Sequencing Depth Coverage Research Articles

Telling plant species apart with DNA: from barcodes to genomes.

Land plants underpin a multitude of ecosystem functions, support human livelihoods and represent a critically important component of terrestrial biodiversity—yet many tens of thousands of species await discovery, and plant identification remains a substantial challenge, especially where material is juvenile, fragmented or processed. In this opinion article, we tackle two main topics. Firstly, we provide a short summary of the strengths and limitations of plant DNA barcoding for addressing these issues. Secondly, we discuss options for enhancing current plant barcodes, focusing on increasing discriminatory power via either gene capture of nuclear markers or genome skimming. The former has the advantage of establishing a defined set of target loci maximizing efficiency of sequencing effort, data storage and analysis. The challenge is developing a probe set for large numbers of nuclear markers that works over sufficient phylogenetic breadth. Genome skimming has the advantage of using existing protocols and being backward compatible with existing barcodes; and the depth of sequence coverage can be increased as sequencing costs fall. Its non-targeted nature does, however, present a major informatics challenge for upscaling to large sample sets.This article is part of the themed issue ‘From DNA barcodes to biomes’.

An analytical workflow for accurate variant discovery in highly divergent regions

BackgroundCurrent variant discovery methods often start with the mapping of short reads to a reference genome; yet, their performance deteriorates in genomic regions where the reads are highly divergent from the reference sequence. This is particularly problematic for the human leukocyte antigen (HLA) region on chromosome 6p21.3. This region is associated with over 100 diseases, but variant calling is hindered by the extreme divergence across different haplotypes.ResultsWe simulated reads from chromosome 6 exonic regions over a wide range of sequence divergence and coverage depth. We systematically assessed combinations between five mappers and five callers for their performance on simulated data and exome-seq data from NA12878, a well-studied individual in which multiple public call sets have been generated. Among those combinations, the number of known SNPs differed by about 5 % in the non-HLA regions of chromosome 6 but over 20 % in the HLA region. Notably, GSNAP mapping combined with GATK UnifiedGenotyper calling identified about 20 % more known SNPs than most existing methods without a noticeable loss of specificity, with 100 % sensitivity in three highly polymorphic HLA genes examined. Much larger differences were observed among these combinations in INDEL calling from both non-HLA and HLA regions. We obtained similar results with our internal exome-seq data from a cohort of chronic lymphocytic leukemia patients.ConclusionsWe have established a workflow enabling variant detection, with high sensitivity and specificity, over the full spectrum of divergence seen in the human genome. Comparing to public call sets from NA12878 has highlighted the overall superiority of GATK UnifiedGenotyper, followed by GATK HaplotypeCaller and SAMtools, in SNP calling, and of GATK HaplotypeCaller and Platypus in INDEL calling, particularly in regions of high sequence divergence such as the HLA region. GSNAP and Novoalign are the ideal mappers in combination with the above callers. We expect that the proposed workflow should be applicable to variant discovery in other highly divergent regions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3045-z) contains supplementary material, which is available to authorized users.

Cancer related gene alterations can be detected with next-generation sequencing analysis of bile in diffusely infiltrating type cholangiocarcinoma

