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Asset Tag: Whole Genome Sequencing,

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.

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June 1, 2021

Highly contiguous de novo human genome assembly and long-range haplotype phasing using SMRT Sequencing

The long reads, random error, and unbiased sampling of SMRT Sequencing enables high quality, de novo assembly of the human genome. PacBio long reads are capable of resolving genomic variations at all size scales, including SNPs, insertions, deletions, inversions, translocations, and repeat expansions, all of which are important in understanding the genetic basis for human disease and difficult to access via other technologies. In demonstration of this, we report a new high-quality, diploid aware de novo assembly of Craig Venter’s well-studied genome.

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June 1, 2021

Metagenomes of native and electrode-enriched microbial communities from the Soudan Iron Mine.

Despite apparent carbon limitation, anoxic deep subsurface brines at the Soudan Underground Iron Mine harbor active microbial communities. To characterize these assemblages, we performed shotgun metagenomics of native and enriched samples. Following enrichment on poised electrodes and long read sequencing, we recovered from the metagenome the closed, circular genome of a novel Desulfuromonas sp. with remarkable genomic features that were not fully resolved by short read assembly alone. This organism was essentially absent in unenriched Soudan communities, indicating that electrodes are highly selective for putative metal reducers. Native community metagenomes suggest that carbon cycling is driven by methyl-C1 metabolism, in particular methylotrophic methanogenesis. Our results highlight the promising potential for long reads in metagenomic surveys of low-diversity environments.

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June 1, 2021

The Wild Vigna

PacBio 2015 User Group Meeting Presentation Slides: Ken Naito of the NIAS Genetic Resource Center presented on whole genome sequencing of the azuki bean (Vigna angularis). Using single molecule real-time (SMRT) sequencing technology, they achieved the best contiguity and coverage among currently assembled legume crops.

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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

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.

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June 1, 2021

Building a platinum human genome assembly from single haplotype human genomes generated from long molecule sequencing

The human reference sequence has provided a foundation for studies of genome structure, human variation, evolutionary biology, and disease. At the time the reference was originally completed there were some loci recalcitrant to closure; however, the degree to which structural variation and diversity affected our ability to produce a representative genome sequence at these loci was still unknown. Many of these regions in the genome are associated with large, repetitive sequences and exhibit complex allelic diversity such producing a single, haploid representation is not possible. To overcome this challenge, we have sequenced DNA from two hydatidiform moles (CHM1 and CHM13), which are essentially haploid. CHM13 was sequenced with the latest PacBio technology (P6-C5) to 52X genome coverage and assembled using Daligner and Falcon v0.2 (GCA_000983455.1, CHM13_1.1). Compared to the first mole (CHM1) PacBio assembly (GCA_001007805.1, 54X) contig N50 of 4.5Mb, the contig N50 of CHM13_1.1 is almost 13Mb, and there is a 13-fold reduction in the number of contigs. This demonstrates the improved contiguity of sequence generated with the new chemistry. We annotated 50,188 RefSeq transcripts of which only 0.63% were split transcripts, and the repetitive and segmental duplication content was within the expected range. These data all indicate an extremely high quality assembly. Additionally, we sequenced CHM13 DNA using Illumina SBS technology to 60X coverage, aligned these reads to the GRCh37, GRCh38, and CHM13_1.1 assemblies and performed variant calling using the SpeedSeq pipeline. The number of single nucleotide variants (SNV) and indels was comparable between GRCh37 and GRCh38. Regions that showed increased SNV density in GRCh38 compared to GRCh37 could be attributed to the addition of centromeric alpha satellite sequence to the reference assembly. Alternatively, regions of decreased SNV density in GRCh38 were concentrated in regions that were improved from BAC based sequencing of CHM1 such as 1p12 and 1q21 containing the SRGAP2 gene family. The alignment of PacBio reads to GRCh37 and GRCh38 assemblies allowed us to resolve complex loci such as the MHC region where the best alignment was to the DBB (A2-B57-DR7) haplotype. Finally, we will discuss how combining the two high quality mole assemblies can be used for benchmarking and novel bioinformatics tool development.

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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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