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June 1, 2021  |  

The resurgence of reference quality genome sequence.

Since the advent of Next-Generation Sequencing (NGS), the cost of de novo genome sequencing and assembly have dropped precipitately, which has spurred interest in genome sequencing overall. Unfortunately the contiguity of the NGS assembled sequences, as well as the accuracy of these assemblies have suffered. Additionally, most NGS de novo assemblies leave large portions of genomes unresolved, and repetitive regions are often collapsed. When compared to the reference quality genome sequences produced before the NGS era, the new sequences are highly fragmented and often prove to be difficult to properly annotate. In some cases the contiguous portions are smaller than the average gene size making the sequence not nearly as useful for biologists as the earlier reference quality genomes including of Human, Mouse, C. elegans, or Drosophila. Recently, new 3rd generation sequencing technologies, long-range molecular techniques, and new informatics tools have facilitated a return to high quality assembly. We will discuss the capabilities of the technologies and assess their impact on assembly projects across the tree of life from small microbial and fungal genomes through large plant and animal genomes. Beyond improvements to contiguity, we will focus on the additional biological insights that can be made with better assemblies, including more complete analysis genes in their flanking regulatory context, in-depth studies of transposable elements and other complex gene families, and long-range synteny analysis of entire chromosomes. We will also discuss the need for new algorithms for representing and analyzing collections of many complete genomes at once.


June 1, 2021  |  

Toward comprehensive genomics analysis with de novo assembly.

Whole genome sequencing can provide comprehensive information important for determining the biochemical and genetic nature of all elements inside a genome. The high-quality genome references produced from past genome projects and advances in short-read sequencing technologies have enabled quick and cheap analysis for simple variants. However even with the focus on genome-wide resequencing for SNPs, the heritability of more than 50% of human diseases remains elusive. For non-human organisms, high-contiguity references are deficient, limiting the analysis of genomic features. The long and unbiased reads from single molecule, real-time (SMRT) Sequencing and new de novo assembly approaches have demonstrated the ability to detect more complicated variants and chromosome-level phasing. Moreover, with the recent advance of bioinformatics algorithms and tools, the computation tasks for completing high-quality de novo assembly of large genomes becomes feasible with commodity hardware. Ongoing development in sequencing technologies and bioinformatics will likely lead to routine generation of high-quality reference assemblies in the future. We discuss the current state of art and the challenges in bioinformatics toward such a goal. More specifically, explicit examples of pragmatic computational requirements for assembling mammalian-size genomes and algorithms suitable for processing diploid genomes are discussed.


June 1, 2021  |  

Whole genome sequencing and epigenome characterization of cancer cells using the PacBio platform.

The comprehensive characterization of cancer genomes and epigenomes for understanding drug resistance remains an important challenge in the field of oncology. For example, PC-9, a non-small cell lung cancer (NSCL) cell line, contains a deletion mutation in exon 19 (DelE746A750) of EGRF that renders it sensitive to erlotinib, an EGFR inhibitor. However, sustained treatment of these cells with erlotinib leads to drug-tolerant cell populations that grow in the presence of erlotinib. However, the resistant cells can be resensitized to erlotinib upon treatment with methyltransferase inhibitors, suggesting a role of epigenetic modification in development of drug resistance. We have characterized for the first time cancer genomes of both drug-sensitive and drug-resistant PC- 9 cells using long-read PacBio sequencing. The PacBio data allowed us to generate a high-quality, de novo assembly of this cancer genome, enabling the detection of forms of genomic variations at all size scales, including SNPs, structural variations, copy number alterations, gene fusions, and translocations. The data simultaneously provide a global view of epigenetic DNA modifications such as methylation. We will present findings on large-scale changes in the methylation status across the cancer genome as a function of drug sensitivity.


June 1, 2021  |  

Full-length env deep sequencing in a donor with broadly neutralizing V1/V2 antibodies.

