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July 7, 2019

Chromosome assembly of large and complex genomes using multiple references

Despite the rapid development of sequencing technologies, assembly of mammalian-scale genomes into complete chromosomes remains one of the most challenging problems in bioinformatics. To help address this difficulty, we developed Ragout, a reference-assisted assembly tool that now works for large and complex genomes. Taking one or more target assemblies (generated from an NGS assembler) and one or multiple related reference genomes, Ragout infers the evolutionary relationships between the genomes and builds the final assemblies using a genome rearrangement approach. Using Ragout, we transformed NGS assemblies of 15 different Mus musculus and one Mus spretus genomes into sets of complete chromosomes, leaving less than 5% of sequence unlocalized per set. Various benchmarks, including PCR testing and realigning of long PacBio reads, suggest only a small number of structural errors in the final assemblies, comparable with direct assembly approaches. Additionally, we applied Ragout to Mus caroli and Mus pahari genomes, which exhibit karyotype-scale variations compared to other genomes from the Muridae family. Chromosome color maps confirmed most large-scale rearrangements that Ragout detected.

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July 7, 2019

WhatsHap: fast and accurate read-based phasing

Read-based phasing allows to reconstruct the haplotype structure of a sample purely from sequencing reads. While phasing is a required step for answering questions about population genetics, compound heterozygosity, and to aid in clinical decision making, there has been a lack of an accurate, usable and standards-based software. WhatsHap is a production-ready tool for highly accurate read-based phasing. It was designed from the beginning to leverage third-generation sequencing technologies, whose long reads can span many variants and are therefore ideal for phasing. WhatsHap works also well with second-generation data, is easy to use and will phase not only SNVs, but also indels and other variants. It is unique in its ability to combine read-based with genetic phasing, allowing to further improve accuracy if multiple related samples are provided.

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July 7, 2019

MICADo – Looking for mutations in targeted PacBio cancer data: an alignment-free method.

Targeted sequencing is commonly used in clinical application of NGS technology since it enables generation of sufficient sequencing depth in the targeted genes of interest and thus ensures the best possible downstream analysis. This notwithstanding, the accurate discovery and annotation of disease causing mutations remains a challenging problem even in such favorable context. The difficulty is particularly salient in the case of third generation sequencing technology, such as PacBio. We present MICADo, a de Bruijn graph based method, implemented in python, that makes possible to distinguish between patient specific mutations and other alterations for targeted sequencing of a cohort of patients. MICADo analyses NGS reads for each sample within the context of the data of the whole cohort in order to capture the differences between specificities of the sample with respect to the cohort. MICADo is particularly suitable for sequencing data from highly heterogeneous samples, especially when it involves high rates of non-uniform sequencing errors. It was validated on PacBio sequencing datasets from several cohorts of patients. The comparison with two widely used available tools, namely VarScan and GATK, shows that MICADo is more accurate, especially when true mutations have frequencies close to backgound noise. The source code is available at http://github.com/cbib/MICADo.

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July 7, 2019

The draft genome of whitefly Bemisia tabaci MEAM1, a global crop pest, provides novel insights into virus transmission, host adaptation, and insecticide resistance.

The whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) is among the 100 worst invasive species in the world. As one of the most important crop pests and virus vectors, B. tabaci causes substantial crop losses and poses a serious threat to global food security. We report the 615-Mb high-quality genome sequence of B. tabaci Middle East-Asia Minor 1 (MEAM1), the first genome sequence in the Aleyrodidae family, which contains 15,664 protein-coding genes. The B. tabaci genome is highly divergent from other sequenced hemipteran genomes, sharing no detectable synteny. A number of known detoxification gene families, including cytochrome P450s and UDP-glucuronosyltransferases, are significantly expanded in B. tabaci. Other expanded gene families, including cathepsins, large clusters of tandemly duplicated B. tabaci-specific genes, and phosphatidylethanolamine-binding proteins (PEBPs), were found to be associated with virus acquisition and transmission and/or insecticide resistance, likely contributing to the global invasiveness and efficient virus transmission capacity of B. tabaci. The presence of 142 horizontally transferred genes from bacteria or fungi in the B. tabaci genome, including genes encoding hopanoid/sterol synthesis and xenobiotic detoxification enzymes that are not present in other insects, offers novel insights into the unique biological adaptations of this insect such as polyphagy and insecticide resistance. Interestingly, two adjacent bacterial pantothenate biosynthesis genes, panB and panC, have been co-transferred into B. tabaci and fused into a single gene that has acquired introns during its evolution.The B. tabaci genome contains numerous genetic novelties, including expansions in gene families associated with insecticide resistance, detoxification and virus transmission, as well as numerous horizontally transferred genes from bacteria and fungi. We believe these novelties likely have shaped B. tabaci as a highly invasive polyphagous crop pest and efficient vector of plant viruses. The genome serves as a reference for resolving the B. tabaci cryptic species complex, understanding fundamental biological novelties, and providing valuable genetic information to assist the development of novel strategies for controlling whiteflies and the viruses they transmit.

