GraphSeq: Accelerating String Graph Construction for De Novo Assembly on Spark

AbstractLong-read de novo genome assembly continues to advance rapidly. However, there is a lack of effective tools to accurately evaluate the assembly results, especially for structural errors. We present Inspector, a reference-free long-read de novo assembly evaluator which faithfully reports types of errors and their precise locations. Notably, Inspector can correct the assembly errors based on consensus sequences derived from raw reads covering erroneous regions. Based on in silico and long-read assembly results from multiple long-read data and assemblers, we demonstrate that in addition to providing generic metrics, Inspector can accurately identify both large-scale and small-scale assembly errors.

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Optimizing de novo genome assembly from PCR-amplified metagenomes

10.7287/peerj.preprints.27453 ◽

2018 ◽

Author(s):

Simon Roux ◽

Gareth Trubl ◽

Danielle Goudeau ◽

Nandita Nath ◽

Estelle Couradeau ◽

...

Keyword(s):

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Pcr Amplification ◽

Error Rates ◽

De Novo Genome Assembly ◽

Low Input ◽

Assembly Algorithm ◽

Coverage Bias ◽

Assembly Pipeline

Background. Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods. Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results. Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥ 10kb by 10 to 100-fold for low input metagenomes. Conclusions. PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

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

Human Genomics ◽

10.1186/s40246-019-0227-1 ◽

2019 ◽

Vol 13 (S1) ◽

Cited By ~ 1

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.

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Optimizing de novo genome assembly from PCR-amplified metagenomes

10.7287/peerj.preprints.27453v1 ◽

2018 ◽

Author(s):

Simon Roux ◽

Gareth Trubl ◽

Danielle Goudeau ◽

Nandita Nath ◽

Estelle Couradeau ◽

...

Keyword(s):

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Pcr Amplification ◽

Error Rates ◽

De Novo Genome Assembly ◽

Low Input ◽

Assembly Algorithm ◽

Coverage Bias ◽

Assembly Pipeline

Background. Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enabling de novo assembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes. Methods. Here we evaluate de novo assembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes. Results. Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥ 10kb by 10 to 100-fold for low input metagenomes. Conclusions. PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improved de novo genome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

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Parallel String Graph Construction and Transitive Reduction for De Novo Genome Assembly

2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS) ◽

10.1109/ipdps49936.2021.00060 ◽

2021 ◽

Author(s):

Giulia Guidi ◽

Oguz Selvitopi ◽

Marquita Ellis ◽

Leonid Oliker ◽

Katherine Yelick ◽

...

Keyword(s):

Genome Assembly ◽

De Novo ◽

De Novo Genome Assembly ◽

Transitive Reduction ◽

String Graph

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De novo genome assembly of Solanum sitiens reveals structural variation associated with drought and salinity tolerance

Bioinformatics ◽

10.1093/bioinformatics/btab048 ◽

2021 ◽

Author(s):

Corentin Molitor ◽

Tomasz J Kurowski ◽

Pedro M Fidalgo de Almeida ◽

Pramod Eerolla ◽

Daniel J Spindlow ◽

...

Keyword(s):

Drought Resistance ◽

Genome Assembly ◽

Reference Genome ◽

De Novo ◽

Transcriptome Assembly ◽

Crop Improvement ◽

Single Copy ◽

Supplementary Information ◽

Analysis Tool ◽

De Novo Genome Assembly

Abstract Motivation Solanum sitiens is a self-incompatible wild relative of tomato, characterized by salt and drought-resistance traits, with the potential to contribute through breeding programmes to crop improvement in cultivated tomato. This species has a distinct morphology, classification and ecotype compared to other stress resistant wild tomato relatives such as S.pennellii and S.chilense. Therefore, the availability of a reference genome for S.sitiens will facilitate the genetic and molecular understanding of salt and drought resistance. Results A high-quality de novo genome and transcriptome assembly for S.sitiens (Accession LA1974) has been developed. A hybrid assembly strategy was followed using Illumina short reads (∼159× coverage) and PacBio long reads (∼44× coverage), generating a total of ∼262 Gbp of DNA sequence. A reference genome of 1245 Mbp, arranged in 1483 scaffolds with an N50 of 1.826 Mbp was generated. Genome completeness was estimated at 95% using the Benchmarking Universal Single-Copy Orthologs (BUSCO) and the K-mer Analysis Tool (KAT). In addition, ∼63 Gbp of RNA-Seq were generated to support the prediction of 31 164 genes from the assembly, and to perform a de novo transcriptome. Lastly, we identified three large inversions compared to S.lycopersicum, containing several drought-resistance-related genes, such as beta-amylase 1 and YUCCA7. Availability and implementation S.sitiens (LA1974) raw sequencing, transcriptome and genome assembly have been deposited at the NCBI’s Sequence Read Archive, under the BioProject number ‘PRJNA633104’. All the commands and scripts necessary to generate the assembly are available at the following github repository: https://github.com/MCorentin/Solanum_sitiens_assembly. Supplementary information Supplementary data are available at Bioinformatics online.

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A long reads-based de-novo assembly of the genome of the Arlee homozygous line reveals chromosomal rearrangements in rainbow trout

G3 Genes|Genome|Genetics ◽

10.1093/g3journal/jkab052 ◽

2021 ◽

Author(s):

Guangtu Gao ◽

Susana Magadan ◽

Geoffrey C Waldbieser ◽

Ramey C Youngblood ◽

Paul A Wheeler ◽

...

Keyword(s):

Rainbow Trout ◽

Chromosome Number ◽

Genome Assembly ◽

De Novo Assembly ◽

De Novo ◽

Sequence Data ◽

Structural Variations ◽

High Coverage ◽

Haploid Chromosome Number ◽

Long Reads

Abstract Currently, there is still a need to improve the contiguity of the rainbow trout reference genome and to use multiple genetic backgrounds that will represent the genetic diversity of this species. The Arlee doubled haploid line was originated from a domesticated hatchery strain that was originally collected from the northern California coast. The Canu pipeline was used to generate the Arlee line genome de-novo assembly from high coverage PacBio long-reads sequence data. The assembly was further improved with Bionano optical maps and Hi-C proximity ligation sequence data to generate 32 major scaffolds corresponding to the karyotype of the Arlee line (2 N = 64). It is composed of 938 scaffolds with N50 of 39.16 Mb and a total length of 2.33 Gb, of which ∼95% was in 32 chromosome sequences with only 438 gaps between contigs and scaffolds. In rainbow trout the haploid chromosome number can vary from 29 to 32. In the Arlee karyotype the haploid chromosome number is 32 because chromosomes Omy04, 14 and 25 are divided into six acrocentric chromosomes. Additional structural variations that were identified in the Arlee genome included the major inversions on chromosomes Omy05 and Omy20 and additional 15 smaller inversions that will require further validation. This is also the first rainbow trout genome assembly that includes a scaffold with the sex-determination gene (sdY) in the chromosome Y sequence. The utility of this genome assembly is demonstrated through the improved annotation of the duplicated genome loci that harbor the IGH genes on chromosomes Omy12 and Omy13.

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