Genome-wide association study in diffusely infiltrating type cholangiocarcinoma (CC) can be limited due to the difficulty of obtaining tumor tissue. We aimed to evaluate the genomic alterations of diffusely infiltrating type CC using next-generation sequencing (NGS) of bile and to compare the variations with those of mass-forming type CC. A total of 24 bile samples obtained during endoscopic retrograde cholangiopancreatography (ERCP) and 17 surgically obtained tumor tissue samples were evaluated. Buffy coat and normal tissue samples were used as controls for a somatic mutation analysis. After extraction of genomic DNA, NGS analysis was performed for 48 cancer related genes. There were 27 men and 14 women with a mean age of 65.0±11.8years. The amount of extracted genomic DNA from 3cm3 of bile was 66.0±84.7μg and revealed a high depth of sequencing coverage. All of the patients had genomic variations, with an average number of 19.4±2.8 and 22.3±3.3 alterations per patient from the bile and tumor tissue, respectively. After filtering process, damaging SNPs (8 sites for each type of CC) were predicted by analyzing tools, and their target genes showed relevant differences between the diffusely infiltrating and mass-forming type CC. Finally, in somatic mutation analysis, tumor-normal paired 14 tissue and 6 bile samples were analyzed, genomic alterations of EGFR, FGFR1, ABL1, PIK3CA, and CDKN2A gene were seen in the diffusely infiltrating type CC, and TP53, KRAS, APC, GNA11, ERBB4, ATM, SMAD4, BRAF, and IDH1 were altered in the mass-forming type CC group. STK11, GNAQ, RB1, KDR, and SMO genes were revealed in both groups. The NGS analysis was feasible with bile sample and diffusely infiltrating type CC revealed genetic differences compared with mass-forming type CC. Genome-wide association study could be performed using bile sample in the patients with CC undergoing ERCP and a different genetic approach for accurate diagnosis, pathogenesis study, and targeted therapy will be needed in diffusely infiltrating type CC.

Analysis of Short Tandem Repeat and Single Nucleotide Polymorphism Loci From Single-Source Samples Using a Custom HaloPlex Target Enrichment System Panel.

Short tandem repeats and single nucleotide polymorphisms (SNPs) are used to individualize biological evidence samples. Short tandem repeat alleles are characterized by size separation during capillary electrophoresis (CE). Massively parallel sequencing (MPS) offers an alternative that can overcome limitations of the CE. With MPS, libraries are prepared for each sample, entailing target enrichment and bar coding, purification, and normalization. The HaloPlex Target Enrichment System (Agilent Technologies) uses a capture-based enrichment system with restriction enzyme digestion to generate fragments containing custom-selected markers. It offers another possible workflow for typing reference samples. Its efficacy was assessed using a panel of 275 human identity SNPs, 88 short tandem repeats, and amelogenin. The data analyzed included locus typing success, depth of sequence coverage, heterozygote balance, and concordance. The results indicate that the HaloPlex Target Enrichment System provides genetic data similar to that obtained by conventional polymerase chain reaction-CE methods with the advantage of analyzing substantially more markers in 1 sequencing run. The genetic typing performance of HaloPlex is comparable to other MPS-based sample preparation systems that utilize primer-based target enrichment.

Overview of Target Enrichment Strategies.

Target enrichment is commonly used in next generation sequencing (NGS) workflows to eliminate genomic DNA regions that are not of interest for a particular experiment. By only targeting specific regions such as exons, one can obtain greater depth of DNA sequencing coverage for regions of interest or increase the sampling numbers of individuals, thereby saving both time and cost. This overview of target enrichment strategies provides a high-level review of distinct approaches to capture specific sequences: (a) hybridization-based strategies, (b) transposon-mediated fragmentation (tagmentation), (c) molecular inversion probes (MIPs), and (d) singleplex and multiplex polymerase chain reaction (PCR) target enrichment. Strategies for assay design and performance criteria are also discussed. Other platforms currently in development are also briefly described.

Exon capture phylogenomics: efficacy across scales of divergence.

The evolutionary histories of species are not measured directly, but estimated using genealogies inferred for particular loci. Individual loci can have discordant histories, but in general we expect to infer evolutionary histories more accurately as more of the genome is sampled. High Throughput Sequencing (HTS) is now providing opportunities to incorporate thousands of loci in 'phylogenomic' studies. Here, we used target enrichment to sequence c.3000 protein-coding exons in a group of Australian skink lizards (crown group age c.80Ma). This method uses synthetic probes to 'capture' target exons that were identified in the transcriptomes of selected probe design (PD) samples. The target exons are then enriched in sample DNA libraries prior to performing HTS. Our main goal was to study the efficacy of enrichment of targeted loci at different levels of phylogenetic divergence from the PD species. In taxa sharing a common ancestor with PD samples up to c.20Ma, we detected little reduction in efficacy, measured here as sequencing depth of coverage. However, at around 80Myr divergence from the PD species, we observed an approximately two-fold reduction in efficacy. A secondary goal was to develop a workflow for analysing exon capture studies of phylogenetically diverse samples, while minimizing potential bias. Our approach assembles each exon in each sample separately, by first recruiting short sequencing reads having homology to the corresponding protein sequence. In sum, custom exon capture provides a complement to existing, more generic target capture methods and is a practical and robust option across low-moderate levels of phylogenetic divergence.

