scholarly journals Higher rates of processed pseudogene acquisition in humans and three great apes revealed by long read assemblies

2020 ◽  
Author(s):  
Xiaowen Feng ◽  
Heng Li
Keyword(s):  
Great Apes ◽  
Comprehensive Analysis ◽  
Active Process ◽  
Protein Coding ◽  
Short Read ◽  
Short Reads ◽  
Human Data ◽  
Genome Wide ◽  
Long Read ◽  
Processed Pseudogene

AbstractLINE-1 mediated retrotransposition of protein-coding mRNAs is an active process in modern humans for both germline and somatic genomes. Prior works that surveyed human data or human cohorts mostly relied on detecting discordant mappings of paired-end short reads, or assumed L1 hallmarks such as polyA tails and target site duplications. Moreover, there has been few genome-wide comparison between gene retrocopies in great apes and humans. In this study, we introduced a more sensitive and accurate approach to the discovery of processed pseudogene. Our method utilizes long read assemblies, and more importantly, is able to provide full retrocopy sequences as well as the neighboring sequences which are missed by short-read based methods reads. We provided an overview of novel gene retrocopies of 40 events (38 parent genes) in 20 human assemblies, a significantly higher discovery rate than previous reports (39 events of 36 parent genes out of 939 individuals). We also performed comprehensive analysis of lineage specific retrocopies in chimpanzee, gorilla and orangutan genomes.

scholarly journals Higher Rates of Processed Pseudogene Acquisition in Humans and Three Great Apes Revealed by Long-Read Assemblies

2021 ◽  
Author(s):  
Xiaowen Feng ◽  
Heng Li
Keyword(s):  
Reference Genome ◽  
Great Apes ◽  
Accurate Method ◽  
Protein Coding ◽  
Short Reads ◽  
Long Read ◽  
Processed Pseudogene ◽  
Processed Pseudogenes ◽  
Exon Junctions ◽  
Flanking Regions

Abstract LINE-1-mediated retrotransposition of protein-coding mRNAs is an active process in modern humans for both germline and somatic genomes. Prior works that surveyed human data mostly relied on detecting discordant mappings of paired-end short reads, or exon junctions contained in short reads. Moreover, there have been few genome-wide comparisons between gene retrocopies in great apes and humans. In this study, we introduced a more sensitive and accurate method to identify processed pseudogenes. Our method utilizes long-read assemblies, and more importantly, is able to provide full-length retrocopy sequences as well as flanking regions which are missed by short-read based methods. From 22 human individuals, we pinpointed 40 processed pseudogenes that are not present in the human reference genome GRCh38 and identified 17 pseudogenes that are in GRCh38 but absent from some input individuals. This represents a significantly higher discovery rate than previous reports (39 pseudogenes not in the reference genome out of 939 individuals). We also provided an overview of lineage-specific retrocopies in chimpanzee, gorilla, and orangutan genomes.

scholarly journals Evaluating the accuracy of Listeria monocytogenes assemblies from quasimetagenomic samples using long and short reads

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Seth Commichaux ◽  
Kiran Javkar ◽  
Padmini Ramachandran ◽  
Niranjan Nagarajan ◽  
Denis Bertrand ◽  
...  
Keyword(s):  
Public Health ◽  
Public Health Response ◽  
High Quality ◽  
Short Read ◽  
Short Reads ◽  
The Core ◽  
Long Reads ◽  
Health Response ◽  
Long Read ◽  
Core Genes

