HapMap Samples Research Articles

Abstract 327: A comparison of Illumina and Element Biosciences sequencing platforms

Abstract Introduction: Advancements in sequencing technologies have revolutionized the field of genomics, enabling scientists to study the genetic information of organisms at unprecedented scale and speed. Next Generation Sequencing (NGS) has been utilized in clinical oncology from discovering and characterizing oncogenic driver mutations to providing personalized treatment of cancer. Among sequencing technologies, Illumina has emerged as the market leader, however, in recent years several alternatives have emerged. Herein, we evaluate the performance of NextSeq2000 and NextSeq550Dx platforms by Illumina to the Aviti platform from Element Biosciences. Method: Eight (8) Archer Core Myeloid Panel libraries previously sequenced on NextSeq550Dx as part of a validated workflow were selected, normalized to 100 nanomolar (nM), pooled and sequenced on NextSeq2000 and Aviti sequencers with 2 × 150 paired-end sequencing. Samples included the HD829 myeloid DNA control from Horizon Discovery, a well-characterized HAPMAP sample, and a mixture of HD829 in HAPMAP. Prior to sequencing on the Aviti system, libraries were circularized with the Elements Adept chemistry. Fastq files from both Aviti and NextSeq2000 sequencing were uploaded to Archer Analysis Software, standardized filtering was applied to all generated datasets, and results compared across platforms. Result: Aviti and NextSeq2000 platforms exhibited comparable sequencing reads, with an average total reads per sample of 76,205,719 and 74,201,570 from Aviti and NextSeq2000, respectively, while the lower throughput NextSeq550 platform yielded an average 17,619,350 reads per sample. Standardized filtering across all platforms provided 100% detection of true positives, however additional false positives (FP) were present in all samples and platforms that mapped to regions requiring normal dataset correction as part of the validated NextSeq550 workflow. The lowest numbers of FPs were detected on the Aviti platform, while both NextSeq550 and NextSeq2000 derived results contained several FP calls at elevated (>10%) variant allele frequency (VAF). Conclusion: The three platforms compared in this study were able to detect all true positives of the tested samples using the same filtering criteria. The performance metrics of NextSeq2000 and Aviti were comparable and higher than NextSeq550Dx, in line with expectations due to the higher sequencing capacity. Although the Aviti platform required additional hands-on time, it in-turn generated cleaner data with less FP variants in comparison to Illumina’s sequencing platforms. Overall, these results indicate robust sequencing throughout all three platforms. Citation Format: Sarah Johnson, Kevin Lee, Nathan Riccitelli. A comparison of Illumina and Element Biosciences sequencing platforms [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 327.

A newly developed capture-based sequencing panel for genomic assay of lung cancer.

The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing. We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance. FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods. FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancer patients also identified all SNVs, indels and fusions. Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancer patients.

Cross-site concordance evaluation for the CIMAC-CIDC network to establish QC metrics enabling reliable generation of WES and RNA-seq data.

e15240 Background: Whole-exome sequencing (WES) and RNA-sequencing (RNA-seq) have become key components of cancer genomics, and analysis to provide comprehensive evaluation of spectrum somatic alterations and changes in gene expression present in cancer samples. To test the ability to generate comparable data for these genomic assays across CIMAC-affiliated sequencing centers, the CIDC performed a cross-site harmonization effort at two CIMAC sites (MD Anderson [MDACC] and DFCI/Broad Institute) and the MoCha Lab (MoCha) at the National Cancer Institute. Fresh frozen (FF) and FFPE samples from 8 non-small cell lung carcinoma (NSCLC) tumors were provided by MDACC, and processed for DNA and RNA extraction, aliquoted, and sent by MDACC to MoCha, MDACC and DFCI/Broad to be processed as replicates. Two reference samples,pools of 10 HapMap cell lines were sent for WES processing. Methods: WES analysis was carried out using center-specific pipelines as and central workflows that included: coverage metrics (target-based and genome-wide), variant calls (somatic and germline), variant annotations, tumor purity and clonality. Only minimal differences in somatic mutation calls were found between different replicates and centers for the HapMap samples, and technical differences were much smaller than biological differences between the patient tumors. For both sets of data, when focusing on reads at > 50X common coverage and events with variant allele frequency (VAF) > 5%, the different centers achieved high precision ( > 98%) and recall ( > 87%).Further, ISA for patient samples ranged from 0.667-0.875, while that for HapMap samples ranged from 0.817-0.827. Results: The RNA-seq analysis pipeline used the tools STAR for read mapping, RSEQC for quality control, SALMON for transcript quantification and LIMMA for batch removal on log transformed TPM values. Our analysis revealed that a DV200 of 24- 30% was a reasonable cutoff to achieve consistent quality in RNA-seq data generation. In addition, a medTIN cutoff value of 50% was found to be effective in determining the quality of the samples. Using these criteria, the Spearman correlation of log(TPM) among all the FF samples from the same tumor were higher than 0.976, and among all FFPE samples from the same tumor were higher than 0.942. Conclusions: In summary,cross-center concordance evaluation has identified the factors that introduce variability in the analyses, while also demonstrating the ability to provide comparable results across CIMAC sites by using a centralized analysis pipeline.

