Enhancing the detection of barcoded reads in high throughput DNA sequencing data by controlling the false discovery rate

Background

DNA barcodes are short unique sequences used to label DNA or RNA-derived samples in multiplexed deep sequencing experiments. During the demultiplexing step, barcodes must be detected and their position identified. In some cases (e.g., with PacBio SMRT), the position of the barcode and DNA context is not well defined. Many reads start inside the genomic insert so that adjacent primers might be missed. The matter is further complicated by coincidental similarities between barcode sequences and reference DNA. Therefore, a robust strategy is required in order to detect barcoded reads and avoid a large number of false positives or negatives.For mass inference problems such as this one, false discovery rate (FDR) methods are powerful and balanced solutions. Since existing FDR methods cannot be applied to this particular problem, we present an adapted FDR method that is suitable for the detection of barcoded reads as well as suggest possible improvements.

Results

In our analysis, barcode sequences showed high rates of coincidental similarities with the Mus musculus reference DNA. This problem became more acute when the length of the barcode sequence decreased and the number of barcodes in the set increased. The method presented in this paper controls the tail area-based false discovery rate to distinguish between barcoded and unbarcoded reads. This method helps to establish the highest acceptable minimal distance between reads and barcode sequences. In a proof of concept experiment we correctly detected barcodes in 83% of the reads with a precision of 89%. Sensitivity improved to 99% at 99% precision when the adjacent primer sequence was incorporated in the analysis. The analysis was further improved using a paired end strategy. Following an analysis of the data for sequence variants induced in the Atp1a1 gene of C57BL/6 murine melanocytes by ultraviolet light and conferring resistance to ouabain, we found no evidence of cross-contamination of DNA material between samples.

Conclusion

Our method offers a proper quantitative treatment of the problem of detecting barcoded reads in a noisy sequencing environment. It is based on the false discovery rate statistics that allows a proper trade-off between sensitivity and precision to be chosen.

Electronic supplementary material

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Validation of multiple single nucleotide variation calls by additional exome analysis with a semiconductor sequencer to supplement data of whole-genome sequencing of a human population

Background

Validation of single nucleotide variations in whole-genome sequencing is critical for studying disease-related variations in large populations. A combination of different types of next-generation sequencers for analyzing individual genomes may be an efficient means of validating multiple single nucleotide variations calls simultaneously.

Results

Here, we analyzed 12 independent Japanese genomes using two next-generation sequencing platforms: the Illumina HiSeq 2500 platform for whole-genome sequencing (average depth 32.4×), and the Ion Proton semiconductor sequencer for whole exome sequencing (average depth 109×). Single nucleotide polymorphism (SNP) calls based on the Illumina Human Omni 2.5-8 SNP chip data were used as the reference. We compared the variant calls for the 12 samples, and found that the concordance between the two next-generation sequencing platforms varied between 83% and 97%.

Conclusions

Our results show the versatility and usefulness of the combination of exome sequencing with whole-genome sequencing in studies of human population genetics and demonstrate that combining data from multiple sequencing platforms is an efficient approach to validate and supplement SNP calls.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-673) contains supplementary material, which is available to authorized users.     

Large scale library generation for high throughput sequencing

Background

Large efforts have recently been made to automate the sample preparation protocols for massively parallel sequencing in order to match the increasing instrument throughput. Still, the size selection through agarose gel electrophoresis separation is a labor-intensive bottleneck of these protocols.

Methodology/Principal Findings

In this study a method for automatic library preparation and size selection on a liquid handling robot is presented. The method utilizes selective precipitation of certain sizes of DNA molecules on to paramagnetic beads for cleanup and selection after standard enzymatic reactions.

Conclusions/Significance

The method is used to generate libraries for de novo and re-sequencing on the Illumina HiSeq 2000 instrument with a throughput of 12 samples per instrument in approximately 4 hours. The resulting output data show quality scores and pass filter rates comparable to manually prepared samples. The sample size distribution can be adjusted for each application, and are suitable for all high throughput DNA processing protocols seeking to control size intervals.     

Scalable transcriptome preparation for massive parallel sequencing

Background

The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity.

Methodology

In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation.

Conclusion/Significance

The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods.     