Abstract Background Whole genome sequencing of cultured pathogens is the state of the art public health response for the bioinformatic source tracking of illness outbreaks. Quasimetagenomics can substantially reduce the amount of culturing needed before a high quality genome can be recovered. Highly accurate short read data is analyzed for single nucleotide polymorphisms and multi-locus sequence types to differentiate strains but cannot span many genomic repeats, resulting in highly fragmented assemblies. Long reads can span repeats, resulting in much more contiguous assemblies, but have lower accuracy than short reads. Results We evaluated the accuracy of Listeria monocytogenes assemblies from enrichments (quasimetagenomes) of naturally-contaminated ice cream using long read (Oxford Nanopore) and short read (Illumina) sequencing data. Accuracy of ten assembly approaches, over a range of sequencing depths, was evaluated by comparing sequence similarity of genes in assemblies to a complete reference genome. Long read assemblies reconstructed a circularized genome as well as a 71 kbp plasmid after 24 h of enrichment; however, high error rates prevented high fidelity gene assembly, even at 150X depth of coverage. Short read assemblies accurately reconstructed the core genes after 28 h of enrichment but produced highly fragmented genomes. Hybrid approaches demonstrated promising results but had biases based upon the initial assembly strategy. Short read assemblies scaffolded with long reads accurately assembled the core genes after just 24 h of enrichment, but were highly fragmented. Long read assemblies polished with short reads reconstructed a circularized genome and plasmid and assembled all the genes after 24 h enrichment but with less fidelity for the core genes than the short read assemblies. Conclusion The integration of long and short read sequencing of quasimetagenomes expedited the reconstruction of a high quality pathogen genome compared to either platform alone. A new and more complete level of information about genome structure, gene order and mobile elements can be added to the public health response by incorporating long read analyses with the standard short read WGS outbreak response.

scholarly journals Mapping and phasing of structural variation in patient genomes using nanopore sequencing

2017 ◽  
Author(s):  
Mircea Cretu Stancu ◽  
Markus J. van Roosmalen ◽  
Ivo Renkens ◽  
Marleen Nieboer ◽  
Sjors Middelkamp ◽  
...  
Keyword(s):  
Single Molecule ◽  
De Novo ◽  
Structural Variants ◽  
Human Genetic Disease ◽  
Structural Genomic ◽  
Short Read ◽  
Sequencing Technologies ◽  
Genome Wide ◽  
Long Read ◽  
Complex Structural

AbstractStructural genomic variants form a common type of genetic alteration underlying human genetic disease and phenotypic variation. Despite major improvements in genome sequencing technology and data analysis, the detection of structural variants still poses challenges, particularly when variants are of high complexity. Emerging long-read single-molecule sequencing technologies provide new opportunities for detection of structural variants. Here, we demonstrate sequencing of the genomes of two patients with congenital abnormalities using the ONT MinION at 11x and 16x mean coverage, respectively. We developed a bioinformatic pipeline - NanoSV - to efficiently map genomic structural variants (SVs) from the long-read data. We demonstrate that the nanopore data are superior to corresponding short-read data with regard to detection of de novo rearrangements originating from complex chromothripsis events in the patients. Additionally, genome-wide surveillance of SVs, revealed 3,253 (33%) novel variants that were missed in short-read data of the same sample, the majority of which are duplications < 200bp in size. Long sequencing reads enabled efficient phasing of genetic variations, allowing the construction of genome-wide maps of phased SVs and SNVs. We employed read-based phasing to show that all de novo chromothripsis breakpoints occurred on paternal chromosomes and we resolved the long-range structure of the chromothripsis. This work demonstrates the value of long-read sequencing for screening whole genomes of patients for complex structural variants.

scholarly journals Assembling reads improves taxonomic classification of species

2020 ◽  
Author(s):  
Quang Tran ◽  
Vinhthuy Phan
Keyword(s):  
Classification Performance ◽  
Performance Characteristics ◽  
Metagenomic Data ◽  
Species Classification ◽  
Short Read ◽  
Short Reads ◽  
Sequencing Errors ◽  
Trade Offs ◽  
Long Reads ◽  
Long Read

