Bioinformatics challenges of new sequencing technology

New DNA sequencing technologies can sequence up to one billion bases in a single day at low cost, putting large-scale sequencing within the reach of many scientists. Many researchers are forging ahead with projects to sequence a range of species using the new technologies. However, these new technologies produce read lengths as short as 35-40 nucleotides, posing challenges for genome assembly and annotation. Here we review the challenges and describe some of the bioinformatics systems that are being proposed to solve them. We specifically address issues arising from using these technologies in assembly projects, both de novo and for resequencing purposes, as well as efforts to improve genome annotation in the fragmented assemblies produced by short read lengths.     

Whole-genome sequencing and assembly with high-throughput, short-read technologies

While recently developed short-read sequencing technologies may dramatically reduce the sequencing cost and eventually achieve the $1000 goal for re-sequencing, their limitations prevent the de novo sequencing of eukaryotic genomes with the standard shotgun sequencing protocol. We present SHRAP (SHort Read Assembly Protocol), a sequencing protocol and assembly methodology that utilizes high-throughput short-read technologies. We describe a variation on hierarchical sequencing with two crucial differences: (1) we select a clone library from the genome randomly rather than as a tiling path and (2) we sample clones from the genome at high coverage and reads from the clones at low coverage. We assume that 200 bp read lengths with a 1% error rate and inexpensive random fragment cloning on whole mammalian genomes is feasible. Our assembly methodology is based on first ordering the clones and subsequently performing read assembly in three stages: (1) local assemblies of regions significantly smaller than a clone size, (2) clone-sized assemblies of the results of stage 1, and (3) chromosome-sized assemblies. By aggressively localizing the assembly problem during the first stage, our method succeeds in assembling short, unpaired reads sampled from repetitive genomes. We tested our assembler using simulated reads from D. melanogaster and human chromosomes 1, 11, and 21, and produced assemblies with large sets of contiguous sequence and a misassembly rate comparable to other draft assemblies. Tested on D. melanogaster and the entire human genome, our clone-ordering method produces accurate maps, thereby localizing fragment assembly and enabling the parallelization of the subsequent steps of our pipeline. Thus, we have demonstrated that truly inexpensive de novo sequencing of mammalian genomes will soon be possible with high-throughput, short-read technologies using our methodology.     

Chromosome‐level hybrid de novo genome assemblies as an attainable option for nonmodel insects

The emergence of third‐generation sequencing (3GS; long‐reads) is bringing closer the goal of chromosome‐size fragments in de novo genome assemblies. This allows the exploration of new and broader questions on genome evolution for a number of nonmodel organisms. However, long‐read technologies result in higher sequencing error rates and therefore impose an elevated cost of sufficient coverage to achieve high enough quality. In this context, hybrid assemblies, combining short‐reads and long‐reads, provide an alternative efficient and cost‐effective approach to generate de novo, chromosome‐level genome assemblies. The array of available software programs for hybrid genome assembly, sequence correction and manipulation are constantly being expanded and improved. This makes it difficult for nonexperts to find efficient, fast and tractable computational solutions for genome assembly, especially in the case of nonmodel organisms lacking a reference genome or one from a closely related species. In this study, we review and test the most recent pipelines for hybrid assemblies, comparing the model organism Drosophila melanogaster to a nonmodel cactophilic Drosophila, D. mojavensis. We show that it is possible to achieve excellent contiguity on this nonmodel organism using the dbg2olc pipeline.     

LOCAS--a low coverage assembly tool for resequencing projects

Motivation

Next Generation Sequencing (NGS) is a frequently applied approach to detect sequence variations between highly related genomes. Recent large-scale re-sequencing studies as the Human 1000 Genomes Project utilize NGS data of low coverage to afford sequencing of hundreds of individuals. Here, SNPs and micro-indels can be detected by applying an alignment-consensus approach. However, computational methods capable of discovering other variations such as novel insertions or highly diverged sequence from low coverage NGS data are still lacking.

Results

We present LOCAS, a new NGS assembler particularly designed for low coverage assembly of eukaryotic genomes using a mismatch sensitive overlap-layout-consensus approach. LOCAS assembles homologous regions in a homology-guided manner while it performs de novo assemblies of insertions and highly polymorphic target regions subsequently to an alignment-consensus approach. LOCAS has been evaluated in homology-guided assembly scenarios with low sequence coverage of Arabidopsis thaliana strains sequenced as part of the Arabidopsis 1001 Genomes Project. While assembling the same amount of long insertions as state-of-the-art NGS assemblers, LOCAS showed best results regarding contig size, error rate and runtime.

