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July 7, 2019

Improved assembly of noisy long reads by k-mer validation.

Genome assembly depends critically on read length. Two recent technologies, from Pacific Biosciences (PacBio) and Oxford Nanopore, produce read lengths >20 kb, which yield de novo genome assemblies with vastly greater contiguity than those based on Sanger, Illumina, or other technologies. However, the very high error rates of these two new technologies (~15% per base) makes assembly imprecise at repeats longer than the read length and computationally expensive. Here we show that the contiguity and quality of the assembly of these noisy long reads can be significantly improved at a minimal cost, by leveraging on the low error rate and low cost of Illumina short reads. Namely, k-mers from the PacBio raw reads that are not present in Illumina reads (which account for ~95% of the distinct k-mers) are deemed sequencing errors and ignored at the seed alignment step. By focusing on the ~5% of k-mers that are error free, read overlap sensitivity is dramatically increased. Of equal importance, the validation procedure can be extended to exclude repetitive k-mers, which prevents read miscorrection at repeats and further improves the resulting assemblies. We tested the k-mer validation procedure using one long-read technology (PacBio) and one assembler (MHAP/Celera Assembler), but it is very likely to yield analogous improvements with alternative long-read technologies and assemblers, such as Oxford Nanopore and BLASR/DALIGNER/Falcon, respectively.© 2016 Carvalho et al.; Published by Cold Spring Harbor Laboratory Press.

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July 7, 2019

Improve homology search sensitivity of PacBio data by correcting frameshifts.

Single-molecule, real-time sequencing (SMRT) developed by Pacific BioSciences produces longer reads than secondary generation sequencing technologies such as Illumina. The long read length enables PacBio sequencing to close gaps in genome assembly, reveal structural variations, and identify gene isoforms with higher accuracy in transcriptomic sequencing. However, PacBio data has high sequencing error rate and most of the errors are insertion or deletion errors. During alignment-based homology search, insertion or deletion errors in genes will cause frameshifts and may only lead to marginal alignment scores and short alignments. As a result, it is hard to distinguish true alignments from random alignments and the ambiguity will incur errors in structural and functional annotation. Existing frameshift correction tools are designed for data with much lower error rate and are not optimized for PacBio data. As an increasing number of groups are using SMRT, there is an urgent need for dedicated homology search tools for PacBio data.In this work, we introduce Frame-Pro, a profile homology search tool for PacBio reads. Our tool corrects sequencing errors and also outputs the profile alignments of the corrected sequences against characterized protein families. We applied our tool to both simulated and real PacBio data. The results showed that our method enables more sensitive homology search, especially for PacBio data sets of low sequencing coverage. In addition, we can correct more errors when comparing with a popular error correction tool that does not rely on hybrid sequencing.The source code is freely available at https://sourceforge.net/projects/frame-pro/yannisun@msu.edu. © 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

SRinversion: a tool for detecting short inversions by splitting and re-aligning poorly mapped and unmapped sequencing reads.

Rapid development in sequencing technologies has dramatically improved our ability to detect genetic variants in human genome. However, current methods have variable sensitivities in detecting different types of genetic variants. One type of such genetic variants that is especially hard to detect is inversions. Analysis of public databases showed that few short inversions have been reported so far. Unlike reads that contain small insertions or deletions, which will be considered through gap alignment, reads carrying short inversions often have poor mapping quality or are unmapped, thus are often not further considered. As a result, the majority of short inversions might have been overlooked and require special algorithms for their detection.Here, we introduce SRinversion, a framework to analyze poorly mapped or unmapped reads by splitting and re-aligning them for the purpose of inversion detection. SRinversion is very sensitive to small inversions and can detect those less than 10?bp in size. We applied SRinversion to both simulated data and high-coverage sequencing data from the 1000 Genomes Project and compared the results with those from Pindel, BreakDancer, DELLY, Gustaf and MID. A better performance of SRinversion was achieved for both datasets for the detection of small inversions.SRinversion is implemented in Perl and is publicly available at http://paed.hku.hk/genome/software/SRinversion/index.html CONTACT: yangwl@hku.hkSupplementary information: Supplementary 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

CoLoRMap: Correcting Long Reads by Mapping short reads.

