26 research outputs found

    Mutational sequencing for accurate count and long-range assembly

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    ABSTRACT We introduce a new protocol, mutational sequencing or muSeq, which randomly deaminates unmethylated cytosines at a fixed and tunable rate. The muSeq protocol marks each initial template molecule with a unique mutation signature that is present in every copy of the template, and in every fragmented copy of a copy. In the sequenced read data, this signature is observed as a unique pattern of C-to-T or G-to-A nucleotide conversions. Clustering reads with the same conversion pattern enables accurate count and long-range assembly of initial template molecules from short-read sequence data. We explore count and low-error sequencing by profiling a 135,000 fragment PstI representation, demonstrating that muSeq improves copy number inference and significantly reduces sporadic sequencer error. We explore long-range assembly in the context of cDNA, generating contiguous transcript clusters greater than 3,000 bp in length. The muSeq assemblies reveal transcriptional diversity not observable from short-read data alone

    Rates of contributory de novo mutation in high and low-risk autism families.

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    Autism arises in high and low-risk families. De novo mutation contributes to autism incidence in low-risk families as there is a higher incidence in the affected of the simplex families than in their unaffected siblings. But the extent of contribution in low-risk families cannot be determined solely from simplex families as they are a mixture of low and high-risk. The rate of de novo mutation in nearly pure populations of high-risk families, the multiplex families, has not previously been rigorously determined. Moreover, rates of de novo mutation have been underestimated from studies based on low resolution microarrays and whole exome sequencing. Here we report on findings from whole genome sequence (WGS) of both simplex families from the Simons Simplex Collection (SSC) and multiplex families from the Autism Genetic Resource Exchange (AGRE). After removing the multiplex samples with excessive cell-line genetic drift, we find that the contribution of de novo mutation in multiplex is significantly smaller than the contribution in simplex. We use WGS to provide high resolution CNV profiles and to analyze more than coding regions, and revise upward the rate in simplex autism due to an excess of de novo events targeting introns. Based on this study, we now estimate that de novo events contribute to 52-67% of cases of autism arising from low risk families, and 30-39% of cases of all autism

    Y oh Y are some men infertile?

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    Detection of Copy Number Variants by Short Multiply Aggregated Sequence Homologies.

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    Chromosomal microarray testing is indicated for patients with diagnoses including unexplained developmental delay or intellectual disability, autism spectrum disorders, and multiple congenital anomalies. The short multiply aggregated sequence homologies (SMASH) genomic assay is a novel next-generation sequencing technology that performs copy number analysis at resolution similar to high-coverage whole genome sequencing but requires far less capacity. We benchmarked the performance of SMASH on a panel of genomic DNAs containing known copy number variants (CNVs). SMASH was able to detect pathogenic copy number variants of ≥10 kb in 77 of 77 samples. No pathogenic events were seen in 32 of 32 controls, indicating 100% sensitivity and specificity for detecting pathogenic CNVs >10 kb. Repeatability (interassay precision) and reproducibility (intra-assay precision) were assessed with 13 samples and showed perfect concordance. We also established that SMASH had a limit of detection of 20% for detection of large mosaic CNVs. Finally, we analyzed seven blinded specimens by SMASH analysis and successfully identified all pathogenic events. These results establish the efficacy of the SMASH genomic assay as a clinical test for the detection of pathogenic copy number variants at a resolution comparable to chromosomal microarray analysis
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