Squire, A. | bioRxiv Science

bioRxiv2022

Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs

Blood vasculature represents a complex network of vessels with varying lengths and diameters that are precisely organized in space to allow proper tissue function. Light-sheet fluorescence microscopy (LSFM) is very useful to generate tomograms of tissue vasculature with high spatial accuracy. Yet, quantitative LSFM analysis is still cumbersome and available methods are restricted to single organs and advanced computing hardware. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM data on average computing hardware. VesselExpress is ~100 times faster than other existing vessel analysis tools, requires no user interaction, integrates batch processing, and parallelization. Employing an innovative dual Frangi filter approach we show that obesity induces a large-scale modulation of brain vasculature in mice and that seven other major organs differ strongly in their 3D vascular makeup. Hence, VesselExpress transforms LSFM from an observational to an analytical working tool.

bioinformatics↗

bioRxiv2020

Targeted long-read sequencing resolves complex structural variants and identifies missing disease-causing variants

BACKGROUNDDespite widespread availability of clinical genetic testing, many individuals with suspected genetic conditions do not have a precise diagnosis. This limits their opportunity to take advantage of state-of-the-art treatments. In such instances, testing sometimes reveals difficult-to-evaluate complex structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in specific genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted. METHODSTargeted long-read sequencing (T-LRS) was performed on 33 individuals using Read Until on the Oxford Nanopore platform. This method allowed us to computationally target up to 100 Mbp of sequence per experiment, resulting in an average of 20x coverage of target regions, a 500% increase over background. We analyzed patient DNA for pathogenic substitutions, structural variants, and methylation differences using a single data source. RESULTSThe effectiveness of T-LRS was validated by detecting all genomic aberrations, including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences, previously identified by prior clinical testing. In 6/7 individuals who had complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, which led, in one case, to a change in clinical management. In nine individuals with suspected Mendelian conditions who lacked a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in five and variants of uncertain significance in two others. CONCLUSIONST-LRS can accurately predict pathogenic copy number variants and triplet repeat expansions, resolve complex rearrangements, and identify single-nucleotide variants not detected by other technologies, including short-read sequencing. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority candidate genes and regions or to further evaluate complex clinical testing results. The application of T-LRS will likely increase the diagnostic rate of rare disorders.

genomics↗