Second generation sequencing technologies paved the way to an exceptional increase in the number of sequenced genomes, both prokaryotic and eukaryotic. However, short reads are difficult to assemble and often lead to highly fragmented assemblies. The recent developments in long reads sequencing methods offer a promising way to address this issue. However, so far long reads are characterized by a high error rate, and assembling from long reads require a high depth of coverage. This motivates the development of hybrid approaches that leverage the high quality of short reads to correct errors in long reads.We introduce CoLoRMap, a hybrid method for correcting noisy long reads, such as the ones produced by PacBio sequencing technology, using high-quality Illumina paired-end reads mapped onto the long reads. Our algorithm is based on two novel ideas: using a classical shortest path algorithm to find a sequence of overlapping short reads that minimizes the edit score to a long read and extending corrected regions by local assembly of unmapped mates of mapped short reads. Our results on bacterial, fungal and insect data sets show that CoLoRMap compares well with existing hybrid correction methods.The source code of CoLoRMap is freely available for non-commercial use at https://github.com/sfu-compbio/colormapehaghshe@sfu.ca or cedric.chauve@sfu.caSupplementary 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

Epigenetic mechanisms in microbial members of the human microbiota: current knowledge and perspectives.

The human microbiota and epigenetic processes have both been shown to play a crucial role in health and disease. However, there is extremely scarce information on epigenetic modulation of microbiota members except for a few pathogens. Mainly DNA adenine methylation has been described extensively in modulating the virulence of pathogenic bacteria in particular. It would thus appear likely that such mechanisms are widespread for most bacterial members of the microbiota. This review will present briefly the current knowledge on epigenetic processes in bacteria, give examples of known methylation processes in microbial members of the human microbiota and summarize the knowledge on regulation of host epigenetic processes by the human microbiota.

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July 7, 2019

A comparison of single-molecule emission in aluminum and gold zero-mode waveguides.

The effect of gold and aluminum zero-mode waveguides (ZMWs) on the brightness of immobilized single emitters was characterized by probing fluorophores that absorb in the green and red regions of the visible spectrum. Aluminum ZMWs enhance the emission of Atto565 fluorophores upon green excitation, but they do not enhance the emission of Atto647N fluorophores upon red excitation. Gold ZMWs increase emission of both fluorophores with Atto647N showing enhancement that is threefold higher than that observed for Atto565. This work indicates that 200 nm gold ZMWs are better suited for single-molecule fluorescence studies in the red region of the visible spectrum, while aluminum appears more suited for the green region of the visible spectrum.

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July 7, 2019

svclassify: a method to establish benchmark structural variant calls.

The human genome contains variants ranging in size from small single nucleotide polymorphisms (SNPs) to large structural variants (SVs). High-quality benchmark small variant calls for the pilot National Institute of Standards and Technology (NIST) Reference Material (NA12878) have been developed by the Genome in a Bottle Consortium, but no similar high-quality benchmark SV calls exist for this genome. Since SV callers output highly discordant results, we developed methods to combine multiple forms of evidence from multiple sequencing technologies to classify candidate SVs into likely true or false positives. Our method (svclassify) calculates annotations from one or more aligned bam files from many high-throughput sequencing technologies, and then builds a one-class model using these annotations to classify candidate SVs as likely true or false positives.We first used pedigree analysis to develop a set of high-confidence breakpoint-resolved large deletions. We then used svclassify to cluster and classify these deletions as well as a set of high-confidence deletions from the 1000 Genomes Project and a set of breakpoint-resolved complex insertions from Spiral Genetics. We find that likely SVs cluster separately from likely non-SVs based on our annotations, and that the SVs cluster into different types of deletions. We then developed a supervised one-class classification method that uses a training set of random non-SV regions to determine whether candidate SVs have abnormal annotations different from most of the genome. To test this classification method, we use our pedigree-based breakpoint-resolved SVs, SVs validated by the 1000 Genomes Project, and assembly-based breakpoint-resolved insertions, along with semi-automated visualization using svviz.We find that candidate SVs with high scores from multiple technologies have high concordance with PCR validation and an orthogonal consensus method MetaSV (99.7 % concordant), and candidate SVs with low scores are questionable. We distribute a set of 2676 high-confidence deletions and 68 high-confidence insertions with high svclassify scores from these call sets for benchmarking SV callers. We expect these methods to be particularly useful for establishing high-confidence SV calls for benchmark samples that have been characterized by multiple technologies.

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July 7, 2019

Susan Celniker: Foundational resources to study a dynamic genome.

