Biology subjects

Wenger, A. M.

Publications and source records attributed to Wenger, A. M..

At least 19 recordsLinked to original sources

bioRxiv2026

A computational model for quantifying instability of tandem repeats across the genome

Tandem repeats (TRs) exhibit high levels of somatic mosaicism, which is increasingly recognized as an important modifier of repeat expansion disorders. Long-read sequencing can capture full-length repeat alleles, yet robust frameworks for quantifying instability across TRs genome-wide are still needed. Here, we introduce a general-purpose model for quantifying TR instability in a given long-read sequencing dataset, without explicitly distinguishing biological mosaicism from technical noise, and which is broadly applicable to both simple and structurally complex loci. This model accurately characterizes allelic instability at each TR locus by representing the distribution of read-to-consensus deviations for each allele. Using HiFi sequencing data from 256 HPRC cell line samples, we fitted models for 617,007 TR loci, including known pathogenic repeats. We observe that instability levels are generally low, but vary substantially across individual TRs, and are driven more strongly by repeat composition than overall repeat length. Furthermore, we applied our method to targeted PureTarget long-read data from samples with known repeat expansions and identified significant mosaicism in the majority of expanded alleles. Our model offers a practical way to quantify instability of tandem repeats across the genome and to detect unusually unstable repeat alleles.

bioinformatics↗

bioRxiv2024

Revealing long-range heterogeneous organization of nucleoproteins with N6-methyladenine footprinting

A major challenge in epigenetics is uncovering the dynamic distribution of nucleosomes and other DNA-binding proteins, which plays a crucial role in regulating cellular functions. Established approaches such as ATAC-seq, ChIP-seq, and CUT&RUN provide valuable insights but are limited by the ensemble nature of their data, masking the cellular and molecular heterogeneity that is often functionally significant. Recently, long-read sequencing technologies, particularly Single Molecule, Real-Time (SMRT/PacBio) sequencing, have introduced transformative capabilities, such as N6-methyladenine (6mA) footprinting. This technique enables the detection of joint binding events and long-range chromatin organization on individual DNA molecules spanning multiple kilobases. Despite the potential of 6mA footprinting, existing analytical tools for 6mA detection in SMRT sequencing data suffer from significant limitations in both performance and applicability, especially with the latest sequencing platform. To address these gaps, we developed a novel 6mA-calling pipeline based on polymerase kinetics analysis. Our approach significantly outperforms current tools in terms of accuracy and computational efficiency, setting a new benchmark for 6mA detection. Utilizing our optimized experimental and computational framework, we extensively mapped nucleosome positioning and transcription factor occupancy at the single-molecule level, revealing critical features of the transcription-associated epigenetic landscape. Additionally, our work established high-resolution, long-range binding events in mitochondrial DNA, revealing simultaneous loading of two sets of replication machinery onto the displacement loop (D-loop). Our study highlights the potential of 6mA footprinting in capturing the coordinate binding of nucleoproteins and unraveling heterogeneous epigenetic states with unprecedented resolution.

bioinformatics↗

bioRxiv2024

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair for somatic benchmarks

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

genomics↗

bioRxiv2023

Synchronized long-read genome, methylome, epigenome, and transcriptome for resolving a Mendelian condition

Resolving the molecular basis of a Mendelian condition (MC) remains challenging owing to the diverse mechanisms by which genetic variants cause disease. To address this, we developed a synchronized long-read genome, methylome, epigenome, and transcriptome sequencing approach, which enables accurate single-nucleotide, insertion-deletion, and structural variant calling and diploid de novo genome assembly, and permits the simultaneous elucidation of haplotype-resolved CpG methylation, chromatin accessibility, and full-length transcript information in a single long-read sequencing run. Application of this approach to an Undiagnosed Diseases Network (UDN) participant with a chromosome X;13 balanced translocation of uncertain significance revealed that this translocation disrupted the functioning of four separate genes (NBEA, PDK3, MAB21L1, and RB1) previously associated with single-gene MCs. Notably, the function of each gene was disrupted via a distinct mechanism that required integration of the four omes to resolve. These included nonsense-mediated decay, fusion transcript formation, enhancer adoption, transcriptional readthrough silencing, and inappropriate X chromosome inactivation of autosomal genes. Overall, this highlights the utility of synchronized long-read multi-omic profiling for mechanistically resolving complex phenotypes.

