RESUMO
Neurodevelopmental disorders (NDDs) are associated with a wide range of clinical features, affecting multiple pathways involved in brain development and function. Recent advances in high-throughput sequencing have unveiled numerous genetic variants associated with NDDs, which further contribute to disease complexity and make it challenging to infer disease causation and underlying mechanisms. Herein, we review current strategies for dissecting the complexity of NDDs using model organisms, induced pluripotent stem cells, single-cell sequencing technologies, and massively parallel reporter assays. We further highlight single-cell CRISPR-based screening techniques that allow genomic investigation of cellular transcriptomes with high efficiency, accuracy, and throughput. Overall, we provide an integrated review of experimental approaches that can be applicable for investigating a broad range of complex disorders.
Assuntos
Transtornos do Neurodesenvolvimento , Humanos , Transtornos do Neurodesenvolvimento/genética , Genômica , GenomaRESUMO
We examined more than 97,000 families from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents contributing to neurodevelopmental disease risk in children. We identified within- and cross-disorder correlations between six phenotypes in parents and children, such as obsessive-compulsive disorder (R = 0.32-0.38, p < 10-126). We also found that measures of sub-clinical autism features in parents are associated with several autism severity measures in children, including biparental mean Social Responsiveness Scale scores and proband Repetitive Behaviors Scale scores (regression coefficient = 0.14, p = 3.38 × 10-4). We further describe patterns of phenotypic similarity between spouses, where spouses show correlations for six neurological and psychiatric phenotypes, including a within-disorder correlation for depression (R = 0.24-0.68, p < 0.001) and a cross-disorder correlation between anxiety and bipolar disorder (R = 0.09-0.22, p < 10-92). Using a simulated population, we also found that assortative mating can lead to increases in disease liability over generations and the appearance of "genetic anticipation" in families carrying rare variants. We identified several families in a neurodevelopmental disease cohort where the proband inherited multiple rare variants in disease-associated genes from each of their affected parents. We further identified parental relatedness as a risk factor for neurodevelopmental disorders through its inverse relationship with variant pathogenicity and propose that parental relatedness modulates disease risk by increasing genome-wide homozygosity in children (R = 0.05-0.26, p < 0.05). Our results highlight the utility of assessing parent phenotypes and genotypes toward predicting features in children who carry rare variably expressive variants and implicate assortative mating as a risk factor for increased disease severity in these families.
Assuntos
Transtorno Autístico , Transtorno Bipolar , Criança , Humanos , Virulência , Pais , Família , Transtorno Autístico/genética , Transtorno Bipolar/genéticaRESUMO
High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.
Assuntos
Genoma , Sequências Reguladoras de Ácido Nucleico , Reprodutibilidade dos Testes , Biologia Computacional/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Sequência de DNA/métodosRESUMO
The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angiotensin-converting enzyme 2 (hACE2) represents the first required step for cellular entry. SARS-CoV-2 has continued to evolve with the emergence of several novel variants, and amino acid changes in the RBD have been implicated with increased fitness and potential for immune evasion. Reliably predicting the effect of amino acid changes on the ability of the RBD to interact more strongly with the hACE2 can help assess the implications for public health and the potential for spillover and adaptation into other animals. Here, we introduce a two-step framework that first relies on 48 independent 4-ns molecular dynamics (MD) trajectories of RBD-hACE2 variants to collect binding energy terms decomposed into Coulombic, covalent, van der Waals, lipophilic, generalized Born solvation, hydrogen bonding, π-π packing, and self-contact correction terms. The second step implements a neural network to classify and quantitatively predict binding affinity changes using the decomposed energy terms as descriptors. The computational base achieves a validation accuracy of 82.8% for classifying single-amino acid substitution variants of the RBD as worsening or improving binding affinity for hACE2 and a correlation coefficient of 0.73 between predicted and experimentally calculated changes in binding affinities. Both metrics are calculated using a fivefold cross-validation test. Our method thus sets up a framework for screening binding affinity changes caused by unknown single- and multiple-amino acid changes offering a valuable tool to predict host adaptation of SARS-CoV-2 variants toward tighter hACE2 binding.