Abstract 1693: Comparison of commercially available myeloid next-generation sequencing assays

Abstract Introduction Myeloid neoplasms are a complex class of disorders characterized by a range of genotypes. Accurate, precise, and rapid identification of these genotypes is crucial in giving the right drug to the right patient at the right time. In this study, we present a comparison of three Next-Generation Sequencing (NGS) panels targeting genes associated with myeloid cancers. We evaluated assay performance as a function of sensitivity and specificity of somatic variant callings, sequencing metrics, and general workflow, for the analytically validated Illumina TruSight Myeloid Sequencing Panel (TSM), the new Illumina AmpliSeq for Illumina Myeloid Panel (IA), and the ThermoFisher Oncomine™ Myeloid Research Assay (TA). Methods Thirty-two libraries were prepared across all three panels. Samples included a mix of Horizon Discovery and SeraCare myeloid DNA controls, a well-characterized Hapmap sample, and six clinical DNAs isolated from peripheral blood of patients with myeloid disorders. Libraries were prepared according to manufacturer protocols, and quantified by Qubit Flourometer. For Illumina panels, libraries were manually prepared, normalized, pooled, and sequenced on Illumina’s MiSeq instruments. For the TA panel, libraries were generated, pooled, templated, and loaded onto sequencing chips by the IonChef, then sequenced on the S5xL system. Primary data analysis was completed using cloud-based bioinformatic solutions followed by manual annotation. Results Hands-on time varied for the assays, with the TA panel requiring just 30 minutes compared to four to eight hours for the TSM and IA protocols. Time to results from DNA dilution to variant calls was comparable, at three days for the TSM panel and four days for the IA and TA protocols. The TSM assay exhibited the highest average coverage, but also the greatest amplicon dropout. Both the IA and TA panels exhibited similar coverage uniformity and read depths. Detection of expected variants in control samples down to 5% allele frequency was robust for all assays, however both the IA and TA panels contained increased regions of poor sequencing quality relative to the TSM panel. No false positives were found in the somatic-variant negative Hapmap sample NA12878, and concordance of variant calls for the clinical samples from the IA and TA assays to the validated TSM assay was greater than 95%. Conclusions In the complex landscape of myeloid neoplasms, NGS is an invaluable tool for the diagnosis and management of the diseases. Overall, the three sequencing panels evaluated herein provided accurate genotype information for actionable targets in myeloid cancers. Although results for the assays were similar, the short time-to-data for the TSM assay, increased coverage and detection of low frequency variants for the IA assay, and fully-automated option for the TA assay should all be considered when determining the optimal panel for a given need. Citation Format: Sarah Johnson, Nathan Riccitelli, Reinhold Pollner. Comparison of commercially available myeloid next-generation sequencing assays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1693.

Abstract 2282: Progress toward non-invasive oncology diagnostics: Evaluation of cfDNA next-generation sequencing assays

Abstract Introduction Surgical biopsy or excisional resection is a standard practice in oncology diagnosis that requires a detectable tumor mass and can be highly invasive, limiting its role in the very early detection, as well as ongoing monitoring efforts, of genetic aberrations relevant to tumor biology. In contrast to surgical biopsies, liquid biopsies provide a readily accessible source of circulating tumor DNA, albeit in a highly diluted state that necessitates a very sensitive and robust method of detection. With recent advents in molecular barcoding and bioinformatics, next-generation sequencing (NGS) has emerged as a platform for probing this liquid oncology space. Herein, we evaluate the ability of the Oncomine™ cell-free DNA (cfDNA) Breast, Colon, and Lung NGS panels to reliably detect clinically relevant genomic alterations in a large background of non-mutated genetic material. Methods A total of 197 individual libraries were prepared across all three cfDNA panels according to the manufacturer protocols. Libraries were manually normalized, pooled, and loaded onto the ThermoFisher IonChef/S5xL system for bead-templating and sequencing. Samples included a mix of commercially available cfDNA controls, plasma samples, and cell lines spiked into healthy donor plasma, and were selected to cover a wide range of clinically relevant mutations and mimic the conditions inherent to real patient specimens. Isolation of cfDNA was performed on both Qiagen and Kingfisher platforms. Raw variant call files were generated using IonReporter and processed through a custom filtering pipeline to generate the final results. Results Nucleic acid isolations yields were comparable for cfDNA samples isolated using the Qiagen or Kingfisher extraction methods, with both yielding a 40-60% DNA recovery rate when known DNA quantities were spiked into plasma background. Library yield mapped to NGS panel size, and the greatest variability was observed for the Colon cfDNA panel. The sensitivity for all Oncomine™ cfDNA assays exceeded 92%, and was highly dependent on sample input, with robust detection at the 0.1% allele frequency requiring up to 50 ng of input cfDNA. A single false positive was present in one HapMap sample analyzed with the breast cfDNA panel. Conclusion The Oncomine™ cfDNA panels provide accurate detection of variants in cfDNA down to 0.1% variant allele frequency. However, increased DNA inputs are required to achieve this highly-sensitive level of detection. Although sensitivity is reduced at lower inputs, the ability to generate high-quality libraries from as little as 10 ng DNA ensures sufficient material can be obtained for sequencing from even low-yielding samples. Overall, these results indicate that the Oncomine™ cfDNA assays can aid in the very early diagnosis and monitoring of tumor populations via minimally-invasive blood-based diagnostics. Citation Format: Nathan Riccitelli, Nancy Valencia, Ashley Beams, Sarah Johnson, Reinhold Pollner. Progress toward non-invasive oncology diagnostics: Evaluation of cfDNA next-generation sequencing assays [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2282.

