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.     

Pollux: platform independent error correction of single and mixed genomes

Background

Second-generation sequencers generate millions of relatively short, but error-prone, reads. These errors make sequence assembly and other downstream projects more challenging. Correcting these errors improves the quality of assemblies and projects which benefit from error-free reads.

Results

We have developed a general-purpose error corrector that corrects errors introduced by Illumina, Ion Torrent, and Roche 454 sequencing technologies and can be applied to single- or mixed-genome data. In addition to correcting substitution errors, we locate and correct insertion, deletion, and homopolymer errors while remaining sensitive to low coverage areas of sequencing projects. Using published data sets, we correct 94% of Illumina MiSeq errors, 88% of Ion Torrent PGM errors, 85% of Roche 454 GS Junior errors. Introduced errors are 20 to 70 times more rare than successfully corrected errors. Furthermore, we show that the quality of assemblies improves when reads are corrected by our software.

Conclusions

Pollux is highly effective at correcting errors across platforms, and is consistently able to perform as well or better than currently available error correction software. Pollux provides general-purpose error correction and may be used in applications with or without assembly.     

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.     

ART: a next-generation sequencing read simulator

ART is a set of simulation tools that generate synthetic next-generation sequencing reads. This functionality is essential for testing and benchmarking tools for next-generation sequencing data analysis including read alignment, de novo assembly and genetic variation discovery. ART generates simulated sequencing reads by emulating the sequencing process with built-in, technology-specific read error models and base quality value profiles parameterized empirically in large sequencing datasets. We currently support all three major commercial next-generation sequencing platforms: Roche's 454, Illumina's Solexa and Applied Biosystems' SOLiD. ART also allows the flexibility to use customized read error model parameters and quality profiles. AVAILABILITY: Both source and binary software packages are available at http://www.niehs.nih.gov/research/resources/software/art.     

MutAid: Sanger and NGS Based Integrated Pipeline for Mutation Identification,Validation and Annotation in Human Molecular Genetics

Traditional Sanger sequencing as well as Next-Generation Sequencing have been used for the identification of disease causing mutations in human molecular research. The majority of currently available tools are developed for research and explorative purposes and often do not provide a complete, efficient, one-stop solution. As the focus of currently developed tools is mainly on NGS data analysis, no integrative solution for the analysis of Sanger data is provided and consequently a one-stop solution to analyze reads from both sequencing platforms is not available. We have therefore developed a new pipeline called MutAid to analyze and interpret raw sequencing data produced by Sanger or several NGS sequencing platforms. It performs format conversion, base calling, quality trimming, filtering, read mapping, variant calling, variant annotation and analysis of Sanger and NGS data under a single platform. It is capable of analyzing reads from multiple patients in a single run to create a list of potential disease causing base substitutions as well as insertions and deletions. MutAid has been developed for expert and non-expert users and supports four sequencing platforms including Sanger, Illumina, 454 and Ion Torrent. Furthermore, for NGS data analysis, five read mappers including BWA, TMAP, Bowtie, Bowtie2 and GSNAP and four variant callers including GATK-HaplotypeCaller, SAMTOOLS, Freebayes and VarScan2 pipelines are supported. MutAid is freely available at https://sourceforge.net/projects/mutaid.     

jackalope: A swift,versatile phylogenomic and high‐throughput sequencing simulator

High‐throughput sequencing (HTS) is central to the study of population genomics and has an increasingly important role in constructing phylogenies. Choices in research design for sequencing projects can include a wide range of factors, such as sequencing platform, depth of coverage and bioinformatic tools. Simulating HTS data better informs these decisions, as users can validate software by comparing output to the known simulation parameters. However, current standalone HTS simulators cannot generate variant haplotypes under even somewhat complex evolutionary scenarios, such as recombination or demographic change. This greatly reduces their usefulness for fields such as population genomics and phylogenomics. Here I present the R package jackalope that simply and efficiently simulates (i) sets of variant haplotypes from a reference genome and (ii) reads from both Illumina and Pacific Biosciences platforms. Haplotypes can be simulated using phylogenies, gene trees, coalescent‐simulation output, population‐genomic summary statistics, and Variant Call Format (VCF) files. jackalope can simulate single, paired‐end or mate‐pair Illumina reads, as well as reads from Pacific Biosciences. These simulations include sequencing errors, mapping qualities, multiplexing and optical/PCR duplicates. It can read reference genomes from fasta files and can simulate new ones, and all outputs can be written to standard file formats. jackalope is available for Mac, Windows and Linux systems.     

