Publications by authors named "Ginger Metcalf"

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study).

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Accurately genotyping structural variant (SV) alleles is crucial to genomics research. We present a novel method (kanpig) for genotyping SVs that leverages variant graphs and k-mer vectors to rapidly generate accurate SV genotypes. We benchmark kanpig against the latest SV benchmarks and show single-sample genotyping concordance of 82.

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The abundance of Lp(a) protein holds significant implications for the risk of cardiovascular disease (CVD), which is directly impacted by the copy number (CN) of KIV-2, a 5.5 kbp sub-region. KIV-2 is highly polymorphic in the population and accurate analysis is challenging.

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Article Synopsis
  • - Respiratory syncytial virus (RSV) and human noroviruses (HuNoV) are major pathogens that cause respiratory and gastrointestinal infections respectively, making it essential to generate full-length genome sequences for studying their diversity and tracking variants.
  • - The study developed oligonucleotide probe sets from numerous viral isolate sequences, which were utilized in a capture enrichment sequencing workflow to analyze samples, significantly improving the quality of viral genome recovery.
  • - The results showed that over 99% of RSV genomes and over 96% of HuNoV genomes were complete post-capture, demonstrating the effectiveness of this method for comprehensive genome sequencing and monitoring emerging variants.
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  • Viral infections involve diverse viral genomes, and high-throughput sequencing can help study these populations, though few examples exist.
  • This study uses advanced sequencing on nasal wash samples from hematopoietic cell transplant recipients with RSV to analyze genomic and transcriptomic data separately.
  • Findings indicate low genetic variation in RSV infections, but reveal differences between genomes and transcripts in genetic diversity, variation hotspots, and alternative amino acid encoding, highlighting the need for separate analyses in viral research.
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Background: Human noroviruses are a leading cause of acute and sporadic gastroenteritis worldwide. The evolution of human noroviruses in immunocompromised persons has been evaluated in many studies. Much less is known about the evolutionary dynamics of human norovirus in healthy adults.

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Long-read sequencing has recently transformed metagenomics, enhancing strain-level pathogen characterization, enabling accurate and complete metagenome-assembled genomes, and improving microbiome taxonomic classification and profiling. These advancements are not only due to improvements in sequencing accuracy, but also happening across rapidly changing analysis methods. In this Review, we explore long-read sequencing's profound impact on metagenomics, focusing on computational pipelines for genome assembly, taxonomic characterization and variant detection, to summarize recent advancements in the field and provide an overview of available analytical methods to fully leverage long reads.

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Comprehending the mechanism behind human diseases with an established heritable component represents the forefront of personalized medicine. Nevertheless, numerous medically important genes are inaccurately represented in short-read sequencing data analysis due to their complexity and repetitiveness or the so-called 'dark regions' of the human genome. The advent of PacBio as a long-read platform has provided new insights, yet HiFi whole-genome sequencing (WGS) cost remains frequently prohibitive.

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Article Synopsis
  • RSV infection in immunocompromised individuals, particularly hematopoietic stem cell transplant (HCT) patients, can lead to severe illness and death, highlighting the need for understanding how the immune environment affects viral behavior.
  • The study used whole genome sequencing of RSV in HCT patients with varying clearance times of the virus, revealing genetic variation primarily in the G and F genes, with notable mutations linked to longer viral shedding and possible immune evasion.
  • Findings emphasize the importance of monitoring RSV genetic changes in these patients, as mutations could affect future treatments and vaccine effectiveness.
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We describe the epidemiology and clinical characteristics of 29 patients with cancer and diarrhea in whom Enteroaggregative (EAEC) was initially identified by GI BioFire panel multiplex. strains were successfully isolated from fecal cultures in 14 of 29 patients. Six of the 14 strains were identified as EAEC and 8 belonged to other diverse groups of unknown pathogenesis.

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Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2.

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Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2.

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Background: Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies.

Methods: The 3793 cases and 7834 controls (11.

