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Biology subjects

Germer, S.

Publications and source records attributed to Germer, S..

15 recordsLinked to original sources

Wavelet Based Whole Genome Doubling Aware Single Cell Copy Number Calling

Advances in single cell whole genome sequencing enable profiling of the copy number state of thousands of cells with minimal sequencing bias across the genome. The Direct Library Preparation + technique is an whole genome amplification-free single cell whole genome sequencing method that achieves high throughput by fragmenting each cells genome and ligating sequencing adapters using a modified Tn5 transposase, and sequencing to less than 0.1x coverage. Despite recent advances in experimental approaches, data analysis of single cell whole genome sequencing lags behind and the existing methods are not optimized for the analysis of frozen samples with variable DNA preservation. Furthermore, existing tools predominantly rely on read depth ratio in predefined genomic bins to call copy number, making whole genome duplication unidentifiable. To address this, we introduce Songbird, a single cell whole genome sequencing copy number caller that is whole genome duplication sensitive, and outperforms existing tools both in breakpoints identification and true copy number detection. We demonstrate that Songbird is robust down to extremely low coverage, adaptable to a variety of genome versions (hg19, hg38, hs.1), and is extensible to other single cell whole genome sequencing methods that rely on Tn5 tagmentation to fragment the genome.

bioinformatics↗

Benchmarking of duplex sequencing approaches to reveal somatic mutation landscapes

Detecting somatic mutations in normal tissues is challenging due to sequencing errors and the low allele fractions of post-zygotic variants. Duplex sequencing greatly reduces errors and can detect mutations at any allele fraction, but systematic, cross-platform comparisons are lacking. We present a comprehensive benchmarking of six duplex sequencing technologies used by the SMaHT Network: CODEC, CompDuplex-seq, HiDEF-seq, NanoSeq, ppmSeq, and VISTA-seq. We evaluated their performance using cord blood DNA, a tumor-normal cell line mixture, and homogenates from six human tissues. Each method shows distinct profiles in genomic footprint, sensitivity, and cost. Despite differences in library construction and sequencing platforms, estimates of mutation rates and mutational signatures are highly concordant. Integration with ultra-deep whole-genome sequencing shows that duplex approaches sensitively capture mutations and signatures beyond embryonic or clonally expanded variants. These results provide a foundation for selecting duplex methods and interpreting their data, enabling scalable single-molecule analyses of somatic mutation landscapes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/692823v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@123b221org.highwire.dtl.DTLVardef@83ba0aorg.highwire.dtl.DTLVardef@2b0ab0org.highwire.dtl.DTLVardef@1cae35e_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

A comprehensive view of somatic mosaicism by single-cell DNA analysis

Single-cell DNA sequencing offers a powerful means of studying somatic mosaicism but requires careful analysis to mitigate DNA amplification-related artifacts. We performed primary template-directed amplification (PTA) and sequencing of 102 nuclei from postmortem lung and colon tissues of a 74-year-old male. Single-cell mutation burdens and spectra were validated by duplex sequencing and revealed heterogeneity across organs and cells, including signatures of APOBEC activity and tobacco exposure. Cells from both tissues exhibited chromosomal aneuploidies, loss of chromosome Y, and chromosomal rearrangements including rearrangements of the T-cell receptor loci indicative of T-cells. Shared embryonic mutations between cells enabled reconstruction of cellular ancestries from the zygote, which were validated by bulk sequencing. Collectively, we demonstrate a comprehensive approach for single-cell genomics that yields an expansive view of diverse somatic mutation types from development through aging across diverse tissues--insights that are obscured in bulk sequencing and only partially captured by other single-cell methods.

genomics↗

Comprehensive benchmarking of somatic single-nucleotide variant and indel detection at ultra-low allele fractions using short- and long-read data

Mosaic mutations in normal tissues occur at low variant allele fractions (VAFs), complicating detection. To benchmark strategies, the SMaHT Network created a cell-line mixture (1:49) and produced ultra-deep whole-genome sequencing using short and long reads (five centers, 180-500x each). We assembled a reference of 44,008 mosaic SNVs and 2,059 Indels, cross-validation between platforms to expose limits of short-read analysis. We also partitioned the genome by mappability to examine the impact of genomic context, added a negative reference set, and accounted for culture-derived mutations. When seven institutions applied eleven algorithms to mixture data, call sets were largely discordant across tools and replicates, partly reflecting stochastic presence of low-VAF mutations in biological replicants. For >2% VAF SNVs, sensitivity and precision approached [~]80% at [≥]300x, with little gain from additional sequencing. This work provides a comprehensive framework for reliable detection of low-VAF mutations in non-cancer tissues and a valuable resource for the community.

