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Coppola, G.

Publications and source records attributed to Coppola, G..

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Whole exome sequencing and characterization of coding variation in 49,960 individuals in the UK Biobank

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world. Here we describe the first tranche of large-scale exome sequence data for 49,960 study participants, revealing approximately 4 million coding variants (of which ~98.4% have frequency < 1%). The data includes 231,631 predicted loss of function variants, a >10-fold increase compared to imputed sequence for the same participants. Nearly all genes (>97%) had [&ge;]1 predicted loss of function carrier, and most genes (>69%) had [&ge;]10 loss of function carriers. We illustrate the power of characterizing loss of function variation in this large population through association analyses across 1,741 phenotypes. In addition to replicating a range of established associations, we discover novel loss of function variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical significance in this population, finding that 2% of the population has a medically actionable variant. Additionally, we leverage the phenotypic data to characterize the relationship between rare BRCA1 and BRCA2 pathogenic variants and cancer risk. Exomes from the first 49,960 participants are now made accessible to the scientific community and highlight the promise offered by genomic sequencing in large-scale population-based studies.

genomics↗

Synaptic and Gene Regulatory Mechanisms in Schizophrenia, Autism, and 22q11.2 CNV Mediated Risk for Neuropsychiatric Disorders

Background22q11.2 copy number variants (CNVs) are among the most highly penetrant genetic risk variants for developmental neuropsychiatric disorders such as schizophrenia (SCZ) and autism spectrum disorder (ASD). However, the specific mechanisms through which they confer risk remain unclear. MethodsUsing a functional genomics approach, we integrated transcriptomic data from the developing human brain, genome-wide association findings for SCZ and ASD, protein interaction data, and pathophysiological signatures of SCZ and ASD to: 1) organize genes into the developmental cellular and molecular systems within which they operate; 2) identify neurodevelopmental processes associated with polygenic risk for SCZ and ASD across the allelic frequency spectrum; and 3) elucidate pathways and individual genes through which 22q11.2 CNVs may confer risk for each disorder. ResultsPolygenic risk for SCZ and ASD converged on partially overlapping gene networks involved in synaptic function and transcriptional regulation, with ASD risk variants additionally enriched for networks involved in neuronal differentiation during fetal development. The 22q11.2 locus formed a large protein network that disproportionately affected SCZ- and ASD-associated neurodevelopmental networks, including loading highly onto synaptic and gene regulatory pathways. SEPT5, PI4KA, and SNAP29 genes are candidate drivers of 22q11.2 synaptic pathology relevant to SCZ and ASD, and DGCR8 and HIRA are candidate drivers of disease-relevant alterations in gene regulation. ConclusionsThe current approach provides a powerful framework to identify neurodevelopmental processes affected by diverse risk variants for SCZ and ASD, and elucidate the mechanisms through which highly penetrant multi-gene CNVs contribute to disease risk.

systems biology↗

Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders.

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

genomics↗

C. elegans granulins promote an age-associated decline in protein homeostasis via lysosomal protease inhibition

The progressive failure of protein homeostasis is a hallmark of aging and a common feature in neurodegenerative disease. As the enzymes executing the final stages of autophagy, lysosomal proteases (or cathepsins) are key contributors to maintenance of protein homeostasis with age. Here, we identify the cysteine-rich granulin peptides as a new class of regulators of lysosomal aspartyl protease activity. Granulins are produced in an age and stress-dependent manner through cleavage of the neurodegenerative disease protein, progranulin. Once liberated, granulins selectively interact with the aspartyl protease ASP-3/cathepsin D to impair enzymatic activity. Consequently, protein homeostasis and lysosome function is disrupted, prompting cells to activate a compensatory transcriptional program. Our results support a model in which granulin production modulates a critical transition between the normal, physiological regulation of protease activity and the impairment of lysosomal function that can occur with age and disease.

neuroscience↗

Transcriptional profiling of isogenic Friedreich ataxia induced pluripotent stem cell-derived neurons