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.     

Comparing High‐throughput Platforms for Sequencing the V4 Region of SSU‐rDNA in Environmental Microbial Eukaryotic Diversity Surveys

High‐throughput sequencing platforms are continuing to increase resulting read lengths, which is allowing for a deeper and more accurate depiction of environmental microbial diversity. With the nascent Reagent Kit v3, Illumina MiSeq now has the ability to sequence the eukaryotic hyper‐variable V4 region of the SSU‐rDNA locus with paired‐end reads. Using DNA collected from soils with analyses of strictly‐ and nearly identical amplicons, here we ask how the new Illumina MiSeq data compares with what we can obtain with Roche/454 GS FLX with regard to quantity and quality, presence and absence, and abundance perspectives. We show that there is an easy qualitative transition from the Roche/454 to the Illumina MiSeq platforms. The ease of this transition is more nuanced quantitatively for low‐abundant amplicons, although estimates of abundances are known to also vary within platforms.     

Direct comparisons of Illumina vs. Roche 454 sequencing technologies on the same microbial community DNA sample

Next-generation sequencing (NGS) is commonly used in metagenomic studies of complex microbial communities but whether or not different NGS platforms recover the same diversity from a sample and their assembled sequences are of comparable quality remain unclear. We compared the two most frequently used platforms, the Roche 454 FLX Titanium and the Illumina Genome Analyzer (GA) II, on the same DNA sample obtained from a complex freshwater planktonic community. Despite the substantial differences in read length and sequencing protocols, the platforms provided a comparable view of the community sampled. For instance, derived assemblies overlapped in ~90% of their total sequences and in situ abundances of genes and genotypes (estimated based on sequence coverage) correlated highly between the two platforms (R(2)>0.9). Evaluation of base-call error, frameshift frequency, and contig length suggested that Illumina offered equivalent, if not better, assemblies than Roche 454. The results from metagenomic samples were further validated against DNA samples of eighteen isolate genomes, which showed a range of genome sizes and G+C% content. We also provide quantitative estimates of the errors in gene and contig sequences assembled from datasets characterized by different levels of complexity and G+C% content. For instance, we noted that homopolymer-associated, single-base errors affected ~1% of the protein sequences recovered in Illumina contigs of 10× coverage and 50% G+C; this frequency increased to ~3% when non-homopolymer errors were also considered. Collectively, our results should serve as a useful practical guide for choosing proper sampling strategies and data possessing protocols for future metagenomic studies.     

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.     

Comparison of alignment software for genome-wide bisulphite sequence data

Recent advances in next generation sequencing (NGS) technology now provide the opportunity to rapidly interrogate the methylation status of the genome. However, there are challenges in handling and interpretation of the methylation sequence data because of its large volume and the consequences of bisulphite modification. We sequenced reduced representation human genomes on the Illumina platform and efficiently mapped and visualized the data with different pipelines and software packages. We examined three pipelines for aligning bisulphite converted sequencing reads and compared their performance. We also comment on pre-processing and quality control of Illumina data. This comparison highlights differences in methods for NGS data processing and provides guidance to advance sequence-based methylation data analysis for molecular biologists.     

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.     

