June 1, 2021  |  

Evaluating the potential of new sequencing technologies for genotyping and variation discovery in human data.

A first look at Pacific Biosciences RS data Pacific Biosciences technology provides a fundamentally new data type that provides the potential to overcome these limitations by providing significantly longer reads (now averaging >1kb), enabling more unique seeds for reference alignment. In addition, the lack of amplification in the library construction step avoids a common source of base composition bias. With these potential advantages in mind, we here evaluate the utility of the Pacific Biosciences RS platform for human medical resequencing projects by assessing the quality of the raw sequencing data, as well as its use for SNP discovery and genotyping using the Genome Analysis Toolkit (GATK).


June 1, 2021  |  

An interactive workflow for the analysis of contigs from the metagenomic shotgun assembly of SMRT Sequencing data.

The data throughput of next-generation sequencing allows whole microbial communities to be analyzed using a shotgun sequencing approach. Because a key task in taking advantage of these data is the ability to cluster reads that belong to the same member in a community, single-molecule long reads of up to 30 kb from SMRT Sequencing provide a unique capability in identifying those relationships and pave the way towards finished assemblies of community members. Long reads become even more valuable as samples get more complex with lower intra-species variation, a larger number of closely related species, or high intra-species variation. Here we present a collection of tools tailored for PacBio data for the analysis of these fragmented metagenomic assembles, allowing improvements in the assembly results, and greater insight into the communities themselves. Supervised classification is applied to a large set of sequence characteristics, e.g., GC content, raw-read coverage, k-mer frequency, and gene prediction information, allowing the clustering of contigs from single or highly related species. A unique feature of SMRT Sequencing data is the availability of base modification / methylation information, which can be used to further analyze clustered contigs expected to be comprised of single or very closely related species. Here we show base modification information can be used to further study variation, based on differences in the methylated DNA motifs involved in the restriction modification system. Application of these techniques is demonstrated on a monkey intestinal microbiome sample and an in silico mix of real sequencing data from distinct bacterial samples.


June 1, 2021  |  

Draft genome of horseweed illuminates expansion of gene families that might endow herbicide resistance.

Conyza canadensis (horseweed), a member of the Compositae (Asteraceae) family, was the first broadleaf weed to evolve resistance to glyphosate. Horseweed, one of the most problematic weeds in the world, is a true diploid (2n=2X=18) with the smallest genome of any known agricultural weed (335 Mb). Thus, it is an appropriate candidate to help us understand the genetic and genomic basis of weediness. We undertook a draft de novo genome assembly of horseweed by combining data from multiple sequencing platforms (454 GS-FLX, Illumina HiSeq 2000 and PacBio RS) using various libraries with different insertion sizes (~350 bp, ~600 bp, ~3 kb and ~10 kb) of a Tennessee-accessed, glyphosate-resistant horseweed biotype. From 116.3 Gb (~350× coverage) of data, the genome was assembled into 13,966 scaffolds with N50 =33,561 bp. The assembly covered 92.3% of the genome, including the complete chloroplast genome (~153 kb) and a nearly-complete mitochondrial genome (~450 kb in 120 scaffolds). The nuclear genome is comprised of 44,592 protein-coding genes. Genome re-sequencing of seven additional horseweed biotypes was performed. These sequence data were assembled and used to analyze genome variation. Simple sequence repeat and single nucleotide polymorphisms were surveyed. Genomic patterns were detected that associated with glyphosate-resistant or –susceptible biotypes. The draft genome will be useful to better understand weediness, the evolution of herbicide resistance, and to devise new management strategies. The genome will also be useful as another reference genome in the Compositae. To our knowledge, this paper represents the first published draft genome of an agricultural weed.


June 1, 2021  |  

Old school/new school genome sequencing: One step backward — a quantum leap forward.

As the costs for genome sequencing have decreased the number of “genome” sequences have increased at a rapid pace. Unfortunately, the quality and completeness of these so–called “genome” sequences have suffered enormously. We prefer to call such genome assemblies as “gene assembly space” (GAS). We believe it is important to distinguish GAS assemblies from reference genome assemblies (RGAs) as all subsequent research that depends on accurate genome assemblies can be highly compromised if the only assembly available is a GAS assembly.