The BisPCR(2) method for targeted bisulfite sequencing.

BackgroundDNA methylation has emerged as an important regulator of development and disease, necessitating the design of more efficient and cost-effective methods for detecting and quantifying this epigenetic modification. Next-generation sequencing (NGS) techniques offer single base resolution of CpG methylation levels with high statistical significance, but are also high cost if performed genome-wide. Here, we describe a simplified targeted bisulfite sequencing approach in which DNA sequencing libraries are prepared following sodium bisulfite conversion and two rounds of PCR for target enrichment and sample barcoding, termed BisPCR2.ResultsWe have applied the BisPCR2 technique to validate differential methylation at several type 2 diabetes risk loci identified in genome-wide studies of human islets. We confirmed some previous findings while not others, in addition to identifying novel differentially methylated CpGs at these genes of interest, due to the much higher depth of sequencing coverage in BisPCR2 compared to prior array-based approaches.ConclusionThis study presents a robust, efficient, and cost-effective technique for targeted bisulfite NGS, and illustrates its utility by reanalysis of prior findings from genome-wide studies.Electronic supplementary materialThe online version of this article (doi:10.1186/s13072-015-0020-x) contains supplementary material, which is available to authorized users.

LayerCake: a tool for the visual comparison of viral deep sequencing data.

The advent of next-generation sequencing (NGS) has created unprecedented opportunities to examine viral populations within individual hosts, among infected individuals and over time. Comparing sequence variability across viral genomes allows for the construction of complex population structures, the analysis of which can yield powerful biological insights. However, the simultaneous display of sequence variation, coverage depth and quality scores across thousands of bases presents a unique visualization challenge that has not been fully met by current NGS analysis tools. Here, we present LayerCake, a self-contained visualization tool that allows for the rapid analysis of variation in viral NGS data. LayerCake enables the user to simultaneously visualize variations in multiple viral populations across entire genomes within a highly customizable framework, drawing attention to pertinent and interesting patterns of variation. We have successfully deployed LayerCake to assist with a variety of different genomics datasets. Program downloads and detailed instructions are available at http://graphics.cs.wisc.edu/WP/layercake under a modified MIT license. LayerCake is a cross-platform tool written in the Processing framework for Java. mcorrell@cs.wisc.edu.

Single-cell genomics-based analysis of virus-host interactions in marine surface bacterioplankton.

Viral infections dynamically alter the composition and metabolic potential of marine microbial communities and the evolutionary trajectories of host populations with resulting feedback on biogeochemical cycles. It is quite possible that all microbial populations in the ocean are impacted by viral infections. Our knowledge of virus–host relationships, however, has been limited to a minute fraction of cultivated host groups. Here, we utilized single-cell sequencing to obtain genomic blueprints of viruses inside or attached to individual bacterial and archaeal cells captured in their native environment, circumventing the need for host and virus cultivation. A combination of comparative genomics, metagenomic fragment recruitment, sequence anomalies and irregularities in sequence coverage depth and genome recovery were utilized to detect viruses and to decipher modes of virus–host interactions. Members of all three tailed phage families were identified in 20 out of 58 phylogenetically and geographically diverse single amplified genomes (SAGs) of marine bacteria and archaea. At least four phage–host interactions had the characteristics of late lytic infections, all of which were found in metabolically active cells. One virus had genetic potential for lysogeny. Our findings include first known viruses of Thaumarchaeota, Marinimicrobia, Verrucomicrobia and Gammaproteobacteria clusters SAR86 and SAR92. Viruses were also found in SAGs of Alphaproteobacteria and Bacteroidetes. A high fragment recruitment of viral metagenomic reads confirmed that most of the SAG-associated viruses are abundant in the ocean. Our study demonstrates that single-cell genomics, in conjunction with sequence-based computational tools, enable in situ, cultivation-independent insights into host–virus interactions in complex microbial communities.