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Article Synopsis
  • Researchers compiled a comprehensive catalog of 355,667 structural variants (SVs) from DNA data, with over half being novel, to better understand the relationship between SVs and diseases.
  • The study involved rigorous methods to ensure high-quality variant identification, showing over 90% accuracy compared to previous genetic assemblies.
  • This catalog reveals significant connections between SVs and various health traits, identifying 690 specific regions that may influence medically relevant genes, providing a crucial resource for disease research.
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Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.

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Infections by non-segmented negative-strand RNA viruses (NNSV) are widely thought to entail gradient gene expression from the well-established existence of a single promoter at the 3' end of the viral genome and the assumption of constant transcriptional attenuation between genes. But multiple recent studies show viral mRNA levels in infections by respiratory syncytial virus (RSV), a major human pathogen and member of NNSV, that are inconsistent with a simple gradient. Here we integrate known and newly predicted phenomena into a biophysically reasonable model of NNSV transcription.

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Background: The growing volume and heterogeneity of next-generation sequencing (NGS) data complicate the further optimization of identifying DNA variation, especially considering that curated high-confidence variant call sets frequently used to validate these methods are generally developed from the analysis of comparatively small and homogeneous sample sets.

Findings: We have developed xAtlas, a single-sample variant caller for single-nucleotide variants (SNVs) and small insertions and deletions (indels) in NGS data. xAtlas features rapid runtimes, support for CRAM and gVCF file formats, and retraining capabilities.

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The fundamental challenge of multi-sample structural variant (SV) analysis such as merging and benchmarking is identifying when two SVs are the same. Common approaches for comparing SVs were developed alongside technologies which produce ill-defined boundaries. As SV detection becomes more exact, algorithms to preserve this refined signal are needed.

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Article Synopsis
  • Genome-wide association studies have found thousands of genetic variations affecting blood traits, but the impact of structural variants on these traits was previously unclear.
  • A study using whole genome sequencing from a diverse group of nearly 50,700 participants identified 21 significant structural variants linked to red and white blood cell traits, with most findings confirmed in other datasets.
  • Experimental evidence showed that a specific deletion linked to lower monocyte counts disrupts an enhancer for the S1PR3 gene, leading to reduced S1PR3 expression.
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  • * The study involved two stages with over 15,000 participants from diverse backgrounds and used advanced statistical models to analyze genetic variants in relation to DKD.
  • * Researchers discovered four significant genetic loci linked to DKD, particularly noting a rare variant in the DIS3L2 gene that greatly increases the risk of developing the disease, providing new insights into DKD's molecular mechanisms.
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Background: Routine genome-wide screening for cardiovascular disease risk may inform clinical decision-making. However, little is known about whether clinicians and patients would find such testing useful or acceptable within the context of a genomics-enabled learning health system.

Methods: We conducted surveys with patients and their clinicians who were participating in the HeartCare Study, a precision cardiology care project that returned results from a next-generation sequencing panel of 158 genes associated with cardiovascular disease risk.

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Plasma levels of fibrinogen, coagulation factors VII and VIII and von Willebrand factor (vWF) are four intermediate phenotypes that are heritable and have been associated with the risk of clinical thrombotic events. To identify rare and low-frequency variants associated with these hemostatic factors, we conducted whole-exome sequencing in 10 860 individuals of European ancestry (EA) and 3529 African Americans (AAs) from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and the National Heart, Lung and Blood Institute's Exome Sequencing Project. Gene-based tests demonstrated significant associations with rare variation (minor allele frequency < 5%) in fibrinogen gamma chain (FGG) (with fibrinogen, P = 9.

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Current publicly available tools that allow rapid exploration of linkage disequilibrium (LD) between markers (e.g., HaploReg and LDlink) are based on whole-genome sequence (WGS) data from 2,504 individuals in the 1000 Genomes Project.

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While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV] and its ratio to forced vital capacity [FEV/FVC]) in the UK Biobank.

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