Sequences of 95 human MHC haplotypes reveal extreme coding variation in genes other than highly polymorphic HLA class I and II.

The most polymorphic part of the human genome, the MHC, encodes over 160 proteins of diverse function. Half of them, including the HLA class I and II genes, are directly involved in immune responses. Consequently, the MHC region strongly associates with numerous diseases and clinical therapies. Notoriously, the MHC region has been intractable to high-throughput analysis at complete sequence resolution, and current reference haplotypes are inadequate for large-scale studies. To address these challenges, we developed a method that specifically captures and sequences the 4.8-Mbp MHC region from genomic DNA. For 95 MHC homozygous cell lines we assembled, de novo, a set of high-fidelity contigs and a sequence scaffold, representing a mean 98% of the target region. Included are six alternative MHC reference sequences of the human genome that we completed and refined. Characterization of the sequence and structural diversity of the MHC region shows the approach accurately determines the sequences of the highly polymorphic HLA class I and HLA class II genes and the complex structural diversity of complement factor C4A/C4B It has also uncovered extensive and unexpected diversity in other MHC genes; an example is MUC22, which encodes a lung mucin and exhibits more coding sequence alleles than any HLA class I or II gene studied here. More than 60% of the coding sequence alleles analyzed were previously uncharacterized. We have created a substantial database of robust reference MHC haplotype sequences that will enable future population scale studies of this complicated and clinically important region of the human genome.

Pisces: an accurate and versatile variant caller for somatic and germline next-generation sequencing data.

MOTIVATION: Next-generation sequencing technology is transitioning quickly from research labs to clinical settings. The diagnosis and treatment selection for many acquired and autosomal conditions necessitate a method for accurately detecting somatic and germline variants. RESULTS: We have developed Pisces, a rapid, versatile and accurate small-variant calling suite designed for somatic and germline amplicon sequencing applications. Accuracy is achieved by four distinct modules, each incorporating a number of novel algorithmic strategies. AVAILABILITY AND IMPLEMENTATION: Pisces is distributed under an open source license and can be downloaded from https://github.com/Illumina/Pisces. Pisces is available on the BaseSpace™ SequenceHub. It is distributed on Illumina sequencing platforms such as the MiSeq™ and is included in the Praxis™ Extended RAS Panel test which was recently approved by the FDA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Development and Analytical Validation of a DNA Dual-Strand Approach for the US Food and Drug Administration-Approved Next-Generation Sequencing-Based Praxis Extended RAS Panel for Metastatic Colorectal Cancer Samples.

A next-generation sequencing method was developed that can distinguish single-stranded modifications from low-frequency somatic mutations present on both strands of DNA in formalin-fixed paraffin-embedded colorectal cancer samples. We applied this method for analytical validation of the Praxis Extended RAS Panel, a US Food and Drug Administration-approved companion diagnostic for panitumumab, on the Illumina MiSeqDx platform. With the use of the TruSeq amplicon workflow, both strands of DNA from the starting material were interrogated independently. Mutations were reported only if found on both strands; artifacts usually present on only one strand would not be reported. A total of 56 mutations were targeted within the KRAS and NRAS genes. A minimum read depth of 1800× per amplicon is required per sample but averaged >30,000× at maximum multiplexing levels. Analytical validation studies were performed to determine the simultaneous detection of mutations on both strands, reproducibility, assay detection level, precision of the assay across various factors, and the impact of interfering substances. In conclusion, this assay can clearly distinguish single-stranded artifacts from low-frequency mutations. Furthermore, the assay is accurate, precise, and reproducible, can achieve consistent detection of a mutation at 5% mutation frequency, exhibits minimal impact from tested interfering substances, and can simultaneously detect 56 mutations in a single run using 10 samples plus controls.