RESUMEN
HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome and has shown promise in detecting genomic rearrangements in translational research studies. To evaluate HiC as a potential clinical diagnostic platform, analytical concordance with routine laboratory testing was assessed using primary pediatric leukemia and sarcoma specimens previously positive for clinically significant genomic rearrangements. Archived specimen types tested included viable and nonviable frozen leukemic cells, as well as formalin-fixed paraffin-embedded (FFPE) tumor tissues. Initially, pediatric acute myeloid leukemia (AML) and alveolar rhabdomyosarcoma (A-RMS) specimens with known genomic rearrangements were subjected to HiC analysis to assess analytical concordance. Subsequently, a discovery cohort consisting of AML and acute lymphoblastic leukemia (ALL) cases with no known genomic rearrangements based on prior clinical diagnostic testing were evaluated to determine whether HiC could detect rearrangements. Using a standard sequencing depth of 50 million raw read-pairs per sample, or approximately 5X raw genomic coverage, 100% concordance was observed between HiC and previous clinical cytogenetic and molecular testing. In the discovery cohort, a clinically relevant gene fusion was detected in 45% of leukemia cases (5/11). This study demonstrates the value of HiC sequencing to medical diagnostic testing as it identified several clinically significant rearrangements, including those that might have been missed by current clinical testing workflows. Key points: HiC sequencing is a DNA-based next-generation sequencing method that preserves the 3D conformation of the genome, facilitating detection of genomic rearrangements.HiC was 100% concordant with clinical diagnostic testing workflows for detecting clinically significant genomic rearrangements in pediatric leukemia and rhabdomyosarcoma specimens.HiC detected clinically significant genomic rearrangements not previously detected by prior clinical cytogenetic and molecular testing.HiC performed well with archived non-viable and viable frozen leukemic cell samples, as well as archived formalin-fixed paraffin-embedded tumor tissue specimens.
RESUMEN
AIMS: Bisulfite sequence analysis of individual CpG sites within genomic DNA is a powerful approach for methylation analysis in the genome. The major limitation of bisulfite-based methods is parallelization. Both array and next-generation sequencing technology are capable of addressing this bottleneck. In this report, we describe the application of Infinium® genotyping technology to analyze bisulfite-converted DNA to simultaneously query the methylation state of over 27,000 CpG sites from promoters of consensus coding sequences (CCDS) genes. MATERIALS & METHODS: We adapted the Infinium genotyping assay to readout an array of over 27,000 pairs of CpG methylation-specific query probes complementary to bisulfite-converted DNA. Two probes were designed to each CpG site: a 'methylated' and an 'unmethylated' query probe. The probe design assumed that all underlying CpG sites were 'in phase' with the queried CpG site due to their close proximity. Bisulfite conversion was performed with a modified version of the Zymo EZ DNA Methylation™ kit. RESULTS: We applied this technology to measuring methylation levels across a panel of 14 different human tissues, four Coriell cell lines and six cancer cell lines. We observed that CpG sites within CpG islands (CGIs) were largely unmethylated across all tissues (~80% sites unmethylated, ß < 0.2), whereas CpG sites in non-CGIs were moderately to highly methylated (only ~12% sites unmethylated, ß < 0.2). Within CGIs, only approximately 3-6% of the loci were highly methylated; in contrast, outside of CGIs approximately 25-40% of loci were highly methylated. Moreover, tissue-specific methylation (variation in methylation across tissues) was much more prevalent in non-CGIs than within CGIs. CONCLUSION: Our results demonstrate a genome-wide scalable array-based methylation readout platform that is both highly reproducible and quantitative. In the near future, this platform should enable the analysis of hundreds of thousands to millions of CpG sites per sample.