Accurate detection of subclonal single nucleotide variants in whole genome amplified and pooled cancer samples using HaloPlex target enrichment

Background

Target enrichment and resequencing is a widely used approach for identification of cancer genes and genetic variants associated with diseases. Although cost effective compared to whole genome sequencing, analysis of many samples constitutes a significant cost, which could be reduced by pooling samples before capture. Another limitation to the number of cancer samples that can be analyzed is often the amount of available tumor DNA. We evaluated the performance of whole genome amplified DNA and the power to detect subclonal somatic single nucleotide variants in non-indexed pools of cancer samples using the HaloPlex technology for target enrichment and next generation sequencing.

Results

We captured a set of 1528 putative somatic single nucleotide variants and germline SNPs, which were identified by whole genome sequencing, with the HaloPlex technology and sequenced to a depth of 792–1752. We found that the allele fractions of the analyzed variants are well preserved during whole genome amplification and that capture specificity or variant calling is not affected. We detected a large majority of the known single nucleotide variants present uniquely in one sample with allele fractions as low as 0.1 in non-indexed pools of up to ten samples. We also identified and experimentally validated six novel variants in the samples included in the pools.

Conclusion

Our work demonstrates that whole genome amplified DNA can be used for target enrichment equally well as genomic DNA and that accurate variant detection is possible in non-indexed pools of cancer samples. These findings show that analysis of a large number of samples is feasible at low cost, even when only small amounts of DNA is available, and thereby significantly increases the chances of indentifying recurrent mutations in cancer samples.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-856) contains supplementary material, which is available to authorized users.     

iMSAT: a novel approach to the development of microsatellite loci using barcoded Illumina libraries

Background

Illumina sequencing with its high number of reads and low per base pair cost is an attractive technology for development of molecular resources for non-model organisms. While many software packages have been developed to identify short tandem repeats (STRs) from next-generation sequencing data, these methods do not inform the investigator as to whether or not candidate loci are polymorphic in their target populations.

Results

We provide a python program iMSAT that uses the polymorphism data obtained from mapping individual Illumina sequence reads onto a reference genome to identify polymorphic STRs. Using this approach, we identified 9,119 candidate polymorphic STRs for use with the parasitoid wasp Trioxys pallidus and 2,378 candidate polymorphic STRs for use with the aphid Chromaphis juglandicola. For both organisms we selected 20 candidate tri-nucleotide STRs for validation. Using fluorescent-labeled oligonucleotide primers, we genotyped 91 female T. pallidus collected in nine localities and 46 female C. juglandicola collected in 4 localities and found 15 of the examined markers to be polymorphic for T. pallidus and 12 of the examined markers to be polymorphic for C. juglandicola.

Conclusions

We present a novel approach that uses standard Illumina barcoding primers and a single Illumina HiSeq run to target polymorphic STR fragments to develop and test STR markers. We validate this approach using the parasitoid wasp T. pallidus and its aphid host C. juglandicola. This approach, which would also be compatible with 454 Sequencing, allowed us to quickly identify markers with known variability. Accordingly, our method constitutes a significant improvement over existing STR identification software packages.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-858) contains supplementary material, which is available to authorized users.     

All-Food-Seq (AFS): a quantifiable screen for species in biological samples by deep DNA sequencing

Background

DNA-based methods like PCR efficiently identify and quantify the taxon composition of complex biological materials, but are limited to detecting species targeted by the choice of the primer assay. We show here how untargeted deep sequencing of foodstuff total genomic DNA, followed by bioinformatic analysis of sequence reads, facilitates highly accurate identification of species from all kingdoms of life, at the same time enabling quantitative measurement of the main ingredients and detection of unanticipated food components.

Results

Sequence data simulation and real-case Illumina sequencing of DNA from reference sausages composed of mammalian (pig, cow, horse, sheep) and avian (chicken, turkey) species are able to quantify material correctly at the 1% discrimination level via a read counting approach. An additional metagenomic step facilitates identification of traces from animal, plant and microbial DNA including unexpected species, which is prospectively important for the detection of allergens and pathogens.

Conclusions

Our data suggest that deep sequencing of total genomic DNA from samples of heterogeneous taxon composition promises to be a valuable screening tool for reference species identification and quantification in biosurveillance applications like food testing, potentially alleviating some of the problems in taxon representation and quantification associated with targeted PCR-based approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-639) contains supplementary material, which is available to authorized users.     