Friedreich ataxia (FRDA) is a rare childhood neurodegenerative disorder with no effective treatment. FRDA is caused by transcriptional silencing of the FXN gene and consequent loss of the essential mitochondrial protein frataxin. Based on the knowledge that a GAA*TTC repeat expansion in the first intron of FXN leads to heterochromatin formation and gene silencing, we have shown that members of the 2-aminobenzamide family of histone deacetylase inhibitors (HDACi) reproducibly increase FXN mRNA levels in induced pluripotent stem cell (iPSC)-derived FRDA neuronal cells and in peripheral blood mononuclear cells from patients treated with the drug in a phase I clinical trial. How the reduced expression of frataxin leads to neurological and other systemic symptoms in FRDA patients remains unclear. Similarly to other triplet repeat disorders, it is not known why only specific cells types are affected in the disease, primarily the large sensory neurons of the dorsal root ganglia and cardiomyocytes. The combination of iPSC technology and genome editing techniques offers the unique possibility of addressing these questions in a relevant cell model of the disease, without the confounding effect of different genetic backgrounds. We derived a set of isogenic iPSC lines that differ only in the length of the GAA*TTC repeats, using \"scarless\" gene-editing methods (helper-dependent adenovirus-mediated homologous recombination). To uncover the gene expression signature due to GAA*TTC repeat expansion in FRDA neuronal cells and the effect of HDACi on these changes, we performed transcriptomic analysis of iPSC-derived central nervous system (CNS) and isogenic sensory neurons by RNA sequencing. We find that multiple cellular pathways are commonly affected by the loss of frataxin in CNS and peripheral nervous system neurons and these changes are partially restored by HDACi treatment.

neuroscience↗

ForestQC: quality control on genetic variants from next-generation sequencing data using random forest

Next-generation sequencing technology (NGS) enables discovery of nearly all genetic variants present in a genome. A subset of these variants, however, may have poor sequencing quality due to limitations in sequencing technology or in variant calling algorithms. In genetic studies that analyze a large number of sequenced individuals, it is critical to detect and remove those variants with poor quality as they may cause spurious findings. In this paper, we present a statistical approach for performing quality control on variants identified from NGS data by combining a traditional filtering approach and a machine learning approach. Our method uses information on sequencing quality such as sequencing depth, genotyping quality, and GC contents to predict whether a certain variant is likely to contain errors. To evaluate our method, we applied it to two whole-genome sequencing datasets where one dataset consists of related individuals from families while the other consists of unrelated individuals. Results indicate that our method outperforms widely used methods for performing quality control on variants such as VQSR of GATK by considerably improving the quality of variants to be included in the analysis. Our approach is also very efficient, and hence can be applied to large sequencing datasets. We conclude that combining a machine learning algorithm trained with sequencing quality information and the filtering approach is an effective approach to perform quality control on genetic variants from sequencing data.\n\nAuthor SummaryGenetic disorders can be caused by many types of genetic mutations, including common and rare single nucleotide variants, structural variants, insertions and deletions. Nowadays, next generation sequencing (NGS) technology allows us to identify various genetic variants that are associated with diseases. However, variants detected by NGS might have poor sequencing quality due to biases and errors in sequencing technologies and analysis tools. Therefore, it is critical to remove variants with low quality, which could cause spurious findings in follow-up analyses. Previously, people applied either hard filters or machine learning models for variant quality control (QC), which failed to filter out those variants accurately. Here, we developed a statistical tool, ForestQC, for variant QC by combining a filtering approach and a machine learning approach. We applied ForestQC to one family-based whole genome sequencing (WGS) dataset and one general case-control WGS dataset, to evaluate our method. Results show that ForestQC outperforms widely used methods for variant QC by considerably improving the quality of variants. Also, ForestQC is very efficient and scalable to large-scale sequencing datasets. Our study indicates that combining filtering approaches and machine learning approaches enables effective variant QC.

