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Park, P. J.

Publications and source records attributed to Park, P. J..

At least 37 records · Page 2Linked to original sources

High-resolution detection of copy number alterations in single cells with HiScanner

Improvements in single-cell whole-genome sequencing (scWGS) assays have enabled detailed characterization of somatic copy number alterations (CNAs) at the single-cell level. Yet, current computational methods are mostly designed for detecting chromosome-scale changes in cancer samples with low sequencing coverage. Here, we introduce HiScanner (High-resolution Single-Cell Allelic copy Number callER), which combines read depth, B-allele frequency, and haplotype phasing to identify CNAs with high resolution. In simulated data, HiScanner consistently outperforms state-of-the-art methods across various CNA types and sizes. When applied to high-coverage scWGS data from 65 cells across 11 neurotypical human brains, HiScanner shows a superior ability to detect smaller CNAs, uncovering distinct CNA patterns between neurons and oligodendrocytes. We also generated low-coverage scWGS data from 179 cells sampled from the same meningioma patient at two time points. For this serial dataset, integration of CNAs with point mutations revealed evolutionary trajectories of tumor cells. These findings show that HiScanner enables accurate characterization of frequency, clonality, and distribution of CNAs at the single-cell level in both non-neoplastic and neoplastic cells.

genomics↗

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.

neuroscience↗

Contrasting patterns of somatic mutations in neurons and glia reveal differential predisposition to disease in the aging human brain

Characterizing the mechanisms of somatic mutations in the brain is important for understanding aging and disease, but little is known about the mutational patterns of different cell types. We performed whole-genome sequencing of 71 oligodendrocytes and 51 neurons from neurotypical individuals (0.4 to 104 years old) and identified >67,000 somatic single nucleotide variants (sSNVs) and small insertions and deletions (indels). While both cell types accumulate mutations with age, oligodendrocytes accumulate sSNVs 69% faster than neurons (27/year versus 16/year) whereas indels accumulate 42% slower (1.8/year versus 3.1/year). Correlation with single-cell RNA and chromatin accessibility from the same brains revealed that oligodendrocyte mutations are enriched in inactive genomic regions and are distributed similarly to mutations in brain cancers. In contrast, neuronal mutations are enriched in open, transcriptionally active chromatin. These patterns highlight differences in the mutagenic processes in glia and neurons and suggest cell type-specific, age-related contributions to neurodegeneration and oncogenesis.

neuroscience↗

Genomic patterns of malignant peripheral nerve sheath tumour (MPNST) evolution correlate with clinical outcome and are detectable in cell-free DNA

Malignant peripheral nerve sheath tumour (MPNST) is an aggressive soft-tissue sarcoma that arises in peripheral nerves. MPNST occurs either sporadically or in people with neurofibromatosis type 1 (NF1), a common cancer predisposition syndrome caused by germline pathogenic variants in NF1. Although MPNST is the most common cause of death and morbidity for individuals with NF1, the molecular underpinnings of MPNST pathogenesis remain unclear. Here, we report the analysis of whole-genome sequencing, multi-regional exome sequencing, transcriptomic and methylation profiling data for 95 MPNSTs and precursor lesions (64 NF1-related; 31 sporadic) from 77 individuals. Early events in tumour evolution include biallelic inactivation of NF1 followed by inactivation of CDKN2A and in some cases also TP53 and polycomb repressive complex 2 (PRC2) genes. Subsequently, both sporadic and NF1-related MPNSTs acquire a high burden of somatic copy number alterations (SCNAs). Our analysis revealed distinct pathways of tumour evolution and immune infiltration associated with inactivation of PRC2 genes and H3K27 trimethylation (H3K27me3) status. Tumours with loss of H3K27me3 evolve through extensive chromosomal losses with retention of chromosome 8 heterozygosity followed by whole genome doubling and chromosome 8 amplification. These tumours show lower levels of immune cell infiltration with low cytotoxic activity and low expression of immune checkpoints. In contrast, tumours with retention of H3K27me3 evolve through extensive genomic instability in the absence of recurrent alterations and exhibit an immune cell-rich phenotype. Specific SCNAs detected in both tumour samples and cell-free DNA (cfDNA) act as a surrogate for loss of H3K27me3 and immune infiltration, and predict prognosis. Our results suggest that SCNA profiling of tumour or cfDNA could serve as a biomarker for early diagnosis and to stratify patients into prognostic and treatment-related subgroups.

