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 ◽  
...  

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.

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Chong Chu ◽  
Rebeca Borges-Monroy ◽  
Vinayak V. Viswanadham ◽  
Soohyun Lee ◽  
Heng Li ◽  
...  

AbstractTransposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea.


2020 ◽  
Author(s):  
Andrew J. Page ◽  
Nabil-Fareed Alikhan ◽  
Michael Strinden ◽  
Thanh Le Viet ◽  
Timofey Skvortsov

AbstractSpoligotyping of Mycobacterium tuberculosis provides a subspecies classification of this major human pathogen. Spoligotypes can be predicted from short read genome sequencing data; however, no methods exist for long read sequence data such as from Nanopore or PacBio. We present a novel software package Galru, which can rapidly detect the spoligotype of a Mycobacterium tuberculosis sample from as little as a single uncorrected long read. It allows for near real-time spoligotyping from long read data as it is being sequenced, giving rapid sample typing. We compare it to the existing state of the art software and find it performs identically to the results obtained from short read sequencing data. Galru is freely available from https://github.com/quadram-institute-bioscience/galru under the GPLv3 open source licence.


Cells ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1776
Author(s):  
Mourdas Mohamed ◽  
Nguyet Thi-Minh Dang ◽  
Yuki Ogyama ◽  
Nelly Burlet ◽  
Bruno Mugat ◽  
...  

Transposable elements (TEs) are the main components of genomes. However, due to their repetitive nature, they are very difficult to study using data obtained with short-read sequencing technologies. Here, we describe an efficient pipeline to accurately recover TE insertion (TEI) sites and sequences from long reads obtained by Oxford Nanopore Technology (ONT) sequencing. With this pipeline, we could precisely describe the landscapes of the most recent TEIs in wild-type strains of Drosophila melanogaster and Drosophila simulans. Their comparison suggests that this subset of TE sequences is more similar than previously thought in these two species. The chromosome assemblies obtained using this pipeline also allowed recovering piRNA cluster sequences, which was impossible using short-read sequencing. Finally, we used our pipeline to analyze ONT sequencing data from a D. melanogaster unstable line in which LTR transposition was derepressed for 73 successive generations. We could rely on single reads to identify new insertions with intact target site duplications. Moreover, the detailed analysis of TEIs in the wild-type strains and the unstable line did not support the trap model claiming that piRNA clusters are hotspots of TE insertions.


2019 ◽  
Vol 8 (34) ◽  
Author(s):  
Natsuki Tomariguchi ◽  
Kentaro Miyazaki

Rubrobacter xylanophilus strain AA3-22, belonging to the phylum Actinobacteria, was isolated from nonvolcanic Arima Onsen (hot spring) in Japan. Here, we report the complete genome sequence of this organism, which was obtained by combining Oxford Nanopore long-read and Illumina short-read sequencing data.


2017 ◽  
Author(s):  
Jia-Xing Yue ◽  
Gianni Liti

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.


2018 ◽  
Author(s):  
Li Fang ◽  
Charlly Kao ◽  
Michael V Gonzalez ◽  
Fernanda A Mafra ◽  
Renata Pellegrino da Silva ◽  
...  

AbstractLinked-read sequencing provides long-range information on short-read sequencing data by barcoding reads originating from the same DNA molecule, and can improve the detection and breakpoint identification for structural variants (SVs). We present LinkedSV for SV detection on linked-read sequencing data. LinkedSV considers barcode overlapping and enriched fragment endpoints as signals to detect large SVs, while it leverages read depth, paired-end signals and local assembly to detect small SVs. Benchmarking studies demonstrates that LinkedSV outperforms existing tools, especially on exome data and on somatic SVs with low variant allele frequencies. We demonstrate clinical cases where LinkedSV identifies disease causal SVs from linked-read exome sequencing data missed by conventional exome sequencing, and show examples where LinkedSV identifies SVs missed by high-coverage long-read sequencing. In summary, LinkedSV can detect SVs missed by conventional short-read and long-read sequencing approaches, and may resolve negative cases from clinical genome/exome sequencing studies.


