Biology subjects

Lee, W.-P.

Publications and source records attributed to Lee, W.-P..

8 recordsLinked to original sources

bioRxiv2024

CNV-Profile Regression: A New Approach for Copy Number Variant Association Analysis in Whole Genome Sequencing Data

Copy number variants (CNVs) are DNA gains or losses involving >50 base pairs. Assessing CNV effects on disease risk requires consideration of several factors. First, there are no natural definitions for CNV loci. Second, CNV effects can depend on dosage and length. Third, CNV effects can be more accurately estimated when all CNV events in a genomic region are analyzed together to assess their joint effects. We propose a new framework for association analysis that directly models an individuals entire CNV profile within a genomic region. This framework represents an individuals CNVs using a CNV profile curve to capture variations in CNV length and dosage and to bypass the need to predefine CNV loci. CNV effects are estimated at each genome position, making the results comparable across different studies. To jointly estimate the effects of all CNVs, we use a Lasso penalty to select CNVs associated with the trait and integrate a weighted L2-fusion penalty to encourage similar effects of adjacent CNVs when supported by the data. Simulations show that the proposed model can more effectively identify causal CNVs while maintaining false positive rates comparable to baseline methods and yield more precise effect-size estimates across different settings. When applied to CNV derived from whole genome sequencing data of the Alzheimers Disease Sequencing Project, the proposed methods identify additional CNVs associated with Alzheimers Disease (AD). These identified CNVs overlap with several known AD-risk genes and are significantly enriched by biological processes related to neuron structures and functions crucial in AD development.

bioinformatics↗

bioRxiv2024

iTome Volumetric Serial Sectioning Apparatus for TEM

An automated ultra-microtome capable of sectioning thousands of ultrathin sections onto standard TEM slot grids was developed and used to section: a complete Drosophila melanogaster first-instar larva, three sections per grid, into 4,866 34-nm-thick sections with a cutting and pickup success rate of 99.74%; 30 microns of mouse cortex measuring roughly 400 um x 2000 um at 40 nm per slice; and a full adult Drosophila brain and ventral nerve column into 9,300 sections with a pickup success rate of 99.95%. The apparatus uses optical interferometers to monitor a reference distance between the cutting knife and multiple sample blocks. Cut sections are picked up from the knife-boat water surface while they are still anchored to the cutting knife. Blocks without embedded tissue are used to displace tissue-containing sections away from the knife edge so that the tissue regions end up in the grid slot instead of on the grid rim.

neuroscience↗

bioRxiv2023

Genetic, transcriptomic, histological, and biochemical analysis of progressive supranuclear palsy implicates glial activation and novel risk genes

Progressive supranuclear palsy (PSP) is a rare Parkinsonian disorder characterized by problems with movement, balance, cognition, and other symptoms. PSP differs from Alzheimers disease (AD) and other neurodegenerative diseases displaying abnormal forms of the microtubule-associated protein tau ("tauopathies") by the presence of pathology not only in neurons, but also in astrocytes and oligodendrocytes. Genetic contributors may mediate these differences, however much of PSP genetics remains unexplained. Here we conducted the largest genome-wide association study (GWAS) of PSP to date including 2,779 cases (2,595 neuropathologically-confirmed) and 5,584 controls and identified six independent PSP susceptibility loci with genome-wide significant (p < 5x10-8) associations including five known (MAPT, MOBP, STX6, RUNX2, SLCO1A2) and one novel locus (C4A). Integration with cell type-specific epigenomic annotations revealed a unique oligodendrocytic signature that distinguishes PSP from AD and Parkinsons disease. Candidate PSP risk gene prioritization using expression quantitative trait loci (eQTLs) identified oligodendrocyte-specific effects on gene expression in half of the genome-wide significant loci, as well as an association with elevated C4A expression in bulk brain tissue which may be driven by increased C4A copy number in PSP cases. Finally, histological studies demonstrated abnormal tau aggregates in oligodendrocytes that colocalize with C4 (complement) deposition. Integrating GWAS with functional studies including epigenomic and eQTL analyses, we identified potential causal roles for variation in MOBP, STX6, RUNX2, SLCO1A2, and C4A in the pathogenesis of PSP.

neuroscience↗

bioRxiv2022

Data Descriptor: Human whole exome genotype data for Alzheimer's Disease

Bigger sample size can help to identify new genetic variants contributing to an increased risk of developing Alzheimers disease. However, the heterogeneity of the whole-exome sequencing (WES) data generation methods presents a challenge to a joint analysis. Here we present a bioinformatics strategy for joint calling 20,504 WES samples collected across nine studies and sequenced using ten different capture kits in fourteen sequencing centers in the Alzheimers Disease Sequencing Project. gVCFs of samples were joint-called by the Genome Center for Alzheimers Disease into a single VCF, containing only positions within the union of capture kits. The VCF was then processed using specific strategies to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 15% are missense variants. 1.8% of the variants are with CADD>30. Our new strategy for processing these diversely generated WES samples has shown to generate high-quality data. The improved ability to combine data sequenced in different batches benefits the whole genomics research community. The WES data are accessible to the scientific community via https://dss.niagads.org/.

