Assessing structural variation in a personal genome-towards a human reference diploid genome.

BACKGROUND: Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods. RESULTS: We demonstrate Parliament's efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus. CONCLUSIONS: HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

ChildSeq-RNA: A next-generation sequencing-based diagnostic assay to identify known fusion transcripts in childhood sarcomas.

Childhood sarcomas can be extremely difficult to accurately diagnose on the basis of morphological characteristics alone. Ancillary methods, such as RT-PCR or fluorescence in situ hybridization, to detect pathognomonic gene fusions can help to distinguish these tumors. Two major deficiencies of these assays are their inability to identify gene fusions at nucleotide resolution or to detect multiple gene fusions simultaneously. We developed a next-generation sequencing-based assay designated ChildSeq-RNA that uses the Ion Torrent platform to screen for EWSR1-FLI1 and EWSR1-ERG, PAX3-FOXO1 and PAX7-FOXO1, EWSR1-WT1, and ETV6-NTRK3 fusions of Ewing sarcoma (ES), alveolar rhabdomyosarcoma, desmoplastic small round cell tumor, and congenital fibrosarcoma, respectively. To rapidly analyze resulting data, we codeveloped a bioinformatics tool, termed ChildDecode, that operates on a scalable, cloud-computing platform. Total RNA from four ES cell lines plus 33 clinical samples representing ES, alveolar rhabdomyosarcoma, desmoplastic small round cell tumor, and congenital fibrosarcoma tumors was subjected to ChildSeq-RNA. This accurately identified corresponding gene fusions in each tumor type, with no examples of false positive fusion detection in this proof-of-concept study. Comparison with previous RT-PCR findings demonstrated high sensitivity (96.4%; 95% CI, 82.3%-99.4%) and specificity (100%; 95% CI, 56.6%-100%) of ChildSeq-RNA to detect gene fusions. Herein, we propose ChildSeq-RNA as a novel tool to detect gene fusions in childhood sarcomas at single-nucleotide resolution.

Imaging retinal capillaries using ultrahigh-resolution optical coherence tomography and adaptive optics.

PURPOSE: Ultrahigh-resolution optical coherence tomography (UHR-OCT) with adaptive optics (AO) provides micrometer-scale 3D resolution that is attractive for imaging the retinal microvasculature. Such imaging may be useful for early detection of pathologic changes as in diabetic retinopathy. Here the authors investigate this potential for detecting individual capillaries in healthy subjects. METHODS: UHR-AO-OCT volumes centered on the fovea were acquired from seven subjects (age range, 25-61 years) with three preselected with no foveal avascular zone (FAZ). Images were compared with entoptic diagrams using the capillaries at the rim of the FAZ. Methods of comparison were testing for the presence of a FAZ, noting distinct features in the capillary pattern, and measuring the size of the FAZ. Additional analysis included measurements of capillary diameter and depth range with retinal eccentricity. RESULTS: UHR-AO-OCT results are consistent with entoptic observations for all three methods of comparison. FAZ diameters measured by UHR-AO-OCT and entoptic imaging are strongly correlated (R(2) = 0.86). Average capillary diameter near the FAZ rim is 5.1 (4.6) ± 1.4 µm, with the value in parentheses accounting for axial image blur. This is consistent with histology (average, ~4.7 µm). Depth range of the capillaries increases monotonically with eccentricity (0°-1.25°) and is larger and more variable for subjects without FAZ. CONCLUSIONS: UHR-AO-OCT permits observation of many of the capillaries proximal to the FAZ, including those of average size based on published histology. This supports the view that the vast majority of capillaries in the retina are likely detectable with UHR-AO-OCT.