cancer biology↗

Accurate and sensitive mutational signature analysis with MuSiCal

Mutational signature analysis is a recent computational approach for interpreting somatic mutations in the genome. Its application to cancer data has enhanced our understanding of mutational forces driving tumorigenesis and demonstrated its potential to inform prognosis and treatment decisions. However, methodological challenges remain for discovering new signatures and assigning proper weights to existing signatures, thereby hindering broader clinical applications. Here we present MuSiCal (Mutational Signature Calculator), a rigorous analytical framework with novel algorithms that solves major problems in the standard workflow. Our simulation studies demonstrate that MuSiCal outperforms state-of-the-art algorithms for both signature discovery and assignment. By reanalyzing over 2,700 cancer genomes, we provide an improved catalog of signatures and their assignments, discover nine indel signatures absent in the current catalog, resolve long-standing issues with the ambiguous flat signatures, and give insights into signatures with unknown etiologies. We expect MuSiCal and the improved catalog to be a step towards establishing best practices for mutational signature analysis.

genomics↗

Enrichment of somatic mutations in schizophrenia brain targets prenatally active transcription factor bindings sites

Schizophrenia (SCZ) is a complex neuropsychiatric disorder in which both germline genetic mutations and maternal factors, such as infection and immune activation, have been implicated, but how these two strikingly different mechanisms might converge on the same phenotype is unknown. During development, cells accumulate somatic, mosaic mutations in ways that can be shaped by the cellular environment or endogenous processes, but these early developmental mutational patterns have not been studied in SCZ. Here we analyzed deep (267x) whole-genome sequencing (WGS) of DNA from cerebral cortical neurons isolated from 61 SCZ and 25 control postmortem brains to capture mutations occurring before or during fetal neurogenesis. SCZ cases showed a >15% increase in genome-wide sSNV compared to controls (p < 2e-10). Remarkably, mosaic T>G mutations and CpG transversions (CpG>GpG or CpG>ApG) were 79- and 62-fold enriched, respectively, at transcription factor binding sites (TFBS) in SCZ, but not in controls. The pattern of T>G mutations resembles mutational processes in cancer attributed to oxidative damage that is sterically blocked from DNA repair by transcription factors (TFs) bound to damaged DNA. The CpG transversions similarly suggest unfinished DNA demethylation resulting in abasic sites that can also be blocked from repair by bound TFs. Allele frequency analysis suggests that both localized mutational spikes occur in the first trimester. We call this prenatal mutational process "skiagenesis" (from the Greek skia, meaning shadow), as these mutations occur in the shadow of bound TFs. Skiagenesis reflects as-yet unidentified prenatal factors and is associated with SCZ risk in a subset ([~]13%) of cases. In turn, mutational disruption of key TFBS active in fetal brain is well positioned to create SCZ-specific gene dysregulation in concert with germline risk genes. Skiagenesis provides a fingerprint for exploring how epigenomic regulation and prenatal factors such as maternal infection or immune activation may shape the developmental mutational landscape of human brain.

genomics↗

The 4D Nucleome Data Portal: a resource for searching and visualizing curated nucleomics data

The 4D Nucleome (4DN) Network aims to elucidate the complex structure and organization of chromosomes in the nucleus and the impact of their disruption in disease biology. We present the 4DN Data Portal (https://data.4dnucleome.org/), a repository for datasets generated in the 4DN network and relevant external datasets. Datasets were generated with a wide range of experiments, including chromosome conformation capture assays such as Hi-C and other innovative sequencing and microscopy-based assays probing chromosome architecture. All together, the 4DN data portal hosts more than 1800 experiment sets and 34000 files. Results of sequencing-based assays from different laboratories are uniformly processed and quality-controlled. The portal interface allows easy browsing, filtering, and bulk downloads, and the integrated HiGlass genome browser allows interactive visualization and comparison of multiple datasets. The 4DN data portal represents a primary resource for chromosome contact and other nuclear architecture data for the scientific community.

genomics↗

Pairs and Pairix: a file format and a tool for efficient storage and retrieval for Hi-C read pairs

SummaryAs the amount of three-dimensional chromosomal interaction data continues to increase, storing and accessing such data efficiently becomes paramount. We introduce Pairs, a block-compressed text file format for storing paired genomic coordinates from Hi-C data, and Pairix, an open-source C application to index and query Pairs files. Pairix (also available in Python and R) extends the functionalities of Tabix to paired coordinates data. We have also developed PairsQC, a collapsible HTML quality control report generator for Pairs files. AvailabilityThe format specification and source code are available at https://github.com/4dn-dcic/pairix, https://github.com/4dn-dcic/Rpairix and https://github.com/4dn-dcic/pairsqc. Contactpeter_park@hms.harvard.edu or burak_alver@hms.harvard.edu

bioinformatics↗

Micro-Meta App: an interactive software tool to facilitate the collection of microscopy metadata based on community-driven specifications

