scholarly journals Empirical evaluation of methods for de novo genome assembly

2021 ◽  
Vol 7 ◽  
pp. e636
Author(s):  
Firaol Dida ◽  
Gangman Yi
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Sequence Data ◽  
Hybrid Approach ◽  
Empirical Evaluation ◽  
De Bruijn Graph ◽  
De Novo Genome Assembly ◽  
String Graph ◽  
Assembly Algorithms ◽  
The Impact

Technologies for next-generation sequencing (NGS) have stimulated an exponential rise in high-throughput sequencing projects and resulted in the development of new read-assembly algorithms. A drastic reduction in the costs of generating short reads on the genomes of new organisms is attributable to recent advances in NGS technologies such as Ion Torrent, Illumina, and PacBio. Genome research has led to the creation of high-quality reference genomes for several organisms, and de novo assembly is a key initiative that has facilitated gene discovery and other studies. More powerful analytical algorithms are needed to work on the increasing amount of sequence data. We make a thorough comparison of the de novo assembly algorithms to allow new users to clearly understand the assembly algorithms: overlap-layout-consensus and de-Bruijn-graph, string-graph based assembly, and hybrid approach. We also address the computational efficacy of each algorithm’s performance, challenges faced by the assem- bly tools used, and the impact of repeats. Our results compare the relative performance of the different assemblers and other related assembly differences with and without the reference genome. We hope that this analysis will contribute to further the application of de novo sequences and help the future growth of assembly algorithms.

scholarly journals Gene Annotation and Transcriptome Delineation on a De Novo Genome Assembly for the Reference Leishmania major Friedlin Strain

Genes ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1359
Author(s):  
Esther Camacho ◽  
Sandra González-de la Fuente ◽  
Jose C. Solana ◽  
Alberto Rastrojo ◽  
Fernando Carrasco-Ramiro ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Genome Assembly ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Leishmania Major ◽  
De Novo ◽  
Gene Annotation ◽  
Leishmania Species ◽  
De Novo Genome Assembly ◽  
Sequencing Platforms

Leishmania major is the main causative agent of cutaneous leishmaniasis in humans. The Friedlin strain of this species (LmjF) was chosen when a multi-laboratory consortium undertook the objective of deciphering the first genome sequence for a parasite of the genus Leishmania. The objective was successfully attained in 2005, and this represented a milestone for Leishmania molecular biology studies around the world. Although the LmjF genome sequence was done following a shotgun strategy and using classical Sanger sequencing, the results were excellent, and this genome assembly served as the reference for subsequent genome assemblies in other Leishmania species. Here, we present a new assembly for the genome of this strain (named LMJFC for clarity), generated by the combination of two high throughput sequencing platforms, Illumina short-read sequencing and PacBio Single Molecular Real-Time (SMRT) sequencing, which provides long-read sequences. Apart from resolving uncertain nucleotide positions, several genomic regions were reorganized and a more precise composition of tandemly repeated gene loci was attained. Additionally, the genome annotation was improved by adding 542 genes and more accurate coding-sequences defined for around two hundred genes, based on the transcriptome delimitation also carried out in this work. As a result, we are providing gene models (including untranslated regions and introns) for 11,238 genes. Genomic information ultimately determines the biology of every organism; therefore, our understanding of molecular mechanisms will depend on the availability of precise genome sequences and accurate gene annotations. In this regard, this work is providing an improved genome sequence and updated transcriptome annotations for the reference L. major Friedlin strain.

scholarly journals Scalable Genome Assembly through Parallel de Bruijn Graph Construction for Multiple k-mers

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kanak Mahadik ◽  
Christopher Wright ◽  
Milind Kulkarni ◽  
Saurabh Bagchi ◽  
Somali Chaterji
Keyword(s):  
De Novo ◽  
De Bruijn Graph ◽  
High Quality ◽  
De Bruijn Graphs ◽  
Sequencing Technologies ◽  
De Bruijn ◽  
Similar Accuracy ◽  
Valued Graph ◽  
Assembly Algorithms ◽  
Level Parallelism