Design of Arab Diabetes Gene-Centric Array (ADGCA) in population with an epidemic of Type 2 Diabetes: A population specific SNP evaluation

In the case of diabetes and other complex diseases, the challenge has always been to find genetic markers that explain the excess risk associated with development of the disease. In the last 12 years, advances in genotyping technology provided substantial development in the discovery of loci contributing to Type 2 diabetes (T2D) susceptibility. Therefore, the aim of this study is to custom design, for the first time in Arab world, an “Arab Diabetes Gene Centric Array” (ADGCA) that assays 643, 745 SNP markers including 50,617 diabetes associated SNPs. The array content was designed after comprehensive literature search prioritizing Diabetes associated SNPs. PCA was performed to evaluate the relationship between world populations and the Saudi population in building the backbone for the array. A genotype data matrix for PCA analysis was produced by including the genotypes of the 270 HapMap samples including JPT, CHB, YRI and CEU to genotypes of the 1457 Saudi samples. Imputation was executed using IMPUTE2 software and the 1000GP Phase III reference panel. All markers incorporated to ADGCA were validated. Quality checks and evaluation of its capacity and performance as a platform for genetic screening for T2D was performed using the latest stastical tools available. We were successful in designing ADGCA as a custom made chip array designed with a motive to capture genetic variation in loci known or reported to be associated with the development of T2D. However, implementation of ADGCA is currently being performed by our research group using 2000 DNA samples respectively from diabetic and non diabetic individuals which could further validate the use of ADGSA in genetic screening of T2D.

Novel findings with reassessment of exome data: implications for validation testing and interpretation of genomic data.

PurposeThe objective of this study was to assess the ability of our laboratory's exome-sequencing test to detect known and novel sequence variants and identify the critical factors influencing the interpretation of a clinical exome test.MethodsWe developed a two-tiered validation strategy: (i) a method-based approach that assessed the ability of our exome test to detect known variants using a reference HapMap sample, and (ii) an interpretation-based approach that assessed our relative ability to identify and interpret disease-causing variants, by analyzing and comparing the results of 19 randomly selected patients previously tested by external laboratories.ResultsWe demonstrate that this approach is reproducible with >99% analytical sensitivity and specificity for single-nucleotide variants and indels <10 bp. Our findings were concordant with the reference laboratories in 84% of cases. A new molecular diagnosis was applied to three cases, including discovery of two novel candidate genes.ConclusionWe provide an assessment of critical areas that influence interpretation of an exome test, including comprehensive phenotype capture, assessment of clinical overlap, availability of parental data, and the addressing of limitations in database updates. These results can be used to inform improvements in phenotype-driven interpretation of medical exomes in clinical and research settings.

ExCNVSS: A Noise-Robust Method for Copy Number Variation Detection in Whole Exome Sequencing Data.

Copy number variations (CNVs) are structural variants associated with human diseases. Recent studies verified that disease-related genes are based on the extraction of rare de novo and transmitted CNVs from exome sequencing data. The need for more efficient and accurate methods has increased, which still remains a challenging problem due to coverage biases, as well as the sparse, small-sized, and noncontinuous nature of exome sequencing. In this study, we developed a new CNV detection method, ExCNVSS, based on read coverage depth evaluation and scale-space filtering to resolve these problems. We also developed the method ExCNVSS_noRatio, which is a version of ExCNVSS, for applying to cases with an input of test data only without the need to consider the availability of a matched control. To evaluate the performance of our method, we tested it with 11 different simulated data sets and 10 real HapMap samples' data. The results demonstrated that ExCNVSS outperformed three other state-of-the-art methods and that our method corrected for coverage biases and detected all-sized CNVs even without matched control data.