bioinformatics↗

Single-cell in situ transcriptomic map of astrocyte cortical layer diversity

During organogenesis, patterns and gradients of gene expression underlie organization and diversified cell specification to generate complex tissue architecture. While the cerebral cortex is organized into six excitatory neuronal layers, it is unclear whether glial cells are diversified to mimic neuronal laminae or show distinct layering. To determine the molecular architecture of the mammalian cortex, we developed a high content pipeline that can quantify single-cell gene expression in situ. The Large-area Spatial Transcriptomic (LaST) map confirmed expected cortical neuron layer organization and also revealed a novel neuronal identity signature. Screening 46 candidate genes for astrocyte diversity across the cortex, we identified grey matter superficial, mid and deep astrocyte identities in gradient layer patterns that were distinct from neurons. Astrocyte layers formed in early postnatal cortex and mostly persisted in adult mouse and human cortex. Mutations that shifted neuronal post-mitotic identity or organization were sufficient to alter glial layering, indicating an instructive role for neuronal cues. In normal mouse cortex, astrocyte layer patterns showed area diversity between functionally distinct cortical regions. These findings indicate that excitatory neurons and astrocytes cells are organized into distinct lineage-associated laminae, which give rise to higher order neuroglial complexity of cortical architecture.

neuroscience↗

Selective axonal translation of prenylated Cdc42 mRNA isoform supports axon growth

The small Rho-family GTPase Cdc42 has long been known to have a role in cell motility and axon growth. The eukaryotic CDC42 gene is alternatively spliced to generate mRNAs with two different 3UTRs that encode proteins with distinct C-termini. The C-termini of these Cdc42 proteins include CAAX and CCAX motifs for post-translational prenylation and palmitoylation, respectively. Palmitoyl-Cdc42 protein was previously shown to contribute to dendrite maturation, while the prenyl-Cdc42 protein contributes to axon specification and its mRNA was detected in neurites. Here, we show that the mRNA encoding prenyl-Cdc42 isoform preferentially localizes into PNS axons and this localization selectively increases in vivo during PNS axon regeneration. Isoform specific siRNA knockdowns, rescue experiments with siRNA-resistant Cdc42 isoforms, and pharmacologically targeting Cdc42 activity indicate that prenyl-Cdc42 promotes axon growth while the palmitoyl-Cdc42 has little growth promoting activity. The growth promotion by prenyl-Cdc42 requires axonal mRNA localization with localized translation and an intact C-terminal CaaX motif for localized prenylation of the encoded protein. Together, these data show that alternative splicing of the CDC42 gene product generates an axon growth promoting locally synthesized prenyl-Cdc42 protein. SUMMARY STATEMENTAxon regeneration drives selective localization of alternatively spliced CDC42 isoform to PNS axons.

neuroscience↗

Contribution of common and rare variants to bipolar disorder susceptibility in extended pedigrees from population isolates

Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP) in numerous multigenerational pedigrees suggests that, in such families, large-effect inherited variants might play a greater role. To evaluate this hypothesis, we conducted genetic analyses in 26 Colombian (CO) and Costa Rican (CR) pedigrees ascertained for BP1, the most severe and heritable form of BP. In these pedigrees, we performed microarray SNP genotyping of 856 individuals and high-coverage whole-genome sequencing of 454 individuals. Compared to their unaffected relatives, BP1 individuals had higher polygenic risk scores estimated from SNPs associated with BP discovered in independent genome-wide association studies, and also displayed a higher burden of rare deleterious single nucleotide variants (SNVs) and rare copy number variants (CNVs) in genes likely to be relevant to BP1. Parametric and non-parametric linkage analyses identified 15 BP1 linkage peaks, encompassing about 100 genes, although we observed no significant segregation pattern for any particular rare SNVs and CNVs. These results suggest that even in extended pedigrees, genetic risk for BP appears to derive mainly from small to moderate effect rare and common variants.

genetics↗

Precision genome-editing with CRISPR/Cas9 in human induced pluripotent stem cells

