includes two functional MRI paradigms and gene scores derived from Single Nucleotide Polymorphism data. Using repeated 10-fold cross-validation, we show that our imaging-genetics fusion achieves the better classification performance than state-of-the-art baselines. In an exploratory analysis, we further show that the biomarkers identified by our model are reproducible and closely associated with deficits in schizophrenia.

bioinformatics↗

Investigating trait variability of gene co-expression network architecture in brain by manipulating genomic signatures of schizophrenia risk

While the role of genomic risk for schizophrenia on brain gene co-expression networks has been described, the patterns of its manifestations are varied and complex. To acquire a deeper understanding of this issue, we implemented a novel approach to network construction by manipulating the RNA-Seq expression input to "integrate" or "remove" the "modulatory" effects of genomic risk for schizophrenia. We created co-expression networks in DLPFC from the adjusted expression input and compared them in terms of gene overlap and connectivity. We used linear regression models to remove variance explained by RNA quality, cell type proportion, age, sex and genetic ancestry. We also created co-expression networks based on the genomic profile of a normative trait, height, as a "negative control"; we also applied the same analytical approach in two independent samples: LIBD Human Brain Repository (HBR) (N=78 brains, European ancestry) and Common Mind Consortium (CMC) (N=116 brains, European ancestry). In addition to direct comparisons, we explored the biological plausibility of the differential gene clusters between co-expression networks by testing them for enrichment in relevant gene ontologies and gene sets of interest (PGC2-CLOZUK GWAS significant loci genes, height GWAS significant loci genes, genes in synaptic ontologies-SynGO and genes of the "druggable genome"). We identify several key aspects of the role of genomic risk for schizophrenia in brain co-expression networks: 1) Variability of co-expression modules with "integration" or "removal" of genomic profiles of complex traits (normal or pathological); 2) Biological plausibility of gene sets represented in the differential co-expression contrasts and potential relevance for illness etiopathogenesis; 3) Non-preferential mapping of schizophrenia GWAS loci genes to network areas apparently influenced by the genomic risk score. Overall, our study supports the notion that genomic risk for schizophrenia has an extensive and non-linear effect on brain gene co-expression networks that possibly manifests as a molecular background for gene-gene, gene-environment interactions that affect various biological pathways.

genomics↗

Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRS) for schizophrenia and a clinical diagnosis of schizophrenia, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures associated with diagnosis that implicated altered Na+ channel function and GABA-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these schizophrenia patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

neuroscience↗

Mapping origins of variation in neural trajectories of human pluripotent stem cells

Variability between human pluripotent stem cell (hPSC) lines remains a challenge and opportunity in biomedicine. We identified differences in the early lineage emergence across hPSC lines that mapped on the antero-posterior axis of embryonic development. RNA-seq analysis revealed dynamic transcriptomic patterns that defined the emergence of mesendodermal versus neuroectodermal lineages conserved across hPSC lines and cell line-specific transcriptional signatures that were invariant across differentiation. The stable cell line-specific transcriptomic patterns predicted the retinoic acid (RA) response of the cell lines, resulting in distinct bias towards fore-versus hind-brain fates. Replicate hPSC lines and paired adult donor tissue demonstrated that cells from individual humans expressed unique and long-lasting transcriptomic signatures associated with evolutionarily recent genes. In addition to this genetic contribution, we found that replicate lines from a single donor showed divergent brain regional fates linked to distinct chromatin states, indicating that epigenetic mechanisms also contribute to neural fate differences. This variation in lineage bias and its correlation with RA responsive gene expression was also observed in a large collection of hPSC lines. These results define transcriptomic differences in hPSCs that initiate a critical early step specifying anterior or posterior neural fates.

neuroscience↗

Developmental profile of psychiatric risk associated with voltage-gated cation channel activity

BackgroundRecent breakthroughs in psychiatric genetics have implicated biological pathways onto which genetic risk for psychiatric disorders converges. However, these studies do not reveal the developmental time point(s) at which these pathways are relevant. MethodsWe aimed to determine the relationship between psychiatric risk and developmental gene expression relating to discrete biological pathways. We used post-mortem RNA sequencing data (BrainSeq and BrainSpan) from brain tissue at multiple pre- and post-natal timepoints and summary statistics from recent genome-wide association studies of schizophrenia, bipolar disorder and major depressive disorder. We prioritised gene sets for overall enrichment of association with each disorder, and then tested the relationship between the association of each of their constituent genes with their relative expression at each developmental stage. ResultsWe observed relationships between the expression of genes involved in voltage-gated cation channel activity during Early Midfetal, Adolescence and Early Adulthood timepoints and association with schizophrenia and bipolar disorder, such that genes more strongly associated with these disorders had relatively low expression during Early Midfetal development and higher expression during Adolescence and Early Adulthood. The relationship with schizophrenia was strongest for the subset of genes related to calcium channel activity, whilst for bipolar disorder the relationship was distributed between calcium and potassium channel activity genes. ConclusionsOur results indicate periods during development when biological pathways related to the activity of calcium and potassium channels may be most vulnerable to the effects of genetic variants conferring risk to psychiatric disorders. Furthermore, they indicate key time points and potential targets for disorder-specific therapeutic interventions.

neuroscience↗

Comprehensive identification of somatic nucleotide variants in human brain tissue

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. Here, the Brain Somatic Mosaicism Network conducted a coordinated, multi-institutional study to: (i) examine the ability of existing methods to detect simulated somatic single nucleotide variants (SNVs) in DNA mixing experiments; (ii) 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; (iii) devise strategies to discover somatic SNVs; and (iv) apply various approaches to validate somatic SNVs. These efforts led to the identification of 43 bona fide somatic SNVs that ranged in variant allele fractions from ~0.005 to ~0.28. Guided by these results, we devised best practices for calling mosaic SNVs from 250X whole genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrated that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. Thus, 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.

genomics↗