For the information content of microscopy images to be appropriately interpreted, reproduced, and meet FAIR (Findable Accessible Interoperable and Reusable) principles, they should be accompanied by detailed descriptions of microscope hardware, image acquisition settings, image pixel and dimensional structure, and instrument performance. Nonetheless, the thorough documentation of imaging experiments is significantly impaired by the lack of community-sanctioned easy-to-use software tools to facilitate the extraction and collection of relevant microscopy metadata. Here we present Micro-Meta App, an intuitive open-source software designed to tackle these issues that was developed in the context of nascent global bioimaging community organizations, including BioImaging North America (BINA) and QUAlity Assessment and REProducibility in Light Microscopy (QUAREP-LiMi), whose goal is to improve reproducibility, data quality and sharing value for imaging experiments. The App provides a user-friendly interface for building comprehensive descriptions of the conditions utilized to produce individual microscopy datasets as specified by the recently proposed 4DN-BINA-OME tiered-system of Microscopy Metadata model. To achieve this goal the App provides a visual guide for a microscope-user to: 1) interactively build diagrammatic representations of hardware configurations of given microscopes that can be easily reused and shared with colleagues needing to document similar instruments. 2) Automatically extracts relevant metadata from image files and facilitates the collection of missing image acquisition settings and calibration metrics associated with a given experiment. 3) Output all collected Microscopy Metadata to interoperable files that can be used for documenting imaging experiments and shared with the community. In addition to significantly lowering the burden of quality assurance, the visual nature of Micro-Meta App makes it particularly suited for training users that have limited knowledge of the intricacies of light microscopy experiments. To ensure wide-adoption by microscope-users with different needs Micro-Meta App closely interoperates with MethodsJ2 and OMERO.mde, two complementary tools described in parallel manuscripts.

bioinformatics↗

Ultraspecific somatic SNV and indel detection in single neurons using primary template-directed amplification

Primary template-directed amplification (PTA) is an improved amplification technique for single-cell DNA sequencing. We generated whole-genome analysis of 76 single neurons and developed SCAN2, a computational method to accurately identify both clonal and non-clonal somatic (i.e., limited to a single neuron) single nucleotide variants (SNVs) and small insertions and deletions (indels) using PTA data. Our analysis confirms an increase in non-clonal somatic mutation in single neurons with age, but revises estimates for the rate of this accumulation to be 15 SNVs per year. We also identify artifacts in other amplification methods. Most importantly, we show that somatic indels also increase by at least 2 indels per year per neuron and that indels may have a larger impact on gene function than somatic SNVs in human neurons.

genomics↗

Whole-genome analysis of de novo and polymorphic retrotransposon insertions in Autism Spectrum Disorder

Retrotransposons are dynamic forces in evolutionary genomics and have been implicated as causes of Mendelian disease and hereditary cancer, but their role in Autism Spectrum Disorder (ASD) has never been systematically defined. Here, we report 86,154 polymorphic retrotransposon insertions including >60% not previously reported and 158 de novo retrotransposition events identified in whole genome sequencing (WGS) data of 2,288 families with ASD from the Simons Simplex Collection (SSC). As expected, the overall burden of de novo events was similar between ASD individuals and unaffected siblings, with 1 de novo insertion per 29, 104, and 192 births for Alu, L1, and SVA respectively, and 1 de novo insertion per 20 births total, while the location of transposon insertions differed between ASD and unaffected individuals. ASD cases showed more de novo L1 insertions than expected in ASD genes, and we also found de novo intronic retrotransposition events in known syndromic ASD genes in affected individuals but not in controls. Additionally, we observed exonic insertions in genes with a high probability of being loss-of-function intolerant, including a likely causative exonic insertion in CSDE1, only in ASD individuals. Although de novo retrotransposition occurs less frequently than single nucleotide and copy number variants, these findings suggest a modest, but important, impact of intronic and exonic retrotransposition mutations in ASD and highlight the utility of developing specific bioinformatic tools for high-throughput detection of transposable element insertions.

genetics↗

Single cell gene fusion detection by scFusion

Gene fusions are widespread in tumor cells and can play important roles in tumor initiation and progression. Using full length single cell RNA sequencing (scRNA-seq), gene fusions can now be detected at single cell level. However, scRNA-seq data has a high noise level and contains various technical artefacts that can lead to spurous fusion discoveries. Here we present a computational tool, scFusion, for gene fusion detection based on scRNA-seq. scFusion can efficiently and sensitively detect fusions with a low false discovery rate. In a T cell data, scFusion detected the invariant TCR gene recombinations in Mucosal-associated invariant T cells that many methods developed for bulk-data failed to detect. In a multiple myeloma data, scFusion detected the known recurrent fusion IgH-WHSC1, which was associated with overexpression of the WHSC1 oncogene.