Abstract Background: Most current metagenomic classifiers and profilers employ short reads to classify, bin and profile microbial genomes that are present in metagenomic samples. Many of these methods adopt techniques that aim to identify unique genomic regions of genomes so as to differentiate them. Because of this, short-read lengths might be suboptimal. Longer read lengths might improve the performance of classification and profiling. However, longer reads produced by current technology tend to have a higher rate of sequencing errors, compared to short reads. It is not clear if the trade-off between longer length versus higher sequencing errors will increase or decrease classification and profiling performance.Results: We compared performance of popular metagenomic classifiers on short reads and longer reads, which are assembled from the same short reads. When using a number of popular assemblers to assemble long reads from the short reads, we discovered that most classifiers made fewer predictions with longer reads and that they achieved higher classification performance on synthetic metagenomic data. Specifically, across most classifiers, we observed a significant increase in precision, while recall remained the same, resulting in higher overall classification performance. On real metagenomic data, we observed a similar trend that classifiers made fewer predictions. This suggested that they might have the same performance characteristics of having higher precision while maintaining the same recall with longer reads.Conclusions: This finding has two main implications. First, it suggests that classifying species in metagenomic environments can be achieved with higher overall performance simply by assembling short reads. This suggested that they might have the same performance characteristics of having higher precision while maintaining the same recall as shorter reads. Second, this finding suggests that it might be a good idea to consider utilizing long-read technologies in species classification for metagenomic applications. Current long-read technologies tend to have higher sequencing errors and are more expensive compared to short-read technologies. The trade-offs between the pros and cons should be investigated.

scholarly journals Systematic analysis of dark and camouflaged genes: disease-relevant genes hiding in plain sight

2019 ◽  
Author(s):  
Mark T. W. Ebbert ◽  
Tanner D. Jensen ◽  
Karen Jansen-West ◽  
Jonathon P. Sens ◽  
Joseph S. Reddy ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Sequencing Data ◽  
Systematic Analysis ◽  
Protein Coding ◽  
Short Read ◽  
Sequencing Project ◽  
Short Read Sequencing ◽  
Sequencing Technologies ◽  
Long Read

AbstractBackgroundThe human genome contains ‘dark’ gene regions that cannot be adequately assembled or aligned using standard short-read sequencing technologies, preventing researchers from identifying mutations within these gene regions that may be relevant to human disease. Here, we identify regions that are ‘dark by depth’ (few mappable reads) and others that are ‘camouflaged’ (ambiguous alignment), and we assess how well long-read technologies resolve these regions. We further present an algorithm to resolve most camouflaged regions (including in short-read data) and apply it to the Alzheimer’s Disease Sequencing Project (ADSP; 13142 samples), as a proof of principle.ResultsBased on standard whole-genome lllumina sequencing data, we identified 37873 dark regions in 5857 gene bodies (3635 protein-coding) from pathways important to human health, development, and reproduction. Of the 5857 gene bodies, 494 (8.4%) were 100% dark (142 protein-coding) and 2046 (34.9%) were ≥5% dark (628 protein-coding). Exactly 2757 dark regions were in protein-coding exons (CDS) across 744 genes. Long-read sequencing technologies from 10x Genomics, PacBio, and Oxford Nanopore Technologies reduced dark CDS regions to approximately 45.1%, 33.3%, and 18.2% respectively. Applying our algorithm to the ADSP, we rescued 4622 exonic variants from 501 camouflaged genes, including a rare, ten-nucleotide frameshift deletion in CR1, a top Alzheimer’s disease gene, found in only five ADSP cases and zero controls.ConclusionsWhile we could not formally assess the CR1 frameshift mutation in Alzheimer’s disease (insufficient sample-size), we believe it merits investigating in a larger cohort. There remain thousands of potentially important genomic regions overlooked by short-read sequencing that are largely resolved by long-read technologies.

scholarly journals Genome Sequence Resource of Phytophthora colocasiae from China Using Nanopore Sequencing Technology

