Menu

Auto Tag: Variant detection

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.

Read more
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.

Read more
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.

Read more
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.

Read more
July 7, 2019

Collection and storage of HLA NGS genotyping data for the 17th International HLA and Immunogenetics Workshop.

For over 50?years, the International HLA and Immunogenetics Workshops (IHIW) have advanced the fields of histocompatibility and immunogenetics (H&I) via community sharing of technology, experience and reagents, and the establishment of ongoing collaborative projects. Held in the fall of 2017, the 17th IHIW focused on the application of next generation sequencing (NGS) technologies for clinical and research goals in the H&I fields. NGS technologies have the potential to allow dramatic insights and advances in these fields, but the scope and sheer quantity of data associated with NGS raise challenges for their analysis, collection, exchange and storage. The 17th IHIW adopted a centralized approach to these issues, and we developed the tools, services and systems to create an effective system for capturing and managing these NGS data. We worked with NGS platform and software developers to define a set of distinct but equivalent NGS typing reports that record NGS data in a uniform fashion. The 17th IHIW database applied our standards, tools and services to collect, validate and store those structured, multi-platform data in an automated fashion. We have created community resources to enable exploration of the vast store of curated sequence and allele-name data in the IPD-IMGT/HLA Database, with the goal of creating a long-term community resource that integrates these curated data with new NGS sequence and polymorphism data, for advanced analyses and applications. Copyright © 2017 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Read more
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

Read more
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.

Read more
July 7, 2019

Enhancing the accuracy of next-generation sequencing for detecting rare and subclonal mutations.

Mutations, the fuel of evolution, are first manifested as rare DNA changes within a population of cells. Although next-generation sequencing (NGS) technologies have revolutionized the study of genomic variation between species and individual organisms, most have limited ability to accurately detect and quantify rare variants among the different genome copies in heterogeneous mixtures of cells or molecules. We describe the technical challenges in characterizing subclonal variants using conventional NGS protocols and the recent development of error correction strategies, both computational and experimental, including consensus sequencing of single DNA molecules. We also highlight major applications for low-frequency mutation detection in science and medicine, describe emerging methodologies and provide our vision for the future of DNA sequencing.

Read more
July 7, 2019

High-quality complete and draft genome sequences for three Escherichia spp. and three Shigella spp. generated with Pacific Biosciences and Illumina sequencing and optical mapping.

Escherichia spp., including E. albertii and E. coli, Shigella dysenteriae, and S. flexneri are causative agents of foodborne disease. We report here reference-level whole-genome sequences of E. albertii (2014C-4356), E. coli (2011C-4315 and 2012C-4431), S. dysenteriae (BU53M1), and S. flexneri (94-3007 and 71-2783).. Copyright © 2018 Schroeder et al.

Read more
July 7, 2019

Complete genome sequence of a type strain of Mycobacterium abscessus subsp. bolletii, a member of the Mycobacterium abscessus complex.

Mycobacterium abscessus subsp. bolletii is a rapidly growing mycobacterial organism for which the taxonomy is unclear. Here, we report the complete genome sequence of a Mycobacterium abscessus subsp. bolletii type strain. This sequence will provide essential information for future taxonomic and comparative genome studies of these mycobacteria.

Read more
July 7, 2019

High-quality complete genome sequences of three bovine Shiga toxin-producing Escherichia coli O177:H- (fliCH25) isolates harboring virulent stx2 and multiple plasmids.

Shiga toxin-producingEscherichia coli(STEC) bacteria are zoonotic pathogens. We report here the high-quality complete genome sequences of three STEC O177:H- (fliCH25) strains, SMN152SH1, SMN013SH2, and SMN197SH3. The assembled genomes consisted of one optical map-verified circular chromosome for each strain, plus two plasmids for SMN013SH2 and three plasmids for SMN152SH1 and SMN197SH3, respectively. Copyright © 2018 Sheng et al.

Read more
July 7, 2019

Complete genome sequence of Pseudomonas sp. strain NC02, isolated from soil.

We report here the complete genome sequence of Pseudomonas sp. strain NC02, isolated from soil in eastern Massachusetts. We assembled PacBio reads into a single closed contig with 132× mean coverage and then polished this contig using Illumina MiSeq reads, yielding a 6,890,566-bp sequence with 61.1% GC content. Copyright © 2018 Cerra et al.

Read more
July 7, 2019

Complete genome sequence of Escherichia coli ML35.

We report here the complete genome sequence of Escherichia coli strain ML35. We assembled PacBio reads into a single closed contig with 169× mean coverage and then polished this contig using Illumina MiSeq reads, yielding a 4,918,774-bp sequence with 50.8% GC content. Copyright © 2018 Casale et al.

Read more
July 7, 2019

Genome sequence of the necrotrophic plant pathogen Alternaria brassicicola Abra43.

Alternaria brassicicola causes dark spot (or black spot) disease, which is one of the most common and destructive fungal diseases of Brassicaceae spp. worldwide. Here, we report the draft genome sequence of strain Abra43. The assembly comprises 29 scaffolds, with an N50 value of 2.1 Mb. The assembled genome was 31,036,461 bp in length, with a G+C content of 50.85%.

Read more

Subscribe for blog updates:

Talk with an expert

If you have a question, need to check the status of an order, or are interested in purchasing an instrument, we're here to help.