2018 ◽  
Author(s):  
Mark T. W. Ebbert ◽  
Stefan Farrugia ◽  
Jonathon Sens ◽  
Karen Jansen-West ◽  
Tania F. Gendron ◽  
...  

AbstractBackground: Many neurodegenerative diseases are caused by nucleotide repeat expansions, but most expansions, like the C9orf72 ‘GGGGCC’ (G4C2) repeat that causes approximately 5-7% of all amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases, are too long to sequence using short-read sequencing technologies. It is unclear whether long-read sequencing technologies can traverse these long, challenging repeat expansions. Here, we demonstrate that two long-read sequencing technologies, Pacific Biosciences’ (PacBio) and Oxford Nanopore Technologies’ (ONT), can sequence through disease-causing repeats cloned into plasmids, including the FTD/ALS-causing G4C2 repeat expansion. We also report the first long-read sequencing data characterizing the C9orf72 G4C2 repeat expansion at the nucleotide level in two symptomatic expansion carriers using PacBio whole-genome sequencing and a no-amplification (No-Amp) targeted approach based on CRISPR/Cas9.Results: Both the PacBio and ONT platforms successfully sequenced through the repeat expansions in plasmids. Throughput on the MinlON was a challenge for whole-genome sequencing; we were unable to attain reads covering the human C9orf72 repeat expansion using 15 flow cells. We obtained 8x coverage across the C9orf72 locus using the PacBio Sequel, accurately reporting the unexpanded allele at eight repeats, and reading through the entire expansion with 1324 repeats (7941 nucleotides). Using the No-Amp targeted approach, we attained >800x coverage and were able to identify the unexpanded allele, closely estimate expansion size, and assess nucleotide content in a single experiment. We estimate the individual’s repeat region was >99% G4C2 content, though we cannot rule out small interruptions.Conclusions: Our findings indicate that long-read sequencing is well suited to characterizing known repeat expansions, and for discovering new disease-causing, disease-modifying, or risk-modifying repeat expansions that have gone undetected with conventional short-read sequencing. The PacBio No-Amp targeted approach may have future potential in clinical and genetic counseling environments. Larger and deeper long-read sequencing studies in C9orf72 expansion carriers will be important to determine heterogeneity and whether the repeats are interrupted by non-G4C2 content, potentially mitigating or modifying disease course or age of onset, as interruptions are known to do in other repeat-expansion disorders. These results have broad implications across all diseases where the genetic etiology remains unclear.


2021 ◽  
Author(s):  
Peipei Wang ◽  
Fanrui Meng ◽  
Bethany M. Moore ◽  
Shin-Han Shiu

Abstract Background: Availability of plant genome sequences has led to significant advances. However, with few exceptions, the great majority of existing genome assemblies are derived from short read sequencing technologies with highly uneven read coverages indicative of sequencing and assembly issues that could significantly impact any downstream analysis of plant genomes. In tomato for example, 0.6% (5.1 Mb) and 9.7% (79.6 Mb) of short-read based assembly had significantly higher and lower coverage compared to background, respectively.Results: To understand what the causes may be for such uneven coverage, we first established machine learning models capable of predicting genomic regions with variable coverages and found that high coverage regions tend to have higher simple sequence repeat and tandem gene densities compared to background regions. To determine if the high coverage regions were misassembled, we examined a recently available tomato long-read based assembly and found that 27.8% (1.41 Mb) of high coverage regions were potentially misassembled of duplicate sequences, compared to 1.4% in background regions. In addition, using a predictive model that can distinguish correctly and incorrectly assembled high coverage regions, we found that misassembled, high coverage regions tend to be flanked by simple sequence repeats, pseudogenes, and transposon elements. Conclusions: Our study provides insights on the causes of variable coverage regions and a quantitative assessment of factors contributing to plant genome misassembly when using short reads.


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