scholarly journals phasebook: haplotype-aware de novo assembly of diploid genomes from long reads

2021 ◽  
Author(s):  
Xiao Luo ◽  
Xiongbin Kang ◽  
Alexander Schoenhuth
Keyword(s):  
Genome Assembly ◽  
De Novo Assembly ◽  
De Novo ◽  
Haplotype Diversity ◽  
Read Length ◽  
Diploid Genome ◽  
Sequencing Technologies ◽  
Novel Approach ◽  
Long Reads ◽  
Long Read

Haplotype-aware diploid genome assembly is crucial in genomics, precision medicine, and many other disciplines. Long-read sequencing technologies have greatly improved genome assembly thanks to advantages of read length. However, current long-read assemblers usually introduce disturbing biases or fail to capture the haplotype diversity of the diploid genome. Here, we present phasebook, a novel approach for reconstructing the haplotypes of diploid genomes from long reads de novo. Benchmarking experiments demonstrate that our method outperforms other approaches in terms of haplotype coverage by large margins, while preserving competitive performance or even achieving advantages in terms of all other aspects relevant for genome assembly.

scholarly journals Impact of Chimera-less Long Reads on Metagenomics of Human Gut Viromes Treated With Multiple Displacement Amplification

2020 ◽  
Author(s):  
Yuya Kiguchi ◽  
Suguru Nishijima ◽  
Naveen Kumar ◽  
Masahira Hattori ◽  
Wataru Suda
Keyword(s):  
De Novo ◽  
Multiple Displacement Amplification ◽  
Read Length ◽  
Human Gut ◽  
Average Read Length ◽  
Sequencing Technologies ◽  
Genomic Complexity ◽  
Long Reads ◽  
Long Read ◽  
The Impact

Abstract Background: The ecological and biological features of the indigenous phage community (virome) in the human gut microbiome are poorly understood, possibly due to many fragmented contigs and fewer complete genomes based on conventional short-read metagenomics. Long-read sequencing technologies have attracted attention as an alternative approach to reconstruct long and accurate contigs from microbial communities. However, the impact of long-read metagenomics on human gut virome analysis has not been well evaluated. Results: Here we present chimera-less PacBio long-read metagenomics of multiple displacement amplification (MDA)-treated human gut virome DNA. The method included the development of a novel bioinformatics tool, SACRA (Split Amplified Chimeric Read Algorithm), which efficiently detects and splits numerous chimeric reads in PacBio reads from the MDA-treated virome samples. SACRA treatment of PacBio reads from five samples markedly reduced the average chimera ratio from 72 to 1.5%, generating chimera-less PacBio reads with an average read-length of 1.8 kb. De novo assembly of the chimera-less long reads generated contigs with an average N50 length of 11.1 kb, whereas those of MiSeq short reads from the same samples were 0.7 kb, dramatically improving contig extension. Alignment of both contig sets generated 378 high-quality merged contigs (MCs) composed of the minimum scaffolds of 434 MiSeq and 637 PacBio contigs, respectively, and also identified numerous MiSeq short fragmented contigs ≤500 bp additionally aligned to MCs, which possibly originated from a small fraction of MiSeq chimeric reads. The alignment also revealed that fragmentations of the scaffolded MiSeq contigs were caused primarily by genomic complexity of the community, including local repeats, hypervariable regions, and highly conserved sequences in and between the phage genomes. We identified 142 complete and near-complete phage genomes including 108 novel genomes, varying from 5 to 185 kb in length, the majority of which were predicted to be Microviridae phages including several variants with homologous but distinct genomes, which were fragmented in MiSeq contigs. Conclusions: Long-read metagenomics coupled with SACRA provides an improved method to reconstruct accurate and extended phage genomes from MDA-treated virome samples of the human gut, and potentially from other environmental virome samples.

scholarly journals Human Genome Assembly in 100 Minutes

2019 ◽  
Author(s):  
Chen-Shan Chin ◽  
Asif Khalak
Keyword(s):  
Single Molecule ◽  
Dna Sequences ◽  
Genome Assembly ◽  
De Novo ◽  
Critical Factor ◽  
Read Length ◽  
De Novo Genome Assembly ◽  
Small Indels ◽  
Sequencing Technologies ◽  
Long Read

