Anchored pseudo-de novo assembly of human genomes identifies extensive sequence variation from unmapped sequence reads

The human genome reference (HGR) completion marked the genomics era beginning, yet despite its utility universal application is limited by the small number of individuals used in its development. This is highlighted by the presence of high-quality sequence reads failing to map within the HGR. Sequences failing to map generally represent 2–5 % of total reads, which may harbor regions that would enhance our understanding of population variation, evolution, and disease. Alternatively, complete de novo assemblies can be created, but these effectively ignore the groundwork of the HGR. In an effort to find a middle ground, we developed a bioinformatic pipeline that maps paired-end reads to the HGR as separate single reads, exports unmappable reads, de novo assembles these reads per individual and then combines assemblies into a secondary reference assembly used for comparative analysis. Using 45 diverse 1000 Genomes Project individuals, we identified 351,361 contigs covering 195.5 Mb of sequence unincorporated in GRCh38. 30,879 contigs are represented in multiple individuals with ~40 % showing high sequence complexity. Genomic coordinates were generated for 99.9 %, with 52.5 % exhibiting high-quality mapping scores. Comparative genomic analyses with archaic humans and primates revealed significant sequence alignments and comparisons with model organism RefSeq gene datasets identified novel human genes. If incorporated, these sequences will expand the HGR, but more importantly our data highlight that with this method low coverage (~10–20×) next-generation sequencing can still be used to identify novel unmapped sequences to explore biological functions contributing to human phenotypic variation, disease and functionality for personal genomic medicine.     

<Emphasis Type="Italic">Tracembler</Emphasis> – software for <Emphasis Type="Italic">in-silico</Emphasis> chromosome walking in unassembled genomes

Background  

Whole genome shotgun sequencing produces increasingly higher coverage of a genome with random sequence reads. Progressive whole genome assembly and eventual finishing sequencing is a process that typically takes several years for large eukaryotic genomes. In the interim, all sequence reads of public sequencing projects are made available in repositories such as the NCBI Trace Archive. For a particular locus, sequencing coverage may be high enough early on to produce a reliable local genome assembly. We have developed software, Tracembler, that facilitates in silico chromosome walking by recursively assembling reads of a selected species from the NCBI Trace Archive starting with reads that significantly match sequence seeds supplied by the user.     

Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing

Background

Whole genome sequence construction is becoming increasingly feasible because of advances in next generation sequencing (NGS), including increasing throughput and read length. By simply overlapping paired-end reads, we can obtain longer reads with higher accuracy, which can facilitate the assembly process. However, the influences of different library sizes and assembly methods on paired-end sequencing-based de novo assembly remain poorly understood.

Results

We used 250 bp Illumina Miseq paired-end reads of different library sizes generated from genomic DNA from Escherichia coli DH1 and Streptococcus parasanguinis FW213 to compare the assembly results of different library sizes and assembly approaches. Our data indicate that overlapping paired-end reads can increase read accuracy but sometimes cause insertion or deletions. Regarding genome assembly, merged reads only outcompete original paired-end reads when coverage depth is low, and larger libraries tend to yield better assembly results. These results imply that distance information is the most critical factor during assembly. Our results also indicate that when depth is sufficiently high, assembly from subsets can sometimes produce better results.

Conclusions

In summary, this study provides systematic evaluations of de novo assembly from paired end sequencing data. Among the assembly strategies, we find that overlapping paired-end reads is not always beneficial for bacteria genome assembly and should be avoided or used with caution especially for genomes containing high fraction of repetitive sequences. Because increasing numbers of projects aim at bacteria genome sequencing, our study provides valuable suggestions for the field of genomic sequence construction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1859-8) contains supplementary material, which is available to authorized users.     

Design of efficient simplified genomic DNA and bisulfite sequencing in large plant populations

The next generation sequencing enables generation of high resolution and high throughput data for structure sequence of any genome at a fast declining cost. This opens opportunity for population based genetic and genomic analyses. In many applications, whole genome sequencing or re-sequencing is unnecessary or prohibited by budget limits. The Reduced Representation Genome Sequencing (RRGS), which sequences only a small proportion of the genome of interest, has been proposed to deal with the situations. Several forms of RRGS are proposed and implemented in the literature. When applied to plant or crop species, the current RRGS protocols shared a key drawback that a significantly high proportion (up to 60%) of sequence reads to be generated may be of non-genomic origin but attributed to chloroplast DNA or rRNA genes, leaving an exceptional low efficiency of the sequencing experiment. We recommended and discussed here the design of optimized simplified genomic DNA and bisulfite sequencing strategies, which may greatly improves efficiency of the sequencing experiments by bringing down the presentation of the undesirable sequencing reads to less than 10% in the whole sequence reads. The optimized RAD-seq and RRBS-seq methods are potentially useful for sequence variant screening and genotyping in large plant/crop populations.     