June 1, 2021  |  

A workflow for the analysis of contigs from the metagenomic shotgun assembly of SMRT Sequencing data

The throughput of SMRT Sequencing and long reads allows microbial communities to be analyzed using a shotgun sequencing approach. Key to leveraging this data is the ability to cluster sequences belonging to the same member of a community. Long reads of up to 40 kb provide a unique capability in identifying those relationships, and pave the way towards finished assemblies of community members. Long reads are highly valuable when samples are more complex and containing lower intra-species variation, such as a larger number of closely related species, or high intra-species variation. Here, we present a collection of tools tailored for the analysis of PacBio metagenomic assemblies. These tools allow for improvements in the assembly results, and greater insight into the complexity of the study communities. Supervised classification is applied to a large set of sequence characteristics (e.g. GC content, raw read coverage, k-mer frequency, and gene prediction information) and to cluster contigs from single or highly related species. Assembly in isolation of the raw data associated with these contigs is shown to improve assembly statistics. A unique feature of SMRT Sequencing is the availability to leverage simultaneously collected base modification / methylation data to aid the clustering of contigs expected to comprise a single or very closely related species. We demonstrate the added value of base modification information to distinguish and study variation within metagenomic samples based on differences in the methylated DNA motifs involved in the restriction modification system. Application of these techniques is demonstrated on a mock community and monkey intestinal microbiome sample.


June 1, 2021  |  

Complete microbial genomes, epigenomes, and transcriptomes using long-read PacBio Sequencing.

For comprehensive metabolic reconstructions and a resulting understanding of the pathways leading to natural products, it is desirable to obtain complete information about the genetic blueprint of the organisms used. Traditional Sanger and next-generation, short-read sequencing technologies have shortcomings with respect to read lengths and DNA-sequence context bias, leading to fragmented and incomplete genome information. The development of long-read, single molecule, real-time (SMRT) DNA sequencing from Pacific Biosciences, with >10,000 bp average read lengths and a lack of sequence context bias, now allows for the generation of complete genomes in a fully automated workflow. In addition to the genome sequence, DNA methylation is characterized in the process of sequencing. PacBio® sequencing has also been applied to microbial transcriptomes. Long reads enable sequencing of full-length cDNAs allowing for identification of complete gene and operon sequences without the need for transcript assembly. We will highlight several examples where these capabilities have been leveraged in the areas of industrial microbiology, including biocommodities, biofuels, bioremediation, new bacteria with potential commercial applications, antibiotic discovery, and livestock/plant microbiome interactions.


June 1, 2021  |  

Full-length isoform sequencing of the human MCF-7 cell line using PacBio long reads.

While advances in RNA sequencing methods have accelerated our understanding of the human transcriptome, isoform discovery remains a challenge because short read lengths require complicated assembly algorithms to infer the contiguity of full-length transcripts. With PacBio’s long reads, one can now sequence full-length transcript isoforms up to 10 kb. The PacBio Iso- Seq protocol produces reads that originate from independent observations of single molecules, meaning no assembly is needed. Here, we sequenced the transcriptome of the human MCF-7 breast cancer cell line using the Clontech SMARTer® cDNA preparation kit and the PacBio RS II. Using PacBio Iso-Seq bioinformatics software, we obtained 55,770 unique, full-length, high-quality transcript sequences that were subsequently mapped back to the human genome with = 99% accuracy. In addition, we identified both known and novel fusion transcripts. To assess our results, we compared the predicted ORFs from the PacBio data against a published mass spectrometry dataset from the same cell line. 84% of the proteins identified with the Uniprot protein database were recovered by the PacBio predictions. Notably, 251 peptides solely matched to the PacBio generated ORFs and were entirely novel, including abundant cases of single amino acid polymorphisms, cassette exon splicing and potential alternative protein coding frames.


June 1, 2021  |  

Highly accurate read mapping of third generation sequencing reads for improved structural variation analysis

