Torrent assembly

Specifically, the PacBio-only assembly resulted in less than 20 scaffolds, while the MiSeq assemblies resulted in over 30 scaffolds. Quiver is a software package that generates high quality consensus sequences by mapping long PacBio reads against a reference [ 16 ]. The assembled scaffolds were used as a reference, and uncorrected PacBio reads were used as the input to generate the consensus.

We found Quiver to be effective at reducing indels and SNPs, often dramatically improving the accuracy of the assembly Table 8. A unique feature of data generated with the PacBio is the ability to call base modifications.

Identification of these modifications is based on the kinetics of base incorporation. When the interpulse distance ratio of base incorporation differs from expected, it indicates the presence of a modified base [ 39 ].

The specific kinetic signatures for 5mC, 6 mA, and 4mC can be reliably modeled and identified from sequencing data. To call 5mC base modifications, a specialized library preparation is required that increases the intensity signal above background [ 40 ]. Current protocols for this library preparation require bp - 1 kb insert libraries treated with tetracycline.

The E. As an E. Finally, Bal is known to lack both the DAM and DCM methylases, and therefore we would expect not to find the motifs associated with these methylases to be methylated. This module requires a reference sequence, and for these studies we used the scaffolds that resulted from self-correction and assembly performed earlier.

In short, all expected modifications were identified, with no false positives. Table 9 shows the methylation patterns identified for each strain, and Figure 5 shows the location of each motif and each modified motif mapped against the assembled scaffolds.

Circos plots of base modifications. In each figure, the assembled contigs are plotted as the inner grey bars. On either side of these grey contigs, the short lines indicate motif positions in the genome the plus sense and minus sense are plotted.

Outside of those are the location of the modifications and the intensity of those modifications. In this study we explore a variety of methodologies for the de novo assembly of bacterial genomes and analyze the epigenetic base modifications associated with the E. Understanding how best to assemble bacterial genomes de novo is important for at least two reasons.

First, bacteria play an important role in nearly all ecological and biological processes on Earth. Full knowledge of how these bacteria interact with the world around them requires an understanding of their underlying genetic architecture. Second, bacterial genomes are relatively simple when compared to more complex eukaryotic genomes. Thus, a firm understanding of how best to assemble bacterial genomes can inform the assembly of larger, more complex genomes.

Here we examined four different methodologies for the assembly of bacterial genomes: short read only assembly, hybrid scaffolding, hybrid assembly, and PacBio-only assembly Figure 1. As was expected, the assemblies with the greatest number of contigs came from assemblies using either the Ion Torrent or MiSeq data alone short read only. Both Velvet and Ray are de Bruijn graph-based assemblers. These assemblers are known to be less tolerant of sequencing errors, which may explain why they struggled with the Ion Torrent data whose Q scores were slightly below that of the MiSeq data We performed a kmer and coverage parameter sweep with Velvet and the MiSeq data, examining 48 different assemblies.

Velvet was capable of assembling the MiSeq data effectively, with generally less than contigs that were typically longer than any of the other short read assemblies. MIRA, which is not a de Bruijn graph assembler, was able to assemble both sets of data, producing the lowest number of contigs with Ion Torrent data, although of the three methods, MIRA had the most trouble with the MiSeq data. Ray stood apart as the most accurate of the three assemblers, based on the number of inversions, relocations, SNPs, and a visual inspection of the associated dot plots Table 2 , Figure 2.

These more accurate assemblies did not come at a cost of assembly completeness Table 1. In particular, the Ray-MiSeq assemblies were often the most complete, with contigs of or less for three of the coverages, the only short read assembler-data combination to achieve such results. One interesting finding from this study is that more short read coverage does not necessarily guarantee a better assembly.

We found that lower coverages, especially for the Ion Torrent data, often resulted in assemblies that were similar to those generated with higher coverage. This is not entirely unexpected for the MIRA assemblies, as overlap graph based assemblers are less tolerant of high coverage [ 42 ].

However this observation held true for the Ray-Ion Torrent assemblies as well. We should also note here that while it is typically thought that paired-end data is significantly better for assembly than is single-end data, there was little difference in assembly completeness between the best MiSeq assembly performed with Ray and the best Ion Torrent assembly assembled with MIRA.