ConDeTri--a content dependent read trimmer for Illumina data

During the last few years, DNA and RNA sequencing have started to play an increasingly important role in biological and medical applications, especially due to the greater amount of sequencing data yielded from the new sequencing machines and the enormous decrease in sequencing costs. Particularly, Illumina/Solexa sequencing has had an increasing impact on gathering data from model and non-model organisms. However, accurate and easy to use tools for quality filtering have not yet been established. We present ConDeTri, a method for content dependent read trimming for next generation sequencing data using quality scores of each individual base. The main focus of the method is to remove sequencing errors from reads so that sequencing reads can be standardized. Another aspect of the method is to incorporate read trimming in next-generation sequencing data processing and analysis pipelines. It can process single-end and paired-end sequence data of arbitrary length and it is independent from sequencing coverage and user interaction. ConDeTri is able to trim and remove reads with low quality scores to save computational time and memory usage during de novo assemblies. Low coverage or large genome sequencing projects will especially gain from trimming reads. The method can easily be incorporated into preprocessing and analysis pipelines for Illumina data. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://code.google.com/p/condetri.     

Mung Bean Nuclease Treatment Increases Capture Specificity of Microdroplet-PCR Based Targeted DNA Enrichment

Targeted DNA enrichment coupled with next generation sequencing has been increasingly used for interrogation of select sub-genomic regions at high depth of coverage in a cost effective manner. Specificity measured by on-target efficiency is a key performance metric for target enrichment. Non-specific capture leads to off-target reads, resulting in waste of sequencing throughput on irrelevant regions. Microdroplet-PCR allows simultaneous amplification of up to thousands of regions in the genome and is among the most commonly used strategies for target enrichment. Here we show that carryover of single-stranded template genomic DNA from microdroplet-PCR constitutes a major contributing factor for off-target reads in the resultant libraries. Moreover, treatment of microdroplet-PCR enrichment products with a nuclease specific to single-stranded DNA alleviates off-target load and improves enrichment specificity. We propose that nuclease treatment of enrichment products should be incorporated in the workflow of targeted sequencing using microdroplet-PCR for target capture. These findings may have a broad impact on other PCR based applications for which removal of template DNA is beneficial.     

Genome Wide Sampling Sequencing for SNP Genotyping: Methods,Challenges and Future Development

Genetic polymorphisms, particularly single nucleotide polymorphisms (SNPs), have been widely used to advance quantitative, functional and evolutionary genomics. Ideally, all genetic variants among individuals should be discovered when next generation sequencing (NGS) technologies and platforms are used for whole genome sequencing or resequencing. In order to improve the cost-effectiveness of the process, however, the research community has mainly focused on developing genome-wide sampling sequencing (GWSS) methods, a collection of reduced genome complexity sequencing, reduced genome representation sequencing and selective genome target sequencing. Here we review the major steps involved in library preparation, the types of adapters used for ligation and the primers designed for amplification of ligated products for sequencing. Unfortunately, currently available GWSS methods have their drawbacks, such as inconsistency in the number of reads per sample library, the number of sites/targets per individual, and the number of reads per site/target, all of which result in missing data. Suggestions are proposed here to improve library construction, genotype calling accuracy, genome-wide marker density and read mapping rate. In brief, optimized GWSS library preparation should generate a unique set of target sites with dense distribution along chromosomes and even coverage per site across all individuals.     