Abstract 3637: Targeted exome and panel analysis from low input and FFPE DNA using hybridization capture for cancer genome studies

Abstract Introduction Hybridization-based target enrichment techniques coupled with Next Generation Sequencing (NGS) provide a useful and cost-efficient means to study disease specific target regions including whole exomes and gene panels. More than 500 whole exome analyses are behind The Cancer Genome Atlas (TCGA), which is the largest knowledge base for cancer studies including research, prevention, treatment, and care. Clinical samples may be limited in input and of compromised quality due to formalin fixation, however most current NGS library preparation methods require 50-100 ng high quality DNA for such studies. Here we present an efficient method which enables high quality target enrichment and variant calling from inputs as low as 1-25 ng. Method NGS libraries for hybridization capture were made from 1 to 100 ng of Coriell Hapmap samples (NA12878, etc), clinical Formalin Fixed Paraffin Embedded (FFPE) and Horizon Discovery (HDx) reference DNA (HDx 701) using the Accel-NGS® 2S Hyb DNA Library Kit. Amplified libraries were then enriched using specific targeted panels (xGen® Pan-Cancer and xGen® AML) or SeqCap™ EZ MedExome using manufacturer's specifications (IDT™ and Roche NimbleGen™). Enriched libraries were captured using streptavidin beads. Captured libraries were then amplified according to the manufacturer's specifications. Targeted panels were sequenced on an Illumina® MiSeq® using V2 chemistry and MedExome on a HiSeq® using V4 chemistry. Sequence analysis was performed with custom pipelines using BWA for alignment and GATK, Samtools, and Freebayes for variant calling. Results Sequencing analyses yielded a minimum average coverage of 30x and more than thirty fold enrichment. Enriched libraries exhibited significant sequence complexity with minimal duplicates and without any base-composition bias. The percent on-target varied with type of input and ranged from 50-80%. Germline variant calling results had &amp;gt; 99% concordance with the NIST GIAB truth list with sensitivity and precision of &amp;gt; 98%, even from inputs as low as 1 ng of DNA. Somatic variant calling down to 1-5% allele frequency was also evaluated at various DNA input quantities and greater depth of sequencing; results for FFPE and DNA standards will be presented. Conclusions Accel-NGS 2S Hyb technology can be used for whole exome and targeted enrichment studies from low quantity and low quality FFPE clinical samples. High complexity libraries with minimal bias yield high quality sequence data which enables discovery and detection of somatic variants in tumor samples to identify molecular drivers associated with different cancer types. The technique facilitates better understanding of complex cancer genomes and guide precision medicine. Citation Format: Sukhinder K. Sandhu, Cassie Schumacher, Laurie Kurihara, Tim Harkins, Vladimir Makarov. Targeted exome and panel analysis from low input and FFPE DNA using hybridization capture for cancer genome studies. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3637.

Abstract 3602: Linked-Reads enable detailed, phased resolution of structural variation in the cancer genome

Abstract Studies have shown that somatic structural variation (SV) plays a key role in the oncogenic process. Traditionally SVs in the cancer genome have been detected using low resolution cytogenetic approaches, such as FISH, or microarray-based techniques. More recently, next-generation sequencing (NGS)-based technologies have been employed to detect SVs, including indels and translocations. However, both short- and long-read NGS-based approaches are limited in their ability to accurately identify SV events and delineate their breakpoints due to the limitations inherent in assembly of billions of short-read sequences across a heterogeneous cancer sample, as well as the costly and burdensome laboratory infrastructure associated with long-read sequencers. We utilized a novel technology that combines microfluidics and molecular barcoding to generate libraries that are sequenced with an Illumina system. Open-source bioinformatics software produces linked-reads that maintain long-range information and single molecule sensitivity. Cell lines and cancer samples were obtained from commercial sources, and genomic DNA was extracted. DNA sample indexing and partitioning was performed using the 10X Genomicx GemCode instrument. One ng of sample DNA was used as input for each reaction, and DNA molecules were partitioned into droplets to fragment the DNA and introduce molecular barcodes. Following barcoding, droplets were fractured, and library DNA was purified and sequenced on Illumina sequencers. The GemCode Long Ranger software suite was used to map sequencing reads back to original long molecules of DNA, generating reads linked to partition barcodes. Thus we can generate phased sequences covering many 10's to 100's of kilobases. We first benchmarked the ability to call multiple SV types using a well-characterized germline HapMap sample (NA12878) as well as two recently characterized haploid hydatidiform moles (CHM1 and CHM13) that have been studied with multiple orthogonal technologies. Regions with evidence for structural variation were reassembled into distinct haplotypes. The barcode information allowed us to both phase the structural variants we detected and disambiguate calls within highly repetitive regions, such as segmental duplications. We demonstrated high concordance with alternative approaches across all major classes of SVs, including long insertions and deletions as well as copy-neutral events. In cancer cell lines, we detected well-annotated gene fusions, such as the EML4/ALK and ALK/PTPN3 fusions in the lung cancer cell line NCI-H2228, and the SLC26A/PRKAR2A fusion in the triple negative breast cancer cell line HCC38. Citation Format: Sofia Kyriazopoulou-Panagiotopoulou, Patrick Marks, Haynes Heaton, Heather Ordonez, Kristina Giorda, Cassandra Jabara, Billy Lau, John M. Bell, Michael Schnall-Levin, Hanlee P. Ji. Linked-Reads enable detailed, phased resolution of structural variation in the cancer genome. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3602.