AbstractDe novo genome assembly provides comprehensive, unbiased genomic information and makes it possible to gain insight into new DNA sequences not present in reference genomes. Many de novo human genomes have been published in the last few years, leveraging a combination of inexpensive short-read and single-molecule long-read technologies. As long-read DNA sequencers become more prevalent, the computational burden of generating assemblies persists as a critical factor. The most common approach to long-read assembly, using an overlap-layout-consensus (OLC) paradigm, requires all-to-all read comparisons, which quadratically scales in computational complexity with the number of reads. We assert that recently achievements in sequencing technology (i.e. with accuracy ~99% and read length ~10-15k) enables a fundamentally better strategy for OLC that is effectively linear rather than quadratic. Our genome assembly implementation, Peregrine uses sparse hierarchical minimizers (SHIMMER) to index reads thereby avoiding the need for an all-to-all read comparison step. Peregrine can assemble 30x human PacBio CCS read datasets in less than 30 CPU hours and around 100 wall-clock minutes to a high contiguity assembly (N50 > 20Mb). The continued advance of sequencing technologies coupled with the Peregrine assembler enables routine generation of human de novo assemblies. This will allow for population scale measurements of more comprehensive genomic variations -- beyond SNPs and small indels -- as well as novel applications requiring rapid access to de novo assemblies.

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

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.

scholarly journals Accurate long-read de novo assembly evaluation with Inspector

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yu Chen ◽  
Yixin Zhang ◽  
Amy Y. Wang ◽  
Min Gao ◽  
Zechen Chong
Keyword(s):  
Genome Assembly ◽  
De Novo Assembly ◽  
In Silico ◽  
Large Scale ◽  
De Novo ◽  
Small Scale ◽  
De Novo Genome Assembly ◽  
Consensus Sequences ◽  
Assembly Evaluation ◽  
Long Read

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.

scholarly journals LRSDAY: Long-read Sequencing Data Analysis for Yeasts

2017 ◽  
Author(s):  
Jia-Xing Yue ◽  
Gianni Liti
Keyword(s):  
Genome Assembly ◽  
Model Organism ◽  
Sequencing Data ◽  
Protein Coding ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Long Read ◽  
Downstream Analysis ◽  
Eukaryotic Organisms ◽  
Genomic Regions

AbstractLong-read sequencing technologies have become increasingly popular in genome projects due to their strengths in resolving complex genomic regions. As a leading model organism with small genome size and great biotechnological importance, the budding yeast, Saccharomyces cerevisiae, has many isolates currently being sequenced with long reads. However, analyzing long-read sequencing data to produce high-quality genome assembly and annotation remains challenging. Here we present LRSDAY, the first one-stop solution to streamline this process. LRSDAY can produce chromosome-level end-to-end genome assembly and comprehensive annotations for various genomic features (including centromeres, protein-coding genes, tRNAs, transposable elements and telomere-associated elements) that are ready for downstream analysis. Although tailored for S. cerevisiae, we designed LRSDAY to be highly modular and customizable, making it adaptable for virtually any eukaryotic organisms. Applying LRSDAY to a S. cerevisiae strain takes ∼43 hrs to generate a complete and well-annotated genome from ∼100X Pacific Biosciences (PacBio) reads using four threads.

scholarly journals Fast-SG: An alignment-free algorithm for hybrid assembly

2017 ◽  
Author(s):  
Alex Di Genova ◽  
Gonzalo A. Ruz ◽  
Marie-France Sagot ◽  
Alejandro Maass
Keyword(s):  
De Novo ◽  
Reference Level ◽  
Hybrid Assembly ◽  
Short Read ◽  
Sequencing Technologies ◽  
Alignment Free ◽  
Long Reads ◽  
Long Read ◽  
Definition Of ◽  
Large Genomes