bioinformatics↗

Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution

Similar forms often evolve repeatedly in nature, raising longstanding questions about the underlying mechanisms. Here we use repeated evolution in sticklebacks to identify a large set of genomic loci that change recurrently during colonization of new freshwater habitats by marine fish. The same loci used repeatedly in extant populations also show rapid allele frequency changes when new freshwater populations are experimentally established from marine ancestors. Dramatic genotypic and phenotypic changes arise within 5-7 years, facilitated by standing genetic variation and linkage between adaptive regions. Both the speed and location of changes can be predicted using empirical observations of recurrence in natural populations or fundamental genomic features like allelic age, recombination rates, density of divergent loci, and overlap with mapped traits. A composite model trained on these stickleback features can also predict the location of key evolutionary loci in Darwins finches, suggesting similar features are important for evolution across diverse taxa.

evolutionary biology↗

Essential histone chaperones collaborate to regulate transcription and chromatin integrity

Histone chaperones are critical for controlling chromatin integrity during transcription, DNA replication, and DNA repair. We have discovered that the physical interaction between two essential histone chaperones, Spt6 and Spn1/Iws1, is required for transcriptional accuracy and nucleosome organization. To understand this requirement, we have isolated suppressors of an spt6 mutation that disrupts the Spt6-Spn1 interaction. Several suppressors are in a third essential histone chaperone, FACT, while another suppressor is in the transcription elongation factor Spt5/DSIF. The FACT suppressors weaken FACT-nucleosome interactions and bypass the requirement for Spn1, possibly by restoring a necessary balance between Spt6 and FACT on chromatin. In contrast, the Spt5 suppressor modulates Spt6 function in a Spn1-dependent manner. Despite these distinct mechanisms, both suppressors alleviate the nucleosome organization defects caused by disruption of the Spt6-Spn1 interaction. Taken together, we have uncovered a network in which histone chaperones and other elongation factors coordinate transcriptional integrity and chromatin structure.

genetics↗

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↗

The conserved elongation factor Spn1 is required for normal transcription, histone modifications, and splicing in Saccharomyces cerevisiae

Spn1/Iws1 is a conserved protein involved in transcription and chromatin dynamics, yet its general in vivo requirement for these functions is unknown. Using a Spn1 depletion system in S. cerevisiae, we demonstrate that Spn1 broadly influences several aspects of gene expression on a genome-wide scale. We show that Spn1 is globally required for normal mRNA levels and for normal splicing of ribosomal protein transcripts. Furthermore, Spn1 maintains the localization of H3K36 and H3K4 methylation across the genome and is required for normal histone levels at highly expressed genes. Finally, we show that the association of Spn1 with the transcription machinery is strongly dependent on its binding partner, Spt6, while the association of Spt6 and Set2 with transcribed regions is partially dependent on Spn1. Taken together, our results show that Spn1 affects multiple aspects of gene expression and provide additional evidence that it functions as a histone chaperone in vivo.

genomics↗

Otx2 and Oc1 directly regulate the transcriptional program of cone photoreceptor development

The vertebrate retina is a highly organized structure of approximately 110 cell types. Retinal progenitor cells (RPCs) produce these cell types in a temporal order that is highly conserved. While some RPCs produce many cell types, some terminally dividing RPCs produce restricted types of daughter cells, such as a cone photoreceptor and a horizontal cell (HC). Here, we compared the transcriptomes and chromatin profiles of such a restricted cone/HC RPC with those of other RPCs. We identified many cis-regulatory modules (CRMs) active in cone/HC RPCs and developing cones. We then showed that Otx2 and Oc1 directly regulate the activity of multiple CRMs genome-wide, including near genes important for cone development, such as Rxrg and Neurod1. In addition, we found that Otx2 regulates itself. These results suggest that Otx2 and Oc1 have a broader role than previously appreciated, and deepen our understanding of retinal development, which may benefit therapies for retinal diseases.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

HiTea: a computational pipeline to identify non-reference transposable element insertions in Hi-C data

Hi-C is a common technique for assessing three-dimensional chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline HiTea (Hi-C based Transposable element analyzer) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE insertion landscape. We employ the pipeline to identify TE insertions from human cell-line Hi-C samples. HiTea is available at https://github.com/parklab/HiTea and as a Docker image.

bioinformatics↗