Multi-Sample Pooling and Illumina Genome Analyzer Sequencing Methods to Determine Gene Sequence Variation for Database Development

Determination of sequence variation within a genetic locus to develop clinically relevant databases is critical for molecular assay design and clinical test interpretation, so multisample pooling for Illumina genome analyzer (GA) sequencing was investigated using the RET proto-oncogene as a model. Samples were Sanger-sequenced for RET exons 10, 11, and 13–16. Ten samples with 13 known unique variants (“singleton variants” within the pool) and seven common changes were amplified and then equimolar-pooled before sequencing on a single flow cell lane, generating 36 base reads. For comparison, a single “control” sample was run in a different lane. After alignment, a 24-base quality score-screening threshold and 3` read end trimming of three bases yielded low background error rates with a 27% decrease in aligned read coverage. Sequencing data were evaluated using an established variant detection method (percent variant reads), by the presented subtractive correction method, and with SNPSeeker software. In total, 41 variants (of which 23 were singleton variants) were detected in the 10 pool data, which included all Sanger-identified variants. The 23 singleton variants were detected near the expected 5% allele frequency (average 5.17%±0.90% variant reads), well above the highest background error (1.25%). Based on background error rates, read coverage, simulated 30, 40, and 50 sample pool data, expected singleton allele frequencies within pools, and variant detection methods; ≥30 samples (which demonstrated a minimum 1% variant reads for singletons) could be pooled to reliably detect singleton variants by GA sequencing.     

Combinatorial pooled sequencing: experiment design and decoding

Owing to rapid advances in the next-generation sequencing technology, the cost of DNA sequencing has been reduced by over several orders of magnitude. However, genomic sequencing of individuals at the population scale is still restricted to a few model species due to the huge challenge of constructing libraries for thousands of samples. Meanwhile, pooled sequencing provides a cost-effective alternative to sequencing individuals separately, which could vastly reduce the time and cost for DNA library preparation. Technological improvements, together with the broad range of biological research questions that require large sample sizes, mean that pooled sequencing will continue to complement the sequencing of individual genomes and become increasingly important in the foreseeable future. However, simply mixing samples together for sequencing makes it impossible to identify reads that belongs to each sample. Barcoding technology could help to solve this problem, nonetheless, currently, barcoding every sample is costly especially for large-scale samples. An alternative to barcoding is combinatorial pooled sequencing which employs pooling pattern rather than short DNA barcodes to encode each sample. In combinatorial pooled sequencing, samples are mixed into few pools according to a carefully designed pooling strategy which allows the sequencing data to be decoded to identify the reads that belongs to the sample that are unique or rare in the population. In this review, we mainly survey the experiment design and decoding procedure for the combinatorial pooled sequencing applied in rare variant and rare haplotype carriers screening, complex genome assembling and single individual haplotyping.     

A Two-Dimensional Pooling Strategy for Rare Variant Detection on Next-Generation Sequencing Platforms

We describe a method for pooling and sequencing DNA from a large number of individual samples while preserving information regarding sample identity. DNA from 576 individuals was arranged into four 12 row by 12 column matrices and then pooled by row and by column resulting in 96 total pools with 12 individuals in each pool. Pooling of DNA was carried out in a two-dimensional fashion, such that DNA from each individual is present in exactly one row pool and exactly one column pool. By considering the variants observed in the rows and columns of a matrix we are able to trace rare variants back to the specific individuals that carry them. The pooled DNA samples were enriched over a 250 kb region previously identified by GWAS to significantly predispose individuals to lung cancer. All 96 pools (12 row and 12 column pools from 4 matrices) were barcoded and sequenced on an Illumina HiSeq 2000 instrument with an average depth of coverage greater than 4,000×. Verification based on Ion PGM sequencing confirmed the presence of 91.4% of confidently classified SNVs assayed. In this way, each individual sample is sequenced in multiple pools providing more accurate variant calling than a single pool or a multiplexed approach. This provides a powerful method for rare variant detection in regions of interest at a reduced cost to the researcher.     