Detection of Genomic Variation by Selection of a 9 Mb DNA Region and High Throughput Sequencing

Detection of the rare polymorphisms and causative mutations of genetic diseases in a targeted genomic area has become a major goal in order to understand genomic and phenotypic variability. We have interrogated repeat-masked regions of 8.9 Mb on human chromosomes 21 (7.8 Mb) and 7 (1.1 Mb) from an individual from the International HapMap Project (NA12872). We have optimized a method of genomic selection for high throughput sequencing. Microarray-based selection and sequencing resulted in 260-fold enrichment, with 41% of reads mapping to the target region. 83% of SNPs in the targeted region had at least 4-fold sequence coverage and 54% at least 15-fold. When assaying HapMap SNPs in NA12872, our sequence genotypes are 91.3% concordant in regions with coverage≥4-fold, and 97.9% concordant in regions with coverage≥15-fold. About 81% of the SNPs recovered with both thresholds are listed in dbSNP. We observed that regions with low sequence coverage occur in close proximity to low-complexity DNA. Validation experiments using Sanger sequencing were performed for 46 SNPs with 15-20 fold coverage, with a confirmation rate of 96%, suggesting that DNA selection provides an accurate and cost-effective method for identifying rare genomic variants.     

Phylogenetic comparative assembly

Background  

Recent high throughput sequencing technologies are capable of generating a huge amount of data for bacterial genome sequencing projects. Although current sequence assemblers successfully merge the overlapping reads, often several contigs remain which cannot be assembled any further. It is still costly and time consuming to close all the gaps in order to acquire the whole genomic sequence.     

Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6–40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.     

Comparison of sequence reads obtained from three next-generation sequencing platforms

Next-generation sequencing technologies enable the rapid cost-effective production of sequence data. To evaluate the performance of these sequencing technologies, investigation of the quality of sequence reads obtained from these methods is important. In this study, we analyzed the quality of sequence reads and SNP detection performance using three commercially available next-generation sequencers, i.e., Roche Genome Sequencer FLX System (FLX), Illumina Genome Analyzer (GA), and Applied Biosystems SOLiD system (SOLiD). A common genomic DNA sample obtained from Escherichia coli strain DH1 was applied to these sequencers. The obtained sequence reads were aligned to the complete genome sequence of E. coli DH1, to evaluate the accuracy and sequence bias of these sequence methods. We found that the fraction of "junk" data, which could not be aligned to the reference genome, was largest in the data set of SOLiD, in which about half of reads could not be aligned. Among data sets after alignment to the reference, sequence accuracy was poorest in GA data sets, suggesting relatively low fidelity of the elongation reaction in the GA method. Furthermore, by aligning the sequence reads to the E. coli strain W3110, we screened sequence differences between two E. coli strains using data sets of three different next-generation platforms. The results revealed that the detected sequence differences were similar among these three methods, while the sequence coverage required for the detection was significantly small in the FLX data set. These results provided valuable information on the quality of short sequence reads and the performance of SNP detection in three next-generation sequencing platforms.     

Identification of mixups among DNA sequencing plates

MOTIVATION: During the process of high-throughput genome sequencing there are opportunities for mixups of reagents and data associated with particular projects. The sequencing templates or sequence data generated for an assembly may become contaminated with reagents or sequences from another project, resulting in poorer quality and inaccurate assemblies. RESULTS: We have developed a system to assess sequence assemblies and monitor for laboratory mixups. We describe several methods for testing the consistency of assemblies and resolving mixed ones. We use statistical tests to evaluate the distribution of sequencing reads from different plates into contigs, and a graph-based approach to resolve situations where data has been inappropriately combined. While these methods have been designed for use in a high-throughput DNA sequencing environment processing thousands of clones, they can be applied in any situation where distinct sequencing projects are performed at redundant coverage.     

Preselection of shotgun clones by oligonucleotide fingerprinting: an efficient and high throughput strategy to reduce redundancy in large-scale sequencing projects.

Large-scale genomic sequencing projects generally rely on random sequencing of shotgun clones, followed by different gap closing strategies. To reduce the overall effort and cost of those projects and to accelerate the sequencing throughput, we have developed an efficient, high throughput oligonucleotide fingerprinting protocol to select optimal shotgun clone sets prior to sequencing. Both computer simulations and experimental results, obtained from five PAC-derived shotgun libraries spanning 535 kb of the 17p11.2 region of the human genome, demonstrate that at least a 2-fold reduction in the number of sequence reads required to sequence an individual genomic clone (cosmid, PAC, etc.) can be achieved. Treatment of clone contigs with significant clone overlaps will allow an even greater reduction.     