ABSTRACTLong read sequencing technologies are the ultimate solution for genome repeats, allowing near reference level reconstructions of large genomes. However, long read de novo assembly pipelines are computationally intense and require a considerable amount of coverage, thereby hindering their broad application to the assembly of large genomes. Alternatively, hybrid assembly methods which combine short and long read sequencing technologies can reduce the time and cost required to produce de novo assemblies of large genomes. In this paper, we propose a new method, called FAST-SG, which uses a new ultra-fast alignment-free algorithm specifically designed for constructing a scaffolding graph using light-weight data structures. FAST-SG can construct the graph from either short or long reads. This allows the reuse of efficient algorithms designed for short read data and permits the definition of novel modular hybrid assembly pipelines. Using comprehensive standard datasets and benchmarks, we show how FAST-SG outperforms the state-of-the-art short read aligners when building the scaffolding graph, and can be used to extract linking information from either raw or error-corrected long reads. We also show how a hybrid assembly approach using FAST-SG with shallow long read coverage (5X) and moderate computational resources can produce long-range and accurate reconstructions of the genomes of Arabidopsis thaliana (Ler-0) and human (NA12878).

scholarly journals Factorial estimating assembly base errors using k-mer abundance difference (KAD) between short reads and genome assembled sequences

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Cheng He ◽  
Guifang Lin ◽  
Hairong Wei ◽  
Haibao Tang ◽  
Frank F White ◽  
...  
Keyword(s):  
Copy Number ◽  
Error Rates ◽  
Genome Sequences ◽  
Short Reads ◽  
Sequencing Technologies ◽  
Insertion And Deletion ◽  
Novel Approach ◽  
Long Reads ◽  
Long Read ◽  
Genome Assemblies

Abstract Genome sequences provide genomic maps with a single-base resolution for exploring genetic contents. Sequencing technologies, particularly long reads, have revolutionized genome assemblies for producing highly continuous genome sequences. However, current long-read sequencing technologies generate inaccurate reads that contain many errors. Some errors are retained in assembled sequences, which are typically not completely corrected by using either long reads or more accurate short reads. The issue commonly exists, but few tools are dedicated for computing error rates or determining error locations. In this study, we developed a novel approach, referred to as k-mer abundance difference (KAD), to compare the inferred copy number of each k-mer indicated by short reads and the observed copy number in the assembly. Simple KAD metrics enable to classify k-mers into categories that reflect the quality of the assembly. Specifically, the KAD method can be used to identify base errors and estimate the overall error rate. In addition, sequence insertion and deletion as well as sequence redundancy can also be detected. Collectively, KAD is valuable for quality evaluation of genome assemblies and, potentially, provides a diagnostic tool to aid in precise error correction. KAD software has been developed to facilitate public uses.

scholarly journals Overcoming uncollapsed haplotypes in long-read assemblies of non-model organisms

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Nadège Guiglielmoni ◽  
Antoine Houtain ◽  
Alessandro Derzelle ◽  
Karine Van Doninck ◽  
Jean-François Flot
Keyword(s):  
Genome Assembly ◽  
Model Organism ◽  
Model Organisms ◽  
Post Processing ◽  
Diploid Genome ◽  
Long Reads ◽  
Long Read ◽  
Eukaryote Genome ◽  
Chromosome Level

Abstract Background Long-read sequencing is revolutionizing genome assembly: as PacBio and Nanopore technologies become more accessible in technicity and in cost, long-read assemblers flourish and are starting to deliver chromosome-level assemblies. However, these long reads are usually error-prone, making the generation of a haploid reference out of a diploid genome a difficult enterprise. Failure to properly collapse haplotypes results in fragmented and structurally incorrect assemblies and wreaks havoc on orthology inference pipelines, yet this serious issue is rarely acknowledged and dealt with in genomic projects, and an independent, comparative benchmark of the capacity of assemblers and post-processing tools to properly collapse or purge haplotypes is still lacking. Results We tested different assembly strategies on the genome of the rotifer Adineta vaga, a non-model organism for which high coverages of both PacBio and Nanopore reads were available. The assemblers we tested (Canu, Flye, NextDenovo, Ra, Raven, Shasta and wtdbg2) exhibited strikingly different behaviors when dealing with highly heterozygous regions, resulting in variable amounts of uncollapsed haplotypes. Filtering reads generally improved haploid assemblies, and we also benchmarked three post-processing tools aimed at detecting and purging uncollapsed haplotypes in long-read assemblies: HaploMerger2, purge_haplotigs and purge_dups. Conclusions We provide a thorough evaluation of popular assemblers on a non-model eukaryote genome with variable levels of heterozygosity. Our study highlights several strategies using pre and post-processing approaches to generate haploid assemblies with high continuity and completeness. This benchmark will help users to improve haploid assemblies of non-model organisms, and evaluate the quality of their own assemblies.