FastPop: a rapid principal component derived method to infer intercontinental ancestry using genetic data.

BackgroundIdentifying subpopulations within a study and inferring intercontinental ancestry of the samples are important steps in genome wide association studies. Two software packages are widely used in analysis of substructure: Structure and Eigenstrat. Structure assigns each individual to a population by using a Bayesian method with multiple tuning parameters. It requires considerable computational time when dealing with thousands of samples and lacks the ability to create scores that could be used as covariates. Eigenstrat uses a principal component analysis method to model all sources of sampling variation. However, it does not readily provide information directly relevant to ancestral origin; the eigenvectors generated by Eigenstrat are sample specific and thus cannot be generalized to other individuals.ResultsWe developed FastPop, an efficient R package that fills the gap between Structure and Eigenstrat. It can: 1, generate PCA scores that identify ancestral origins and can be used for multiple studies; 2, infer ancestry information for data arising from two or more intercontinental origins. We demonstrate the use of FastPop using 2318 SNP markers selected from the genome based on high variability among European, Asian and West African (African) populations. We conducted an analysis of 505 Hapmap samples with European, African or Asian ancestry along with 19661 additional samples of unknown ancestry. The results from FastPop are highly consistent with those obtained by Structure across the 19661 samples we studied. The correlations of the results between FastPop and Structure are 0.99, 0.97 and 0.99 for European, African and Asian ancestry scores, respectively. Compared with Structure, FastPop is more efficient as it finished ancestry inference for 19661 samples in 16 min compared with 21–24 h required by Structure. FastPop also provided scores based on SNP weights so the scores of reference population can be applied to other studies provided the same set of markers are used. We also present application of the method for studying four continental populations (European, Asian, African, and Native American).ConclusionsWe developed an algorithm that can infer ancestries on data involving two or more intercontinental origins. It is efficient for analyzing large datasets. Additionally the PCA derived scores can be applied to multiple data sets to ensure the same ancestry analysis is applied to all studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-0965-1) contains supplementary material, which is available to authorized users.

Smokescreen: a targeted genotyping array for addiction research.

BackgroundAddictive disorders are a class of chronic, relapsing mental disorders that are responsible for increased risk of mental and medical disorders and represent the largest, potentially modifiable cause of death. Tobacco dependence is associated with increased risk of disease and premature death. While tobacco control efforts and therapeutic interventions have made good progress in reducing smoking prevalence, challenges remain in optimizing their effectiveness based on patient characteristics, including genetic variation. In order to maximize collaborative efforts to advance addiction research, we have developed a genotyping array called Smokescreen. This custom array builds upon previous work in the analyses of human genetic variation, the genetics of addiction, drug metabolism, and response to therapy, with an emphasis on smoking and nicotine addiction.ResultsThe Smokescreen genotyping array includes 646,247 markers in 23 categories. The array design covers genome-wide common variation (65.67, 82.37, and 90.72 % in African (YRI), East Asian (ASN), and European (EUR) respectively); most of the variation with a minor allele frequency ≥ 0.01 in 1014 addiction genes (85.16, 89.51, and 90.49 % for YRI, ASN, and EUR respectively); and nearly all variation from the 1000 Genomes Project Phase 1, NHLBI GO Exome Sequencing Project and HapMap databases in the regions related to smoking behavior and nicotine metabolism: CHRNA5-CHRNA3-CHRNB4 and CYP2A6-CYP2B6. Of the 636 pilot DNA samples derived from blood or cell line biospecimens that were genotyped on the array, 622 (97.80 %) passed quality control. In passing samples, 90.08 % of markers passed quality control. The genotype reproducibility in 25 replicate pairs was 99.94 %. For 137 samples that overlapped with HapMap2 release 24, the genotype concordance was 99.76 %. In a genome-wide association analysis of the nicotine metabolite ratio in 315 individuals participating in nicotine metabolism laboratory studies, we identified genome-wide significant variants in the CYP2A6 region (min p = 9.10E-15).ConclusionsWe developed a comprehensive genotyping array for addiction research and demonstrated its analytic validity and utility through pilot genotyping of HapMap and study samples. This array allows researchers to perform genome-wide, candidate gene, and pathway-based association analyses of addiction, tobacco-use, treatment response, comorbidities, and associated diseases in a standardized, high-throughput platform.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2495-7) contains supplementary material, which is available to authorized users.

SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.