genetics↗

bioRxiv2023

HiPhase: Jointly phasing small and structural variants from HiFi sequencing

BackgroundIn diploid organisms, phasing is the problem of assigning the heterozygous variants to one of two haplotypes. Reads from PacBio HiFi sequencing provide long, accurate observations that can be used as the basis for both calling and phasing variants. HiFi reads also excel at calling larger classes of variation such as structural variants. However, current phasing tools typically only phase small variants, leaving larger structural variants unphased. MethodsWe developed HiPhase, a tool that jointly phases SNVs, indels, and structural variants. The main benefits of HiPhase are 1) dual mode allele assignment for detecting structural variants, 2) a novel application of the A*-algorithm to phasing, and 3) logic allowing phase blocks to span breaks caused by alignment issues around reference gaps and homozygous deletions. ResultsIn our assessment, HiPhase produced an average phase block NG50 of 493 kb with 933 switchflip errors and fully phased 95.2% of genes, improving over the current state of the art. Additionally, HiPhase jointly phases SNVs, indels, and structural variants and includes innate multi-threading, statistics gathering, and concurrent phased alignment output generation. Availabilityhttps://github.com/PacificBiosciences/HiPhase

bioinformatics↗

bioRxiv2022

Sentieon DNAscope LongRead - A highly Accurate, Fast, and Efficient Pipeline for Germline Variant Calling from PacBio HiFi reads

PacBio(R) HiFi sequencing is the first technology to offer economical and highly accurate long-read sequencing, with average read lengths greater than 10kb and average base accuracy of 99.8%1. Here, we present DNAscope LongRead, an accurate and efficient pipeline for germline variant calling from PacBio(R) HiFi reads. DNAscope LongRead is a modification and extension of Sentieons DNAscope tool, a precisionFDA award-winning variant caller. DNAscope LongRead is computationally efficient, calling variants from 30x HiFi samples in under 4 hours on a 16-core machine (120 virtual core-hours) and highly accurate, with precision and recall on the most recent GIAB benchmark dataset exceeding 99.83% for HiFi samples sequenced at 30x coverage, and robust to changes in benchmark dataset and upstream library preparation and sequencing.

bioinformatics↗

bioRxiv2021

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

Pacific BioScience (PacBio) circular consensus sequencing (CCS) generates long (10-25 kb), accurate "HiFi" reads by combining serial observations of a DNA molecule into a consensus sequence. The standard approach to consensus generation uses a hidden Markov model (pbccs). Here, we introduce DeepConsensus, which uses a unique alignment-based loss to train a gap-aware transformer-encoder (GATE) for sequence correction. Compared to pbccs, DeepConsensus reduces read errors in the same dataset by 42%. This increases the yield of PacBio HiFi reads at Q20 by 9%, at Q30 by 27%, and at Q40 by 90%. With two SMRT Cells of HG003, reads from DeepConsensus improve hifiasm assembly contiguity (NG50 4.9Mb to 17.2Mb), increase gene completeness (94% to 97%), reduce false gene duplication rate (1.1% to 0.5%), improve assembly base accuracy (Q43 to Q45), and also reduce variant calling errors by 24%.

bioinformatics↗

bioRxiv2021

Towards a Comprehensive Variation Benchmark for Challenging Medically-Relevant Autosomal Genes

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

genomics↗

bioRxiv2020

De novo assembly of 64 haplotype-resolved human genomes of diverse ancestry and integrated analysis of structural variation

Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average contig N50: 26 Mbp) integrate all forms of genetic variation across even complex loci such as the major histocompatibility complex. We focus on 107,590 structural variants (SVs), of which 68% are inaccessible by short-read sequencing. We identify new SV hotspots (spanning megabases of gene-rich sequence), characterize 130 of the most active mobile element source elements, and find that 63% of all SVs arise by homology-mediated mechanisms--a twofold increase from previous studies. Our resource now enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1,525 expression quantitative trait loci (SV-eQTLs) as well as SV candidates for adaptive selection within the human population.