Comparative analysis of algorithms for whole-genome assembly of pyrosequencing data

Next-generation sequencing technologies have fostered an unprecedented proliferation of high-throughput sequencing projects and a concomitant development of novel algorithms for the assembly of short reads. In this context, an important issue is the need of a careful assessment of the accuracy of the assembly process. Here, we review the efficiency of a panel of assemblers, specifically designed to handle data from GS FLX 454 platform, on three bacterial data sets with different characteristics in terms of reads coverage and repeats content. Our aim is to investigate their strengths and weaknesses in the reconstruction of the reference genomes. In our benchmarking, we assess assemblers' performance, quantifying and characterizing assembly gaps and errors, and evaluating their ability to solve complex genomic regions containing repeats. The final goal of this analysis is to highlight pros and cons of each method, in order to provide the final user with general criteria for the right choice of the appropriate assembly strategy, depending on the specific needs. A further aspect we have explored is the relationship between coverage of a sequencing project and quality of the obtained results. The final outcome suggests that, for a good tradeoff between costs and results, the planned genome coverage of an experiment should not exceed 20-30 ×.     

Efficiency and power as a function of sequence coverage, SNP array density, and imputation

High coverage whole genome sequencing provides near complete information about genetic variation. However, other technologies can be more efficient in some settings by (a) reducing redundant coverage within samples and (b) exploiting patterns of genetic variation across samples. To characterize as many samples as possible, many genetic studies therefore employ lower coverage sequencing or SNP array genotyping coupled to statistical imputation. To compare these approaches individually and in conjunction, we developed a statistical framework to estimate genotypes jointly from sequence reads, array intensities, and imputation. In European samples, we find similar sensitivity (89%) and specificity (99.6%) from imputation with either 1× sequencing or 1 M SNP arrays. Sensitivity is increased, particularly for low-frequency polymorphisms (MAF < 5%), when low coverage sequence reads are added to dense genome-wide SNP arrays--the converse, however, is not true. At sites where sequence reads and array intensities produce different sample genotypes, joint analysis reduces genotype errors and identifies novel error modes. Our joint framework informs the use of next-generation sequencing in genome wide association studies and supports development of improved methods for genotype calling.     

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.     

Improved Multiple Displacement Amplification (iMDA) and Ultraclean Reagents

Background

Next-generation sequencing sample preparation requires nanogram to microgram quantities of DNA; however, many relevant samples are comprised of only a few cells. Genomic analysis of these samples requires a whole genome amplification method that is unbiased and free of exogenous DNA contamination. To address these challenges we have developed protocols for the production of DNA-free consumables including reagents and have improved upon multiple displacement amplification (iMDA).

Results

A specialized ethylene oxide treatment was developed that renders free DNA and DNA present within Gram positive bacterial cells undetectable by qPCR. To reduce DNA contamination in amplification reagents, a combination of ion exchange chromatography, filtration, and lot testing protocols were developed. Our multiple displacement amplification protocol employs a second strand-displacing DNA polymerase, improved buffers, improved reaction conditions and DNA free reagents. The iMDA protocol, when used in combination with DNA-free laboratory consumables and reagents, significantly improved efficiency and accuracy of amplification and sequencing of specimens with moderate to low levels of DNA. The sensitivity and specificity of sequencing of amplified DNA prepared using iMDA was compared to that of DNA obtained with two commercial whole genome amplification kits using 10 fg (~1-2 bacterial cells worth) of bacterial genomic DNA as a template. Analysis showed >99% of the iMDA reads mapped to the template organism whereas only 0.02% of the reads from the commercial kits mapped to the template. To assess the ability of iMDA to achieve balanced genomic coverage, a non-stochastic amount of bacterial genomic DNA (1 pg) was amplified and sequenced, and data obtained were compared to sequencing data obtained directly from genomic DNA. The iMDA DNA and genomic DNA sequencing had comparable coverage 99.98% of the reference genome at ≥1X coverage and 99.9% at ≥5X coverage while maintaining both balance and representation of the genome.

Conclusions

The iMDA protocol in combination with DNA-free laboratory consumables, significantly improved the ability to sequence specimens with low levels of DNA. iMDA has broad utility in metagenomics, diagnostics, ancient DNA analysis, pre-implantation embryo screening, single-cell genomics, whole genome sequencing of unculturable organisms, and forensic applications for both human and microbial targets.