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July 7, 2019  |  

Information-optimal genome assembly via sparse read-overlap graphs.

In the context of third-generation long-read sequencing technologies, read-overlap-based approaches are expected to play a central role in the assembly step. A fundamental challenge in assembling from a read-overlap graph is that the true sequence corresponds to a Hamiltonian path on the graph, and, under most formulations, the assembly problem becomes NP-hard, restricting practical approaches to heuristics. In this work, we avoid this seemingly fundamental barrier by first setting the computational complexity issue aside, and seeking an algorithm that targets information limits In particular, we consider a basic feasibility question: when does the set of reads contain enough information to allow unambiguous reconstruction of the true sequence?Based on insights from this information feasibility question, we present an algorithm-the Not-So-Greedy algorithm-to construct a sparse read-overlap graph. Unlike most other assembly algorithms, Not-So-Greedy comes with a performance guarantee: whenever information feasibility conditions are satisfied, the algorithm reduces the assembly problem to an Eulerian path problem on the resulting graph, and can thus be solved in linear time. In practice, this theoretical guarantee translates into assemblies of higher quality. Evaluations on both simulated reads from real genomes and a PacBio Escherichia coli K12 dataset demonstrate that Not-So-Greedy compares favorably with standard string graph approaches in terms of accuracy of the resulting read-overlap graph and contig N50.Available at github.com/samhykim/nsgcourtade@eecs.berkeley.edu or dntse@stanford.eduSupplementary 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  |  

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  |  

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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July 7, 2019  |  

Complete genome sequence of Escherichia coli 81009, a representative of the sequence type 131 C1-M27 clade with a multidrug-resistant phenotype.

The sequence type 131 (ST131)-H30 clone is responsible for a significant proportion of multidrug-resistant extraintestinal Escherichia coli infections. Recently, the C1-M27 clade of ST131-H30, associated with blaCTX-M-27, has emerged. The complete genome sequence of E. coli isolate 81009 belonging to this clone, previously used during the development of ST131-specific monoclonal antibodies, is reported here. Copyright © 2018 Mutti et al.

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July 7, 2019  |  

Complete genome sequence of uropathogenic Escherichia coli isolate UPEC 26-1.

Urinary tract infections (UTIs) are among the most common infections in humans, predominantly caused by uropathogenic Escherichia coli (UPEC). The diverse genomes of UPEC strains mostly impede disease prevention and control measures. In this study, we comparatively analyzed the whole genome sequence of a highly virulent UPEC strain, namely UPEC 26-1, which was isolated from urine sample of a patient suffering from UTI in Korea. Whole genome analysis showed that the genome consists of one circular chromosome of 5,329,753 bp, comprising 5064 protein-coding genes, 122 RNA genes (94 tRNA, 22 rRNA and 6 ncRNA genes), and 100 pseudogenes, with an average G+C content of 50.56%. In addition, we identified 8 prophage regions comprising 5 intact, 2 incomplete and 1 questionable ones and 63 genomic islands, suggesting the possibility of horizontal gene transfer in this strain. Comparative genome analysis of UPEC 26-1 with the UPEC strain CFT073 revealed an average nucleotide identity of 99.7%. The genome comparison with CFT073 provides major differences in the genome of UPEC 26-1 that would explain its increased virulence and biofilm formation. Nineteen of the total GIs were unique to UPEC 26-1 compared to CFT073 and nine of them harbored unique genes that are involved in virulence, multidrug resistance, biofilm formation and bacterial pathogenesis. The data from this study will assist in future studies of UPEC strains to develop effective control measures.

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July 7, 2019  |  

Draft genome assembly of the sheep scab mite, Psoroptes ovis.

Sheep scab, caused by infestation with Psoroptes ovis, is highly contagious, results in intense pruritus, and represents a major welfare and economic concern. Here, we report the first draft genome assembly and gene prediction of P. ovis based on PacBio de novo sequencing. The ~63.2-Mb genome encodes 12,041 protein-coding genes. Copyright © 2018 Burgess et al.

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July 7, 2019  |  

RIFRAF: a frame-resolving consensus algorithm.