Assuntos
Enzima de Conversão de Angiotensina 2/metabolismo , Interações Hospedeiro-Patógeno/genética , Redes Neurais de Computação , SARS-CoV-2/metabolismo , Glicoproteína da Espícula de Coronavírus/metabolismo , Substituição de Aminoácidos , Sítios de Ligação/genética , Humanos , Simulação de Dinâmica Molecular , SARS-CoV-2/genética , Glicoproteína da Espícula de Coronavírus/genéticaRESUMO
About two-thirds of the genes in the Drosophila melanogaster genome are also involved in its eye development, making the Drosophila eye an ideal system for genetic studies. We previously developed Flynotyper, a software that uses image processing operations to identify and quantify the degree of roughness by measuring disorderliness of ommatidial arrangement in the fly eye. This software has enabled researchers to quantify morphological defects of thousands of eye images caused by genetic perturbations. Here, we present Flynotyper 2.0, a software that has an updated computer vision library, improved performance, and a streamlined pipeline for high-throughput analysis of multiple eye images. We also tested several batches of Drosophila eye images to ensure robustness and reproducibility of the updated Flynotyper 2.0 software. Availability and implementation: The source code for Flynotyper 2.0 can be downloaded and installed from https://github.com/girirajanlab/flynotyper-desktop-application .
RESUMO
Analyses of postmortem human brains and preclinical studies of rodents have identified somatostatin (SST)-positive interneurons as key elements that regulate the vulnerability to stress-related psychiatric disorders. Conversely, genetically induced disinhibition of SST neurons or brain region-specific chemogenetic activation of SST neurons in mice results in stress resilience. Here, we used RNA sequencing of mice with disinhibited SST neurons to characterize the transcriptome changes underlying GABAergic control of stress resilience. We found that stress resilience of male but not female mice with disinhibited SST neurons is characterized by resilience to chronic stress-induced transcriptome changes in the medial prefrontal cortex. Interestingly, the transcriptome of non-stressed stress-resilient male mice resembled the transcriptome of chronic stress-exposed stress-vulnerable mice. However, the behavior and the serum corticosterone levels of non-stressed stress-resilient mice showed no signs of physiological stress. Most strikingly, chronic stress exposure of stress-resilient mice was associated with an almost complete reversal of their chronic stress-like transcriptome signature, along with pathway changes indicating stress-induced enhancement of mRNA translation. Behaviorally, the mice with disinhibited SST neurons were not only resilient to chronic stress-induced anhedonia - they also showed an inversed anxiolytic-like response to chronic stress exposure that mirrored the chronic stress-induced reversal of the chronic stress-like transcriptome signature. We conclude that GABAergic dendritic inhibition by SST neurons exerts bidirectional control over behavioral vulnerability and resilience to chronic stress exposure that is mirrored in bidirectional changes in expression of putative stress resilience genes, through a sex-specific brain substrate.
RESUMO
We examined more than 38,000 spouse pairs from four neurodevelopmental disease cohorts and the UK Biobank to identify phenotypic and genetic patterns in parents associated with neurodevelopmental disease risk in children. We identified correlations between six phenotypes in parents and children, including correlations of clinical diagnoses such as obsessive-compulsive disorder (R=0.31-0.49, p<0.001), and two measures of sub-clinical autism features in parents affecting several autism severity measures in children, such as bi-parental mean Social Responsiveness Scale (SRS) scores affecting proband SRS scores (regression coefficient=0.11, p=0.003). We further describe patterns of phenotypic and genetic similarity between spouses, where spouses show both within- and cross-disorder correlations for seven neurological and psychiatric phenotypes, including a within-disorder correlation for depression (R=0.25-0.72, p<0.001) and a cross-disorder correlation between schizophrenia and personality disorder (R=0.20-0.57, p<0.001). Further, these spouses with similar phenotypes were significantly correlated for rare variant burden (R=0.07-0.57, p<0.0001). We propose that assortative mating on these features may drive the increases in genetic risk over generations and the appearance of "genetic anticipation" associated with many variably expressive variants. We further identified parental relatedness as a risk factor for neurodevelopmental disorders through its inverse correlations with burden and pathogenicity of rare variants and propose that parental relatedness drives disease risk by increasing genome-wide homozygosity in children (R=0.09-0.30, p<0.001). Our results highlight the utility of assessing parent phenotypes and genotypes in predicting features in children carrying variably expressive variants and counseling families carrying these variants.