genetics↗

bioRxiv2022

A comparative study of structural variant calling strategies using the Alzheimer's Disease Sequencing Project's whole genome family data

BackgroundReliable detection and accurate genotyping of structural variants (SVs) and insertion/deletions (indels) from whole-genome sequence (WGS) data is a significant challenge. We present a protocol for variant calling, quality control, call merging, sensitivity analysis, in silico genotyping, and laboratory validation protocols for generating a high-quality deletion call set from whole genome sequences as part of the Alzheimers Disease Sequencing Project (ADSP). This dataset contains 578 individuals from 111 families. MethodsWe applied two complementary pipelines (Scalpel and Parliament) for SV/indel calling, break-point refinement, genotyping, and local reassembly to produce a high-quality annotated call set. Sensitivity was measured in sample replicates (N=9) for all callers using in silico variant spike-in for a wide range of event sizes. We focused on deletions because these events were more reliably called. To evaluate caller specificity, we developed a novel metric called the D-score that leverages deletion sharing frequencies within and outside of families to rank recurring deletions. Assessment of overall quality across size bins was measured with the kinship coefficient. Individual callers were evaluated for computational cost, performance, sensitivity, and specificity. Quality of calls were evaluated by Sanger sequencing of predicted loss-of-function (LOF) variants, variants near AD candidate genes, and randomly selected genome-wide deletions ranging from 2 to 17,000 bp. ResultsWe generated a high-quality deletion call set across a wide range of event sizes consisting of 152,301 deletions with an average of 263 per genome. A total of 114 of 146 predicted deletions (78.1%) were validated by Sanger sequencing. Scalpel was more accurate in calling deletions [≤]100 bp, whereas for Parliament, sensitivity was improved for deletions > 900 bp. We validated 83.0% (88/106) and 72.5% (37/51) of calls made by Scalpel and Parliament, respectively. Eleven deletions called by both Parliament and Scalpel in the 101-900 bin were tested and all were confirmed by Sanger sequencing. ConclusionsWe developed a flexible protocol to assess the quality of deletion detection across a wide range of sizes. We also generated a truth set of Sanger sequencing validated deletions with precise breakpoints covering a wide spectrum of sizes between 1 and 17,000 bp.

genetics↗

bioRxiv2020

Expectations and blind spots for structural variation detection from short-read alignment and long-read assembly

Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and emerging clinical diagnostic approaches utilize short-reads (srWGS), which present constraints for genome-wide discovery of structural variants (SVs). Alternative long-read single molecule technologies (lrWGS) offer significant advantages for genome assembly and SV detection, while these technologies are currently cost prohibitive for large-scale disease studies and clinical diagnostics (∼5-12X higher cost than comparable coverage srWGS). Moreover, only dozens of such genomes are currently publicly accessible by comparison to millions of srWGS genomes that have been commissioned for international initiatives. Given this ubiquitous reliance on srWGS in human genetics and genomics, we sought to characterize and quantify the properties of SVs accessible to both srWGS and lrWGS to establish benchmarks and expectations in ongoing medical and population genetic studies, and to project the added value of SVs uniquely accessible to each technology. In analyses of three trios with matched srWGS and lrWGS from the Human Genome Structural Variation Consortium (HGSVC), srWGS captured ∼11,000 SVs per genome using reference-based algorithms, while haplotype-resolved assembly from lrWGS identified ∼25,000 SVs per genome. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplications (SD) and simple repeats (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of the human reference, we observed extremely high concordance (93.8%) for deletions discovered by srWGS and lrWGS after error correction using the raw lrWGS reads. Conversely, lrWGS was superior for detection of insertions across all genomic contexts. Given that the non-SD/SR sequences span 90.3% of the GRCh38 reference, and encompass 95.9% of coding exons in currently annotated disease associated genes, improved sensitivity from lrWGS to discover novel and interpretable pathogenic deletions not already accessible to srWGS is likely to be incremental. However, these analyses highlight the added value of assembly-based lrWGS to create new catalogues of functional insertions and transposable elements, as well as disease associated repeat expansions in genomic regions previously recalcitrant to routine assessment.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genomics↗

bioRxiv2017

Fast and Accurate Genomic Analyses using Genome Graphs

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, which impairs read alignment and downstream analysis accuracy. Reference genome structures incorporating known genetic variation have been shown to improve the accuracy of genomic analyses, but have so far remained computationally prohibitive for routine large-scale use. Here we present a graph genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million indels. Our Graph Genome Pipeline requires 6.5 hours to process a 30x coverage WGS sample on a system with 36 CPU cores compared with 11 hours required by the GATK Best Practices pipeline. Using complementary benchmarking experiments based on real and simulated data, we show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, or about 20,000 additional variants being detected per sample, while variant calling specificity is unaffected. Structural variations (SVs) incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is a significant advance towards fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.

bioinformatics↗

bioRxiv2017

Multi-platform discovery of haplotype-resolved structural variation in human genomes

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, and strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three human parent-child trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs ([≥]50 bp) per human genome. We also discover 156 inversions per genome--most of which previously escaped detection. Fifty-eight of the inversions we discovered intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The method and the dataset serve as a gold standard for the scientific community and we make specific recommendations for maximizing structural variation sensitivity for future large-scale genome sequencing studies.

genomics↗