Protein coding genes can be studied using long-read next generation sequencing. However, high rates of indel sequencing errors are problematic, corrupting the reading frame. Even the consensus of multiple independent sequence reads retains indel errors. To solve this problem, we introduce Reference-Informed Frame-Resolving multiple-Alignment Free template inference algorithm (RIFRAF), a sequence consensus algorithm that takes a set of error-prone reads and a reference sequence and infers an accurate in-frame consensus. RIFRAF uses a novel structure, analogous to a two-layer hidden Markov model: the consensus is optimized to maximize alignment scores with both the set of noisy reads and with a reference. The template-to-reads component of the model encodes the preponderance of indels, and is sensitive to the per-base quality scores, giving greater weight to more accurate bases. The reference-to-template component of the model penalizes frame-destroying indels. A local search algorithm proceeds in stages to find the best consensus sequence for both objectives.Using Pacific Biosciences SMRT sequences from an HIV-1 env clone, NL4-3, we compare our approach to other consensus and frame correction methods. RIFRAF consistently finds a consensus sequence that is more accurate and in-frame, especially with small numbers of reads. It was able to perfectly reconstruct over 80% of consensus sequences from as few as three reads, whereas the best alternative required twice as many. RIFRAF is able to achieve these results and keep the consensus in-frame even with a distantly related reference sequence. Moreover, unlike other frame correction methods, RIFRAF can detect and keep true indels while removing erroneous ones.RIFRAF is implemented in Julia, and source code is publicly available at https://github.com/MurrellGroup/Rifraf.jl.Supplementary data are available at Bioinformatics online.

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July 7, 2019  |  

Assembly of a complete genome sequence for Gemmata obscuriglobus reveals a novel prokaryotic rRNA operon gene architecture.

Gemmata obscuriglobus is a Gram-negative bacterium with several intriguing biological features. Here, we present a complete, de novo whole genome assembly for G. obscuriglobus which consists of a single, circular 9 Mb chromosome, with no plasmids detected. The genome was annotated using the NCBI Prokaryotic Genome Annotation pipeline to generate common gene annotations. Analysis of the rRNA genes revealed three interesting features for a bacterium. First, linked G. obscuriglobus rrn operons have a unique gene order, 23S-5S-16S, compared to typical prokaryotic rrn operons (16S-23S-5S). Second, G. obscuriglobus rrn operons can either be linked or unlinked (a 16S gene is in a separate genomic location from a 23S and 5S gene pair). Third, all of the 23S genes (5 in total) have unique polymorphisms. Genome analysis of a different Gemmata species (SH-PL17), revealed a similar 23S-5S-16S gene order in all of its linked rrn operons and the presence of an unlinked operon. Together, our findings show that unique and rare features in Gemmata rrn operons among prokaryotes provide a means to better define the evolutionary relatedness of Gemmata species and the divergence time for different Gemmata species. Additionally, these rrn operon differences provide important insights into the rrn operon architecture of common ancestors of the planctomycetes.

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July 7, 2019  |  

GtTR: Bayesian estimation of absolute tandem repeat copy number using sequence capture and high throughput sequencing.

Tandem repeats comprise significant proportion of the human genome including coding and regulatory regions. They are highly prone to repeat number variation and nucleotide mutation due to their repetitive and unstable nature, making them a major source of genomic variation between individuals. Despite recent advances in high throughput sequencing, analysis of tandem repeats in the context of complex diseases is still hindered by technical limitations. We report a novel targeted sequencing approach, which allows simultaneous analysis of hundreds of repeats. We developed a Bayesian algorithm, namely – GtTR – which combines information from a reference long-read dataset with a short read counting approach to genotype tandem repeats at population scale. PCR sizing analysis was used for validation.We used a PacBio long-read sequenced sample to generate a reference tandem repeat genotype dataset with on average 13% absolute deviation from PCR sizing results. Using this reference dataset GtTR generated estimates of VNTR copy number with accuracy within 95% high posterior density (HPD) intervals of 68 and 83% for capture sequence data and 200X WGS data respectively, improving to 87 and 94% with use of a PCR reference. We show that the genotype resolution increases as a function of depth, such that the median 95% HPD interval lies within 25, 14, 12 and 8% of the its midpoint copy number value for 30X, 200X WGS, 395X and 800X capture sequence data respectively. We validated nine targets by PCR sizing analysis and genotype estimates from sequencing results correlated well with PCR results.The novel genotyping approach described here presents a new cost-effective method to explore previously unrecognized class of repeat variation in GWAS studies of complex diseases at the population level. Further improvements in accuracy can be obtained by improving accuracy of the reference dataset.

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July 7, 2019  |  

HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning.