After generating these short read assemblies, we chose 1 representative assembly from each data:assembler combination highlighted in Table 1 and attempted to connect the contigs with long, uncorrected PacBio reads. The assembly that seemed to benefit the most from hybrid scaffolding was the Ray-Ion Torrent assembly Table 3. This is not terribly surprising, as the Ray-Ion Torrent assemblies were the most accurate, and yet the most fractured, and therefore should be the easiest to connect.

Far more relocations, inversions, indels, and SNPs are present in these assemblies than in the short read only assemblies Table 4 and Figure 3. Errors in hybrid scaffolding represent overly aggressive attempts to connect contigs, some of which are connected erroneously.

Therefore, it should be possible to reduce the aggressiveness of this process in order to eliminate some of these introduced errors, and others may be resolved by running Quiver post-assembly. Reducing the aggressiveness of contig scaffolding will result in less complete assemblies, but the gains made in accuracy may be acceptable in some circumstances. In spite of these potential errors, we employed the hybrid scaffolding technique on all subsequent assemblies.

Often, the goal of assemblies is to achieve as complete an assembly as possible. There are always tradeoffs to be made, but in the end we believed that the gains resulting from scaffolding were worth the potential of introduced errors.

While short read only assemblies are still popular because of the relative newness, cost of entry, and throughput concerns associated with long read sequencing technology, the state of the art in genome assembly lies with the long reads generated by the PacBio. We therefore wanted to see how hybrid assembly and PacBio-only assemblies would compare with short read only assemblies and each other.

Unexpectedly, the Ion Torrent error-corrected reads assembled far more efficiently for each of the three strains examined across all coverages and parameter sweeps when compared to MiSeq error-corrected reads.

These results can be traced back to longer corrected reads post-Ion Torrent correction. This may be due to the fact that the Ion Torrent reads themselves are longer than the MiSeq reads. These longer reads should be easier to map back to the PacBio reads, increasing error correction efficiency.

MiSeq libraries were made using the Nextera kit, which fractures DNA with transposons as opposed to the mechanical shearing used to create the PacBio and Ion Torrent libraries or chemical shearing typical of other Illumina library preparation kits. The insert sizes associated with these libraries were far more varied than what is typically encountered with Illumina libraries, and this may have contributed to the poorer performance of the MiSeq data in both hybrid assembly and the short read only data assembly using MIRA Additional file 2 : Figure S1.

We used Preassembler with the same PacBio data that was used in the previous analyses. Remarkably, the PacBio-only assemblies were superior to the MiSeq-PacBio hybrid assembly across all strains and coverages examined. Furthermore, the completeness of these assemblies were generally comparable to, and often slightly superior to the best Ion Torrent-PacBio hybrid assemblies Tables 5 and 7. This accuracy improves even further when one finishes the assembly with Quiver Table 8.

The assembly results here fall largely in line with two recent papers [ 16 , 17 ]. Chin et al. In Koren, et al. Similar to the results shown here, the investigators found that self-correction of PacBio long reads lead to as good, or better, assemblies than hybrid-based approaches, and that assembly polishing with the Quiver package led to highly accurate assemblies [ 17 ].

This investigation diverges slightly from these two reports in that we unable to close the genome of the three investigated E. Closing the genome of microbes is generally thought to be highly correlated to the number and size of the repetitive elements found in the sequenced genomes.

Sequence reads must span the repeat regions in order to properly resolve these elements. When these reads are not present, gaps will occur. Two factors are thus important when considering whether or a bacterial genome can be closed — the expected maximum length of repetitive elements in the genome of interest, and the length of the sequencing reads. Read lengths of the corrected reads must be longer than the longest repeat, and have sufficient depth as to cover and resolve the repeat regions.

This should be close to the necessary lengths needed to resolve these repetitive elements, but were not sufficient in this case. It should be noted that in the time since this data has been generated, both Illumina and Life Technologies have introduced sequencing kits that produce even longer reads than what was used here — both platforms yield sequence reads that are twice as long as what was used in this study. These reads will undoubtedly improve assemblies with data generated solely by these machines.

Additionally, hybrid assemblies should be improved, as longer short read data seems to result in longer error-corrected reads. Still, given the difficulty these two technologies have with repetitive sequences and read lengths that still fall far short of those produced by PacBio, it is unlikely that these advancements would alter any of the conclusions made here.