The Feasibility Study of Non-Invasive Fetal Trisomy 18 and 21 Detection with Semiconductor Sequencing Platform

Objective

Recent non-invasive prenatal testing (NIPT) technologies are based on next-generation sequencing (NGS). NGS allows rapid and effective clinical diagnoses to be determined with two common sequencing systems: Illumina and Ion Torrent platforms. The majority of NIPT technology is associated with Illumina platform. We investigated whether fetal trisomy 18 and 21 were sensitively and specifically detectable by semiconductor sequencer: Ion Proton.

Methods

From March 2012 to October 2013, we enrolled 155 pregnant women with fetuses who were diagnosed as high risk of fetal defects at Xiamen Maternal & Child Health Care Hospital (Xiamen, Fujian, China). Adapter-ligated DNA libraries were analyzed by the Ion Proton™ System (Life Technologies, Grand Island, NY, USA) with an average 0.3× sequencing coverage per nucleotide. Average total raw reads per sample was 6.5 million and mean rate of uniquely mapped reads was 59.0%. The results of this study were derived from BWA mapping. Z-score was used for fetal trisomy 18 and 21 detection.

Results

Interactive dot diagrams showed the minimal z-score values to discriminate negative versus positive cases of fetal trisomy 18 and 21. For fetal trisomy 18, the minimal z-score value of 2.459 showed 100% positive predictive and negative predictive values. The minimal z-score of 2.566 was used to classify negative versus positive cases of fetal trisomy 21.

Conclusion

These results provide the evidence that fetal trisomy 18 and 21 detection can be performed with semiconductor sequencer. Our data also suggest that a prospective study should be performed with a larger cohort of clinically diverse obstetrics patients.     

Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the HumanMethylation450 array

Background

The Illumina HumanMethylation450 BeadChip (HM450K) measures the DNA methylation of 485,512 CpGs in the human genome. The technology relies on hybridization of genomic fragments to probes on the chip. However, certain genomic factors may compromise the ability to measure methylation using the array such as single nucleotide polymorphisms (SNPs), small insertions and deletions (INDELs), repetitive DNA, and regions with reduced genomic complexity. Currently, there is no clear method or pipeline for determining which of the probes on the HM450K bead array should be retained for subsequent analysis in light of these issues.

Results

We comprehensively assessed the effects of SNPs, INDELs, repeats and bisulfite induced reduced genomic complexity by comparing HM450K bead array results with whole genome bisulfite sequencing. We determined which CpG probes provided accurate or noisy signals. From this, we derived a set of high-quality probes that provide unadulterated measurements of DNA methylation.

Conclusions

Our method significantly reduces the risk of false discoveries when using the HM450K bead array, while maximising the power of the array to detect methylation status genome-wide. Additionally, we demonstrate the utility of our method through extraction of biologically relevant epigenetic changes in prostate cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-51) contains supplementary material, which is available to authorized users.     

Experimental validation of methods for differential gene expression analysis and sample pooling in RNA-seq

Background

Massively parallel cDNA sequencing (RNA-seq) experiments are gradually superseding microarrays in quantitative gene expression profiling. However, many biologists are uncertain about the choice of differentially expressed gene (DEG) analysis methods and the validity of cost-saving sample pooling strategies for their RNA-seq experiments. Hence, we performed experimental validation of DEGs identified by Cuffdiff2, edgeR, DESeq2 and Two-stage Poisson Model (TSPM) in a RNA-seq experiment involving mice amygdalae micro-punches, using high-throughput qPCR on independent biological replicate samples. Moreover, we sequenced RNA-pools and compared their results with sequencing corresponding individual RNA samples.

Results

False-positivity rate of Cuffdiff2 and false-negativity rates of DESeq2 and TSPM were high. Among the four investigated DEG analysis methods, sensitivity and specificity of edgeR was relatively high. We documented the pooling bias and that the DEGs identified in pooled samples suffered low positive predictive values.

Conclusions

Our results highlighted the need for combined use of more sensitive DEG analysis methods and high-throughput validation of identified DEGs in future RNA-seq experiments. They indicated limited utility of sample pooling strategies for RNA-seq in similar setups and supported increasing the number of biological replicate samples.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1767-y) contains supplementary material, which is available to authorized users.     