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July 7, 2019

Whole genome sequence and comparative genomics of the novel Lyme borreliosis causing pathogen, Borrelia mayonii.

Borrelia mayonii, a Borrelia burgdorferi sensu lato (Bbsl) genospecies, was recently identified as a cause of Lyme borreliosis (LB) among patients from the upper midwestern United States. By microscopy and PCR, spirochete/genome loads in infected patients were estimated at 105 to 106 per milliliter of blood. Here, we present the full chromosome and plasmid sequences of two B. mayonii isolates, MN14-1420 and MN14-1539, cultured from blood of two of these patients. Whole genome sequencing and assembly was conducted using PacBio long read sequencing (Pacific Biosciences RSII instrument) followed by hierarchical genome-assembly process (HGAP). The B. mayonii genome is ~1.31 Mbp in size (26.9% average GC content) and is comprised of a linear chromosome, 8 linear and 7 circular plasmids. Consistent with its taxonomic designation as a new Bbsl genospecies, the B. mayonii linear chromosome shares only 93.83% average nucleotide identity with other genospecies. Both B. mayonii genomes contain plasmids similar to B. burgdorferi sensu stricto lp54, lp36, lp28-3, lp28-4, lp25, lp17, lp5, 5 cp32s, cp26, and cp9. The vls locus present on lp28-10 of B. mayonii MN14-1420 is remarkably long, being comprised of 24 silent vls cassettes. Genetic differences between the two B. mayonii genomes are limited and include 15 single nucleotide variations as well as 7 fewer silent vls cassettes and a lack of the lp5 plasmid in MN14-1539. Notably, 68 homologs to proteins present in B. burgdorferi sensu stricto appear to be lacking from the B. mayonii genomes. These include the complement inhibitor, CspZ (BB_H06), the fibronectin binding protein, BB_K32, as well as multiple lipoproteins and proteins of unknown function. This study shows the utility of long read sequencing for full genome assembly of Bbsl genomes, identifies putative genome regions of B. mayonii that may be linked to clinical manifestation or tissue tropism, and provides a valuable resource for pathogenicity, diagnostic and vaccine studies.

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July 7, 2019

Colib’read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads

With next-generation sequencing (NGS) technologies, the life sciences face a deluge of raw data. Classical analysis processes for such data often begin with an assembly step, needing large amounts of computing resources, and potentially removing or modifying parts of the biological information contained in the data. Our approach proposes to focus directly on biological questions, by considering raw unassembled NGS data, through a suite of six command-line tools.

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July 7, 2019

STR-realigner: a realignment method for short tandem repeat regions.

In the estimation of repeat numbers in a short tandem repeat (STR) region from high-throughput sequencing data, two types of strategies are mainly taken: a strategy based on counting repeat patterns included in sequence reads spanning the region and a strategy based on estimating the difference between the actual insert size and the insert size inferred from paired-end reads. The quality of sequence alignment is crucial, especially in the former approaches although usual alignment methods have difficulty in STR regions due to insertions and deletions caused by the variations of repeat numbers.We proposed a new dynamic programming based realignment method named STR-realigner that considers repeat patterns in STR regions as prior knowledge. By allowing the size change of repeat patterns with low penalty in STR regions, accurate realignment is expected. For the performance evaluation, publicly available STR variant calling tools were applied to three types of aligned reads: synthetically generated sequencing reads aligned with BWA-MEM, those realigned with STR-realigner, those realigned with ReviSTER, and those realigned with GATK IndelRealigner. From the comparison of root mean squared errors between estimated and true STR region size, the results for the dataset realigned with STR-realigner are better than those for other cases. For real data analysis, we used a real sequencing dataset from Illumina HiSeq 2000 for a parent-offspring trio. RepeatSeq and lobSTR were applied to the sequence reads for these individuals aligned with BWA-MEM, those realigned with STR-realigner, ReviSTER, and GATK IndelRealigner. STR-realigner shows the best performance in terms of consistency of the size of estimated STR regions in Mendelian inheritance. Root mean squared error values were also calculated from the comparison of these estimated results with STR region sizes obtained from high coverage PacBio sequencing data, and the results from the realigned sequencing data with STR-realigner showed the least (the best) root mean squared error value.The effectiveness of the proposed realignment method for STR regions was verified from the comparison with an existing method on both simulation datasets and real whole genome sequencing dataset.

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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

Jabba: hybrid error correction for long sequencing reads.