Multi-locus analysis of genomic time series data from experimental evolution.

Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the genome and across sampled time points, in an approximate but principled manner. We first use simulated data to demonstrate the power of our method to correctly detect, locate and estimate the fitness of a selected allele from among several linked sites. We study how this power changes for different values of selection strength, initial haplotypic diversity, population size, sampling frequency, experimental duration, number of replicates, and sequencing coverage depth. In addition to providing quantitative estimates of selection parameters from experimental evolution data, our model can be used by practitioners to design E&R experiments with requisite power. We also explore how our likelihood-based approach can be used to infer other model parameters, including effective population size and recombination rate. Then, we apply our method to analyze genome-wide data from a real E&R experiment designed to study the adaptation of D. melanogaster to a new laboratory environment with alternating cold and hot temperatures.

Clinical exome performance for reporting secondary genetic findings.

Reporting clinically actionable incidental genetic findings in the course of clinical exome testing is recommended by the American College of Medical Genetics and Genomics (ACMG). However, the performance of clinical exome methods for reporting small subsets of genes has not been previously reported. In this study, 57 exome data sets performed as clinical (n = 12) or research (n = 45) tests were retrospectively analyzed. Exome sequencing data was examined for adequacy in the detection of potentially pathogenic variant locations in the 56 genes described in the ACMG incidental findings recommendation. All exons of the 56 genes were examined for adequacy of sequencing coverage. In addition, nucleotide positions annotated in HGMD (Human Gene Mutation Database) were examined. The 56 ACMG genes have 18 336 nucleotide variants annotated in HGMD. None of the 57 exome data sets possessed a HGMD variant. The clinical exome test had inadequate coverage for >50% of HGMD variant locations in 7 genes. Six exons from 6 different genes had consistent failure across all 3 test methods; these exons had high GC content (76%-84%). The use of clinical exome sequencing for the interpretation and reporting of subsets of genes requires recognition of the substantial possibility of inadequate depth and breadth of sequencing coverage at clinically relevant locations. Inadequate depth of coverage may contribute to false-negative clinical exome results.

Quality scores for 32,000 genomes.

BackgroundMore than 80% of the microbial genomes in GenBank are of ‘draft’ quality (12,553 draft vs. 2,679 finished, as of October, 2013). We have examined all the microbial DNA sequences available for complete, draft, and Sequence Read Archive genomes in GenBank as well as three other major public databases, and assigned quality scores for more than 30,000 prokaryotic genome sequences.ResultsScores were assigned using four categories: the completeness of the assembly, the presence of full-length rRNA genes, tRNA composition and the presence of a set of 102 conserved genes in prokaryotes. Most (~88%) of the genomes had quality scores of 0.8 or better and can be safely used for standard comparative genomics analysis. We compared genomes across factors that may influence the score. We found that although sequencing depth coverage of over 100x did not ensure a better score, sequencing read length was a better indicator of sequencing quality. With few exceptions, most of the 30,000 genomes have nearly all the 102 essential genes.ConclusionsThe score can be used to set thresholds for screening data when analyzing “all published genomes” and reference data is either not available or not applicable. The scores highlighted organisms for which commonly used tools do not perform well. This information can be used to improve tools and to serve a broad group of users as more diverse organisms are sequenced. Unexpectedly, the comparison of predicted tRNAs across 15,000 high quality genomes showed that anticodons beginning with an ‘A’ (codons ending with a ‘U’) are almost non-existent, with the exception of one arginine codon (CGU); this has been noted previously in the literature for a few genomes, but not with the depth found here.