Conclusion

LOCAS produces excellent results for homology-guided assembly of eukaryotic genomes with short reads and low sequencing depth, and therefore appears to be the assembly tool of choice for the detection of novel sequence variations in this scenario.     

Optical mapping of DNA: single-molecule-based methods for mapping genomes

The technologies associated with DNA sequencing are rapidly evolving. Indeed, single-molecule DNA sequencing strategies are cheaper and faster than ever before. Despite this progress, every sequencing platform to date relies on reading the genome in small, abstract fragments, typically of less than 1000 bases in length. The overarching aim of the optical map is to complement the information derived from DNA sequencing by providing long-range context on which these short sequence reads can be built. This is typically done using an enzyme to target and modify at short DNA sequences of, say, six bases in length throughout the genome. By accurately placing these short pieces of sequence on long genomic DNA fragments, up to several millions of bases in length, a scaffold for sequence assembly can be obtained. This review focuses on three enzymatic approaches to optical mapping. Optical mapping was first developed using restriction enzymes to sequence-specifically cleave DNA that is immobilized on a surface. More recently, nicking enzymes have found application in the sequence-specific fluorescent labeling of DNA for optical mapping. Such covalent modification allows the DNA to be imaged in solution, and this, in combination with developing nanofluidic technologies, is enabling new high-throughput approaches to mapping. And, finally, this review will discuss the recent development of mapping with subdiffraction-limit precision using methyltransferase enzymes to label the DNA with an ultrahigh density.     

Evaluation of methods for de novo genome assembly from high-throughput sequencing reads reveals dependencies that affect the quality of the results

Recent developments in high-throughput sequencing technology have made low-cost sequencing an attractive approach for many genome analysis tasks. Increasing read lengths, improving quality and the production of increasingly larger numbers of usable sequences per instrument-run continue to make whole-genome assembly an appealing target application. In this paper we evaluate the feasibility of de novo genome assembly from short reads (≤100 nucleotides) through a detailed study involving genomic sequences of various lengths and origin, in conjunction with several of the currently popular assembly programs. Our extensive analysis demonstrates that, in addition to sequencing coverage, attributes such as the architecture of the target genome, the identity of the used assembly program, the average read length and the observed sequencing error rates are powerful variables that affect the best achievable assembly of the target sequence in terms of size and correctness.     

Enhanced De Novo Assembly of High Throughput Pyrosequencing Data Using Whole Genome Mapping

Despite major advances in next-generation sequencing, assembly of sequencing data, especially data from novel microorganisms or re-emerging pathogens, remains constrained by the lack of suitable reference sequences. De novo assembly is the best approach to achieve an accurate finished sequence, but multiple sequencing platforms or paired-end libraries are often required to achieve full genome coverage. In this study, we demonstrated a method to assemble complete bacterial genome sequences by integrating shotgun Roche 454 pyrosequencing with optical whole genome mapping (WGM). The whole genome restriction map (WGRM) was used as the reference to scaffold de novo assembled sequence contigs through a stepwise process. Large de novo contigs were placed in the correct order and orientation through alignment to the WGRM. De novo contigs that were not aligned to WGRM were merged into scaffolds using contig branching structure information. These extended scaffolds were then aligned to the WGRM to identify the overlaps to be eliminated and the gaps and mismatches to be resolved with unused contigs. The process was repeated until a sequence with full coverage and alignment with the whole genome map was achieved. Using this method we were able to achieved 100% WGRM coverage without a paired-end library. We assembled complete sequences for three distinct genetic components of a clinical isolate of Providencia stuartii: a bacterial chromosome, a novel bla _NDM-1 plasmid, and a novel bacteriophage, without separately purifying them to homogeneity.     

Scaffolding pre-assembled contigs using SSPACE

SUMMARY: De novo assembly tools play a main role in reconstructing genomes from next-generation sequencing (NGS) data and usually yield a number of contigs. Using paired-read sequencing data it is possible to assess the order, distance and orientation of contigs and combine them into so-called scaffolds. Although the latter process is a crucial step in finishing genomes, scaffolding algorithms are often built-in functions in de novo assembly tools and cannot be independently controlled. We here present a new tool, called SSPACE, which is a stand-alone scaffolder of pre-assembled contigs using paired-read data. Main features are: a short runtime, multiple library input of paired-end and/or mate pair datasets and possible contig extension with unmapped sequence reads. SSPACE shows promising results on both prokaryote and eukaryote genomic testsets where the amount of initial contigs was reduced by at least 75%.     