Index hopping on the Illumina HiseqX platform and its consequences for ancient DNA studies

The high‐throughput capacities of the Illumina sequencing platforms and the possibility to label samples individually have encouraged wide use of sample multiplexing. However, this practice results in read misassignment (usually <1%) across samples sequenced on the same lane. Alarmingly high rates of read misassignment of up to 10% were reported for lllumina sequencing machines with exclusion amplification chemistry. This may make use of these platforms prohibitive, particularly in studies that rely on low‐quantity and low‐quality samples, such as historical and archaeological specimens. Here, we use barcodes, short sequences that are ligated to both ends of the DNA insert, to directly quantify the rate of index hopping in 100‐year old museum‐preserved gorilla (Gorilla beringei) samples. Correcting for multiple sources of noise, we identify on average 0.470% of reads containing a hopped index. We show that sample‐specific quantity of misassigned reads depends on the number of reads that any given sample contributes to the total sequencing pool, so that samples with few sequenced reads receive the greatest proportion of misassigned reads. This particularly affects ancient DNA samples, as these frequently differ in their DNA quantity and endogenous content. Through simulations we show that even low rates of index hopping, as reported here, can lead to biases in ancient DNA studies when multiplexing samples with vastly different quantities of endogenous material.     

Efficient and cost effective population resequencing by pooling and in-solution hybridization

High-throughput sequencing of targeted genomic loci in large populations is an effective approach for evaluating the contribution of rare variants to disease risk. We evaluated the feasibility of using in-solution hybridization-based target capture on pooled DNA samples to enable cost-efficient population sequencing studies. For this, we performed pooled sequencing of 100 HapMap samples across ～ 600 kb of DNA sequence using the Illumina GAIIx. Using our accurate variant calling method for pooled sequence data, we were able to not only identify single nucleotide variants with a low false discovery rate (<1%) but also accurately detect short insertion/deletion variants. In addition, with sufficient coverage per individual in each pool (30-fold) we detected 97.2% of the total variants and 93.6% of variants below 5% in frequency. Finally, allele frequencies for single nucleotide variants (SNVs) estimated from the pooled data and the HapMap genotype data were tightly correlated (correlation coefficient > = 0.995).     

Alta-Cyclic: a self-optimizing base caller for next-generation sequencing

Next-generation sequencing is limited to short read lengths and by high error rates. We systematically analyzed sources of noise in the Illumina Genome Analyzer that contribute to these high error rates and developed a base caller, Alta-Cyclic, that uses machine learning to compensate for noise factors. Alta-Cyclic substantially improved the number of accurate reads for sequencing runs up to 78 bases and reduced systematic biases, facilitating confident identification of sequence variants.     

Comparison of the Illumina Genome Analyzer and Roche 454 GS FLX for Resequencing of Hypertrophic Cardiomyopathy-Associated Genes

Next-generation sequencing (NGS) is widely used in biomedical research, but its adoption has been limited in molecular diagnostics. One application of NGS is the targeted resequencing of genes whose mutations lead to an overlapping clinical phenotype. This study evaluated the comparative performance of the Illumina Genome Analyzer and Roche 454 GS FLX for the resequencing of 16 genes associated with hypertrophic cardiomyopathy (HCM). Using a single human genomic DNA sample enriched by long-range PCR (LR-PCR), 40 GS FLX and 31 Genome Analyzer exon variants were identified using ≥30-fold read-coverage and ≥20% read-percentage selection criteria. Twenty-seven platform concordant variants were Sanger-confirmed. The discordant variants segregated into two categories: variants with read coverages ≥30 on one platform but <30-fold on the alternate platform and variants with read percentages ≥20% on one platform but <20% on the alternate platform. All variants with <30-fold coverage were Sanger-confirmed, suggesting that the coverage criterion of ≥30-fold is too stringent for variant discovery. The variants with <20% read percentage were identified as reference sequence based on Sanger sequencing. These variants were found in homopolymer tracts and short-read misalignments, specifically in genes with high identity. The results of the current study demonstrate the feasibility of combining LR-PCR with the Genome Analyzer or GS FLX for targeted resequencing of HCM-associated genes.     