HiTSelect: a comprehensive tool for high-complexity-pooled screen analysis.

Genetic screens of an unprecedented scale have recently been made possible by the availability of high-complexity libraries of synthetic oligonucleotides designed to mediate either gene knockdown or gene knockout, coupled with next-generation sequencing. However, several sources of random noise and statistical biases complicate the interpretation of the resulting high-throughput data. We developed HiTSelect, a comprehensive analysis pipeline for rigorously selecting screen hits and identifying functionally relevant genes and pathways by addressing off-target effects, controlling for variance in both gene silencing efficiency and sequencing depth of coverage and integrating relevant metadata. We document the superior performance of HiTSelect using data from both genome-wide RNAi and CRISPR/Cas9 screens. HiTSelect is implemented as an open-source package, with a user-friendly interface for data visualization and pathway exploration. Binary executables are available at http://sourceforge.net/projects/hitselect/, and the source code is available at https://github.com/diazlab/HiTSelect.

Choice of reference sequence and assembler for alignment of Listeria monocytogenes short-read sequence data greatly influences rates of error in SNP analyses.

The wide availability of whole-genome sequencing (WGS) and an abundance of open-source software have made detection of single-nucleotide polymorphisms (SNPs) in bacterial genomes an increasingly accessible and effective tool for comparative analyses. Thus, ensuring that real nucleotide differences between genomes (i.e., true SNPs) are detected at high rates and that the influences of errors (such as false positive SNPs, ambiguously called sites, and gaps) are mitigated is of utmost importance. The choices researchers make regarding the generation and analysis of WGS data can greatly influence the accuracy of short-read sequence alignments and, therefore, the efficacy of such experiments. We studied the effects of some of these choices, including: i) depth of sequencing coverage, ii) choice of reference-guided short-read sequence assembler, iii) choice of reference genome, and iv) whether to perform read-quality filtering and trimming, on our ability to detect true SNPs and on the frequencies of errors. We performed benchmarking experiments, during which we assembled simulated and real Listeria monocytogenes strain 08-5578 short-read sequence datasets of varying quality with four commonly used assemblers (BWA, MOSAIK, Novoalign, and SMALT), using reference genomes of varying genetic distances, and with or without read pre-processing (i.e., quality filtering and trimming). We found that assemblies of at least 50-fold coverage provided the most accurate results. In addition, MOSAIK yielded the fewest errors when reads were aligned to a nearly identical reference genome, while using SMALT to align reads against a reference sequence that is ∼0.82% distant from 08-5578 at the nucleotide level resulted in the detection of the greatest numbers of true SNPs and the fewest errors. Finally, we show that whether read pre-processing improves SNP detection depends upon the choice of reference sequence and assembler. In total, this study demonstrates that researchers should test a variety of conditions to achieve optimal results.

Population-Genetic Inference from Pooled-Sequencing Data

Although pooled-population sequencing has become a widely used approach for estimating allele frequencies, most work has proceeded in the absence of a proper statistical framework. We introduce a self-sufficient, closed-form, maximum-likelihood estimator for allele frequencies that accounts for errors associated with sequencing, and a likelihood-ratio test statistic that provides a simple means for evaluating the null hypothesis of monomorphism. Unbiased estimates of allele frequencies (where N is the number of individuals sampled) appear to be unachievable, and near-certain identification of a polymorphism requires a minor-allele frequency . A framework is provided for testing for significant differences in allele frequencies between populations, taking into account sampling at the levels of individuals within populations and sequences within pooled samples. Analyses that fail to account for the two tiers of sampling suffer from very large false-positive rates and can become increasingly misleading with increasing depths of sequence coverage. The power to detect significant allele-frequency differences between two populations is very limited unless both the number of sampled individuals and depth of sequencing coverage exceed 100.