Abstract Remarkable advancements in high-throughput gene sequencing technologies have led to an exponential growth in the number of sequenced genomes. However, unavailability of highly parallel and scalable de novo assembly algorithms have hindered biologists attempting to swiftly assemble high-quality complex genomes. Popular de Bruijn graph assemblers, such as IDBA-UD, generate high-quality assemblies by iterating over a set of k-values used in the construction of de Bruijn graphs (DBG). However, this process of sequentially iterating from small to large k-values slows down the process of assembly. In this paper, we propose ScalaDBG, which metamorphoses this sequential process, building DBGs for each distinct k-value in parallel. We develop an innovative mechanism to “patch” a higher k-valued graph with contigs generated from a lower k-valued graph. Moreover, ScalaDBG leverages multi-level parallelism, by both scaling up on all cores of a node, and scaling out to multiple nodes simultaneously. We demonstrate that ScalaDBG completes assembling the genome faster than IDBA-UD, but with similar accuracy on a variety of datasets (6.8X faster for one of the most complex genome in our dataset).

scholarly journals Assessing Genome-Wide Diversity in European Hantaviruses through Sequence Capture from Natural Host Samples

Viruses ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 749 ◽  
Author(s):  
Melanie Hiltbrunner ◽  
Gerald Heckel
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Phylogenetic Analyses ◽  
Common Vole ◽  
Natural Host ◽  
Sequence Information ◽  
Coding Region ◽  
Sequence Capture ◽  
Genome Wide ◽  
The Impact

Research on the ecology and evolution of viruses is often hampered by the limitation of sequence information to short parts of the genomes or single genomes derived from cultures. In this study, we use hybrid sequence capture enrichment in combination with high-throughput sequencing to provide efficient access to full genomes of European hantaviruses from rodent samples obtained in the field. We applied this methodology to Tula (TULV) and Puumala (PUUV) orthohantaviruses for which analyses from natural host samples are typically restricted to partial sequences of their tri-segmented RNA genome. We assembled a total of ten novel hantavirus genomes de novo with very high coverage (on average >99%) and sequencing depth (average >247×). A comparison with partial Sanger sequences indicated an accuracy of >99.9% for the assemblies. An analysis of two common vole (Microtus arvalis) samples infected with two TULV strains each allowed for the de novo assembly of all four TULV genomes. Combining the novel sequences with all available TULV and PUUV genomes revealed very similar patterns of sequence diversity along the genomes, except for remarkably higher diversity in the non-coding region of the S-segment in PUUV. The genomic distribution of polymorphisms in the coding sequence was similar between the species, but differed between the segments with the highest sequence divergence of 0.274 for the M-segment, 0.265 for the S-segment, and 0.248 for the L-segment (overall 0.258). Phylogenetic analyses showed the clustering of genome sequences consistent with their geographic distribution within each species. Genome-wide data yielded extremely high node support values, despite the impact of strong mutational saturation that is expected for hantavirus sequences obtained over large spatial distances. We conclude that genome sequencing based on capture enrichment protocols provides an efficient means for ecological and evolutionary investigations of hantaviruses at an unprecedented completeness and depth.

scholarly journals A benchmarking of human mitochondrial DNA haplogroup classifiers from whole-genome and whole-exome sequence data

2021 ◽  
Author(s):  
Víctor García-Olivares ◽  
Adrián Muñoz-Barrera ◽  
José Miguel Lorenzo-Salazar ◽  
Carlos Zaragoza-Trello ◽  
Luis A. Rubio-Rodríguez ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Sequence Data ◽  
Qualitative Assessment ◽  
Whole Genome ◽  
Third Generation ◽  
Sequencing Data ◽  
Short Read ◽  
Bioinformatic Tools ◽  
Whole Exome

AbstractThe mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short-read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

scholarly journals Using Apache Spark on genome assembly for scalable overlap-graph reduction

2019 ◽  
Vol 13 (S1) ◽  
Author(s):  
Alexander J. Paul ◽  
Dylan Lawrence ◽  
Myoungkyu Song ◽  
Seung-Hwan Lim ◽  
Chongle Pan ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Time Frame ◽  
Apache Spark ◽  
Reference Sequence ◽  
Graph Reduction ◽  
De Novo Genome Assembly ◽  
String Graph ◽  
Edge Graph ◽  
Generation Sequencing