genetics↗

bioRxiv2020

A multi-platform reference for somatic structural variation detection

Accurate detection of somatic structural variation (SV) in cancer genomes remains a challenging problem. This is in part due to the lack of high-quality gold standard datasets that enable the benchmarking of experimental approaches and bioinformatic analysis pipelines for comprehensive somatic SV detection. Here, we approached this challenge by genome-wide somatic SV analysis of the paired melanoma and normal lymphoblastoid COLO829 cell lines using four different technologies: Illumina HiSeq, Oxford Nanopore, Pacific Biosciences and 10x Genomics. Based on the evidence from multiple technologies combined with extensive experimental validation, including Bionano optical mapping data and targeted detection of candidate breakpoint junctions, we compiled a comprehensive set of true somatic SVs, comprising all SV types. We demonstrate the utility of this resource by determining the SV detection performance of each technology as a function of tumor purity and sequence depth, highlighting the importance of assessing these parameters in cancer genomics projects and data analysis tool evaluation. The reference truth somatic SV dataset as well as the underlying raw multi-platform sequencing data are freely available and are an important resource for community somatic benchmarking efforts.

genomics↗

bioRxiv2020

Benchmarking challenging small variants with linked and long reads

Genome in a Bottle (GIAB) benchmarks have been widely used to help validate clinical sequencing pipelines and develop new variant calling and sequencing methods. Here, we use accurate linked reads and long reads to expand the prior benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are not readily accessible to short reads. Our new benchmark adds more than 300,000 SNVs, 50,000 indels, and 16 % new exonic variants, many in challenging, clinically relevant genes not previously covered (e.g., PMS2). For HG002, we include 92% of the autosomal GRCh38 assembly, while excluding problematic regions for benchmarking small variants (e.g., copy number variants and reference errors) that should not have been in the previous version, which included 85% of GRCh38. By including difficult-to-map regions, this benchmark identifies eight times more false negatives in a short read variant call set relative to our previous benchmark.We have demonstrated the utility of this benchmark to reliably identify false positives and false negatives across technologies in more challenging regions, which enables continued technology and bioinformatics development.

genomics↗

bioRxiv2019

AMELIE 2 speeds up Mendelian diagnosis by matching patient phenotype & genotype to primary literature

The diagnosis of Mendelian disorders requires labor-intensive literature research. Trained clinicians can spend hours looking for the right publication/s supporting a single gene that best explains a patients disease. AMELIE (Automatic Mendelian Literature Evaluation) greatly accelerates this process. AMELIE parses all 29 million PubMed abstracts, downloads and further parses hundreds of thousands of full text articles in search of information supporting the causality and associated phenotypes of any published genetic variant. AMELIE then prioritizes patient candidate variants for their likelihood of explaining any patients given set of phenotypes. Diagnosis of singleton patients (without relatives exomes) is the most time-consuming scenario. AMELIE ranked the causative gene at the very top in 2/3 of 215 diagnosed singleton Mendelian patients. Evaluating only the top 11 AMELIE scored genes of 127 (median) candidate genes per patient results in rapid diagnosis for 90+% of cases. AMELIE-based evaluation of all cases is 3-19x more efficient than hand-curated database-based approaches. We replicate these results on a cohort of clinical cases from Stanford Childrens Health and the Manton Center for Orphan Disease Research. An analysis web portal with our most recent update, programmatic interface and code will be available at AMELIE.stanford.edu. A pilot run of the web portal has already served many thousands of job submissions from dozens of countries.

genetics↗

bioRxiv2019

A robust benchmark for germline structural variant detection

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls [≥]50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

genomics↗

bioRxiv2019

SVCurator: A Crowdsourcing app to visualize evidence of structural variants for the human genome

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is yet to be defined. In this study, we manually curated 1235 SVs which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app - SVCurator - to help curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy.\n\nSVCurator is a Python Flask-based web platform that displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002], We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. The crowdsourced results were highly concordant with 37 out of the 61 curators having at least 78% concordance with a set of expert curators, where there was 93% concordance amongst expert curators. This produced high confidence labels for 935 events. When compared to the heuristic-based draft benchmark SV callset from GIAB, the SVCurator crowdsourced labels were 94.5% concordant with the benchmark set. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.

genomics↗

bioRxiv2019

High-coverage, long-read sequencing of Han Chinese trio reference samples.

