Dataset Information

STEAK: A specific tool for transposable elements and retrovirus detection in high-throughput sequencing data.

ABSTRACT: The advancements of high-throughput genomics have unveiled much about the human genome highlighting the importance of variations between individuals and their contribution to disease. Even though numerous software have been developed to make sense of large genomics datasets, a major short falling of these has been the inability to cope with repetitive regions, specifically to validate structural variants and accordingly assess their role in disease. Here we describe our program STEAK, a massively parallel software designed to detect chimeric reads in high-throughput sequencing data for a broad number of applications such as identifying presence/absence, as well as discovery of transposable elements (TEs), and retroviral integrations. We highlight the capabilities of STEAK by comparing its efficacy in locating HERV-K HML-2 in clinical whole genome projects, target enrichment sequences, and in the 1000 Genomes CEU Trio to the performance of other TE and virus detecting tools. We show that STEAK outperforms other software in terms of computational efficiency, sensitivity, and specificity. We demonstrate that STEAK is a robust tool, which allows analysts to flexibly detect and evaluate TE and retroviral integrations in a diverse range of sequencing projects for both research and clinical purposes.

SUBMITTER: Santander CG

PROVIDER: S-EPMC5597868 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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STEAK: A specific tool for transposable elements and retrovirus detection in high-throughput sequencing data.

Santander Cindy G CG Gambron Philippe P Marchi Emanuele E Karamitros Timokratis T Katzourakis Aris A Magiorkinis Gkikas G

Virus evolution 20170701 2

The advancements of high-throughput genomics have unveiled much about the human genome highlighting the importance of variations between individuals and their contribution to disease. Even though numerous software have been developed to make sense of large genomics datasets, a major short falling of these has been the inability to cope with repetitive regions, specifically to validate structural variants and accordingly assess their role in disease. Here we describe our program <i>STEAK</i>, a m ...[more]

PMID: 28948042

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Project description:Transposables elements (TEs) contribute to both structural and functional dynamics of most eukaryotic genomes. Because of their propensity to densely populate plant and animal genomes, the precise estimation of the impact of transposition on genomic diversity has been considered as one of the main challenges of today's genomics. The recent development of NGS (next generation sequencing) technologies has open new perspectives in population genomics by providing new methods for high throughput detection of Transposable Elements-associated Structural Variants (TEASV). However, these have relied on Illumina platform that generates short reads (up to 350 nucleotides). This limitation in size of sequence reads can cause high false discovery rate (FDR) and therefore limit the power of detection of TEASVs, especially in the case of large, complex genomes. The newest sequencing technologies, such as Oxford Nanopore Technologies (ONT) can generate kilobases-long reads thus representing a promising tool for TEASV detection in plant and animals.We present the results of a pilot experiment for TEASV detection on the model plant species Arabidopsis thaliana using ONT sequencing and show that it can be used efficiently to detect TE movements. We generated a ~0.8X genome coverage of a met1-derived epigenetic recombinant inbred line (epiRIL) using a MinIon device with R7 chemistry. We were able to detect nine new copies of the LTR-retrotransposon Evadé (EVD). We also evidenced the activity of the DNA transposon CACTA, CAC1.Even at a low sequence coverage (0.8X), ONT sequencing allowed us to reliably detect several TE insertions in Arabidopsis thaliana genome. The long read length allowed a precise and un-ambiguous mapping of the structural variations caused by the activity of TEs. This suggests that the trade-off between read length and genome coverage for TEASV detection may be in favor of the former. Should the technology be further improved both in terms of lower error rate and operation costs, it could be efficiently used in diversity studies at population level.

Project description:BackgroundDespite the advent of Chromatin Immunoprecipitation Sequencing (ChIP-seq) having revolutionised our understanding of the mammalian genome's regulatory landscape, many challenges remain. In particular, because of their repetitive nature, the sequencing reads derived from transposable elements (TEs) pose a real bioinformatics challenge, to the point that standard analysis pipelines typically ignore reads whose genomic origin cannot be unambiguously ascertained.ResultsWe show that discarding ambiguously mapping reads may lead to a systematic underestimation of the number of reads associated with young TE families/subfamilies. We also provide evidence suggesting that the strategy of randomly permuting the location of the read mappings (or the TEs) that is often used to compute the background for enrichment calculations at TE families/subfamilies can result in both false positive and negative enrichments. To address these problems, we present the Transposable Element Enrichment Estimator (T3E), a tool that makes use of ChIP-seq data to characterise the epigenetic profile of associated TE families/subfamilies. T3E weights the number of read mappings assigned to the individual TE copies of a family/subfamily by the overall number of genomic loci to which the corresponding reads map, and this is done at the single nucleotide level. In addition, T3E computes ChIP-seq enrichment relative to a background estimated based on the distribution of the read mappings in the input control DNA. We demonstrated the capabilities of T3E on 23 different ChIP-seq libraries. T3E identified enrichments that were consistent with previous studies. Furthermore, T3E detected context-specific enrichments that are likely to pinpoint unexplored TE families/subfamilies with individual TE copies that have been frequently exapted as cis-regulatory elements during the evolution of mammalian regulatory networks.ConclusionsT3E is a novel open-source computational tool (available for use at: https://github.com/michelleapaz/T3E ) that overcomes some of the pitfalls associated with the analysis of ChIP-seq data arising from the repetitive mammalian genome and provides a framework to shed light on the epigenetics of entire TE families/subfamilies.

Dataset Information

STEAK: A specific tool for transposable elements and retrovirus detection in high-throughput sequencing data.

Publications

STEAK: A specific tool for transposable elements and retrovirus detection in high-throughput sequencing data.

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