A Bead-based Normalization for Uniform Sequencing depth (BeNUS) protocol for multi-samples sequencing exemplified by HLA-B

Background

Human leukocyte antigen (HLA) is a group of genes that are extremely polymorphic among individuals and populations and have been associated with more than 100 different diseases and adverse drug effects. HLA typing is accordingly an important tool in clinical application, medical research, and population genetics. We have previously developed a phase-defined HLA gene sequencing method using MiSeq sequencing.

Results

Here we report a simple, high-throughput, and cost-effective sequencing method that includes normalized library preparation and adjustment of DNA molar concentration. We applied long-range PCR to amplify HLA-B for 96 samples followed by transposase-based library construction and multiplex sequencing with the MiSeq sequencer. After sequencing, we observed low variation in read percentages (0.2% to 1.55%) among the 96 demultiplexed samples. On this basis, all the samples were amenable to haplotype phasing using our phase-defined sequencing method. In our study, a sequencing depth of 800x was necessary and sufficient to achieve full phasing of HLA-B alleles with reliable assignment of the allelic sequence to the 8 digit level.

Conclusions

Our HLA sequencing method optimized for 96 multiplexing samples is highly time effective and cost effective and is especially suitable for automated multi-sample library preparation and sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-645) contains supplementary material, which is available to authorized users.     

Performance comparison of four exome capture systems for deep sequencing

Background

Recent developments in deep (next-generation) sequencing technologies are significantly impacting medical research. The global analysis of protein coding regions in genomes of interest by whole exome sequencing is a widely used application. Many technologies for exome capture are commercially available; here we compare the performance of four of them: NimbleGen’s SeqCap EZ v3.0, Agilent’s SureSelect v4.0, Illumina’s TruSeq Exome, and Illumina’s Nextera Exome, all applied to the same human tumor DNA sample.

Results

Each capture technology was evaluated for its coverage of different exome databases, target coverage efficiency, GC bias, sensitivity in single nucleotide variant detection, sensitivity in small indel detection, and technical reproducibility. In general, all technologies performed well; however, our data demonstrated small, but consistent differences between the four capture technologies. Illumina technologies cover more bases in coding and untranslated regions. Furthermore, whereas most of the technologies provide reduced coverage in regions with low or high GC content, the Nextera technology tends to bias towards target regions with high GC content.

Conclusions

We show key differences in performance between the four technologies. Our data should help researchers who are planning exome sequencing to select appropriate exome capture technology for their particular application.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-449) contains supplementary material, which is available to authorized users.     

Pseudo-Sanger sequencing: massively parallel production of long and near error-free reads using NGS technology

Background

Usually, next generation sequencing (NGS) technology has the property of ultra-high throughput but the read length is remarkably short compared to conventional Sanger sequencing. Paired-end NGS could computationally extend the read length but with a lot of practical inconvenience because of the inherent gaps. Now that Illumina paired-end sequencing has the ability of read both ends from 600 bp or even 800 bp DNA fragments, how to fill in the gaps between paired ends to produce accurate long reads is intriguing but challenging.

Results

We have developed a new technology, referred to as pseudo-Sanger (PS) sequencing. It tries to fill in the gaps between paired ends and could generate near error-free sequences equivalent to the conventional Sanger reads in length but with the high throughput of the Next Generation Sequencing. The major novelty of PS method lies on that the gap filling is based on local assembly of paired-end reads which have overlaps with at either end. Thus, we are able to fill in the gaps in repetitive genomic region correctly. The PS sequencing starts with short reads from NGS platforms, using a series of paired-end libraries of stepwise decreasing insert sizes. A computational method is introduced to transform these special paired-end reads into long and near error-free PS sequences, which correspond in length to those with the largest insert sizes. The PS construction has 3 advantages over untransformed reads: gap filling, error correction and heterozygote tolerance. Among the many applications of the PS construction is de novo genome assembly, which we tested in this study. Assembly of PS reads from a non-isogenic strain of Drosophila melanogaster yields an N50 contig of 190 kb, a 5 fold improvement over the existing de novo assembly methods and a 3 fold advantage over the assembly of long reads from 454 sequencing.

Conclusions

Our method generated near error-free long reads from NGS paired-end sequencing. We demonstrated that de novo assembly could benefit a lot from these Sanger-like reads. Besides, the characteristic of the long reads could be applied to such applications as structural variations detection and metagenomics.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-711) contains supplementary material, which is available to authorized users.     