A platform-independent method for detecting errors in metagenomic sequencing data: DRISEE

We provide a novel method, DRISEE (duplicate read inferred sequencing error estimation), to assess sequencing quality (alternatively referred to as "noise" or "error") within and/or between sequencing samples. DRISEE provides positional error estimates that can be used to inform read trimming within a sample. It also provides global (whole sample) error estimates that can be used to identify samples with high or varying levels of sequencing error that may confound downstream analyses, particularly in the case of studies that utilize data from multiple sequencing samples. For shotgun metagenomic data, we believe that DRISEE provides estimates of sequencing error that are more accurate and less constrained by technical limitations than existing methods that rely on reference genomes or the use of scores (e.g. Phred). Here, DRISEE is applied to (non amplicon) data sets from both the 454 and Illumina platforms. The DRISEE error estimate is obtained by analyzing sets of artifactual duplicate reads (ADRs), a known by-product of both sequencing platforms. We present DRISEE as an open-source, platform-independent method to assess sequencing error in shotgun metagenomic data, and utilize it to discover previously uncharacterized error in de novo sequence data from the 454 and Illumina sequencing platforms.     

The effects of read length,quality and quantity on microsatellite discovery and primer development: from Illumina to PacBio

The advent of next‐generation sequencing (NGS) technologies has transformed the way microsatellites are isolated for ecological and evolutionary investigations. Recent attempts to employ NGS for microsatellite discovery have used the 454, Illumina, and Ion Torrent platforms, but other methods including single‐molecule real‐time DNA sequencing (Pacific Biosciences or PacBio) remain viable alternatives. We outline a workflow from sequence quality control to microsatellite marker validation in three plant species using PacBio circular consensus sequencing (CCS). We then evaluate the performance of PacBio CCS in comparison with other NGS platforms for microsatellite isolation, through simulations that focus on variations in read length, read quantity and sequencing error rate. Although quality control of CCS reads reduced microsatellite yield by around 50%, hundreds of microsatellite loci that are expected to have improved conversion efficiency to functional markers were retrieved for each species. The simulations quantitatively validate the advantages of long reads and emphasize the detrimental effects of sequencing errors on NGS‐enabled microsatellite development. In view of the continuing improvement in read length on NGS platforms, sequence quality and the corresponding strategies of quality control will become the primary factors to consider for effective microsatellite isolation. Among current options, PacBio CCS may be optimal for rapid, small‐scale microsatellite development due to its flexibility in scaling sequencing effort, while platforms such as Illumina MiSeq will provide cost‐efficient solutions for multispecies microsatellite projects.     

Read length versus Depth of Coverage for Viral Quasispecies Reconstruction

Recent advancements of sequencing technology have opened up unprecedented opportunities in many application areas. Virus samples can now be sequenced efficiently with very deep coverage to infer the genetic diversity of the underlying virus populations. Several sequencing platforms with different underlying technologies and performance characteristics are available for viral diversity studies. Here, we investigate how the differences between two common platforms provided by 454/Roche and Illumina affect viral diversity estimation and the reconstruction of viral haplotypes. Using a mixture of ten HIV clones sequenced with both platforms and additional simulation experiments, we assessed the trade-off between sequencing coverage, read length, and error rate. For fixed costs, short Illumina reads can be generated at higher coverage and allow for detecting variants at lower frequencies. They can also be sufficient to assess the diversity of the sample if sequences are dissimilar enough, but, in general, assembly of full-length haplotypes is feasible only with the longer 454/Roche reads. The quantitative comparison highlights the advantages and disadvantages of both platforms and provides guidance for the design of viral diversity studies.     

Analysis of the genetic diversity of influenza A viruses using next-generation DNA sequencing

Background

Influenza viruses exist as a large group of closely related viral genomes, also called quasispecies. The composition of this influenza viral quasispecies can be determined by an accurate and sensitive sequencing technique and data analysis pipeline. We compared the suitability of two benchtop next-generation sequencers for whole genome influenza A quasispecies analysis: the Illumina MiSeq sequencing-by-synthesis and the Ion Torrent PGM semiconductor sequencing technique.

