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July 7, 2019  |  

Rapid and affordable size-selected PacBio single-molecule real-time sequencing template library construction using the bead-beating DNA extraction method

This study demonstrated that bead-beating method facilitates a simple and rapid protocol for genomic DNA isolation for Pacific BioSciences (PacBio) sequencing with library construction of sufficient length. The protocol may also be beneficial for inactivating pathogens by simultaneous and instant DNA fragmentation, with no special equipment required to obtain large DNA fragments. This protocol was comparable in terms of quality to the standard protocol suggested by PacBioand represents an alternative, rapid shortcut for performing accurate PacBio sequencing.

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July 7, 2019  |  

Identification of low allele frequency mosaic mutations in Alzheimer disease

Germline mutations ofAPP,PSEN1, andPSEN2 genes cause autosomal dominant Alzheimer disease (AD). Somatic variants of the same genes may underlie pathogenesis in sporadic AD, which is the most prevalent form of the disease. Importantly, such somatic variants may be present at very low allelic frequency, confined to the brain, and are thus very difficult or impossible to detect in blood-derived DNA. Ever-refined methodologies to identify mutations present in a fraction of the DNA of the original tissue are rapidly transforming our understanding of DNA mutation and their role in complex pathologies such as tumors. These methods stand poised to test to what extend somatic variants may play a role in AD and other neurodegenerative diseases.

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July 7, 2019  |  

GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly.

The identification of genomic rearrangements with high sensitivity and specificity using massively parallel sequencing remains a major challenge, particularly in precision medicine and cancer research. Here, we describe a new method for detecting rearrangements, GRIDSS (Genome Rearrangement IDentification Software Suite). GRIDSS is a multithreaded structural variant (SV) caller that performs efficient genome-wide break-end assembly prior to variant calling using a novel positional de Bruijn graph-based assembler. By combining assembly, split read, and read pair evidence using a probabilistic scoring, GRIDSS achieves high sensitivity and specificity on simulated, cell line, and patient tumor data, recently winning SV subchallenge #5 of the ICGC-TCGA DREAM8.5 Somatic Mutation Calling Challenge. On human cell line data, GRIDSS halves the false discovery rate compared to other recent methods while matching or exceeding their sensitivity. GRIDSS identifies nontemplate sequence insertions, microhomologies, and large imperfect homologies, estimates a quality score for each breakpoint, stratifies calls into high or low confidence, and supports multisample analysis.© 2017 Cameron et al.; Published by Cold Spring Harbor Laboratory Press.

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July 7, 2019  |  

Interrogating the “unsequenceable” genomic trinucleotide repeat disorders by long-read sequencing.

Microsatellite expansion, such as trinucleotide repeat expansion (TRE), is known to cause a number of genetic diseases. Sanger sequencing and next-generation short-read sequencing are unable to interrogate TRE reliably. We developed a novel algorithm called RepeatHMM to estimate repeat counts from long-read sequencing data. Evaluation on simulation data, real amplicon sequencing data on two repeat expansion disorders, and whole-genome sequencing data generated by PacBio and Oxford Nanopore technologies showed superior performance over competing approaches. We concluded that long-read sequencing coupled with RepeatHMM can estimate repeat counts on microsatellites and can interrogate the “unsequenceable” genomic trinucleotide repeat disorders.

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July 7, 2019  |  

Hunting structural variants: Population by population

Until recently, most population-scale genome sequencing studies have focused on identifying single nucleotide variants (SNVs) to explore genetic differences between individuals. Like so many SNV-based genome-wide association studies, however, these efforts have had difficulty identifying causative genetic mechanisms underlying most complex functions. More and more, the genomics community has realised that structural variation is likely responsible for many of the traits and phenotypes that scientists have not been able to attribute to SNVs. This class of variants, defined as genetic differences of 50 bp or larger, accounts for most of the DNA sequence differences between any two people. Structural variants (SVs) are also already known to cause many common and rare diseases including ALS, schizophrenia, leukemia, Carney complex, and Huntington’s disease. Despite the importance of SVs, these larger variants have been understudied and underreported compared to their single-nucleotide counterparts. One reason is that they remain difficult to detect. Their length often means they cannot be fully spanned using short sequencing reads. They also often occur in highly repetitive or GC-rich regions of the genome, making them challenging targets. As such, this class of human genetic variation has remained vastly under-explored in global populations and is now ripe for discovery.

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July 7, 2019  |  

Hybrid de novo genome assembly and centromere characterization of the gray mouse lemur (Microcebus murinus).