GBSX: a toolkit for experimental design and demultiplexing genotyping by sequencing experiments

Background

Massive parallel sequencing is a powerful tool for variant discovery and genotyping. To reduce costs, sequencing of restriction enzyme based reduced representation libraries can be utilized. This technology is generally referred to as Genotyping By Sequencing (GBS). To deal with GBS experimental design and initial processing specific bioinformatic tools are needed.

Results

GBSX is a package that assists in selecting the appropriate enzyme and the design of compatible in-line barcodes. Post sequencing, it performs optimized demultiplexing using these barcodes to create fastq files per barcode which can easily be plugged into existing variant analysis pipelines. Here we demonstrate the usability of the GBSX toolkit and demonstrate improved in-line barcode demultiplexing and trimming performance compared to existing tools.

Conclusions

GBSX provides an easy to use suite of tools for designing and demultiplexing of GBS experiments.     

Rapid identification and recovery of ENU-induced mutations with next-generation sequencing and Paired-End Low-Error analysis

Background

Targeting Induced Local Lesions IN Genomes (TILLING) is a reverse genetics approach to directly identify point mutations in specific genes of interest in genomic DNA from a large chemically mutagenized population. Classical TILLING processes, based on enzymatic detection of mutations in heteroduplex PCR amplicons, are slow and labor intensive.

Results

Here we describe a new TILLING strategy in zebrafish using direct next generation sequencing (NGS) of 250bp amplicons followed by Paired-End Low-Error (PELE) sequence analysis. By pooling a genomic DNA library made from over 9,000 N-ethyl-N-nitrosourea (ENU) mutagenized F1 fish into 32 equal pools of 288 fish, each with a unique Illumina barcode, we reduce the complexity of the template to a level at which we can detect mutations that occur in a single heterozygous fish in the entire library. MiSeq sequencing generates 250 base-pair overlapping paired-end reads, and PELE analysis aligns the overlapping sequences to each other and filters out any imperfect matches, thereby eliminating variants introduced during the sequencing process. We find that this filtering step reduces the number of false positive calls 50-fold without loss of true variant calls. After PELE we were able to validate 61.5% of the mutant calls that occurred at a frequency between 1 mutant call:100 wildtype calls and 1 mutant call:1000 wildtype calls in a pool of 288 fish. We then use high-resolution melt analysis to identify the single heterozygous mutation carrier in the 288-fish pool in which the mutation was identified.

Conclusions

Using this NGS-TILLING protocol we validated 28 nonsense or splice site mutations in 20 genes, at a two-fold higher efficiency than using traditional Cel1 screening. We conclude that this approach significantly increases screening efficiency and accuracy at reduced cost and can be applied in a wide range of organisms.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1263-4) contains supplementary material, which is available to authorized users.     

A fault-tolerant method for HLA typing with PacBio data

Background

Human leukocyte antigen (HLA) genes are critical genes involved in important biomedical aspects, including organ transplantation, autoimmune diseases and infectious diseases. The gene family contains the most polymorphic genes in humans and the difference between two alleles is only a single base pair substitution in many cases. The next generation sequencing (NGS) technologies could be used for high throughput HLA typing but in silico methods are still needed to correctly assign the alleles of a sample. Computer scientists have developed such methods for various NGS platforms, such as Illumina, Roche 454 and Ion Torrent, based on the characteristics of the reads they generate. However, the method for PacBio reads was less addressed, probably owing to its high error rates. The PacBio system has the longest read length among available NGS platforms, and therefore is the only platform capable of having exon 2 and exon 3 of HLA genes on the same read to unequivocally solve the ambiguity problem caused by the “phasing” issue.

Results

We proposed a new method BayesTyping1 to assign HLA alleles for PacBio circular consensus sequencing reads using Bayes’ theorem. The method was applied to simulated data of the three loci HLA-A, HLA-B and HLA-DRB1. The experimental results showed its capability to tolerate the disturbance of sequencing errors and external noise reads.

Conclusions

The BayesTyping1 method could overcome the problems of HLA typing using PacBio reads, which mostly arise from sequencing errors of PacBio reads and the divergence of HLA genes, to some extent.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-296) contains supplementary material, which is available to authorized users.