Results

We first compared the accuracy and sensitivity of both sequencers using plasmid DNA and different ratios of wild type and mutant plasmid. Illumina MiSeq sequencing reads were one and a half times more accurate than those of the Ion Torrent PGM. The majority of sequencing errors were substitutions on the Illumina MiSeq and insertions and deletions, mostly in homopolymer regions, on the Ion Torrent PGM. To evaluate the suitability of the two techniques for determining the genome diversity of influenza A virus, we generated plasmid-derived PR8 virus and grew this virus in vitro. We also optimized an RT-PCR protocol to obtain uniform coverage of all eight genomic RNA segments. The sequencing reads obtained with both sequencers could successfully be assembled de novo into the segmented influenza virus genome. After mapping of the reads to the reference genome, we found that the detection limit for reliable recognition of variants in the viral genome required a frequency of 0.5% or higher. This threshold exceeds the background error rate resulting from the RT-PCR reaction and the sequencing method. Most of the variants in the PR8 virus genome were present in hemagglutinin, and these mutations were detected by both sequencers.

Conclusions

Our approach underlines the power and limitations of two commonly used next-generation sequencers for the analysis of influenza virus gene diversity. We conclude that the Illumina MiSeq platform is better suited for detecting variant sequences whereas the Ion Torrent PGM platform has a shorter turnaround time. The data analysis pipeline that we propose here will also help to standardize variant calling in small RNA genomes based on next-generation sequencing data.     

NGSpeciesID: DNA barcode and amplicon consensus generation from long‐read sequencing data

Third‐generation sequencing technologies, such as Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), have gained popularity over the last years. These platforms can generate millions of long‐read sequences. This is not only advantageous for genome sequencing projects, but also advantageous for amplicon‐based high‐throughput sequencing experiments, such as DNA barcoding. However, the relatively high error rates associated with these technologies still pose challenges for generating high‐quality consensus sequences. Here, we present NGSpeciesID, a program which can generate highly accurate consensus sequences from long‐read amplicon sequencing technologies, including ONT and PacBio. The tool includes clustering of the reads to help filter out contaminants or reads with high error rates and employs polishing strategies specific to the appropriate sequencing platform. We show that NGSpeciesID produces consensus sequences with improved usability by minimizing preprocessing and software installation and scalability by enabling rapid processing of hundreds to thousands of samples, while maintaining similar consensus accuracy as current pipelines.     

Are special read alignment strategies necessary and cost-effective when handling sequencing reads from patient-derived tumor xenografts?

Background

Patient-derived tumor xenografts in mice are widely used in cancer research and have become important in developing personalized therapies. When these xenografts are subject to DNA sequencing, the samples could contain various amounts of mouse DNA. It has been unclear how the mouse reads would affect data analyses. We conducted comprehensive simulations to compare three alignment strategies at different mutation rates, read lengths, sequencing error rates, human-mouse mixing ratios and sequenced regions. We also sequenced a nasopharyngeal carcinoma xenograft and a cell line to test how the strategies work on real data.

Results

We found the "filtering" and "combined reference" strategies performed better than aligning reads directly to human reference in terms of alignment and variant calling accuracies. The combined reference strategy was particularly good at reducing false negative variants calls without significantly increasing the false positive rate. In some scenarios the performance gain of these two special handling strategies was too small for special handling to be cost-effective, but it was found crucial when false non-synonymous SNVs should be minimized, especially in exome sequencing.

Conclusions

Our study systematically analyzes the effects of mouse contamination in the sequencing data of human-in-mouse xenografts. Our findings provide information for designing data analysis pipelines for these data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1172) contains supplementary material, which is available to authorized users.     

Effective detection of rare variants in pooled DNA samples using Cross-pool tailcurve analysis

Sequencing targeted DNA regions in large samples is necessary to discover the full spectrum of rare variants. We report an effective Illumina sequencing strategy utilizing pooled samples with novel quality (Srfim) and filtering (SERVIC ⁴ E) algorithms. We sequenced 24 exons in two cohorts of 480 samples each, identifying 47 coding variants, including 30 present once per cohort. Validation by Sanger sequencing revealed an excellent combination of sensitivity and specificity for variant detection in pooled samples of both cohorts as compared to publicly available algorithms.     