Plant Disease ◽  
2021 ◽  
Author(s):  
Zhixin Wang ◽  
Jiandong Bao ◽  
Lin Lv ◽  
Lianyu Lin ◽  
Zhiting Li ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Protein Coding ◽  
Short Read ◽  
Rxlr Effectors ◽  
Phytophthora Colocasiae ◽  
Oxford Nanopore ◽  
Long Read ◽  
Infection Mechanisms ◽  
Oomycete Pathogen ◽  
Taro Leaf Blight

Phytophthora colocasiae is a destructive oomycete pathogen of taro (Colocasia esculenta), which causes taro leaf blight. To date, only one highly fragmented Illumina short-read-based genome assembly is available for this species. To address this problem, we sequenced strain Lyd2019 from China using Oxford Nanopore Technologies (ONT) long-read sequencing and Illumina short-read sequencing. We generated a 92.51-Mb genome assembly consisting of 105 contigs with an N50 of 1.70 Mb and a maximum length of 4.17 Mb. In the genome assembly, we identified 52.78% repeats and 18,322 protein-coding genes, of which 12,782 genes were annotated. We also identified 191 candidate RXLR effectors and 1 candidate CRN effectors. The updated near-chromosome genome assembly and annotation resources will provide a better understanding of the infection mechanisms of P. colocasiae.

scholarly journals A hybrid and scalable error correction algorithm for indel and substitution errors of long reads

BMC Genomics ◽  
2019 ◽  
Vol 20 (S11) ◽  
Author(s):  
Arghya Kusum Das ◽  
Sayan Goswami ◽  
Kisung Lee ◽  
Seung-Jong Park
Keyword(s):  
Error Correction ◽  
Error Rates ◽  
De Bruijn Graph ◽  
Correction Algorithm ◽  
Short Read ◽  
Short Reads ◽  
Long Reads ◽  
Long Read ◽  
De Bruijn ◽  
Error Correction Algorithm

Abstract Background Long-read sequencing has shown the promises to overcome the short length limitations of second-generation sequencing by providing more complete assembly. However, the computation of the long sequencing reads is challenged by their higher error rates (e.g., 13% vs. 1%) and higher cost ($0.3 vs. $0.03 per Mbp) compared to the short reads. Methods In this paper, we present a new hybrid error correction tool, called ParLECH (Parallel Long-read Error Correction using Hybrid methodology). The error correction algorithm of ParLECH is distributed in nature and efficiently utilizes the k-mer coverage information of high throughput Illumina short-read sequences to rectify the PacBio long-read sequences.ParLECH first constructs a de Bruijn graph from the short reads, and then replaces the indel error regions of the long reads with their corresponding widest path (or maximum min-coverage path) in the short read-based de Bruijn graph. ParLECH then utilizes the k-mer coverage information of the short reads to divide each long read into a sequence of low and high coverage regions, followed by a majority voting to rectify each substituted error base. Results ParLECH outperforms latest state-of-the-art hybrid error correction methods on real PacBio datasets. Our experimental evaluation results demonstrate that ParLECH can correct large-scale real-world datasets in an accurate and scalable manner. ParLECH can correct the indel errors of human genome PacBio long reads (312 GB) with Illumina short reads (452 GB) in less than 29 h using 128 compute nodes. ParLECH can align more than 92% bases of an E. coli PacBio dataset with the reference genome, proving its accuracy. Conclusion ParLECH can scale to over terabytes of sequencing data using hundreds of computing nodes. The proposed hybrid error correction methodology is novel and rectifies both indel and substitution errors present in the original long reads or newly introduced by the short reads.

scholarly journals Toward perfect reads: self-correction of short reads via mapping on de Bruijn graphs

2019 ◽  
Vol 36 (5) ◽  
pp. 1374-1381 ◽  
Author(s):  
Antoine Limasset ◽  
Jean-François Flot ◽  
Pierre Peterlongo
Keyword(s):  
Supplementary Information ◽  
De Bruijn Graph ◽  
Sequence Information ◽  
Short Read ◽  
De Bruijn Graphs ◽  
Short Reads ◽  
Sequencing Errors ◽  
Long Read ◽  
De Bruijn ◽  
Read Accuracy

