Advances in whole-genome sequencing (WGS) promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from WGS data presents a substantial number of challenges and a plethora of SV detection methods have been developed. Currently, evidence that investigators can use to select appropriate SV detection tools is lacking. In this article, we have evaluated the performance of SV detection tools on mouse and human WGS data using a comprehensive polymerase chain reaction-confirmed gold standard set of SVs and the genome-in-a-bottle variant set, respectively. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of the SV detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance as the SV detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low- and ultralow-pass sequencing data as well as for different deletion length categories.

The emergence and mutation of pathogenic viruses have been occurring at an unprecedented rate in recent decades. The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has developed into a global public health crisis due to extensive viral transmission. In situ RNA mapping has revealed angiotensin-converting enzyme 2 (ACE2) expression to be highest in the nose and lower in the lung, pointing to nasal susceptibility as a predominant route for infection and the cause of subsequent pulmonary effects. By blocking viral attachment and entry at the nasal airway using a cyclodextrin-based formulation, a preventative therapy can be developed to reduce viral infection at the site of entry. Here, we assess the safety and antiviral efficacy of cyclodextrin-based formulations. From these studies, hydroxypropyl beta-cyclodextrin (HPBCD) and hydroxypropyl gamma-cyclodextrin (HPGCD) were then further evaluated for antiviral effects using SARS-CoV-2 pseudotypes. Efficacy findings were confirmed with SARS-CoV-2 Delta variant infection of Calu-3 cells and using a K18-hACE2 murine model. Intranasal pre-treatment with HPBCD-based formulations reduced viral load and inflammatory signaling in the lung. In vitro efficacy studies were further conducted using lentiviruses, murine hepatitis virus (MHV), and influenza A virus subtype H1N1. These findings suggest HPBCD may be used as an agnostic barrier against transmissible pathogens, including but not limited to SARS-CoV-2.

Retinitis pigmentosa (RP) is a retinal degenerative disease associated with a diversity of genetic mutations. In a natural progression study (NPS) evaluating the molecular changes in Royal College of Surgeons (RCS) rats using lipidomic profiling, RNA sequencing, and gene expression analyses, changes associated with retinal degeneration from p21 to p60 were evaluated, where reductions in retinal ALOX15 expression corresponded with disease progression. This important enzyme catalyzes the formation of specialized pro-resolving mediators (SPMs) such as lipoxins (LXs), resolvins (RvDs), and docosapentaenoic acid resolvins (DPA RvDs), where reduced ALOX15 corresponded with reduced SPMs. Retinal DPA RvD2 levels were found to correlate with retinal structural and functional decline. Retinal RNA sequencing comparing p21 with p60 showed an upregulation of microglial inflammatory pathways accompanied by impaired damage-associated molecular pattern (DAMP) clearance pathways. This analysis suggests that ALXR/FPR2 activation can ameliorate disease progression, which was supported by treatment with an LXA4 analog, NAP1051, which was able to promote the upregulation of ALOX12 and ALOX15. This study showed that retinal inflammation from activated microglia and dysregulation of lipid metabolism were central to the pathogenesis of retinal degeneration in RP, where ALXR/FPR2 activation was able to preserve retinal structure and function.

Chronic HIV infection has long been associated with an increased risk for cardiovascular diseases. The metabolites of the renin–angiotensin system (RAS) such as angiotensin II (AngII) play an important role in regulating blood pressure and fluid dynamics. Cross-sectional analysis of HIV-positive individuals (n = 71, age > 40 years, stable ART > 3 months with HIV viral load < 50 copies/mL) were compared to a similar HIV seronegative group (n = 72). High-resolution B-mode ultrasound images of the right carotid bifurcation (RBIF) and right common carotid artery (RCCA) were conducted to measure the extent of carotid atherosclerotic vascular disease. Plasma RAS peptide levels were quantified using a liquid chromatography-mass spectrometry-based metabolomics assay. RAS peptide concentrations were compared between persons with HIV and persons without HIV, correlating their association with clinical and cardiac measures. Median precursor peptides (Ang(1-12) and AngI) were significantly higher in the HIV-positive group compared to the HIV-negative. Analyses of the patient subgroup not on antihypertensive medication revealed circulating levels of AngII to be four-fold higher in the HIV-positive subgroup. AngII and TNF-alpha levels were found to have a positive association with RCCA, and AngI/Ang(1-12) ratio and TNF-alpha levels were found to have a positive association with RBIF. In both predictive models, AngIII had a negative association with either RCCA or RBIF, which may be attributed to its ability to bind onto AT2R and thus oppose pro-inflammatory events. These results reveal systemic alterations in RAS as a result of chronic HIV infection, which may lead to the activation of inflammatory pathways associated with carotid thickening. RAS peptide levels and cytokine markers were associated with RCCA and RBIF measurements.

More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.