Third generation sequencing platforms produce longer reads with higher error rates than second generation technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes. Recently, a new hybrid error correcting method has been proposed, where the second generation data is first assembled into a de Bruijn graph, on which the long reads are then aligned.In this context we present Jabba, a hybrid method to correct long third generation reads by mapping them on a corrected de Bruijn graph that was constructed from second generation data. Unique to our method is the use of a pseudo alignment approach with a seed-and-extend methodology, using maximal exact matches (MEMs) as seeds. In addition to benchmark results, certain theoretical results concerning the possibilities and limitations of the use of MEMs in the context of third generation reads are presented.Jabba produces highly reliable corrected reads: almost all corrected reads align to the reference, and these alignments have a very high identity. Many of the aligned reads are error-free. Additionally, Jabba corrects reads using a very low amount of CPU time. From this we conclude that pseudo alignment with MEMs is a fast and reliable method to map long highly erroneous sequences on a de Bruijn graph.

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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

Genomic sequencing-based mutational enrichment analysis identifies motility genes in a genetically intractable gut microbe.

A major roadblock to understanding how microbes in the gastrointestinal tract colonize and influence the physiology of their hosts is our inability to genetically manipulate new bacterial species and experimentally assess the function of their genes. We describe the application of population-based genomic sequencing after chemical mutagenesis to map bacterial genes responsible for motility in Exiguobacterium acetylicum, a representative intestinal Firmicutes bacterium that is intractable to molecular genetic manipulation. We derived strong associations between mutations in 57 E. acetylicum genes and impaired motility. Surprisingly, less than half of these genes were annotated as motility-related based on sequence homologies. We confirmed the genetic link between individual mutations and loss of motility for several of these genes by performing a large-scale analysis of spontaneous suppressor mutations. In the process, we reannotated genes belonging to a broad family of diguanylate cyclases and phosphodiesterases to highlight their specific role in motility and assigned functions to uncharacterized genes. Furthermore, we generated isogenic strains that allowed us to establish that Exiguobacterium motility is important for the colonization of its vertebrate host. These results indicate that genetic dissection of a complex trait, functional annotation of new genes, and the generation of mutant strains to define the role of genes in complex environments can be accomplished in bacteria without the development of species-specific molecular genetic tools.

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July 7, 2019

Spontaneous chloroplast mutants mostly occur by replication slippage and show a biased pattern in the plastome of Oenothera.

Spontaneous plastome mutants have been used as a research tool since the beginning of genetics. However, technical restrictions have severely limited their contributions to research in physiology and molecular biology. Here, we used full plastome sequencing to systematically characterize a collection of 51 spontaneous chloroplast mutants in Oenothera (evening primrose). Most mutants carry only a single mutation. Unexpectedly, the vast majority of mutations do not represent single nucleotide polymorphisms but are insertions/deletions originating from DNA replication slippage events. Only very few mutations appear to be caused by imprecise double-strand break repair, nucleotide misincorporation during replication, or incorrect nucleotide excision repair following oxidative damage. U-turn inversions were not detected. Replication slippage is induced at repetitive sequences that can be very small and tend to have high A/T content. Interestingly, the mutations are not distributed randomly in the genome. The underrepresentation of mutations caused by faulty double-strand break repair might explain the high structural conservation of seed plant plastomes throughout evolution. In addition to providing a fully characterized mutant collection for future research on plastid genetics, gene expression, and photosynthesis, our work identified the spectrum of spontaneous mutations in plastids and reveals that this spectrum is very different from that in the nucleus.© 2016 American Society of Plant Biologists. All rights reserved.

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July 7, 2019

Characterization of tet(Y)-carrying LowGC plasmids exogenously captured from cow manure at a conventional dairy farm.

Manure from dairy farms has been shown to contain diverse tetracycline resistance genes that are transferable to soil. Here, we focus on conjugative plasmids that may spread tetracycline resistance at a conventional dairy farm. We performed exogenous plasmid isolation from cattle feces using chlortetracycline for transconjugant selection. The transconjugants obtained harbored LowGC-type plasmids and tet(Y). A representative plasmid (pFK2-7) was fully sequenced and this was compared with previously described LowGC plasmids from piggery manure-treated soil and a GenBank record from Acinetobacter nosocomialis that we also identified as a LowGC plasmid. The pFK2-7 plasmid had the conservative backbone typical of LowGC plasmids, though this region was interrupted with an insert containing the tet(Y)-tet(R) tetracycline resistance genes and the strA-strB streptomycin resistance genes. Despite Acinetobacter populations being considered natural hosts of LowGC plasmids, these plasmids were not found in three Acinetobacter isolates from the study farm. The isolates harbored tet(Y)-tet(R) genes in identical genetic surroundings as pFK2-7, however, suggesting genetic exchange between Acinetobacter and LowGC plasmids. Abundance of LowGC plasmids and tet(Y) was correlated in manure and soil samples from the farm, indicating that LowGC plasmids may be involved in the spread of tet(Y) in the environment.© FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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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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