Genome engineering in human induced pluripotent stem cells (iPSCs) represent an opportunity to examine the contribution of pathogenic and disease modifying alleles to molecular and cellular phenotypes. However, the practical application of genome-editing approaches in human iPSCs has been challenging. We have developed a precise and efficient genome-editing platform that relies on allele-specific guideRNAs (gRNAs) paired with a robust method for culturing and screening the modified iPSC clones. By applying an allele-specific gRNA design strategy, we have demonstrated greatly improved editing efficiency without the introduction of additional modifications of unknown consequence in the genome. Using this approach, we have modified nine independent iPSC lines at five loci associated with neurodegeneration. This genome-editing platform allows for efficient and precise production of isogenic cell lines for disease modeling. Because the impact of CRISPR/Cas9 on off-target sites remains poorly understood, we went on to perform thorough off-target profiling by comparing the mutational burden in edited iPSC lines using whole genome sequencing. The bioinformatically predicted off-target sites were unmodified in all edited iPSC lines. We also found that the numbers of de novo genetic variants detected in the edited and unedited iPSC lines were similar. Thus, our CRISPR/Cas9 strategy does not specifically increase the mutational burden. Furthermore, our analyses of the de novo genetic variants that occur during iPSC culture and genome-editing indicate an enrichment of de novo variants at sites identified in dbSNP. Taken together, we propose that this enrichment represents regions of the genome more susceptible to mutation. Herein, we present an efficient and precise method for allele-specific genome-editing in iPSC and an analyses pipeline to distinguish off-target events from de novo mutations occurring with culture.

genetics↗

Enhanced neuronal regeneration in the CAST/Ei mouse strain is linked to expression of differentiation markers after injury

Peripheral nerve regeneration after injury requires a broad program of transcriptional changes. We investigated the basis for the enhanced nerve regenerative capacity of the CAST/Ei mouse strain relative to C57BL/6 mice. RNA sequencing of dorsal root ganglia (DRG) showed a CAST/Ei specific upregulation of Ascl1 after injury. Ascl1 overexpression in C57BL/6 mice DRG neurons enhanced their neurite outgrowth. Ascl1 is regulated by miR-7048-3p, which is down-regulated in CAST/Ei mice. Inhibition of miR-7048-3p enhances neurite outgrowth. Following injury, CAST/Ei neurons largely retained their mature neuronal profile as determined by single cell RNAseq, whereas the C57BL/6 neurons acquired an immature profile. These findings suggest that one facet of the enhanced regenerative phenotype is preservation of neuronal identity in response to injury.

molecular biology↗

Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

genetics↗

Ancient hybridization and strong adaptation to viruses across African vervet monkey populations

Vervet monkeys (genus Chlorocebus, also known as African green monkeys), are highly abundant in savannahs and riverine forests throughout sub-Saharan Africa. They are amongst the most widely distributed nonhuman primates, show considerable phenotypic diversity, and have long been an important biomedical model for a variety of human diseases1 and in vaccine research2-4. They are particularly interesting for HIV/AIDS research as they are the most abundant natural hosts of simian immunodeficiency virus (SIV), a close relative of HIV. Here we present the first genome-wide survey of polymorphism in vervets, using sequencing data from 163 individuals sampled from across Africa and the Caribbean islands where vervets were introduced during the colonial era. We find high diversity, within and between taxa, and clear evidence that taxonomic divergence was reticulate rather than following a simple branching pattern. A scan for diversifying selection across vervet taxa yields gene enrichments much stronger than in similar studies on humans5. In particular, we report strong and highly polygenic selection signals affecting viral processes -- in line with recent evidence that proposes a driving role for viruses in protein evolution in mammals6. Furthermore, selection scores are highly elevated in genes whose human orthologs interact with HIV, and in genes that show a response to experimental SIV infection in vervet monkeys but not in rhesus macaques, suggesting that part of the signal reflects taxon-specific adaptation to SIV. Intriguingly, rather than affecting genes with antiviral and inflammatory-related functions7, selection in vervets appears to have primarily targeted genes involved in the transcriptional regulation of viruses, and in particular those that are harmful only under immunodeficiency, suggesting adaptation to living with SIV rather than defense against infection.

evolutionary biology↗