The Accuracy,Feasibility and Challenges of Sequencing Short Tandem Repeats Using Next-Generation Sequencing Platforms

To date we have little knowledge of how accurate next-generation sequencing (NGS) technologies are in sequencing repetitive sequences beyond known limitations to accurately sequence homopolymers. Only a handful of previous reports have evaluated the potential of NGS for sequencing short tandem repeats (microsatellites) and no empirical study has compared and evaluated the performance of more than one NGS platform with the same dataset. Here we examined yeast microsatellite variants from both long-read (454-sequencing) and short-read (Illumina) NGS platforms and compared these to data derived through Sanger sequencing. In addition, we investigated any locus-specific biases and differences that might have resulted from variability in microsatellite repeat number, repeat motif or type of mutation. Out of 112 insertion/deletion variants identified among 45 microsatellite amplicons in our study, we found 87.5% agreement between the 454-platform and Sanger sequencing in frequency of variant detection after Benjamini-Hochberg correction for multiple tests. For a subset of 21 microsatellite amplicons derived from Illumina sequencing, the results of short-read platform were highly consistent with the other two platforms, with 100% agreement with 454-sequencing and 93.6% agreement with the Sanger method after Benjamini-Hochberg correction. We found that the microsatellite attributes copy number, repeat motif and type of mutation did not have a significant effect on differences seen between the sequencing platforms. We show that both long-read and short-read NGS platforms can be used to sequence short tandem repeats accurately, which makes it feasible to consider the use of these platforms in high-throughput genotyping. It appears the major requirement for achieving both high accuracy and rare variant detection in microsatellite genotyping is sufficient read depth coverage. This might be a challenge because each platform generates a consistent pattern of non-uniform sequence coverage, which, as our study suggests, may affect some types of tandem repeats more than others.     

SeqSQC: A Bioconductor Package for Evaluating the Sample Quality of Next-generation Sequencing Data

As next-generation sequencing (NGS) technology has become widely used to identify genetic causal variants for various diseases and traits,a number of packages for checking NGS data quality have sprung up in public domains. In addition to the quality of sequencing data,sample quality issues,such as gender mismatch,abnormal inbreeding coefficient,cryptic relatedness,and population outliers,can also have fundamental impact on downstream analysis. However,there is a lack of tools specialized in identifying problematic samples from NGS data,often due to the limitation of sample size and variant counts. We developed SeqSQC,a Bioconductor package,to automate and accelerate sample cleaning in NGS data of any scale. SeqSQC is designed for efficient data storage and access,and equipped with interactive plots for intuitive data visualization to expedite the identification of problematic samples. SeqSQC is available at http://bioconductor. org/packages/SeqSQC.     

The Quantification of Representative Sequences pipeline for amplicon sequencing: case study on within‐population ITS1 sequence variation in a microparasite infecting Daphnia

Next generation sequencing (NGS) platforms are replacing traditional molecular biology protocols like cloning and Sanger sequencing. However, accuracy of NGS platforms has rarely been measured when quantifying relative frequencies of genotypes or taxa within populations. Here we developed a new bioinformatic pipeline (QRS) that pools similar sequence variants and estimates their frequencies in NGS data sets from populations or communities. We tested whether the estimated frequency of representative sequences, generated by 454 amplicon sequencing, differs significantly from that obtained by Sanger sequencing of cloned PCR products. This was performed by analysing sequence variation of the highly variable first internal transcribed spacer (ITS1) of the ichthyosporean Caullerya mesnili, a microparasite of cladocerans of the genus Daphnia. This analysis also serves as a case example of the usage of this pipeline to study within‐population variation. Additionally, a public Illumina data set was used to validate the pipeline on community‐level data. Overall, there was a good correspondence in absolute frequencies of C. mesnili ITS1 sequences obtained from Sanger and 454 platforms. Furthermore, analyses of molecular variance (amova ) revealed that population structure of C. mesnili differs across lakes and years independently of the sequencing platform. Our results support not only the usefulness of amplicon sequencing data for studies of within‐population structure but also the successful application of the QRS pipeline on Illumina‐generated data. The QRS pipeline is freely available together with its documentation under GNU Public Licence version 3 at http://code.google.com/p/quantification-representative-sequences .