Semyon Kruglyak

Isaac: Ultra-fast whole genome secondary analysis on Illumina sequencing platforms

SUMMARY An ultrafast DNA sequence aligner (Isaac Genome Alignment Software) that takes advantage of high-memory hardware (>48 GB) and variant caller (Isaac Variant Caller) have been developed. We demonstrate that our combined pipeline (Isaac) is four to five times faster than BWA + GATK on equivalent hardware, with comparable accuracy as measured by trio conflict rates and sensitivity. We further show that Isaac is effective in the detection of disease-causing variants and can easily/economically be run on commodity hardware. AVAILABILITY Isaac has an open source license and can be obtained at https://github.com/sequencing.

Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications

UNLABELLED : We describe Manta, a method to discover structural variants and indels from next generation sequencing data. Manta is optimized for rapid germline and somatic analysis, calling structural variants, medium-sized indels and large insertions on standard compute hardware in less than a tenth of the time that comparable methods require to identify only subsets of these variant types: for example NA12878 at 50× genomic coverage is analyzed in less than 20 min. Manta can discover and score variants based on supporting paired and split-read evidence, with scoring models optimized for germline analysis of diploid individuals and somatic analysis of tumor-normal sample pairs. Call quality is similar to or better than comparable methods, as determined by pedigree consistency of germline calls and comparison of somatic calls to COSMIC database variants. Manta consistently assembles a higher fraction of its calls to base-pair resolution, allowing for improved downstream annotation and analysis of clinical significance. We provide Manta as a community resource to facilitate practical and routine structural variant analysis in clinical and research sequencing scenarios. AVAILABILITY AND IMPLEMENTATION Manta is released under the open-source GPLv3 license. Source code, documentation and Linux binaries are available from https://github.com/Illumina/manta. CONTACT csaunders@illumina.com SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Whole-genome haplotyping by dilution, amplification, and sequencing

Standard whole-genome genotyping technologies are unable to determine haplotypes. Here we describe a method for rapid and cost-effective long-range haplotyping. Genomic DNA is diluted and distributed into multiple aliquots such that each aliquot receives a fraction of a haploid copy. The DNA template in each aliquot is amplified by multiple displacement amplification, converted into barcoded sequencing libraries using Nextera technology, and sequenced in multiplexed pools. To assess the performance of our method, we combined two male genomic DNA samples at equal ratios, resulting in a sample with diploid X chromosomes with known haplotypes. Pools of the multiplexed sequencing libraries were subjected to targeted pull-down of a 1-Mb contiguous region of the X-chromosome Duchenne muscular dystrophy gene. We were able to phase the Duchenne muscular dystrophy region into two contiguous haplotype blocks with a mean length of 494 kb. The haplotypes showed 99% agreement with the consensus base calls made by sequencing the individual DNAs. We subsequently used the strategy to haplotype two human genomes. Standard genomic sequencing to identify all heterozygous SNPs in the sample was combined with dilution-amplification–based sequencing data to resolve the phase of identified heterozygous SNPs. Using this procedure, we were able to phase >95% of the heterozygous SNPs from the diploid sequence data. The N50 for a Yoruba male DNA was 702 kb whereas the N50 for a European female DNA was 358 kb. Therefore, the strategy described here is suitable for haplotyping of a set of targeted regions as well as of the entire genome.

Personalized treatment of Sézary syndrome by targeting a novel CTLA4:CD28 fusion

Matching molecularly targeted therapies with cancer subtype‐specific gene mutations is revolutionizing oncology care. However, for rare cancers this approach is problematic due to the often poor understanding of the diseases natural history and phenotypic heterogeneity, making treatment of these cancers a particularly unmet medical need in clinical oncology. Advanced Sézary syndrome (SS), an aggressive, exceedingly rare variant of cutaneous T‐cell lymphoma (CTCL) is a prototypical example of a rare cancer. Through whole genome and RNA sequencing (RNA‐seq) of a SS patients tumor we discovered a highly expressed gene fusion between CTLA4 (cytotoxic T lymphocyte antigen 4) and CD28 (cluster of differentiation 28), predicting a novel stimulatory molecule on the surface of tumor T cells. Treatment with the CTLA4 inhibitor ipilimumab resulted in a rapid clinical response. Our findings suggest a novel driver mechanism for SS, and cancer in general, and exemplify an emerging model of cancer treatment using exploratory genomic analysis to identify a personally targeted treatment option when conventional therapies are exhausted.

Multistage sequencing by hybridization.

The sequencing of DNA is an important and difficult problem. Many interesting algorithms combine various technologies in an attempt to sequence long regions of DNA. One such algorithm is sequencing by hybridization (SBH). We briefly review SBH and mention the drawbacks that prevent it from being used in practice. We then present a theoretical algorithm that uniquely determines a sequence of length n through hybridization experiments that require the examination of only O(n2log(n)) subsequences. The key idea is to double subsequence length in each iteration of the algorithm. There are various problems associated with transforming the theoretical algorithm into a practical biological procedure. However, the general strategy of increasing subsequence length may be used to develop algorithms that are feasible given the current state of technology. Combining this strategy with a computer processing phase leads to a novel method of extending the resolving power of standard SBH techniques.

Manta: Rapid detection of structural variants and indels for clinical sequencing applications

Summary We describe Manta, a method to discover structural variants and indels from next generation sequencing data. Manta is optimized for rapid clinical analysis, calling structural variants, medium-sized indels and large insertions on standard compute hardware in less than a tenth of the time that comparable methods require to identify only subsets of these variant types: for example NA12878 at 50x genomic coverage is analyzed in less than 20 minutes. Manta can discover and score variants based on supporting paired and split-read evidence, with scoring models optimized for germline analysis of diploid individuals and somatic analysis of tumor-normal sample pairs. Call quality is similar to or better than comparable methods, as determined by pedigree consistency of germline calls and comparison of somatic calls to COSMIC database variants. Manta consistently assembles a higher fraction of its calls to basepair resolution, allowing for improved downstream annotation and analysis of clinical significance. We provide Manta as a community resource to facilitate practical and routine structural variant analysis in clinical and research sequencing scenarios. Availability Manta source code and Linux binaries are available from http://github.com/sequencing/manta. Contact csaunders@illumina.com Supplementary information Supplementary data are available at Bioinformatics online.