bioinformatics↗

Paired plus-minus sequencing is an ultra-high throughput and accurate method for dual strand sequencing of DNA molecules

Distinguishing real biological variation in the form of single-nucleotide variants (SNVs) from errors is a major challenge for genome sequencing technologies. This is particularly true in settings where SNVs are at low frequency such as cancer detection through liquid biopsy, or human somatic mosaicism. State-of-the-art molecular denoising approaches for DNA sequencing rely on duplex sequencing, where both strands of a single DNA molecule are sequenced to discern true variants from errors arising from single stranded DNA damage. However, such duplex approaches typically require massive over-sequencing to overcome low capture rates of duplex molecules. To address these challenges, we introduce paired plus-minus sequencing (ppmSeq) technology, in which both DNA strands are partitioned and clonally amplified on sequencing beads through emulsion PCR. In this reaction, both strands of a double-stranded DNA molecule contribute to a single sequencing read, allowing for a duplex yield that scales linearly with sequencing coverage across a wide range of inputs (1.8-98 ng). We benchmarked ppmSeq against current duplex sequencing technologies, demonstrating superior duplex recovery with ppmSeq, with a rate of 44%{+/-}5.5% (compared to [~]5-11% for leading duplex technologies). Using both genomic as well as cell-free DNA, we established error rates for ppmSeq, which had residual SNV detection error rates as low as 7.98x10-8 for gDNA (using an end-repair protocol with dideoxy nucleotides) and 3.5x10-7{+/-}7.5x10-8 for cell-free DNA. To test the capabilities of ppmSeq for error-corrected whole-genome sequencing (WGS) for clinical application, we assessed circulating tumor DNA (ctDNA) detection for disease monitoring in cancer patients. We demonstrated that ppmSeq enables powerful tumor-informed ctDNA detection at concentrations of 10-4 across most cancers, parts per million sensitivity in cancers with high mutation burden, and further increased sensitivity with higher sequencing depth. We then leveraged genome-wide trinucleotide mutation patterns characteristic of urothelial (APOBEC3-related and platinum exposure-related signatures) and lung (tobacco-exposure-related signatures) cancers to perform tumor-naive ctDNA detection, showing that ppmSeq can identify a disease-specific signal in plasma cell-free DNA without a matched tumor, and that this signal correlates with imaging-based disease metrics. Altogether, ppmSeq provides an error-corrected, cost-efficient and scalable approach for high-fidelity WGS that can be harnessed for challenging clinical applications and emerging frontiers in human somatic genetics where high accuracy is required for mutation identification.

genomics↗

A General Method to Accurately Count Molecular Complexes and Determine the Degree of Labelling in Cells Using Protein Tags

Determining the label to target ratio, also known as degree of labelling (DOL), is crucial for quantitative fluorescence microscopy and a high DOL with minimal unspecific labelling is beneficial for fluorescence microscopy in general. Yet, robust, versatile, and easy-to-use tools for measuring cell-specific labelling efficiencies are not available. This study presents a novel DOL determination technique named Protein-tag DOL (ProDOL), which enables fast DOL measurements and optimisation of protein-tag labelling. With ProDOL various factors affecting labelling efficiency, including substrate type, incubation time, and concentration, as well as sample fixation and cell type can be easily assessed. We applied ProDOL to investigate how HIV-1 pathogenesis factor Nef modulates CD4 T cell activation measuring total and activated copy numbers of the adaptor protein SLP-76 in signalling microclusters. ProDOL proved to be a versatile and robust tool for labelling calibration, enabling determination of labelling efficiencies, optimisation of strategies, and quantification of protein stoichiometry.

cell biology↗

Genetic control of mRNA splicing as a potential mechanism for incomplete penetrance of rare coding variants

Exonic variants present some of the strongest links between genotype and phenotype. However, these variants can have significant inter-individual pathogenicity differences, known as variable penetrance. In this study, we propose a model where genetically controlled mRNA splicing modulates the pathogenicity of exonic variants. By first cataloging exonic inclusion from RNA-seq data in GTEx v8, we find that pathogenic alleles are depleted on highly included exons. Using a large-scale phased WGS data from the TOPMed consortium, we observe that this effect may be driven by common splice-regulatory genetic variants, and that natural selection acts on haplotype configurations that reduce the transcript inclusion of putatively pathogenic variants, especially when limiting to haploinsufficient genes. Finally, we test if this effect may be relevant for autism risk using families from the Simons Simplex Collection, but find that splicing of pathogenic alleles has a penetrance reducing effect here as well. Overall, our results indicate that common splice-regulatory variants may play a role in reducing the damaging effects of rare exonic variants.

genetics↗

Whole genome error-corrected sequencing for sensitive circulating tumor DNA cancer monitoring