The Genetics Society of America’s George W. Beadle Award honors individuals who have made outstanding contributions to the community of genetics researchers and who exemplify the qualities of its namesake. The 2016 recipient, Susan E. Celniker, played a key role in the sequencing, annotation, and characterization of the Drosophila genome. She participated in early sequencing efforts at the Lawrence Berkeley National Laboratory and led the modENCODE Fly Transcriptome Consortium. Her efforts were critical to ensuring that the Drosophila genome was well-annotated, making it one of the best curated animal genomes available. As the Principal Investigator for the BDGP, Celniker has enabled the study of proteomes by creating a collection of over 13,000 clones that match annotated genes for protein expression in cells or transgenic flies, and she has established the most comprehensive spatial gene expression atlas in any organism, with in situ imaging of more than 80% of the Drosophila protein-coding transcriptome through embryogenesis. In addition to providing the research community with these invaluable resources and reagents, she continues to develop new tools and datasets for genetics researchers to explore the spatial and temporal control of gene expression.

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July 7, 2019

Exploiting next-generation sequencing to solve the haplotyping puzzle in polyploids: a simulation study.

Haplotypes are the units of inheritance in an organism, and many genetic analyses depend on their precise determination. Methods for haplotyping single individuals use the phasing information available in next-generation sequencing reads, by matching overlapping single-nucleotide polymorphisms while penalizing post hoc nucleotide corrections made. Haplotyping diploids is relatively easy, but the complexity of the problem increases drastically for polyploid genomes, which are found in both model organisms and in economically relevant plant and animal species. Although a number of tools are available for haplotyping polyploids, the effects of the genomic makeup and the sequencing strategy followed on the accuracy of these methods have hitherto not been thoroughly evaluated.We developed the simulation pipeline haplosim to evaluate the performance of three haplotype estimation algorithms for polyploids: HapCompass, HapTree and SDhaP, in settings varying in sequencing approach, ploidy levels and genomic diversity, using tetraploid potato as the model. Our results show that sequencing depth is the major determinant of haplotype estimation quality, that 1?kb PacBio circular consensus sequencing reads and Illumina reads with large insert-sizes are competitive and that all methods fail to produce good haplotypes when ploidy levels increase. Comparing the three methods, HapTree produces the most accurate estimates, but also consumes the most resources. There is clearly room for improvement in polyploid haplotyping algorithms.

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July 7, 2019

ReMILO: reference assisted misassembly detection algorithm using short and long reads.

Contigs assembled from the second generation sequencing short reads may contain misassemblies, and thus complicate downstream analysis or even lead to incorrect analysis results. Fortunately, with more and more sequenced species available, it becomes possible to use the reference genome of a closely related species to detect misassemblies. In addition, long reads of the third generation sequencing technology have been more and more widely used, and can also help detect misassemblies.Here, we introduce ReMILO, a reference assisted misassembly detection algorithm that uses both short reads and PacBio SMRT long reads. ReMILO aligns the initial short reads to both the contigs and reference genome, and then constructs a novel data structure called red-black multipositional de Bruijn graph to detect misassemblies. In addition, ReMILO also aligns the contigs to long reads and find their differences from the long reads to detect more misassemblies. In our performance test on short read assemblies of human chromosome 14 data, ReMILO can detect 41.8-77.9% extensive misassemblies and 33.6-54.5% local misassemblies. On hybrid short and long read assemblies of S.pastorianus data, ReMILO can also detect 60.6-70.9% extensive misassemblies and 28.6-54.0% local misassemblies.The ReMILO software can be downloaded for free under Artistic License 2.0 from this site: https://github.com/songc001/remilo.baoe@bjtu.edu.cn.Supplementary data are available at Bioinformatics online.© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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July 7, 2019

Microbial sequence typing in the genomic era.

Next-generation sequencing (NGS), also known as high-throughput sequencing, is changing the field of microbial genomics research. NGS allows for a more comprehensive analysis of the diversity, structure and composition of microbial genes and genomes compared to the traditional automated Sanger capillary sequencing at a lower cost. NGS strategies have expanded the versatility of standard and widely used typing approaches based on nucleotide variation in several hundred DNA sequences and a few gene fragments (MLST, MLVA, rMLST and cgMLST). NGS can now accommodate variation in thousands or millions of sequences from selected amplicons to full genomes (WGS, NGMLST and HiMLST). To extract signals from high-dimensional NGS data and make valid statistical inferences, novel analytic and statistical techniques are needed. In this review, we describe standard and new approaches for microbial sequence typing at gene and genome levels and guidelines for subsequent analysis, including methods and computational frameworks. We also present several applications of these approaches to some disciplines, namely genotyping, phylogenetics and molecular epidemiology. Copyright © 2017 Elsevier B.V. All rights reserved.

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July 7, 2019

A high throughput screen for active human transposable elements.