Haplotype Estimation Using Sequencing Reads

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5–20 kb read with 4%–15% error per base), phasing performance was substantially improved.     

Targeted single molecule sequencing methodology for ovarian hyperstimulation syndrome

Background

One of the most significant issues surrounding next generation sequencing is the cost and the difficulty assembling short read lengths. Targeted capture enrichment of longer fragments using single molecule sequencing (SMS) is expected to improve both sequence assembly and base-call accuracy but, at present, there are very few examples of successful application of these technologic advances in translational research and clinical testing. We developed a targeted single molecule sequencing (T-SMS) panel for genes implicated in ovarian response to controlled ovarian hyperstimulation (COH) for infertility.

Results

Target enrichment was carried out using droplet-base multiplex polymerase chain reaction (PCR) technology (RainDance®) designed to yield amplicons averaging 1 kb fragment size from candidate 44 loci (99.8% unique base-pair coverage). The total targeted sequence was 3.18 Mb per sample. SMS was carried out using single molecule, real-time DNA sequencing (SMRT® Pacific Biosciences®), average raw read length = 1178 nucleotides, 5% of the amplicons >6000 nucleotides). After filtering with circular consensus (CCS) reads, the mean read length was 3200 nucleotides (97% CCS accuracy). Primary data analyses, alignment and filtering utilized the Pacific Biosciences® SMRT portal. Secondary analysis was conducted using the Genome Analysis Toolkit for SNP discovery l and wANNOVAR for functional analysis of variants. Filtered functional variants 18 of 19 (94.7%) were further confirmed using conventional Sanger sequencing. CCS reads were able to accurately detect zygosity. Coverage within GC rich regions (i.e.VEGFR; 72% GC rich) was achieved by capturing long genomic DNA (gDNA) fragments and reading into regions that flank the capture regions. As proof of concept, a non-synonymous LHCGR variant captured in two severe OHSS cases, and verified by conventional sequencing.

Conclusions

Combining emulsion PCR-generated 1 kb amplicons and SMRT DNA sequencing permitted greater depth of coverage for T-SMS and facilitated easier sequence assembly. To the best of our knowledge, this is the first report combining emulsion PCR and T-SMS for long reads using human DNA samples, and NGS panel designed for biomarker discovery in OHSS.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1451-2) contains supplementary material, which is available to authorized users.     

Genome assembly using Nanopore-guided long and error-free DNA reads

Background

Long-read sequencing technologies were launched a few years ago, and in contrast with short-read sequencing technologies, they offered a promise of solving assembly problems for large and complex genomes. Moreover by providing long-range information, it could also solve haplotype phasing. However, existing long-read technologies still have several limitations that complicate their use for most research laboratories, as well as in large and/or complex genome projects. In 2014, Oxford Nanopore released the MinION® device, a small and low-cost single-molecule nanopore sequencer, which offers the possibility of sequencing long DNA fragments.

Results

The assembly of long reads generated using the Oxford Nanopore MinION® instrument is challenging as existing assemblers were not implemented to deal with long reads exhibiting close to 30% of errors. Here, we presented a hybrid approach developed to take advantage of data generated using MinION® device. We sequenced a well-known bacterium, Acinetobacter baylyi ADP1 and applied our method to obtain a highly contiguous (one single contig) and accurate genome assembly even in repetitive regions, in contrast to an Illumina-only assembly. Our hybrid strategy was able to generate NaS (Nanopore Synthetic-long) reads up to 60 kb that aligned entirely and with no error to the reference genome and that spanned highly conserved repetitive regions. The average accuracy of NaS reads reached 99.99% without losing the initial size of the input MinION® reads.

Conclusions

We described NaS tool, a hybrid approach allowing the sequencing of microbial genomes using the MinION® device. Our method, based ideally on 20x and 50x of NaS and Illumina reads respectively, provides an efficient and cost-effective way of sequencing microbial or small eukaryotic genomes in a very short time even in small facilities. Moreover, we demonstrated that although the Oxford Nanopore technology is a relatively new sequencing technology, currently with a high error rate, it is already useful in the generation of high-quality genome assemblies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1519-z) contains supplementary material, which is available to authorized users.