Possible Loss of the Chloroplast Genome in the Parasitic Flowering Plant Rafflesia lagascae (Rafflesiaceae)

Rafflesia is a genus of holoparasitic plants endemic to Southeast Asia that has lost the ability to undertake photosynthesis. With short-read sequencing technology, we assembled a draft sequence of the mitochondrial genome of Rafflesia lagascae Blanco, a species endemic to the Philippine island of Luzon, with ∼350× sequencing depth coverage. Using multiple approaches, however, we were only able to identify small fragments of plastid sequences at low coverage depth (<2×) and could not recover any substantial portion of a chloroplast genome. The gene fragments we identified included photosynthesis and energy production genes (atp, ndh, pet, psa, psb, rbcL), ribosomal RNA genes (rrn16, rrn23), ribosomal protein genes (rps7, rps11, rps16), transfer RNA genes, as well as matK, accD, ycf2, and multiple nongenic regions from the inverted repeats. None of the identified plastid gene sequences had intact reading frames. Phylogenetic analysis suggests that ∼33% of these remnant plastid genes may have been horizontally transferred from the host plant genus Tetrastigma with the rest having ambiguous phylogenetic positions (<50% bootstrap support), except for psaB that was strongly allied with the plastid homolog in Nicotiana. Our inability to identify substantial plastid genome sequences from R. lagascae using multiple approaches—despite success in identifying and developing a draft assembly of the much larger mitochondrial genome—suggests that the parasitic plant genus Rafflesia may be the first plant group for which there is no recognizable plastid genome, or if present is found in cryptic form at very low levels.

Profiling Genomic Alterations Of Diffuse Large B-Cell Lymphoma (DLBCL) At Diagnosis, Relapse, and Transformation, Using a Novel Clinical Diagnostic Targeted Sequencing Platform