Cancer genomes exhibit profound somatic copy number alterations (SCNAs). Studying tumor SCNAs using massively parallel sequencing provides unprecedented resolution and meanwhile gives rise to new challenges in data analysis, complicated by tumor aneuploidy and heterogeneity as well as normal cell contamination. While the majority of read depth based methods utilize total sequencing depth alone for SCNA inference, the allele specific signals are undervalued. We proposed a joint segmentation and inference approach using both signals to meet some of the challenges. Our method consists of four major steps: 1) extracting read depth supporting reference and alternative alleles at each SNP/Indel locus and comparing the total read depth and alternative allele proportion between tumor and matched normal sample; 2) performing joint segmentation on the two signal dimensions; 3) correcting the copy number baseline from which the SCNA state is determined; 4) calling SCNA state for each segment based on both signal dimensions. The method is applicable to whole exome/genome sequencing (WES/WGS) as well as SNP array data in a tumor-control study. We applied the method to a dataset containing no SCNAs to test the specificity, created by pairing sequencing replicates of a single HapMap sample as normal/tumor pairs, as well as a large-scale WGS dataset consisting of 88 liver tumors along with adjacent normal tissues. Compared with representative methods, our method demonstrated improved accuracy, scalability to large cancer studies, capability in handling both sequencing and SNP array data, and the potential to improve the estimation of tumor ploidy and purity.

The Paternal Landscape along the Bight of Benin - Testing Regional Representativeness of West-African Population Samples Using Y-Chromosomal Markers.

Patterns of genetic variation in human populations across the African continent are still not well studied in comparison with Eurasia and America, despite the high genetic and cultural diversity among African populations. In population and forensic genetic studies a single sample is often used to represent a complete African region. In such a scenario, inappropriate sampling strategies and/or the use of local, isolated populations may bias interpretations and pose questions of representativeness at a macrogeographic-scale. The non-recombining region of the Y-chromosome (NRY) has great potential to reveal the regional representation of a sample due to its powerful phylogeographic information content. An area poorly characterized for Y-chromosomal data is the West-African region along the Bight of Benin, despite its important history in the trans-Atlantic slave trade and its large number of ethnic groups, languages and lifestyles. In this study, Y-chromosomal haplotypes from four Beninese populations were determined and a global meta-analysis with available Y-SNP and Y-STR data from populations along the Bight of Benin and surrounding areas was performed. A thorough methodology was developed allowing comparison of population samples using Y-chromosomal lineage data based on different Y-SNP panels and phylogenies. Geographic proximity turned out to be the best predictor of genetic affinity between populations along the Bight of Benin. Nevertheless, based on Y-chromosomal data from the literature two population samples differed strongly from others from the same or neighbouring areas and are not regionally representative within large-scale studies. Furthermore, the analysis of the HapMap sample YRI of a Yoruban population from South-western Nigeria based on Y-SNPs and Y-STR data showed for the first time its regional representativeness, a result which is important for standard population and forensic genetic applications using the YRI sample. Therefore, the uniquely and powerful geographical information carried by the Y-chromosome makes it an important locus to test the representativeness of a certain sample even in the genomic era, especially in poorly investigated areas like Africa.

MG-134 Validation of a customizable next generation sequencing panel for ear and eye diseases

<h3>Background</h3> Hearing and/or vision loss can result from both genetic and non-genetic etiologies. Up to 70% of prelingual hearing loss has a genetic basis, as does up to 60% of congenital blindness among infants. Next generation sequencing (NGS) technology is ideal for diagnostic testing for such disorders due to extreme locus heterogeneity and phenotypic overlap. <h3>Objectives</h3> The aim is to design and validate a comprehensive, customizable NGS panel for detection of pathogenic variants in genes involved in hearing and/or vision loss. <h3>Design/method</h3> 380 genes were selected for inclusion based on literature review and comparison with commercially available assays, including 245 genes for vision loss and 83 genes for hearing loss. Agilent SureSelect biotinylated RNA baits were designed to capture 1.5 Mb of DNA using SureSelect XT target enrichment followed by Illumina HiSeq 2500 sequencing. DNA from six HapMap cell lines and five Coriell repository samples with known pathogenic variants were used to assess intra-run and inter-run variability. Additionally, DNA from a family with a known hearing loss aetiology was included. <h3>Results</h3> An average yield of 6 Gb of sequence per sample was obtained, where 94% of bases were covered at a depth &gt;20X. Genotype calls from HapMap samples were highly concordant across three runs. Eight known pathogenic variants were confirmed in <i>GJB2, USH1C, MARVELD2, TRIOBP, and OAT.</i> <h3>Conclusions</h3> This NGS panel targets an extensive list of genes implicated in diseases of the ear and the eye. Customizable testing allows ordering of an ear-specific or eye-specific gene panel, or both.

Concept and design of a genome-wide association genotyping array tailored for transplantation-specific studies.