Abstract Background De novo genome assembly is a technique that builds the genome of a specimen using overlaps of genomic fragments without additional work with reference sequence. Sequence fragments (called reads) are assembled as contigs and scaffolds by the overlaps. The quality of the de novo assembly depends on the length and continuity of the assembly. To enable faster and more accurate assembly of species, existing sequencing techniques have been proposed, for example, high-throughput next-generation sequencing and long-reads-producing third-generation sequencing. However, these techniques require a large amounts of computer memory when very huge-size overlap graphs are resolved. Also, it is challenging for parallel computation. Results To address the limitations, we propose an innovative algorithmic approach, called Scalable Overlap-graph Reduction Algorithms (SORA). SORA is an algorithm package that performs string graph reduction algorithms by Apache Spark. The SORA’s implementations are designed to execute de novo genome assembly on either a single machine or a distributed computing platform. SORA efficiently compacts the number of edges on enormous graphing paths by adapting scalable features of graph processing libraries provided by Apache Spark, GraphX and GraphFrames. Conclusions We shared the algorithms and the experimental results at our project website, https://github.com/BioHPC/SORA. We evaluated SORA with the human genome samples. First, it processed a nearly one billion edge graph on a distributed cloud cluster. Second, it processed mid-to-small size graphs on a single workstation within a short time frame. Overall, SORA achieved the linear-scaling simulations for the increased computing instances.

scholarly journals Clover: a clustering-oriented de novo assembler for Illumina sequences

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Ming-Feng Hsieh ◽  
Chin Lung Lu ◽  
Chuan Yi Tang
Keyword(s):  
De Novo Assembly ◽  
De Novo ◽  
Low Cost ◽  
De Bruijn Graph ◽  
Illumina Platform ◽  
Sequencing Errors ◽  
Sequencing Technologies ◽  
String Graph ◽  
Clustering Approach ◽  
De Bruijn

Abstract Background Next-generation sequencing technologies revolutionized genomics by producing high-throughput reads at low cost, and this progress has prompted the recent development of de novo assemblers. Multiple assembly methods based on de Bruijn graph have been shown to be efficient for Illumina reads. However, the sequencing errors generated by the sequencer complicate analysis of de novo assembly and influence the quality of downstream genomic researches. Results In this paper, we develop a de Bruijn assembler, called Clover (clustering-oriented de novo assembler), that utilizes a novel k-mer clustering approach from the overlap-layout-consensus concept to deal with the sequencing errors generated by the Illumina platform. We further evaluate Clover’s performance against several de Bruijn graph assemblers (ABySS, SOAPdenovo, SPAdes and Velvet), overlap-layout-consensus assemblers (Bambus2, CABOG and MSR-CA) and string graph assembler (SGA) on three datasets (Staphylococcus aureus, Rhodobacter sphaeroides and human chromosome 14). The results show that Clover achieves a superior assembly quality in terms of corrected N50 and E-size while remaining a significantly competitive in run time except SOAPdenovo. In addition, Clover was involved in the sequencing projects of bacterial genomes Acinetobacter baumannii TYTH-1 and Morganella morganii KT. Conclusions The marvel clustering-based approach of Clover that integrates the flexibility of the overlap-layout-consensus approach and the efficiency of the de Bruijn graph method has high potential on de novo assembly. Now, Clover is freely available as open source software from https://oz.nthu.edu.tw/~d9562563/src.html.