Abstract Motivation Short-read accuracy is important for downstream analyses such as genome assembly and hybrid long-read correction. Despite much work on short-read correction, present-day correctors either do not scale well on large datasets or consider reads as mere suites of k-mers, without taking into account their full-length sequence information. Results We propose a new method to correct short reads using de Bruijn graphs and implement it as a tool called Bcool. As a first step, Bcool constructs a compacted de Bruijn graph from the reads. This graph is filtered on the basis of k-mer abundance then of unitig abundance, thereby removing most sequencing errors. The cleaned graph is then used as a reference on which the reads are mapped to correct them. We show that this approach yields more accurate reads than k-mer-spectrum correctors while being scalable to human-size genomic datasets and beyond. Availability and implementation The implementation is open source, available at http://github.com/Malfoy/BCOOL under the Affero GPL license and as a Bioconda package. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Improved Transcriptome Assembly Using a Hybrid of Long and Short Reads with StringTie

2021 ◽  
Author(s):  
Alaina Shumate ◽  
Brandon Wong ◽  
Geo Pertea ◽  
Mihaela Pertea
Keyword(s):  
Rna Sequencing ◽  
Open Source Software ◽  
Transcriptome Assembly ◽  
Simulated Data ◽  
Real Data ◽  
Short Read ◽  
Short Reads ◽  
Long Reads ◽  
Long Read ◽  
Improved Accuracy

Short-read RNA sequencing and long-read RNA sequencing each have their strengths and weaknesses for transcriptome assembly. While short reads are highly accurate, they are unable to span multiple exons. Long-read technology can capture full-length transcripts, but its high error rate often leads to mis-identified splice sites, and its low throughput makes quantification difficult. Here we present a new release of StringTie that performs hybrid-read assembly. By taking advantage of the strengths of both long and short reads, hybrid-read assembly with StringTie is more accurate than long-read only or short-read only assembly, and on some datasets it can more than double the number of correctly assembled transcripts, while obtaining substantially higher precision than the long-read data assembly alone. Here we demonstrate the improved accuracy on simulated data and real data from Arabidopsis thaliana, Mus musculus,and human. We also show that hybrid-read assembly is more accurate than correcting long reads prior to assembly while also being substantially faster. StringTie is freely available as open source software at https://github.com/gpertea/stringtie.

scholarly journals ecc_finder: A Robust and Accurate Tool for Detecting Extrachromosomal Circular DNA From Sequencing Data

2021 ◽  
Vol 12 ◽  
Author(s):  
Panpan Zhang ◽  
Haoran Peng ◽  
Christel Llauro ◽  
Etienne Bucher ◽  
Marie Mirouze
Keyword(s):  
Computational Time ◽  
Rapid Adaptation ◽  
Sequencing Data ◽  
Short Read ◽  
Circular Dna ◽  
Short Reads ◽  
Wide Applicability ◽  
Time Sensitivity ◽  
Bioinformatic Tool ◽  
Long Read

Extrachromosomal circular DNA (eccDNA) has been observed in different species for decades, and more and more evidence shows that this specific type of DNA molecules may play an important role in rapid adaptation. Therefore, characterizing the full landscape of eccDNA has become critical, and there are several protocols for enriching eccDNAs and performing short-read or long-read sequencing. However, there is currently no available bioinformatic tool to identify eccDNAs from Nanopore reads. More importantly, the current tools based on Illumina short reads lack an efficient standardized pipeline notably to identify eccDNA originating from repeated loci and cannot be applied to very large genomes. Here, we introduce a comprehensive tool to solve both of these two issues.1 Applying ecc_finder to eccDNA-seq data (either mobilome-seq, Circle-Seq and CIDER-seq) from Arabidopsis, human, and wheat (with genome sizes ranging from 120Mb to 17 Gb), we document the improvement of computational time, sensitivity, and accuracy and demonstrate ecc_finder wide applicability and functionality.

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