BackgroundIn addition to HLA genetic incompatibility, non-HLA difference between donor and recipients of transplantation leading to allograft rejection are now becoming evident. We aimed to create a unique genome-wide platform to facilitate genomic research studies in transplant-related studies. We designed a genome-wide genotyping tool based on the most recent human genomic reference datasets, and included customization for known and potentially relevant metabolic and pharmacological loci relevant to transplantation.MethodsWe describe here the design and implementation of a customized genome-wide genotyping array, the ‘TxArray’, comprising approximately 782,000 markers with tailored content for deeper capture of variants across HLA, KIR, pharmacogenomic, and metabolic loci important in transplantation. To test concordance and genotyping quality, we genotyped 85 HapMap samples on the array, including eight trios.ResultsWe show low Mendelian error rates and high concordance rates for HapMap samples (average parent-parent-child heritability of 0.997, and concordance of 0.996). We performed genotype imputation across autosomal regions, masking directly genotyped SNPs to assess imputation accuracy and report an accuracy of >0.962 for directly genotyped SNPs. We demonstrate much higher capture of the natural killer cell immunoglobulin-like receptor (KIR) region versus comparable platforms. Overall, we show that the genotyping quality and coverage of the TxArray is very high when compared to reference samples and to other genome-wide genotyping platforms.ConclusionsWe have designed a comprehensive genome-wide genotyping tool which enables accurate association testing and imputation of ungenotyped SNPs, facilitating powerful and cost-effective large-scale genotyping of transplant-related studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-015-0211-x) contains supplementary material, which is available to authorized users.

Abstract 1093: Sensitive detection of somatic mutations in class I HLA genes reveals enrichment for functional events in cancer

Abstract Recent studies have revealed enhanced somatic mutation rate in HLA genes in several tumor types and has strongly implicated HLA dysfunction as a possible mediator of immune evasion. Mutation detection in this highly polymorphic and GC-rich locus, however, is complicated by suboptimal alignment to the canonical reference genome and lowered capture efficiency. To address this challenge, we developed the POLYSOLVER (POLYmorphic loci reSOLVER) algorithm for accurate inference of class I HLA-A, -B and -C alleles from whole exome sequencing (WES) data, which can then be used for more sensitive and specific mutation detection. POLYSOLVER comprises two broad steps: alignment optimization and subsequent inference of the alleles using a Bayesian classifier. When applied to 133 HapMap samples of known HLA type, POLYSOLVER outperformed other publicly available tools with an overall protein-level accuracy of 97% and was particularly more powerful at low sequencing depths with an overall accuracy of 96%. To accurately detect HLA mutations in tumor samples, we performed HLA typing by applying POLYSOLVER to the paired germline sample, re-aligned the HLA reads from both tumor and normal to the inferred HLA alleles while filtering out likely erroneous alignments, and then applied standard tools (MuTect and Strelka) to detect somatic mutations by comparing the re-aligned tumor and normal HLA reads. Based on orthogonal RNA-Seq validation, we estimate an improvement in sensitivity from 57.1% to 94.3% and specificity from 43.8% to 81.3% over standard methods. Pan-cancer analysis of TCGA data from 3,608 tumor/normal pairs by POLYSOLVER across 12 tumor types revealed 147 non-silent HLA mutations in 121 patients. We identified colon adenocarcinoma to be significantly affected by somatic mutation in class I HLA genes, further supporting HLA mutation as a common oncogenic mechanism. By contrast, HLA mutations were not detected in chronic lymphocytic leukemia (n = 129). Alterations likely to have a functional effect, including loss-of-function, were significantly enriched in HLA mutations compared to non-HLA mutations (P &amp;lt; 2.2×10-16). We also observed that 70 of the 147 total HLA mutations (47.6%) fell in 23 recurrent sites suggesting positive selection at these positions. Finally, we determined that the majority of the detected mutations mapped to regions critical for antigen presentation. In addition to enabling better detection of HLA mutations, accurate HLA typing by POLYSOLVER can also be used to study germline associations of HLA alleles in diseases, and in donor screening for organ transplantation. It may be extended to extracting typing and mutation information from whole genome or RNA sequencing data and from other polymorphic regions in the genome such as MHC class II, TAP1 and TAP2 genes, and MIC-A and MIC-B ligands. POLYSOLVER hence is a generally applicable analysis framework to address these otherwise challenging loci. Citation Format: Sachet A. Shukla, Mohini Rajasagi, Philip Dixon, Grace Tiao, Michael S. Lawrence, Carrie Sougnez, Vladimir Brusic, Kristian Cibulskis, Adam Kiezun, Catherine J. Wu, Gad Getz. Sensitive detection of somatic mutations in class I HLA genes reveals enrichment for functional events in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1093. doi:10.1158/1538-7445.AM2015-1093

Abstract 4868: CODEX: a normalization and copy number variation detection method for whole-exome sequencing