Whole genome and exome sequencing studies have identified numerous genomic alterations in DLBCL, but these methods have limited applicability for the clinical care of lymphoma patients due to cost, specific tissue requirements, and laborious bioinformatic analysis. FoundationOne-Heme (FOH) is a novel next-generation sequencing platform designed to provide targeted assessment of the genomic landscape of hematologic malignancies, including identification of mutations within specific genes, copy number changes, and translocations. FOH can be performed on small quantities of formalin-fixed paraffin-embedded (FFPE) tissue, detect rare variants due to extensive depth of sequencing coverage, and rapidly provide results via streamlined bioinformatic interpretation. Here we report the first experience using this novel platform to evaluate the genetic landscape of DLBCL.Genomic DNA and total RNA were isolated from FFPE tissue on a cohort of 53 cases of DLBCL, including de novo (n=30), relapsed/refractory (n=12), and large cell transformation from low-grade lymphoma (n=11). The cohort included 25 cases with combined MYC and BCL2 overexpression by IHC (criteria for positivity: >40% MYC, >70% BCL2), of which only one had a known translocation involving MYC. Adaptor ligated sequencing libraries were captured by solution hybridization using two custom bait sets targeting 374 cancer-related genes and 24 genes frequently rearranged for DNA-seq, and 258 frequently-rearranged genes for RNA-seq. All captured libraries were sequenced to high depth (Illumina HiSeq), averaging >658x for DNA and >20,000,000 total pairs for RNA, to enable the sensitive and specific detection of genomic alterations. Significant non-synonomous variants were identified as mutations from the COSMIC database, amplifications of established oncogenes, or homozygous deletions and/or clear loss-of-function mutations of known tumor suppressors.The DNA sequencing component of FOH detected translocations in BCL2, BCL6, and MYC, while the RNA sequencing component detected fusion transcripts involving BLC6 and MYC, in agreement with independent cytogenetic analysis via karyotype and FISH where available. The assay detected copy number alterations of 44 different genes, most commonly amplification of REL (15%) or loss of CDKN2A/CDKN2B (17%). The most frequent alterations of known significance are detailed in Figure 1. The most commonly altered gene was CDKN2A, exhibiting either homozygous deletion or loss of function mutation in 28% of cases. Chromatin modifying factors (e.g. MLL2, CREBBP, EZH2) represented the most frequently altered biologic category with alterations occurring in >50% of cases. Recurrent alterations in components of the Notch pathway (NOTCH1/2/4, FBXW7, SPEN), each predicted to activate the pathway, were identified in 23% of cases. Cell-of-origin was determined as per the Hans model using IHC for CD10, BCL6, and IRF4/MUM1; CD79B mutations were detected exclusively in non-GCB and EZH2 mutations were found exclusively in GCB-phenotype cases. Furthermore, IHC MYC+/BCL2+ de novo DLBCL cases (n=11) exhibited more frequent hypermutation of PIM1 (46%) compared with the 19 cases of IHC MYC-/BCL2- de novo DLBCL (11%). When comparing the various clinical categories, we found that mutations in tumor suppressors were significantly more common in relapsed/refractory than de novo DLBCL (47% vs 75%, p=0.02). Alterations in TP53 were most frequently observed in transformed lymphoma (55%).Our results demonstrate the feasibility of using a targeted next-generation sequencing platform on FFPE clinical specimens from patients with DLBCL as a means of providing an integrated analysis of gene mutations, copy number alterations, and translocations. This streamlined approach combines multiple molecular and cytogenetic tests into a single platform and uses a small amount of tissue to perform a multifaceted assessment of genomic alterations with potential diagnostic, prognostic, and therapeutic implications. Future efforts will be directed at analyzing additional cases of DLBCL to better establish the biologic and clinical significance of the observed genetic alterations, and to prospectively incorporate this novel platform to select patients for mechanism-based targeted therapy. Disclosures:Intlekofer:Foundation Medicine, Inc: Consultancy. Levine:Foundation Medicine, Inc: Consultancy. Zelenetz:Foundation Medicine, Inc: Consultancy. Palomba:Foundation Medicine, Inc: Consultancy. van den Brink:Foundation Medicine, Inc: Consultancy. Brennan:Foundation Medicine, Inc: Employment. Young:Foundation Medicine, Inc: Employment. He:Foundation Medicine, Inc: Employment. Nahas:Foundation Medicine, Inc: Employment. Yelensky:Foundation Medicine, Inc: Employment. Otto:Foundation Medicine, Inc: Employment. Lipson:Foundation Medicine, Inc: Employment. Stephens:Foundation Medicine, Inc: Employment. Miller:Foundation Medicine, Inc: Employment. Younes:Foundation Medicine, Inc: Consultancy.▪

Targeted next‐generation sequencing using fine‐needle aspirates from adenocarcinomas of the lung

Molecular testing of cancer is increasingly critical to medicine. Next-generation sequencing (NGS) provides comprehensive, unbiased, and inexpensive mutation analysis of multiple genes with a single test. However, to the authors' knowledge, the usefulness of NGS in fine-needle aspiration (FNA) specimens, which may be the only specimens available, is unknown. Non-small cell lung cancer (NSCLC) is an ideal model in which to evaluate cytopathologic applications of NGS because FNA is used for diagnosis and staging and specific molecular therapeutic targets in NSCLC are known. Herein, the performance and quality of targeted NGS in FNA specimens from a small series of lung adenocarcinomas is evaluated. Sequence data were generated from FNA specimens and paired formalin-fixed paraffin-embedded (FFPE) tissues from 5 patients with lung adenocarcinoma. DNA was isolated from FNA aspirate smears and cores of FFPE tissue. Multiplex sequencing of 27 cancer-related genes was performed after hybrid capture enrichment. Read-quality metrics and single-nucleotide variant calls were compared. The overall concordance of total reads across specimens was > 99% and the average concordance of single-nucleotide variants was 99.5%. The total reads generated, as well as the percentages of mapped, on-target, and unique reads were statistically indistinguishable (P > 0.05) between FFPE and FNA preparations. There also was no difference in the depth of sequencing coverage, including exon-level coverage in known lung cancer mutation hotspots. DNA isolated from FNA slides yields comprehensive, accurate, and statistically indistinguishable sequence information compared with that obtained from FFPE tissue. These results support the integration of NGS technologies into the standard cytopathology workflow. Cancer (Cancer Cytopathol) 2014;122:104-13. © 2013 American Cancer Society.