Circulating cell-free DNA (ccfDNA) sequencing for low-burden cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), the abundance of genomic material within a plasma sample, and pre-analytical error rates due to library preparation, and sequencing errors. Sequencing costs have historically favored the development of deep targeted sequencing approaches for overcoming sparsity in ctDNA detection, but these techniques are limited by the abundance of ccfDNA in samples, which imposes a ceiling on the maximal depth of coverage in targeted panels. Whole genome sequencing (WGS) is an orthogonal approach to ctDNA detection that can overcome the low abundance of ccfDNA by supplanting sequencing depth with breadth, integrating signal across the entire tumor mutation landscape. However, the higher cost of WGS limits the practical depth of coverage and hinders broad adoption. Lower sequencing costs may thus allow for enhanced ctDNA cancer monitoring via WGS. We therefore applied emerging lower-cost WGS (Ultima Genomics, 1USD/Gb) to plasma samples at [~]120x coverage. Copy number and single nucleotide variation profiles were comparable between matched Ultima and Illumina datasets, and the deeper WGS coverage enabled ctDNA detection at the parts per million range. We further harnessed these lower sequencing costs to implement duplex error-corrected sequencing at the scale of the entire genome, demonstrating a [~]1,500x decrease in errors in the plasma of patient-derived xenograft mouse models, and error rates of [~]10-7 in patient plasma samples. We leveraged this highly de-noised plasma WGS to undertake cancer monitoring in the more challenging context of resectable melanoma without matched tumor sequencing. In this context, duplex-corrected WGS allowed us to harness known mutational signature patterns for disease monitoring without matched tumors, paving the way for de novo cancer monitoring.

genomics↗

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

microbiology↗

High coverage whole genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole genome sequencing (WGS) data consented for public distribution of raw sequence data without access or use restrictions. The final release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low coverage WGS. Here, we present a new, high coverage 3,202-sample WGS 1kGP resource, sequenced to a targeted depth of 30X using the Illumina NovaSeq 6000 system, which now includes 602 complete trios. We performed SNV/INDEL calling against the GRCh38 reference using GATKs HaplotypeCaller, and generated a comprehensive set of SVs by integrating multiple analytic methods through a sophisticated machine learning model. We make all the data generated as part of this project publicly available and we envision it to become the new de facto public resource for the worldwide genomics and genetics community.

genomics↗

Type 2 and interferon inflammation strongly regulate SARS-CoV-2 related gene expression in the airway epithelium

Coronavirus disease 2019 (COVID-19) outcomes vary from asymptomatic infection to death. This disparity may reflect different airway levels of the SARS-CoV-2 receptor, ACE2, and the spike protein activator, TMPRSS2. Here we explore the role of genetics and co-expression networks in regulating these genes in the airway, through the analysis of nasal airway transcriptome data from 695 children. We identify expression quantitative trait loci (eQTL) for both ACE2 and TMPRSS2, that vary in frequency across world populations. Importantly, we find TMPRSS2 is part of a mucus secretory network, highly upregulated by T2 inflammation through the action of interleukin-13, and that interferon response to respiratory viruses highly upregulates ACE2 expression. Finally, we define airway responses to coronavirus infections in children, finding that these infections upregulate IL6 while also stimulating a more pronounced cytotoxic immune response relative to other respiratory viruses. Our results reveal mechanisms likely influencing SARS-CoV-2 infectivity and COVID-19 clinical outcomes.

genomics↗

Deep sequencing of 3 cancer cell lines on 2 sequencing platforms

To test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we sequenced 3 common cancer cell lines along with their matched normal cell lines to great sequencing depths (up to 278X coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. Somatic calling was generally consistent between the two platforms despite minor differences at the read level. We designed and implemented a novel pipeline for the analysis of tumor-normal samples, using multiple variant callers. We show that coupled with a high-confidence filtering strategy, it improves the accuracy of somatic calls. We also demonstrate the utility of the dataset by creating an artificial purity ladder to evaluate the somatic pipeline and benchmark methods for estimating purity and ploidy from tumor-normal pairs. The data and results of the pipeline are made accessible to the cancer genomics community.

genomics↗

YES1 amplification: a mechanism of acquired resistance to EGFR inhibitors identified by transposon mutagenesis and clinical genomics