Transposable elements (TEs) are mobile genetic sequences that randomly propagate within their host’s genome. This mobility has the potential to affect gene transcription and cause disease. However, TEs are technically challenging to identify, which complicates efforts to assess the impact of TE insertions on disease. Here we present a targeted sequencing protocol and computational pipeline to identify polymorphic and novel TE insertions using next-generation sequencing: TE-NGS. The method simultaneously targets the three subfamilies that are responsible for the majority of recent TE activity (L1HS, AluYa5/8, and AluYb8/9) thereby obviating the need for multiple experiments and reducing the amount of input material required.Here we describe the laboratory protocol and detection algorithm, and a benchmark experiment for the reference genome NA12878. We demonstrate a substantial enrichment for on-target fragments, and high sensitivity and precision to both reference and NA12878-specific insertions. We report 17 previously unreported loci for this individual which are supported by orthogonal long-read evidence, and we identify 1470 polymorphic and novel TEs in 12 additional samples that were previously undocumented in databases of insertion polymorphisms.We anticipate that future applications of TE-NGS alongside exome sequencing of patients with sporadic disease will reduce the number of unresolved cases, and improve estimates of the contribution of TEs to human genetic disease.

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July 7, 2019

Complete genomic and transcriptional landscape analysis using third-generation sequencing: a case study of Saccharomyces cerevisiae CEN.PK113-7D.

Completion of eukaryal genomes can be difficult task with the highly repetitive sequences along the chromosomes and short read lengths of second-generation sequencing. Saccharomyces cerevisiae strain CEN.PK113-7D, widely used as a model organism and a cell factory, was selected for this study to demonstrate the superior capability of very long sequence reads for de novo genome assembly. We generated long reads using two common third-generation sequencing technologies (Oxford Nanopore Technology (ONT) and Pacific Biosciences (PacBio)) and used short reads obtained using Illumina sequencing for error correction. Assembly of the reads derived from all three technologies resulted in complete sequences for all 16 yeast chromosomes, as well as the mitochondrial chromosome, in one step. Further, we identified three types of DNA methylation (5mC, 4mC and 6mA). Comparison between the reference strain S288C and strain CEN.PK113-7D identified chromosomal rearrangements against a background of similar gene content between the two strains. We identified full-length transcripts through ONT direct RNA sequencing technology. This allows for the identification of transcriptional landscapes, including untranslated regions (UTRs) (5′ UTR and 3′ UTR) as well as differential gene expression quantification. About 91% of the predicted transcripts could be consistently detected across biological replicates grown either on glucose or ethanol. Direct RNA sequencing identified many polyadenylated non-coding RNAs, rRNAs, telomere-RNA, long non-coding RNA and antisense RNA. This work demonstrates a strategy to obtain complete genome sequences and transcriptional landscapes that can be applied to other eukaryal organisms.

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July 7, 2019

NanoPack: visualizing and processing long-read sequencing data.

Here we describe NanoPack, a set of tools developed for visualization and processing of long-read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.Supplementary data are available at Bioinformatics online.

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July 7, 2019

RepLong: de novo repeat identification using long read sequencing data.

The identification of repetitive elements is important in genome assembly and phylogenetic analyses. The existing de novo repeat identification methods exploiting the use of short reads are impotent in identifying long repeats. Since long reads are more likely to cover repeat regions completely, using long reads is more favorable for recognizing long repeats.In this study, we propose a novel de novo repeat elements identification method namely RepLong based on PacBio long reads. Given that the reads mapped to the repeat regions are highly overlapped with each other, the identification of repeat elements is equivalent to the discovery of consensus overlaps between reads, which can be further cast into a community detection problem in the network of read overlaps. In RepLong, we first construct a network of read overlaps based on pair-wise alignment of the reads, where each vertex indicates a read and an edge indicates a substantial overlap between the corresponding two reads. Secondly, the communities whose intra connectivity is greater than the inter connectivity are extracted based on network modularity optimization. Finally, representative reads in each community are extracted to form the repeat library. Comparison studies on Drosophila melanogaster and human long read sequencing data with genome-based and short-read-based methods demonstrate the efficiency of RepLong in identifying long repeats. RepLong can handle lower coverage data and serve as a complementary solution to the existing methods to promote the repeat identification performance on long-read sequencing data.The software of RepLong is freely available at https://github.com/ruiguo-bio/replong.ywsun@szu.edu.cn or zhuzx@szu.edu.cn.Supplementary data are available at Bioinformatics online.

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