Abstract Background: High throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of cancer. Copy number aberration (CNA) is an important type of genomic change, but detecting and characterizing CNA from whole-exome sequencing (WES) is challenging due to the high level of biases and artifacts. Methods: We propose CODEX, a normalization and CNA calling procedure for WES data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based WES data. CODEX can be used to detect both germline and somatic CNAs in cancer samples with or without matched normal. Results: Compared to existing approaches, CODEX is shown to be more effective in removing the biases in WES, and attains better sensitivity and specificity in detecting copy number aberrations by in silico spike-in studies. We further evaluate performance on 222 neuroblastoma samples with matched normal from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Project. We carry out systematic genome-wide analysis and detailed characterization of both germline and somatic copy number events. With a focus on a well-studied rare somatic CNV within the ATRX gene, we show that the cross-sample normalization procedure of CODEX is more effective in removing noise than the standard pipeline of normalizing the tumor against the matched normal, and that the segmentation procedure performs well in detecting CNVs with recurrent complex nested structures. For detecting germline mutations, CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be perform well on three microarray-based validation data sets. Conclusions: The cross-sample normalization procedure of CODEX, when applied to the matrix of tumor and normal samples, is more effective in reducing noise than normalizing each tumor to its matched normal. The somatic deletions in the ATRX region have a nested structure, which CODEX was able to recover. Through multiple types of validation, CODEX is shown to be applicable to a wide range of study designs for copy number estimation using WES data. Citation Format: Yuchao Jiang, Derek A. Oldridge, Sharon J. Diskin, Nancy R. Zhang. CODEX: a normalization and copy number variation detection method for whole-exome sequencing. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4868. doi:10.1158/1538-7445.AM2015-4868

Genome-wide analysis links NFATC2 with asparaginase hypersensitivity

AbstractAsparaginase is used to treat acute lymphoblastic leukemia (ALL); however, hypersensitivity reactions can lead to suboptimal asparaginase exposure. Our objective was to use a genome-wide approach to identify loci associated with asparaginase hypersensitivity in children with ALL enrolled on St. Jude Children's Research Hospital (SJCRH) protocols Total XIIIA (n = 154), Total XV (n = 498), and Total XVI (n = 271), or Children's Oncology Group protocols POG 9906 (n = 222) and AALL0232 (n = 2163). Germline DNA was genotyped using the Affymetrix 500K, Affymetrix 6.0, or the Illumina Exome BeadChip array. In multivariate logistic regression, the intronic rs6021191 variant in nuclear factor of activated T cells 2 (NFATC2) had the strongest association with hypersensitivity (P = 4.1 × 10−8; odds ratio [OR] = 3.11). RNA-seq data available from 65 SJCRH ALL tumor samples and 52 Yoruba HapMap samples showed that samples carrying the rs6021191 variant had higher NFATC2 expression compared with noncarriers (P = 1.1 × 10−3 and 0.03, respectively). The top ranked nonsynonymous polymorphism was rs17885382 in HLA-DRB1 (P = 3.2 × 10−6; OR = 1.63), which is in near complete linkage disequilibrium with the HLA-DRB1*07:01 allele we previously observed in a candidate gene study. The strongest risk factors for asparaginase allergy are variants within genes regulating the immune response.

Heritability, SNP- and Gene-Based Analyses of Cannabis Use Initiation and Age at Onset.

Prior searches for genetic variants (GVs) implicated in initiation of cannabis use have been limited to common single nucleotide polymorphisms (SNPs) typed in HapMap samples. Denser SNPs are now available with the completion of the 1000 Genomes and the Genome of the Netherlands projects. More densely distributed SNPs are expected to track the causal variants better. Therefore we extend the search for variants implicated in early stages of cannabis use to previously untagged common and low-frequency variants. We run heritability, SNP and gene-based analyses of initiation and age at onset. This is the first genome-wide study of age at onset to date. Using GCTA and a sample of distantly related individuals from the Netherlands Twin Register, we estimated that the currently measured (and tagged) SNPs collectively explain 25 % of the variance in initiation (SE = 0.088; P = 0.0016). Chromosomes 4 and 18, previously linked with cannabis use and other addiction phenotypes, account for the largest amount of variance in initiation (6.8 %, SE = 0.025, P = 0.002 and 3.6 %, SE = 0.01, P = 0.012, respectively). No individual SNP- or gene-based test reached genomewide significance in the initiation or age at onset analyses. Our study detected association signal in the currently measured SNPs. A comparison with prior SNP-heritability estimates suggests that at least part of the signal is likely coming from previously untyped common and low frequency variants. Our results do not rule out the contribution of rare variants of larger effect—a plausible source of the difference between the twin-based heritability estimate and that from GCTA. The causal variants are likely of very small effect (i.e., <1 % explained variance) and are uniformly distributed over the genome in proportion to chromosomes’ length. Similar to other complex traits and diseases, detecting such small effects is to be expected in sufficiently large samples.Electronic supplementary materialThe online version of this article (doi:10.1007/s10519-015-9723-9) contains supplementary material, which is available to authorized users.