Characterizing genomic structural variations (SV) is vital for understanding how genomes evolve. Furthermore, SVs are known for playing a role in a wide range of diseases including cancer, autism, and schizophrenia. Nevertheless, due to their complexity they remain harder to detect and less understood than single nucleotide variations. Recently, third-generation sequencing has proven to be an invaluable tool for detecting SVs. The markedly higher read length not only allows single reads to span a SV, it also enables reliable mapping to repetitive regions of the genome. These regions often contain SVs and are inaccessible to short-read mapping. However, current sequencing technologies like PacBio show a raw read error rate of 10% or more consisting mostly of insertions and deletions. Especially in repetitive regions the high error rate causes current mapping methods to fail finding exact borders for SVs, to split up large deletions and insertions into several small ones, or in some cases, like inversions, to fail reporting them at all. Furthermore, for complex SVs it is not possible to find one end-to-end alignment for a given read. The decision of when to split a read into two or more separate alignments without knowledge of the underlying SV poses an even bigger challenge to current read mappers. Here we present NextGenMap-LR for long single molecule PacBio reads which addresses these issues. NextGenMap-LR uses a fast k-mer search to quickly find anchor regions between parts of a read and the reference and evaluates them using a vectorized implementation of the Smith-Waterman (SW) algorithm. The resulting high-quality anchors are then used to determine whether a read spans an SV and has to be split or can be aligned contiguously. Finally, NextGenMap-LR uses a banded SW algorithm to compute the final alignment(s). In this last step, to account for both the sequencing error and real genomic variations, we employ a non-affine gap model that penalizes gap extensions for longer gaps less than for shorter ones. Based on simulated as well as verified human breast cancer SV data we show how our approach significantly improves mapping of long reads around SVs. The non-affine gap model is especially effective at more precisely identifying the position of the breakpoint, and the enhanced scoring scheme enables subsequent variation callers to identify SVs that would have been missed otherwise.


June 1, 2021  |  

Comprehensive genome and transcriptome structural analysis of a breast cancer cell line using PacBio long read sequencing

Genomic instability is one of the hallmarks of cancer, leading to widespread copy number variations, chromosomal fusions, and other structural variations. The breast cancer cell line SK-BR-3 is an important model for HER2+ breast cancers, which are among the most aggressive forms of the disease and affect one in five cases. Through short read sequencing, copy number arrays, and other technologies, the genome of SK-BR-3 is known to be highly rearranged with many copy number variations, including an approximately twenty-fold amplification of the HER2 oncogene. However, these technologies cannot precisely characterize the nature and context of the identified genomic events and other important mutations may be missed altogether because of repeats, multi-mapping reads, and the failure to reliably anchor alignments to both sides of a variation. To address these challenges, we have sequenced SK-BR-3 using PacBio long read technology. Using the new P6-C4 chemistry, we generated more than 70X coverage of the genome with average read lengths of 9-13kb (max: 71kb). Using Lumpy for split-read alignment analysis, as well as our novel assembly-based algorithms for finding complex variants, we have developed a detailed map of structural variations in this cell line. Taking advantage of the newly identified breakpoints and combining these with copy number assignments, we have developed an algorithm to reconstruct the mutational history of this cancer genome. From this we have discovered a complex series of nested duplications and translocations between chr17 and chr8, two of the most frequent translocation partners in primary breast cancers, resulting in amplification of HER2. We have also carried out full-length transcriptome sequencing using PacBio’s Iso-Seq technology, which has revealed a number of previously unrecognized gene fusions and isoforms. Combining long-read genome and transcriptome sequencing technologies enables an in-depth analysis of how changes in the genome affect the transcriptome, including how gene fusions are created across multiple chromosomes. This analysis has established the most complete cancer reference genome available to date, and is already opening the door to applying long-read sequencing to patient samples with complex genome structures.


June 1, 2021  |  

From Sequencing to Chromosomes: New de novo assembly and scaffolding methods improve the goat reference genome

Single-molecule sequencing is now routinely used to assemble complete, high-quality microbial genomes, but these assembly methods have not scaled well to large genomes. To address this problem, we previously introduced the MinHash Alignment Process (MHAP) for overlapping single-molecule reads using probabilistic, locality-sensitive hashing. Integrating MHAP with Celera Assembler (CA) has enabled reference-grade assemblies of model organisms, revealing novel heterochromatic sequences and filling low-complexity gap sequences in the GRCh38 human reference genome. We have applied our methods to assemble the San Clemente goat genome. Combining single-molecule sequencing from Pacific Biosciences and BioNano Genomics generates and assembly that is over 150-fold more contiguous than the latest Capra hircus reference. In combination with Hi-C sequencing, the assembly surpasses reference assemblies, de novo, with minimal manual intervention. The autosomes are each assembled into a single scaffold. Our assembly provides a more complete gene reconstruction, better alignments with Goat 52k chip, and improved allosome reconstruction. In addition to providing increased continuity of sequence, our assembly achieves a higher BUSCO completion score (84%) than the existing goat reference assembly suggesting better quality annotation of gene models. Our results demonstrate that single-molecule sequencing can produce near-complete eukaryotic genomes at modest cost and minimal manual effort.