The de novo assembly of repeat-rich mammalian genomes using only high-throughput short read sequencing data typically results in highly fragmented genome assemblies that limit downstream applications. Here, we present an iterative approach to hybrid de novo genome assembly that incorporates datasets stemming from multiple genomic technologies and methods. We used this approach to improve the gray mouse lemur (Microcebus murinus) genome from early draft status to a near chromosome-scale assembly.We used a combination of advanced genomic technologies to iteratively resolve conflicts and super-scaffold the M. murinus genome.We improved the M. murinus genome assembly to a scaffold N50 of 93.32 Mb. Whole genome alignments between our primary super-scaffolds and 23 human chromosomes revealed patterns that are congruent with historical comparative cytogenetic data, thus demonstrating the accuracy of our de novo scaffolding approach and allowing assignment of scaffolds to M. murinus chromosomes. Moreover, we utilized our independent datasets to discover and characterize sequences associated with centromeres across the mouse lemur genome. Quality assessment of the final assembly found 96% of mouse lemur canonical transcripts nearly complete, comparable to other published high-quality reference genome assemblies.We describe a new assembly of the gray mouse lemur (Microcebus murinus) genome with chromosome-scale scaffolds produced using a hybrid bioinformatic and sequencing approach. The approach is cost effective and produces superior results based on metrics of contiguity and completeness. Our results show that emerging genomic technologies can be used in combination to characterize centromeres of non-model species and to produce accurate de novo chromosome-scale genome assemblies of complex mammalian genomes.

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July 7, 2019  |  

DNA methylation profiling using long-read Single Molecule Real-Time bisulfite sequencing (SMRT-BS).

For the past two decades, bisulfite sequencing has been a widely used method for quantitative CpG methylation detection of genomic DNA. Coupled with PCR amplicon cloning, bisulfite Sanger sequencing allows for allele-specific CpG methylation assessment; however, its time-consuming protocol and inability to multiplex has recently been overcome by next-generation bisulfite sequencing techniques. Although high-throughput sequencing platforms have enabled greater accuracy in CpG methylation quantitation as a result of increased bisulfite sequencing depth, most common sequencing platforms generate reads that are similar in length to the typical bisulfite PCR size range (~300-500 bp). Using the Pacific Biosciences (PacBio) sequencing platform, we developed single molecule real-time bisulfite sequencing (SMRT-BS), which is an accurate targeted CpG methylation analysis method capable of a high degree of multiplexing and long read lengths. SMRT-BS is reproducible and was found to be concordant with other lower throughput quantitative CpG methylation methods. Moreover, the ability to sequence up to ~1.5-2.0 kb amplicons, when coupled with an optimized bisulfite-conversion protocol, allows for more thorough assessment of CpG islands and increases the capacity for studying the relationship between single nucleotide variants and allele-specific CpG methylation.

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July 7, 2019  |  

Assembly of an early-matured japonica (Geng) rice genome, Suijing18, based on PacBio and Illumina sequencing.

The early-matured japonica (Geng) rice variety, Suijing18 (SJ18), carries multiple elite traits including durable blast resistance, good grain quality, and high yield. Using PacBio SMRT technology, we produced over 25?Gb of long-read sequencing raw data from SJ18 with a coverage of 62×. Using Illumina paired-end whole-genome shotgun sequencing technology, we generated 59?Gb of short-read sequencing data from SJ18 (23.6?Gb from a 200?bp library with a coverage of 59× and 35.4?Gb from an 800?bp library with a coverage of 88×). With these data, we assembled a single SJ18 genome and then generated a set of annotation data. These data sets can be used to test new programs for variation deep mining, and will provide new insights into the genome structure, function, and evolution of SJ18, and will provide essential support for biological research in general.

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July 7, 2019  |  

Complete genome sequences of two plant-associated Pseudomonas putida isolates with increased heavy-metal tolerance.

We report here the complete genome sequences of two Pseudomonas putida isolates recovered from surfac e-sterilized roots of Sida hermaphrodita The two isolates were characterized by an increased tolerance to zinc, cadmium, and lead. Furthermore, the strains showed typical plant growth-promoting properties, such as the production of indole acetic acid, cellulolytic enzymes, and siderophores. Copyright © 2017 Nesme et al.

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July 7, 2019  |  

An update on bioinformatics resources for plant genomics research

Next-generation sequencing and traditional Sanger sequencing methods are of great significance in unraveling the complexity of plant genomes. These are constantly generating heaps of sequence data to be analyzed, annotated and stored. This has created a revolutionary demand for bioinformatics tools and software that can perform these functions. A large number of potentially useful bioinformatics tools and plant genome databases are created that have greatly simplified the analysis and storage of vast amounts of sequence data. The information garnered using the available bioinformatics methods have greatly helped in understanding the plant genome structure. Despite the availability of a good number of such tools, the information pouring from single gene-sequencing, and various whole-genome sequencing projects is overwhelming; thus, further innovations and improved methods are needed to sift through this sequence data, and assemble genomes. The current review focuses on diverse bioinformatics approaches and methods developed to systematically analyze and store plant sequence data. Finally, it outlines the bottlenecks in plant genome analysis, and some possible solutions that could be utilized to overcome the problems associated with plant genome analysis.

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July 7, 2019  |  

Third-generation sequencing and the future of genomics

Third-generation long-range DNA sequencing and mapping technologies are creating a renaissance in high-quality genome sequencing. Unlike second-generation sequencing, which produces short reads a few hundred base-pairs long, third-generation single-molecule technologies generate over 10,000 bp reads or map over 100,000 bp molecules. We analyze how increased read lengths can be used to address long-standing problems in de novo genome assembly, structural variation analysis and haplotype phasing.