Inference of viral quasispecies with a paired de Bruijn graph

2020 ◽  
Author(s):  
Borja Freire ◽  
Susana Ladra ◽  
Jose R Paramá ◽  
Leena Salmela
Keyword(s):  
High Throughput Sequencing ◽  
De Novo ◽  
Supplementary Information ◽  
De Bruijn Graph ◽  
Viral Quasispecies ◽  
Sequencing Data ◽  
De Bruijn Graphs ◽  
Sequencing Errors ◽  
High Throughput Sequencing Data ◽  
De Bruijn

Abstract Motivation RNA viruses exhibit a high mutation rate and thus they exist in infected cells as a population of closely related strains called viral quasispecies. The viral quasispecies assembly problem asks to characterize the quasispecies present in a sample from high-throughput sequencing data. We study the de novo version of the problem, where reference sequences of the quasispecies are not available. Current methods for assembling viral quasispecies are either based on overlap graphs or on de Bruijn graphs. Overlap graph-based methods tend to be accurate but slow, whereas de Bruijn graph-based methods are fast but less accurate. Results We present viaDBG, which is a fast and accurate de Bruijn graph-based tool for de novo assembly of viral quasispecies. We first iteratively correct sequencing errors in the reads, which allows us to use large k-mers in the de Bruijn graph. To incorporate the paired-end information in the graph, we also adapt the paired de Bruijn graph for viral quasispecies assembly. These features enable the use of long-range information in contig construction without compromising the speed of de Bruijn graph-based approaches. Our experimental results show that viaDBG is both accurate and fast, whereas previous methods are either fast or accurate but not both. In particular, viaDBG has comparable or better accuracy than SAVAGE, while being at least nine times faster. Furthermore, the speed of viaDBG is comparable to PEHaplo but viaDBG is able to retrieve also low abundance quasispecies, which are often missed by PEHaplo. Availability and implementation viaDBG is implemented in C++ and it is publicly available at https://bitbucket.org/bfreirec1/viadbg. All datasets used in this article are publicly available at https://bitbucket.org/bfreirec1/data-viadbg/. Supplementary information Supplementary data are available at Bioinformatics online.

Clinical utilization of targetable molecular results in pancreatic cancer: Longer-term outcomes from the Individualized Molecular Pancreatic Cancer Therapy (IMPACT) trial.

2017 ◽  
Vol 35 (4_suppl) ◽  
pp. 314-314
Author(s):  
Lorraine A. Chantrill ◽  
Adnan Nagrial ◽  
Amber Johns ◽  
Skye McKay ◽  
Anthony J. Gill ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Pancreas Cancer ◽  
De Novo ◽  
Sequence Data ◽  
Clinical Care ◽  
Molecular Targets ◽  
Second Primary ◽  
Personalised Treatment ◽  
The Impact

314 Background: The IMPaCT trial screened patients with advanced pancreas cancer for molecular targets and aimed to test molecularly guided therapy in a pilot randomized study, but closed in December 2015 having delivered personalized treatment to only 1 patient. A follow up analysis of the screened cohort provides insight into the clinical utilisation of targetable molecular results in pancreas cancer. Methods: IMPaCT screened for 3 genetic phenotypes matched to precision treatment: Her2 amplification (trastuzamab + gemcitabine), KRAS wildtype (erlotinib + gemcitabine) and DNA damage repair pathway defects (platinum-based). Previously recruited primary resected APGI participants known to be alive were also screened for these targets. The initial pilot protocol included randomisation, but after amendment in early 2015, became a single-arm study allowing one cycle of gemcitabine + nab-paclitaxel during screening. Results: A total of 101 potential patients were screened. This was enriched for patients with known targets where sequence data was available from primary pancreatectomy. 23 had one of the 3 molecular targets in this enriched population (4 Her2 amplified, 16 KRAS wt, 2 BRCA2, 1 ATM). The prospectively recruited de novo metastatic cohort (n = 63) had an actionable mutation detection rate of 14.3%. Of the 23 patients identified, 3 received personalised treatment off study, 1 on study, 3 are currently alive without recurrence, 1 is monitored for suspected recurrence, 2 developed second primary malignancies, 10 died or progressed prior to result and 3 decided not to use personalised treatment. The identification of a molecular target did not significantly affect overall survival. Conclusions: Although actionable molecular targets were detected, recruitment rates on the IMPaCT trial were low (1%). Follow up illustrates that these molecular results were incorporated into clinical care off trial or still have the potential to be utilised in another 6.9% of the cohort. Further follow up is planned for long term outcomes. Clinical trial information: ACTRN12612000777897.

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