Rapid genome wide mapping of phosphine resistance loci by a simple regional averaging analysis in the red flour beetle, Tribolium castaneum

BackgroundNext-generation sequencing technology is an important tool for the rapid, genome-wide identification of genetic variations. However, it is difficult to resolve the ‘signal’ of variations of interest and the ‘noise’ of stochastic sequencing and bioinformatic errors in the large datasets that are generated. We report a simple approach to identify regional linkage to a trait that requires only two pools of DNA to be sequenced from progeny of a defined genetic cross (i.e. bulk segregant analysis) at low coverage (<10×) and without parentage assignment of individual SNPs. The analysis relies on regional averaging of pooled SNP frequencies to rapidly scan polymorphisms across the genome for differential regional homozygosity, which is then displayed graphically.ResultsProgeny from defined genetic crosses of Tribolium castaneum (F4 and F19) segregating for the phosphine resistance trait were exposed to phosphine to select for the resistance trait while the remainders were left unexposed. Next generation sequencing was then carried out on the genomic DNA from each pool of selected and unselected insects from each generation. The reads were mapped against the annotated T. castaneum genome from NCBI (v3.0) and analysed for SNP variations. Since it is difficult to accurately call individual SNP frequencies when the depth of sequence coverage is low, variant frequencies were averaged across larger regions. Results from regional SNP frequency averaging identified two loci, tc_rph1 on chromosome 8 and tc_rph2 on chromosome 9, which together are responsible for high level resistance. Identification of the two loci was possible with only 5-7× average coverage of the genome per dataset. These loci were subsequently confirmed by direct SNP marker analysis and fine-scale mapping. Individually, homozygosity of tc_rph1 or tc_rph2 results in only weak resistance to phosphine (estimated at up to 1.5-2.5× and 3-5× respectively), whereas in combination they interact synergistically to provide a high-level resistance >200×. The tc_rph2 resistance allele resulted in a significant fitness cost relative to the wild type allele in unselected beetles over eighteen generations.ConclusionWe have validated the technique of linkage mapping by low-coverage sequencing of progeny from a simple genetic cross. The approach relied on regional averaging of SNP frequencies and was used to successfully identify candidate gene loci for phosphine resistance in T. castaneum. This is a relatively simple and rapid approach to identifying genomic regions associated with traits in defined genetic crosses that does not require any specialised statistical analysis.

Simultaneous and complete genome sequencing of influenza A and B with high coverage by Illumina MiSeq Platform

Active global surveillance and characterization of influenza viruses are essential for better preparation against possible pandemic events. Obtaining comprehensive information about the influenza genome can improve our understanding of the evolution of influenza viruses and emergence of new strains, and improve the accuracy when designing preventive vaccines. This study investigated the use of deep sequencing by the next-generation sequencing (NGS) Illumina MiSeq Platform to obtain complete genome sequence information from influenza virus isolates. The influenza virus isolates were cultured from 6 respiratory acute clinical specimens collected in Thailand and Nepal. DNA libraries obtained from each viral isolate were mixed and all were sequenced simultaneously. Total information of 2.6Gbases was obtained from a 455±14K/mm2 density with 95.76% (8,571,655/8,950,724 clusters) of the clusters passing quality control (QC) filters. Approximately 93.7% of all sequences from Read1 and 83.5% from Read2 contained high quality sequences that were ≥Q30, a base calling QC score standard. Alignments analysis identified three seasonal influenza A H3N2 strains, one 2009 pandemic influenza A H1N1 strain and two influenza B strains. The nearly entire genomes of all six virus isolates yielded equal or greater than 600-fold sequence coverage depth. MiSeq Platform identified seasonal influenza A H3N2, 2009 pandemic influenza A H1N1and influenza B in the DNA library mixtures efficiently.