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July 7, 2019  |  

The challenges of implementing next generation sequencing across a large healthcare system, and the molecular epidemiology and antibiotic susceptibilities of carbapenemase-producing bacteria in the healthcare system of the U.S. Department of Defense.

We sought to: 1) provide an overview of the genomic epidemiology of an extensive collection of carbapenemase-producing bacteria (CPB) collected in the U.S. Department of Defense health system; 2) increase awareness of the public availability of the sequences, isolates, and customized antimicrobial resistance database of that system; and 3) illustrate challenges and offer mitigations for implementing next generation sequencing (NGS) across large health systems.Prospective surveillance and system-wide implementation of NGS.288-hospital healthcare network.All phenotypically carbapenem resistant bacteria underwent CarbaNP® testing and PCR, followed by NGS. Commercial (Newbler and Geneious), on-line (ResFinder), and open-source software (Btrim, FLASh, Bowtie2, an Samtools) were used for assembly, SNP detection and clustering. Laboratory capacity, throughput, and response time were assessed. From 2009 through 2015, 27,000 multidrug-resistant Gram-negative isolates were submitted. 225 contained carbapenemase-encoding genes (most commonly blaKPC, blaNDM, and blaOXA23). These were found in 15 species from 146 inpatients in 19 facilities. Genetically related CPB were found in more than one hospital. Other clusters or outbreaks were not clonal and involved genetically related plasmids, while some involved several unrelated plasmids. Relatedness depended on the clustering algorithm used. Transmission patterns of plasmids and other mobile genetic elements could not be determined without ultra-long read, single-molecule real-time sequencing. 80% of carbapenem-resistant phenotypes retained susceptibility to aminoglycosides, and 70% retained susceptibility to fluoroquinolones. However, among the CPB-confirmed genotypes, fewer than 25% retained susceptibility to aminoglycosides or fluoroquinolones.Although NGS is increasingly acclaimed to revolutionize clinical practice, resource-constrained environments, large or geographically dispersed healthcare networks, and military or government-funded public health laboratories are likely to encounter constraints and challenges as they implement NGS across their health systems. These include lack of standardized definitions and quality control metrics, limitations of short-read sequencing, insufficient bandwidth, and the current limited availability of very expensive and scarcely available sequencing platforms. Possible solutions and mitigations are also proposed.

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July 7, 2019  |  

Assembly of long error-prone reads using de Bruijn graphs.

The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the OLC approaches and results in accurate genome reconstructions.

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July 7, 2019  |  

Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences.

Single Molecule Real-Time (SMRT) sequencing technology and Oxford Nanopore technologies (ONT) produce reads over 10?kb in length, which have enabled high-quality genome assembly at an affordable cost. However, at present, long reads have an error rate as high as 10-15%. Complex and computationally intensive pipelines are required to assemble such reads.We present a new mapper, minimap and a de novo assembler, miniasm, for efficiently mapping and assembling SMRT and ONT reads without an error correction stage. They can often assemble a sequencing run of bacterial data into a single contig in a few minutes, and assemble 45-fold Caenorhabditis elegans data in 9?min, orders of magnitude faster than the existing pipelines, though the consensus sequence error rate is as high as raw reads. We also introduce a pairwise read mapping format and a graphical fragment assembly format, and demonstrate the interoperability between ours and current tools.https://github.com/lh3/minimap and https://github.com/lh3/miniasmhengli@broadinstitute.orgSupplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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July 7, 2019  |  

Sparc: a sparsity-based consensus algorithm for long erroneous sequencing reads.

Motivation. The third generation sequencing (3GS) technology generates long sequences of thousands of bases. However, its current error rates are estimated in the range of 15-40%, significantly higher than those of the prevalent next generation sequencing (NGS) technologies (less than 1%). Fundamental bioinformatics tasks such as de novo genome assembly and variant calling require high-quality sequences that need to be extracted from these long but erroneous 3GS sequences. Results. We describe a versatile and efficient linear complexity consensus algorithm Sparc to facilitate de novo genome assembly. Sparc builds a sparse k-mer graph using a collection of sequences from a targeted genomic region. The heaviest path which approximates the most likely genome sequence is searched through a sparsity-induced reweighted graph as the consensus sequence. Sparc supports using NGS and 3GS data together, which leads to significant improvements in both cost efficiency and computational efficiency. Experiments with Sparc show that our algorithm can efficiently provide high-quality consensus sequences using both PacBio and Oxford Nanopore sequencing technologies. With only 30× PacBio data, Sparc can reach a consensus with error rate <0.5%. With the more challenging Oxford Nanopore data, Sparc can also achieve similar error rate when combined with NGS data. Compared with the existing approaches, Sparc calculates the consensus with higher accuracy, and uses approximately 80% less memory and time. Availability. The source code is available for download at https://github.com/yechengxi/Sparc.

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