Single-molecule long-read sequencing datasets were generated for a son-father-mother trio of Han Chinese descent that is part of the Genome In a Bottle (GIAB) consortium portfolio. The dataset was generated using the Pacific Biosciences Sequel System. The son and each parent were sequenced to an average coverage of 60 and 30, respectively, with N50 subread lengths between 16 and 18 kb. Raw reads and reads aligned to both the GRCh37 and GRCh38 are available at the NCBI GIAB ftp site (ftp://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/ChineseTrio/) and the raw read data is archived in NCBI SRA (SRX4739017, SRX4739121, and SRX4739122). This dataset is available for anyone to develop and evaluate long-read bioinformatics methods.

genomics↗

bioRxiv2019

Highly-accurate long-read sequencing improves variant detection and assembly of a human genome

The major DNA sequencing technologies in use today produce either highly-accurate short reads or noisy long reads. We developed a protocol based on single-molecule, circular consensus sequencing (CCS) to generate highly-accurate (99.8%) long reads averaging 13.5 kb and applied it to sequence the well-characterized human HG002/NA24385. We optimized existing tools to comprehensively detect variants, achieving precision and recall above 99.91% for SNVs, 95.98% for indels, and 95.99% for structural variants. We estimate that 2,434 discordances are correctable mistakes in the high-quality Genome in a Bottle benchmark. Nearly all (99.64%) variants are phased into haplotypes, which further improves variant detection. De novo assembly produces a highly contiguous and accurate genome with contig N50 above 15 Mb and concordance of 99.998%. CCS reads match short reads for small variant detection, while enabling structural variant detection and de novo assembly at similar contiguity and markedly higher concordance than noisy long reads.

genomics↗

bioRxiv2018

Phrank measures phenotype sets similarity to greatly improve Mendelian diagnostic disease prioritization

PurposeExome sequencing and diagnosis is beginning to spread across the medical establishment. The most time-consuming part of genome based diagnosis is the manual step of matching the potentially long list of patient candidate genes to patient phenotypes to identify the causative disease.\n\nMethodsWe introduce Phrank (for phenotype ranking), an information-theory inspired method that utilizes a Bayesian Network to prioritize candidate diseases or genes, as a stand-alone module that can be run with any underlying knowledgebase and any variant filtering scheme.\n\nResultsPhrank outperforms existing methods at ranking the causative disease or gene when applied to 169 real patient exomes with Mendelian diagnoses. Phranks greatest improvement is in disease space, where across all 169 patients it ranks only 3 diseases on average ahead of the true diagnosis, whereas Phenomizer ranks 32 diseases ahead of the causal one.\n\nConclusionUsing Phrank to rank all patient candidate genes or diseases, as they start working through a new case, will save the busy clinician much time in deriving a genetic diagnosis.

genomics↗

bioRxiv2017

Independent erosion of conserved transcription factor binding sites points to shared hindlimb, vision, and scrotum loss in different mammals

Genetic variation in cis-regulatory elements is thought to be a major driving force in morphological and physiological change. However, identifying transcription factor binding events which code for complex traits remains a challenge, motivating novel means of detecting putatively important binding events. Using a curated set of 1,154 high-quality transcription factor motifs, we demonstrate that independently eroded binding sites are enriched for independently lost traits in three distinct pairs of placental mammals. We show that these independently eroded events pinpoint the loss of hindlimbs in dolphin and manatee, degradation of vision in naked mole-rat and star-nosed mole, and the loss of scrotum in white rhinoceros and Weddell seal. Our study exhibits a novel methodology to detect cis-regulatory mutations which help explain a portion of the molecular mechanism underlying complex trait formation and loss.\n\nAuthor SummaryEvolution has produced an astounding variety of species with incredibly diverse phenotypes. A central question in evolutionary developmental biology is how (and which) DNA evolves to encode all of these different traits. A prevailing hypothesis is that changes in regulatory DNA, short stretches of DNA which control the expression of protein-coding genes, drive important differences in trait formation between species. The basic building block of regulatory DNA is thought to be transcription factor binding sites, shortl genomic sequences which attract proteins whose central role is to control the rate of transcription. In this study, we asked whether the independent erosion of otherwise highly conserved transcription factor binding sites points to a trait shared between species which have undergone similar adaptations. We show that our method is able to point to the loss of hindlimbs in dolphin and manatee, poor vision in naked mole-rat and star-nosed mole, and loss of scrotum in Weddell seal and white rhinoceros. Overall, our study exhibits a means of detecting evolutionarily important genomic regions which help explain a portion of complex trait loss and retention.

evolutionary biology↗