Background: Understanding the co-evolution of HIV populations and broadly neutralizing antibody (bNAb) lineages may inform vaccine design. Novel long-read, next-generation sequencing methods allow, for the first time, full-length deep sequencing of HIV env populations. Methods: We longitudinally examined env populations (12 time points) in a subtype A infected individual from the IAVI primary infection cohort (Protocol C) who developed bNAbs (62% ID50>50 on a diverse panel of 105 viruses) targeting the V1/V2 region. We developed a Pacific Biosciences single molecule, real-time sequencing protocol to deeply sequence full-length env from HIV RNA. Bioinformatics tools were developed to align env sequences, infer phylogenies, and interrogate escape dynamics of key residues and glycosylation sites. PacBio env sequences were compared to env sequences generated through amplification and cloning. Env dynamics were interpreted in the context of the development of a V1/V2-targeting bNAb lineage isolated from the donor. Results: We collected a median of 6799 high quality full-length env sequences per timepoint (median per-base accuracy of 99.7%). A phylogeny inferred with PacBio and 100 cloned env sequences (10 time points) found cloned env sequences evenly distributed among PacBio sequences. Phylogenetic analyses also revealed a potential transient intra-clade superinfection visible as a minority variant (~5%) at 9 months post-infection (MPI), and peaking in prevalence at 12MPI (~64%), just preceding the development of heterologous neutralization. Viral escape from the bNAb lineage was evident at V2 positions 160, 166, 167, 169 and 181 (HxB2 numbering), exhibiting several distinct escape pathways by 40MPI. Conclusions: Our PacBio full-length env sequencing method allowed unprecedented characterization of env dynamics and revealed an intra-clade superinfection that was not detected through conventional methods. The importance of superinfection in the development of this donor’s V1/V2-directed bNAb lineage is under investigation. Longitudinal full-length env deep sequencing allows accurate phylogenetic inference, provides a detailed picture of escape dynamics in epitope regions, and can identify minority variants, all of which may prove useful for understanding how env evolution can drive the development of antibody breadth.


June 1, 2021  |  

Profiling metagenomic communities using circular consensus and Single Molecule, Real-Time Sequencing.

There are many sequencing-based approaches to understanding complex metagenomic communities spanning targeted amplification to whole-sample shotgun sequencing. While targeted approaches provide valuable data at low sequencing depth, they are limited by primer design and PCR amplification. Whole-sample shotgun experiments generally use short-read, second-generation sequencing, which results in data processing difficulties. For example, reads less than 1 kb in length will likely not cover a complete gene or region of interest, and will require assembly. This not only introduces the possibility of incorrectly combining sequence from different community members, it requires a high depth of coverage. As such, rare community members may not be represented in the resulting assembly. Circular-consensus, single molecule, real-time (SMRT) Sequencing reads in the 1-2 kb range, with >99% accuracy can be efficiently generated for low amounts of input DNA. 10 ng of input DNA sequenced in 4 SMRT Cells would generate >100,000 such reads. While throughput is low compared to second-generation sequencing, the reads are a true random sampling of the underlying community, since SMRT Sequencing has been shown to have no sequence-context bias. Long read lengths mean that that it would be reasonable to expect a high number of the reads to include gene fragments useful for analysis.


June 1, 2021  |  

The “Art” of shotgun sequencing

2015 SMRT Informatics Developers Conference Presentation Slides: Jason Chin of PacBio highlighted some of the challenges for shotgun assembly while suggesting some potential solutions to obtain diploid assemblies, including the FALCON method.


June 1, 2021  |  

MinHash for overlapping and assembly

2015 SMRT Informatics Developers Conference Presentation Slides: Sergey Koren of National Biodefense Analysis and Countermeasures Center (NBACC) provided an overview of the MHAP algorithm, a method for assembling large genomes with Sing-Molecule Sequencing and locality sensitive hashing. Using MHAP, Koren produced a human assembly (CHM1) with a contig N50 of >23 Mb.