June 1, 2021  |  

Minimization of chimera formation and substitution errors in full-length 16S PCR amplification

The constituents and intra-communal interactions of microbial populations have garnered increasing interest in areas such as water remediation, agriculture and human health. One popular, efficient method of profiling communities is to amplify and sequence the evolutionarily conserved 16S rRNA sequence. Currently, most targeted amplification focuses on short, hypervariable regions of the 16S sequence. Distinguishing information not spanned by the targeted region is lost and species-level classification is often not possible. SMRT Sequencing easily spans the entire 1.5 kb 16S gene, and in combination with highly-accurate single-molecule sequences, can improve the identification of individual species in a metapopulation. However, when amplifying a mixture of sequences with close similarities, the products may contain chimeras, or recombinant molecules, at rates as high as 20-30%. These PCR artifacts make it difficult to identify novel species, and reduce the amount of productive sequences. We investigated multiple factors that have been hypothesized to contribute to chimera formation, such as template damage, denaturing time before and during cycling, polymerase extension time, and reaction volume. Of the factors tested, we found two major related contributors to chimera formation: the amount of input template into the PCR reaction and the number of PCR cycles. Sequence errors generated during amplification and sequencing can also confound the analysis of complex populations. Circular Consensus Sequencing (CCS) can generate single-molecule reads with >99% accuracy, and the SMRT Analysis software provides filtering of these reads to >99.99% accuracies. Remaining substitution errors in these highly-filtered reads are likely dominated by mis-incorporations during amplification. Therefore, we compared the impact of several commercially-available high-fidelity PCR kits with full-length 16S amplification. We show results of our experiments and describe an optimized protocol for full-length 16S amplification for SMRT Sequencing. These optimizations have broader implications for other applications that use PCR amplification to phase variations across targeted regions and to generate highly accurate reference sequences.


June 1, 2021  |  

An improved circular consensus algorithm with an application to detection of HIV-1 Drug-Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger Sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach arbitrarily high quality across longer insert lengths at a lower cost and higher throughput than Sanger Sequencing. We apply this new algorithm, dubbed CCS2, to the characterization of the HIV-1 K103N drug-resistance associated mutation, which is both important clinically, and represents a challenge due to regional sequence context. A mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1,300 bp were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to arbitrarily high accuracy. This result, previously demonstrated for multi-molecule consensus sequences with the Quiver algorithm, is made possible by incorporating per-Zero Mode Waveguide (ZMW) characteristics, thus accounting for the intrinsic changes in the sequencing process that are unique to each ZMW. With CCS2, we are able to achieve a per-read empirical quality of QV30 with 19X coverage. This yields ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40. Additionally, we demonstrate a 0% miscall rate in both unmixed samples, and estimate a 48:52% frequency for the K103N mutation in the mixed sample, consistent with data produced by orthogonal platforms.


June 1, 2021  |  

Candidate gene screening using long-read sequencing

We have developed several candidate gene screening applications for both Neuromuscular and Neurological disorders. The power behind these applications comes from the use of long-read sequencing. It allows us to access previously unresolvable and even unsequencable genomic regions. SMRT Sequencing offers uniform coverage, a lack of sequence context bias, and very high accuracy. In addition, it is also possible to directly detect epigenetic signatures and characterize full-length gene transcripts through assembly-free isoform sequencing. In addition to calling the bases, SMRT Sequencing uses the kinetic information from each nucleotide to distinguish between modified and native bases.


June 1, 2021  |  

An improved circular consensus algorithm with an application to detect HIV-1 Drug Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach high quality across longer insert lengths at a lower cost and higher throughput than Sanger sequencing. We applied CCS2 to the characterization of the HIV-1 K103N drug-resistance associated mutation in both clonal and patient samples. This particular DRAM has previously proved to be clinically relevant, but challenging to characterize due to regional sequence context. First, a mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1.3 kb were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Additionally, the proviral reservoir of a subject with known dates of virologic failure of an Efavirenz-based regimen and with documented emergence of drug resistant (K103N) viremia was sequenced at several time points as a proof-of-concept study to determine the kinetics of retention and decay of K103N.Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to high accuracy. With CCS2, we are able to achieve a per-read empirical quality of QV30 (99.9% accuracy) at 19X coverage. A total of ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40 (99.99%) were obtained for each sample. We demonstrate a 0% miscall rate in both unmixed control samples, and estimate a 48:52 frequency for the K103N mutation in the mixed (50:50) plasmid sample, consistent with data produced by orthogonal platforms. Additionally, the K103N escape variant was only detected in proviral samples from time points subsequent (19%) to the emergence of drug resistant viremia. This tool might be used to monitor the HIV reservoir for stable evolutionary changes throughout infection.


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