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Asset Tag: bioinformatics

June 1, 2021

Resources for advanced bioinformaticians working in plant and animal genomes with SMRT Sequencing.

Significant advances in bioinformatics tool development have been made to more efficiently leverage and deliver high-quality genome assemblies with PacBio long-read data. Current data throughput of SMRT Sequencing delivers average read lengths ranging from 10-15 kb with the longest reads exceeding 40 kb. This has resulted in consistent demonstration of a minimum 10-fold improvement in genome assemblies with contig N50 in the megabase range compared to assemblies generated using only short- read technologies. This poster highlights recent advances and resources available for advanced bioinformaticians and developers interested in the current state-of-the-art large genome solutions available as open-source code from PacBio and third-party solutions, including HGAP, MHAP, and ECTools. Resources and tools available on GitHub are reviewed, as well as datasets representing major model research organisms made publically available for community evaluation or interested developers.

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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.

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June 1, 2021

Sequencing complex mixtures of HIV-1 genomes with single-base resolution.

A large number of distinct HIV-1 genomes can be present in a single clinical sample from a patient chronically infected with HIV-1. We examined samples containing complex mixtures of near-full-length HIV-1 genomes. Single molecules were sequenced as near-full-length (9.6 kb) amplicons directly from PCR products without shearing. Mathematical analysis techniques deconvolved the complex mixture of reads into estimates of distinct near-full-length viral genomes with their relative abundances. We correctly estimated the originating genomes to single-base resolution along with their relative abundances for mixtures where the truth was known exactly by independent sequencing methods. Correct estimates were made even when genomes diverged by a single base. Minor abundances of 5% were reliably detected. SMRT Sequencing data contained near-full-length continuous reads for each sample including some runs with greater than 10,000 near-full-length-genome reads in a three-hour collection time. SMRT Sequencing yields long- read sequencing results from individual DNA molecules with a rapid time-to-result. The single-molecule, full-length nature of the sequencing method allows us to estimate variant subspecies and relative abundances even from samples containing complex mixtures of genomes that differ by single bases. These results open the possibility of cost-effective full-genome sequencing of HIV-1 in mixed populations for applications such as incorporated-HIV-1 screening. In screening, genomes can differ by one to many thousands of bases and the ability to measure them can help scientifically inform treatment strategies.

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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.

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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.

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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.

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June 1, 2021

Making the most of long reads: towards efficient assemblers for reference quality, de novo reconstructions

2015 SMRT Informatics Developers Conference Presentation Slides: Gene Myers, Ph.D., Founding Director, Systems Biology Center, Max Planck Institute delivered the keynote presentation. He talked about building efficient assemblers, the importance of random error distribution in sequencing data, and resolving tricky repeats with very long reads. He also encouraged developers to release assembly modules openly, and noted that data should be straightforward to parse since sharing data interfaces is easier than sharing software interfaces.

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June 1, 2021

Transcriptome analysis using Hybrid-Seq

2015 SMRT Informatics Developers Conference Presentation Slides: Kin Fau Au of the University of Iowa presented on a suite of transcriptome analysis tools for junction detection, error correction, isoform detection and prediction, and gene fusion.

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June 1, 2021

Introduction to SMRT informatics developers conference

2015 SMRT Informatics Developers Conference Presentation Slides: Kevin Corcoran of PacBio provided a brief review of community involvement in the development of analysis tools and showed a preview of upcoming sample preparation, chemistry and informatics improvements.

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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.

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