Comparative studies of de novo assembly tools for next-generation sequencing technologies

MOTIVATION: Several new de novo assembly tools have been developed recently to assemble short sequencing reads generated by next-generation sequencing platforms. However, the performance of these tools under various conditions has not been fully investigated, and sufficient information is not currently available for informed decisions to be made regarding the tool that would be most likely to produce the best performance under a specific set of conditions. RESULTS: We studied and compared the performance of commonly used de novo assembly tools specifically designed for next-generation sequencing data, including SSAKE, VCAKE, Euler-sr, Edena, Velvet, ABySS and SOAPdenovo. Tools were compared using several performance criteria, including N50 length, sequence coverage and assembly accuracy. Various properties of read data, including single-end/paired-end, sequence GC content, depth of coverage and base calling error rates, were investigated for their effects on the performance of different assembly tools. We also compared the computation time and memory usage of these seven tools. Based on the results of our comparison, the relative performance of individual tools are summarized and tentative guidelines for optimal selection of different assembly tools, under different conditions, are provided.     

Extending assembly of short DNA sequences to handle error

Inexpensive de novo genome sequencing, particularly in organisms with small genomes, is now possible using several new sequencing technologies. Some of these technologies such as that from Illumina's Solexa Sequencing, produce high genomic coverage by generating a very large number of small reads ( approximately 30 bp). While prior work shows that partial assembly can be performed by k-mer extension in error-free reads, this algorithm is unsuccessful with the sequencing error rates found in practice. We present VCAKE (Verified Consensus Assembly by K-mer Extension), a modification of simple k-mer extension that overcomes error by using high depth coverage. Though it is a simple modification of a previous approach, we show significant improvements in assembly results on simulated and experimental datasets that include error. AVAILABILITY: http://152.2.15.114/~labweb/VCAKE     

Finding the right coverage: the impact of coverage and sequence quality on single nucleotide polymorphism genotyping error rates

Restriction‐enzyme‐based sequencing methods enable the genotyping of thousands of single nucleotide polymorphism (SNP) loci in nonmodel organisms. However, in contrast to traditional genetic markers, genotyping error rates in SNPs derived from restriction‐enzyme‐based methods remain largely unknown. Here, we estimated genotyping error rates in SNPs genotyped with double digest RAD sequencing from Mendelian incompatibilities in known mother–offspring dyads of Hoffman's two‐toed sloth (Choloepus hoffmanni) across a range of coverage and sequence quality criteria, for both reference‐aligned and de novo‐assembled data sets. Genotyping error rates were more sensitive to coverage than sequence quality and low coverage yielded high error rates, particularly in de novo‐assembled data sets. For example, coverage ≥5 yielded median genotyping error rates of ≥0.03 and ≥0.11 in reference‐aligned and de novo‐assembled data sets, respectively. Genotyping error rates declined to ≤0.01 in reference‐aligned data sets with a coverage ≥30, but remained ≥0.04 in the de novo‐assembled data sets. We observed approximately 10‐ and 13‐fold declines in the number of loci sampled in the reference‐aligned and de novo‐assembled data sets when coverage was increased from ≥5 to ≥30 at quality score ≥30, respectively. Finally, we assessed the effects of genotyping coverage on a common population genetic application, parentage assignments, and showed that the proportion of incorrectly assigned maternities was relatively high at low coverage. Overall, our results suggest that the trade‐off between sample size and genotyping error rates be considered prior to building sequencing libraries, reporting genotyping error rates become standard practice, and that effects of genotyping errors on inference be evaluated in restriction‐enzyme‐based SNP studies.     