In approximately 30% of patients with EGFR-mutant lung adenocarcinomas whose disease progresses on EGFR inhibitors, the basis for acquired resistance remains unclear. We have integrated transposon mutagenesis screening in an EGFR-mutant cell line and clinical genomic sequencing in cases of acquired resistance to identify novel mechanisms of resistance to EGFR inhibitors. The most prominent candidate genes identified by insertions in or near the genes during the screen were MET, a gene whose amplification is known to mediate resistance to EGFR inhibitors, and the gene encoding the Src family kinase YES1. Cell clones with transposon insertions that activated expression of YES1 exhibited resistance to all three generations of EGFR inhibitors and sensitivity to pharmacologic and siRNA-mediated inhibition of YES1. Analysis of clinical genomic sequencing data from cases of acquired resistance to EGFR inhibitors revealed amplification of YES1 in 5 cases, 4 of which lacked any other known mechanisms of resistance. Pre-inhibitor samples, available for 2 of the 5 patients, lacked YES1 amplification. None of 136 post-inhibitor samples had detectable amplification of other Src family kinases (SRC, FYN). YES1 amplification was also found in 2 of 17 samples from ALK fusion-positive lung cancer patients who had progressed on ALK TKIs. Taken together, our findings identify acquired amplification of YES1 as a novel, recurrent, and targetable mechanism of resistance to EGFR inhibition in EGFR-mutant lung cancers, and demonstrate the utility of transposon mutagenesis in discovering clinically relevant mechanisms of drug resistance.\n\nSIGNIFICANCEDespite high response rates to treatment with small molecule inhibitors of EGFR tyrosine kinase activity, patients with EGFR-mutant lung adenocarcinomas eventually develop resistance to these drugs. In many cases, the basis of acquired resistance remains unclear. We have used a transposon mutagenesis screen in an EGFR-mutant cell line and clinical genomic sequencing in cases of acquired resistance to identify amplification of YES1 as a novel and targetable mechanism of resistance to EGFR inhibitors in EGFR-mutant lung cancers.

cancer biology↗

WHOLE GENOME BISULPHITE SEQUENCING USING THE ILLUMINA HISEQ X SYSTEM

The Illumina HiSeq X platform has helped to reduce the cost of whole genome sequencing substantially, but its application for bisulphite sequencing is not straightforward. We describe the optimization of a library preparation and sequencing approach that maximizes the yield and quality of sequencing, and the elimination of a previously unrecognized artefact affecting several percent of bisulphite sequencing reads.

genomics↗

Whole Genome Sequencing of Pharmacogenetic Drug Response in Racially and Ethnically Diverse Children with Asthma

Asthma is the most common chronic disease of children, with significant racial/ethnic differences in prevalence, morbidity, mortality and therapeutic response. Albuterol, a bronchodilator medication, is the first-line therapy for asthma treatment worldwide. We performed the largest whole genome sequencing (WGS) pharmacogenetics study to date using data from 1,441 minority children with asthma who had extremely high or low bronchodilator drug response (BDR). We identified population-specific and shared pharmacogenetic variants associated with BDR, including genome-wide significant (p < 3.53 x 10-7) and suggestive (p < 7.06 x 10-6) loci near genes previously associated with lung capacity (DNAH5), immunity (NFKB1 and PLCB1), and {beta}-adrenergic signaling pathways (ADAMTS3 and COX18). Functional analyses centered on NFKB1 revealed potential regulatory function of our BDR-associated SNPs in bronchial smooth muscle cells. Specifically, these variants are in linkage disequilibrium with SNPs in a functionally active enhancer, and are also expression quantitative trait loci (eQTL) for a neighboring gene, SLC39A8. Given the lack of other asthma study populations with WGS data on minority children, replication of our rare variant associations is infeasible. We attempted to replicate our common variant findings in five independent studies with GWAS data. The age-specific associations previously found in asthma and asthma-related traits suggest that the over-representation of adults in our replication populations may have contributed to our lack of statistical replication, despite the functional relevance of the NFKB1 variants demonstrated by our functional assays. Our study expands the understanding of pharmacogenetic analyses in racially/ethnically diverse populations and advances the foundation for precision medicine in at-risk and understudied minority populations.\n\nAUTHOR SUMMARYAsthma is the most common chronic disease among children. Albuterol, a bronchodilator medication, is the first-line therapy for asthma treatment worldwide. In the U.S., asthma prevalence is the highest among Puerto Ricans, intermediate among African Americans and lowest in Whites and Mexicans. Asthma disparities extend to mortality, which is four- to five-fold higher in Puerto Ricans and African Americans compared to Mexicans [1]. Puerto Ricans and African Americans, the populations with the highest asthma prevalence and death rate, also have the lowest albuterol bronchodilator drug response (BDR). We conducted the largest pharmacogenetic study using whole genome sequencing data from 1,441 minority children with asthma who had extremely high or low albuterol bronchodilator drug response. We identified population-specific and shared pharmacogenetic variants associated with BDR. Our findings help inform the direction of future development of asthma medications and our study advances the foundation of precision medicine for at-risk, yet understudied, racially/ethnically diverse populations.

genetics↗