However, Illumina has recently purchased a technology that rivals the PacBio in read length, known as Moleculo sequencing. This technology stitches together standard Illumina reads into long reads of approximately 10 kb in length.

These reads have the advantage of being both high quality and long, eliminating the need for error correction. Unfortunately since it is based on stitching together short reads, resolution of repetitive regions is likely to remain difficult. Until Moleculo becomes widely available, and the question of repetitive sequence resolution can be answered, the PacBio should be the platform of choice for any de novo bacterial assembly. In addition to superior assemblies, the PacBio offers a unique capability — the ability to call covalent base modifications.

The three strains in this study were specifically chosen to test the specificity and sensitivity of the PacBio sequencer and associated software to call modifications. We failed to find enrichments of the motifs associated with EcoKI, but in contrast, high rates of GATC modification were both expected and found.

Indeed, we found all three motifs to be modified. In summary, we compare and contrast competing methods for the assembly of bacterial genomes, demonstrating that PacBio-only assembly is comparable to hybrid assembly and significantly superior to assemblies performed with short read only data. We go on to demonstrate the sensitivity and specificity of calling base modifications using PacBio data. A recent report demonstrates that if enough long read data is obtained, a single contig will be the end result, however if individual contigs remain, researchers can improve the assembly by scaffolding with AHA, and gap-filling with PBJelly [ 15 — 17 , 19 ].

Finally, using Quiver as a final error correction step will improve the accuracy of the assembly even further and should be implemented to ensure the most accurate assembly possible. Ion Torrent Suite software version 3.

B October Briefly, genomic DNA was tagmented tagged with PCR adapters and fragmented , followed by purification of tagmented DNA and limited-cycle PCR during which indexes, sequencing adapters, and common adapters are added for subsequent cluster generation and sequencing.

Three libraries were prepared for each strain: long insert, long insert with Tet1-treatment and 1 kb insert with Tet1-treatment. Libraries were subsequently prepared following PacBio guidelines.

End-repair was performed, followed by ligation of universal hairpin adapters to produce the SMRTbell library. The PacBio specific sequencing primer was annealed to the SMRTbell library followed by binding of the polymerase to the primer-library complex.

Both libraries were sequenced using the C2 chemistry and C2-XL enzyme. Ion Torrent data was de-multiplexed using Ion Torrent Suite software version 3. Unless otherwise noted, all data was clipped for adapters and quality scores with fastq-mcf, also internally developed and available for download [ 46 ].

MiSeq reads were assembled with the Velvet v. Specifically, kmers were varied from 21 to Statistics such as contig number, N50, and max contig length were generated from each assembly using the script contig-stats available for download from ea-utils , and visually inspected.

Based on these statistics, a kmer of 59 was chosen as consistently among the best for the four coverages examined. In a similar manner, assemblies with the Ray assembler v.

Ray was capable of assembling both the Ion Torrent and MiSeq data. Assemblies were again inspected for completeness, and based on these statistics, a kmer of 36 for the MiSeq data and 29 for the Ion Torrent data consistently resulted in the best assemblies across the four different coverages. PacBio long reads were error-corrected by x coverage of either MiSeq reads or Ion Torrent reads essentially as described [ 12 ].

These frg files were then used as input, along with the uncorrected reads into pacBioToCA. SMRT cells were chosen in the interface for use in each set of corrections.

Celera assembler v. Ten different parameter settings for each data set was used, mostly variations of ErrorRates and merSize Additional file 4 : Table S3. Celera assemblies were assessed with amosvalidate and FRCurve as described [ 37 , 38 ]. PacBio reads were used to scaffold the contigs using default parameters.

The resultant scaffolds were gap-filled with PBJelly [ 19 ], again using default parameters. It allows you and your friends to build your own unique robot or vehicle, determine the conditions of the game and compete against each other.

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The site is non-commercial and we are not able to check all user posts. Main Assembly screenshots:. Size: 1. If you come across it, the password is: online-fix. The sequences of novel transcripts can be reconstructed from deep RNA-Seq data, but this is computationally challenging due to sequencing errors, uneven coverage of expressed transcripts, and the need to distinguish between highly similar transcripts produced by alternative splicing.

Another challenge in transcriptomic analysis comes from the ambiguities in mapping reads to transcripts. Our approach explores transcriptome structure and incorporates a maximum likelihood model into the assembly and quantification procedure.