June 1, 2021  |  

Epigenome characterization of human genomes using the PacBio platform

In addition to the genome and transcriptome, epigenetic information is essential to understand biological processes and their regulation, and their misregulation underlying disease. Traditionally, epigenetic DNA modifications are detected using upfront sample preparation steps such as bisulfite conversion, followed by sequencing. Bisulfite sequencing has provided a wealth of knowledge about human epigenetics, however it does not access the entire genome due to limitations in read length and GC- bias of the sequencing technologies used. In contrast, Single Molecule, Real-Time (SMRT) DNA Sequencing is unique in that it can detect DNA base modifications as part of the sequencing process. It can thereby leverage the long read lengths and lack of GC bias for more comprehensive views of the human epigenome. I will highlight several examples of this capability towards the generation of new biological insights, including the resolution of methylation states in repetitive and GC-rich regions of the genome, and large-scale changes in the methylation status across a cancer genome as a function of drug sensitivity.


June 1, 2021  |  

Genome in a Bottle: You’ve sequenced. How well did you do?

Purpose: Clinical laboratories, research laboratories and technology developers all need DNA samples with reliably known genotypes in order to help validate and improve their methods. The Genome in a Bottle Consortium (genomeinabottle.org) has been developing Reference Materials with high-accuracy whole genome sequences to support these efforts.Methodology: Our pilot reference material is based on Coriell sample NA12878 and was released in May 2015 as NIST RM 8398 (tinyurl.com/giabpilot). To minimize bias and improve accuracy, 11 whole-genome and 3 exome data sets produced using 5 different technologies were integrated using a systematic arbitration method [1]. The Genome in a Bottle Analysis Group is adapting these methods and developing new methods to characterize 2 families, one Asian and one Ashkenazi Jewish from the Personal Genome Project, which are consented for public release of sequencing and phenotype data. We have generated a larger and even more diverse data set on these samples, including high-depth Illumina paired-end and mate-pair, Complete Genomics, and Ion Torrent short-read data, as well as Moleculo, 10X, Oxford Nanopore, PacBio, and BioNano Genomics long-read data. We are analyzing these data to provide an accurate assessment of not just small variants but also large structural variants (SVs) in both “easy” regions of the genome and in some “hard” repetitive regions. We have also made all of the input data sources publicly available for download, analysis, and publication.Results: Our arbitration method produced a reference data set of 2,787,291 single nucleotide variants (SNVs), 365,135 indels, 2744 SVs, and 2.2 billion homozygous reference calls for our pilot genome. We found that our call set is highly sensitive and specific in comparison to independent reference data sets. We have also generated preliminary assemblies and structural variant calls for the next 2 trios from long read data and are currently integrating and validating these.Discussion: We combined the strengths of each of our input datasets to develop a comprehensive and accurate benchmark call set. In the short time it has been available, over 20 published or submitted papers have used our data. Many challenges exist in comparing to our benchmark calls, and thus we have worked with the Global Alliance for Genomics and Health to develop standardized methods, performance metrics, and software to assist in its use.[1] Zook et al, Nat Biotech. 2014.


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  |  

Detection of structural variants using third generation sequencing

Structural Variants (SVs), which include deletions, insertions, duplications, inversions and chromosomal rearrangements, have been shown to effect organism phenotypes, including changing gene expression, increasing disease risk, and playing an important role in cancer development. Still it remains challenging to detect all types of SVs from high throughput sequencing data and it is even harder to detect more complex SVs such as a duplication nested within an inversion. To overcome these challenges we developed algorithms for SV analysis using longer third generation sequencing reads. The increased read lengths allow us to span more complex SVs and accurately assess SVs in repetitive regions, two of the major limitations when using short Illumina data. Our enhanced open-source analysis method Sniffles accurately detects structural variants based on split read mapping and assessment of the alignments. Sniffles uses a self-balancing interval tree in combination with a plane sweep algorithm to manage and assess the identified SVs. Central to its high accuracy is its advanced scoring model that can distinguish erroneous alignments from true breakpoints flanking SVs. In experiments with simulated and real genomes (e.g human breast cancer), we find that Sniffles outperforms all other SV analysis approaches in both the sensitivity of finding events as well as the specificity of those events. Sniffles is available at: https://github.com/fritzsedlazeck/Sniffles


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.


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