scholarly journals LongStitch: High-quality genome assembly correction and scaffolding using long reads

2021 ◽  
Author(s):  
Lauren Coombe ◽  
Janet X Li ◽  
Theodora Lo ◽  
Johnathan Wong ◽  
Vladimir Nikolic ◽  
...  
Keyword(s):  
Genome Assembly ◽  
De Novo ◽  
Draft Genome ◽  
Model Organisms ◽  
High Quality ◽  
De Novo Genome Assembly ◽  
Long Reads ◽  
Long Read ◽  
Genomic Regions ◽  
Genome Assemblies

Background Generating high-quality de novo genome assemblies is foundational to the genomics study of model and non-model organisms. In recent years, long-read sequencing has greatly benefited genome assembly and scaffolding, a process by which assembled sequences are ordered and oriented through the use of long-range information. Long reads are better able to span repetitive genomic regions compared to short reads, and thus have tremendous utility for resolving problematic regions and helping generate more complete draft assemblies. Here, we present LongStitch, a scalable pipeline that corrects and scaffolds draft genome assemblies exclusively using long reads. Results LongStitch incorporates multiple tools developed by our group and runs in up to three stages, which includes initial assembly correction (Tigmint-long), followed by two incremental scaffolding stages (ntLink and ARKS-long). Tigmint-long and ARKS-long are misassembly correction and scaffolding utilities, respectively, previously developed for linked reads, that we adapted for long reads. Here, we describe the LongStitch pipeline and introduce our new long-read scaffolder, ntLink, which utilizes lightweight minimizer mappings to join contigs. LongStitch was tested on short and long-read assemblies of three different human individuals using corresponding nanopore long-read data, and improves the contiguity of each assembly from 2.0-fold up to 304.6-fold (as measured by NGA50 length). Furthermore, LongStitch generates more contiguous and correct assemblies compared to state-of-the-art long-read scaffolder LRScaf in most tests, and consistently runs in under five hours using less than 23GB of RAM. Conclusions Due to its effectiveness and efficiency in improving draft assemblies using long reads, we expect LongStitch to benefit a wide variety of de novo genome assembly projects. The LongStitch pipeline is freely available at https://github.com/bcgsc/longstitch.

scholarly journals Highly-accurate long-read sequencing improves variant detection and assembly of a human genome

2019 ◽  
Author(s):  
Aaron M. Wenger ◽  
Paul Peluso ◽  
William J. Rowell ◽  
Pi-Chuan Chang ◽  
Richard J. Hall ◽  
...  
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Structural Variants ◽  
Short Reads ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Long Read ◽  
Variant Detection ◽  
High Quality Genome ◽  
Circular Consensus Sequencing

AbstractThe major DNA sequencing technologies in use today produce either highly-accurate short reads or noisy long reads. We developed a protocol based on single-molecule, circular consensus sequencing (CCS) to generate highly-accurate (99.8%) long reads averaging 13.5 kb and applied it to sequence the well-characterized human HG002/NA24385. We optimized existing tools to comprehensively detect variants, achieving precision and recall above 99.91% for SNVs, 95.98% for indels, and 95.99% for structural variants. We estimate that 2,434 discordances are correctable mistakes in the high-quality Genome in a Bottle benchmark. Nearly all (99.64%) variants are phased into haplotypes, which further improves variant detection. De novo assembly produces a highly contiguous and accurate genome with contig N50 above 15 Mb and concordance of 99.998%. CCS reads match short reads for small variant detection, while enabling structural variant detection and de novo assembly at similar contiguity and markedly higher concordance than noisy long reads.

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