De novo assembly of human genome at single-cell levels

Genome assembly has been benefited from long-read sequencing technologies with higher accuracy and higher continuity. However, most human genome assembly require large amount of DNAs from homogeneous cell lines without keeping cell heterogeneities, since cell heterogeneity could profoundly affect haplotype assembly results. Herein, using single-cell genome long-read sequencing technology (SMOOTH-seq), we have sequenced K562 and HG002 cells on PacBio HiFi and Oxford Nanopore Technologies (ONT) platforms and conducted de novo genome assembly. For the first time, we have completed the human genome assembly with high continuity (with NG50 of ∼2 Mb using 95 individual K562 cells) at single-cell levels, and explored the impact of different assemblers and sequencing strategies on genome assembly. With sequencing data from 30 diploid individual HG002 cells of relatively high genome coverage (average coverage ∼41.7%) on ONT platform, the NG50 can reach over 1.3 Mb. Furthermore, with the assembled genome from K562 single-cell dataset, more complete and accurate set of insertion events and complex structural variations could be identified. This study opened a new chapter on the practice of single-cell genome de novo assembly.     

Evaluating the fidelity of de novo short read metagenomic assembly using simulated data

A frequent step in metagenomic data analysis comprises the assembly of the sequenced reads. Many assembly tools have been published in the last years targeting data coming from next-generation sequencing (NGS) technologies but these assemblers have not been designed for or tested in multi-genome scenarios that characterize metagenomic studies. Here we provide a critical assessment of current de novo short reads assembly tools in multi-genome scenarios using complex simulated metagenomic data. With this approach we tested the fidelity of different assemblers in metagenomic studies demonstrating that even under the simplest compositions the number of chimeric contigs involving different species is noticeable. We further showed that the assembly process reduces the accuracy of the functional classification of the metagenomic data and that these errors can be overcome raising the coverage of the studied metagenome. The results presented here highlight the particular difficulties that de novo genome assemblers face in multi-genome scenarios demonstrating that these difficulties, that often compromise the functional classification of the analyzed data, can be overcome with a high sequencing effort.     

采用诱导环化酶制备Illumina Mate-paired DNA文库

新一代测序技术(NGS)的文库制备方法在基因组的拼装中起着重要作用。但是NGS技术制备的普通DNA文库片段只有500 bp左右,难以满足复杂基因组的从头(de novo)拼装要求。三代测序技术的读长可以达到20 kb,但是其高错误率及测序成本过高使得其又不易推广。因此二代测序的Mate-paired文库制备技术一直在基因组的de novo拼装中扮演着非常重要的角色。目前主流的NGS平台Illumina制备的Mate-paired文库的片段范围只有2~5 kb,为了得到更长的可用于Illumina平台测序的Mate-paired文库,本研究首次整合并优化了Illumina和Roche/454两种测序平台的Mate-paired文库制备技术,采用诱导环化酶来提高基因组长片段DNA的环化效率,成功建立了20 kb Mate-paired文库制备技术,并已将该技术应用于人类基因组20 kb Mate-paired文库制备。该技术为Illumina平台制备长片段Mate-paired库提供了方法指导。     

BAC-Pool Sequencing and Analysis of Large Segments of A12 and D12 Homoeologous Chromosomes in Upland Cotton

Although new and emerging next-generation sequencing (NGS) technologies have reduced sequencing costs significantly, much work remains to implement them for de novo sequencing of complex and highly repetitive genomes such as the tetraploid genome of Upland cotton (Gossypium hirsutum L.). Herein we report the results from implementing a novel, hybrid Sanger/454-based BAC-pool sequencing strategy using minimum tiling path (MTP) BACs from Ctg-3301 and Ctg-465, two large genomic segments in A12 and D12 homoeologous chromosomes (Ctg). To enable generation of longer contig sequences in assembly, we implemented a hybrid assembly method to process ~35x data from 454 technology and 2.8-3x data from Sanger method. Hybrid assemblies offered higher sequence coverage and better sequence assemblies. Homology studies revealed the presence of retrotransposon regions like Copia and Gypsy elements in these contigs and also helped in identifying new genomic SSRs. Unigenes were anchored to the sequences in Ctg-3301 and Ctg-465 to support the physical map. Gene density, gene structure and protein sequence information derived from protein prediction programs were used to obtain the functional annotation of these genes. Comparative analysis of both contigs with Arabidopsis genome exhibited synteny and microcollinearity with a conserved gene order in both genomes. This study provides insight about use of MTP-based BAC-pool sequencing approach for sequencing complex polyploid genomes with limited constraints in generating better sequence assemblies to build reference scaffold sequences. Combining the utilities of MTP-based BAC-pool sequencing with current longer and short read NGS technologies in multiplexed format would provide a new direction to cost-effectively and precisely sequence complex plant genomes.