Second-generation DNA sequencing techniques generate short reads that can result in fragmented genome assemblies. Third-generation sequencing platforms mitigate this limitation by producing longer reads that span across complex and repetitive regions. However, the usefulness of such long reads is limited because of high sequencing error rates. To exploit the full potential of these longer reads, it is imperative to correct the underlying errors. We propose HECIL-Hybrid Error Correction with Iterative Learning-a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments. We demonstrate that HECIL outperforms state-of-the-art error correction algorithms for an overwhelming majority of evaluation metrics on diverse, real-world data sets including E. coli, S. cerevisiae, and the malaria vector mosquito A. funestus. Additionally, we provide an optional avenue of improving the performance of HECIL’s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.

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July 7, 2019  |  

Clustering of circular consensus sequences: accurate error correction and assembly of single molecule real-time reads from multiplexed amplicon libraries.

Targeted resequencing with high-throughput sequencing (HTS) platforms can be used to efficiently interrogate the genomes of large numbers of individuals. A critical issue for research and applications using HTS data, especially from long-read platforms, is error in base calling arising from technological limits and bioinformatic algorithms. We found that the community standard long amplicon analysis (LAA) module from Pacific Biosciences is prone to substantial bioinformatic errors that raise concerns about findings based on this pipeline, prompting the need for a new method.A single molecule real-time (SMRT) sequencing-error correction and assembly pipeline, C3S-LAA, was developed for libraries of pooled amplicons. By uniquely leveraging the structure of SMRT sequence data (comprised of multiple low quality subreads from which higher quality circular consensus sequences are formed) to cluster raw reads, C3S-LAA produced accurate consensus sequences and assemblies of overlapping amplicons from single sample and multiplexed libraries. In contrast, despite read depths in excess of 100X per amplicon, the standard long amplicon analysis module from Pacific Biosciences generated unexpected numbers of amplicon sequences with substantial inaccuracies in the consensus sequences. A bootstrap analysis showed that the C3S-LAA pipeline per se was effective at removing bioinformatic sources of error, but in rare cases a read depth of nearly 400X was not sufficient to overcome minor but systematic errors inherent to amplification or sequencing.C3S-LAA uses a divide and conquer processing algorithm for SMRT amplicon-sequence data that generates accurate consensus sequences and local sequence assemblies. Solving the confounding bioinformatic source of error in LAA allowed for the identification of limited instances of errors due to DNA amplification or sequencing of homopolymeric nucleotide tracts. For research and development in genomics, C3S-LAA allows meaningful conclusions and biological inferences to be made from accurately polished sequence output.

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July 7, 2019  |  

Complete genome sequence of Clostridium kluyveri JZZ applied in Chinese strong-flavor liquor production.

Chinese strong-flavor liquor (CSFL), accounting for more than 70% of both Chinese liquor production and sales, was produced by complex fermentation with pit mud. Clostridium kluyveri, an important species coexisted with other microorganisms in fermentation pit mud (FPM), could produce caproic acid, which was subsequently converted to the key CSFL flavor substance ethyl caproate. In this study, we present the first complete genome sequence of C. kluyveri isolated from FPM. Clostridium kluyveri JZZ contains one circular chromosome and one circular plasmid with length of 4,454,353 and 58,581 bp, respectively. 4158 protein-coding genes were predicted and 2792 genes could be assigned with COG categories. It possesses the pathway predicted for biosynthesis of caproic acid with ethanol. Compared to other two C. kluyveri genomes, JZZ consists of longer chromosome with multiple gene rearrangements, and contains more genes involved in defense mechanisms, as well as DNA replication, recombination, and repair. Meanwhile, JZZ contains fewer genes involved in secondary metabolites biosynthesis, transport, and catabolism, including genes encoding Polyketide Synthases/Non-ribosomal Peptide Synthetases. Additionally, JZZ possesses 960 unique genes with relatively aggregating in defense mechanisms and transcription. Our study will be available for further research about C. kluyveri isolated from FPM, and will also facilitate the genetic engineering to increase biofuel production and improve fragrance flavor of CSFL.

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July 7, 2019  |  

STRetch: detecting and discovering pathogenic short tandem repeat expansions.

Short tandem repeat (STR) expansions have been identified as the causal DNA mutation in dozens of Mendelian diseases. Most existing tools for detecting STR variation with short reads do so within the read length and so are unable to detect the majority of pathogenic expansions. Here we present STRetch, a new genome-wide method to scan for STR expansions at all loci across the human genome. We demonstrate the use of STRetch for detecting STR expansions using short-read whole-genome sequencing data at known pathogenic loci as well as novel STR loci. STRetch is open source software, available from github.com/Oshlack/STRetch .

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