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A novel method for identifying polymorphic transposable elements via scanning of high-throughput short reads.

ABSTRACT: Identification of polymorphic transposable elements (TEs) is important because TE polymorphism creates genetic diversity and influences the function of genes in the host genome. However, de novo scanning of polymorphic TEs remains a challenge. Here, we report a novel computational method, called PTEMD (polymorphic TEs and their movement detection), for de novo discovery of genome-wide polymorphic TEs. PTEMD searches highly identical sequences using reads supported breakpoint evidences. Using PTEMD, we identified 14 polymorphic TE families (905 sequences) in rice blast fungus Magnaporthe oryzae, and 68 (10,618 sequences) in maize. We validated one polymorphic TE family experimentally, MoTE-1; all MoTE-1 family members are located in different genomic loci in the three tested isolates. We found that 57.1% (8 of 14) of the PTEMD-detected polymorphic TE families in M. oryzae are active. Furthermore, our data indicate that there are more polymorphic DNA transposons in maize than their counterparts of retrotransposons despite the fact that retrotransposons occupy largest fraction of genomic mass. We demonstrated that PTEMD is an effective tool for identifying polymorphic TEs in M. oryzae and maize genomes. PTEMD and the genome-wide polymorphic TEs in M. oryzae and maize are publically available at http://www.kanglab.cn/blast/PTEMD_V1.02.htm.

SUBMITTER: Kang H

PROVIDER: S-EPMC4909310 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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A novel method for identifying polymorphic transposable elements via scanning of high-throughput short reads.

Kang Houxiang H Zhu Dan D Lin Runmao R Opiyo Stephen Obol SO Jiang Ning N Shiu Shin-Han SH Wang Guo-Liang GL

DNA research : an international journal for rapid publication of reports on genes and genomes 20160420 3

Identification of polymorphic transposable elements (TEs) is important because TE polymorphism creates genetic diversity and influences the function of genes in the host genome. However, de novo scanning of polymorphic TEs remains a challenge. Here, we report a novel computational method, called PTEMD (polymorphic TEs and their movement detection), for de novo discovery of genome-wide polymorphic TEs. PTEMD searches highly identical sequences using reads supported breakpoint evidences. Using PTE ...[more]

PMID: 27098848

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Project description:BackgroundTransposable elements (TEs) are mobile sequences found in nearly all eukaryotic genomes. They have the ability to move and replicate within a genome, often influencing genome evolution and gene expression. The identification of TEs is an important part of every genome project. The number of sequenced genomes is rapidly rising, and the need to identify TEs within them is also growing. The ability to do this automatically and effectively in a manner similar to the methods used for genes is of increasing importance. There exist many difficulties in identifying TEs, including their tendency to degrade over time and that many do not adhere to a conserved structure. In this work, we describe a homology-based approach for the automatic identification of high-quality consensus TEs, aimed for use in the analysis of newly sequenced genomes.ResultsWe describe a homology-based approach for the automatic identification of TEs in genomes. Our modular approach is dependent on a thorough and high-quality library of representative TEs. The implementation of the approach, named TESeeker, is BLAST-based, but also makes use of the CAP3 assembly program and the ClustalW2 multiple sequence alignment tool, as well as numerous BioPerl scripts. We apply our approach to newly sequenced genomes and successfully identify consensus TEs that are up to 99% identical to manually annotated TEs.ConclusionsWhile TEs are known to be a major force in the evolution of genomes, the automatic identification of TEs in genomes is far from mature. In particular, there is a lack of automated homology-based approaches that produce high-quality TEs. Our approach is able to generate high-quality consensus TE sequences automatically, requiring the user to only provide a few basic parameters. This approach is intentionally modular, allowing researchers to use components separately or iteratively. Our approach is most effective for TEs with intact reading frames. The implementation, TESeeker, is available for download as a virtual appliance, while the library of representative TEs is available as a separate download.

Project description:BackgroundTransposable elements (TEs) are DNA sequences able to mobilize themselves and to increase their copy-number in the host genome. In the past, they have been considered mainly selfish DNA without evident functions. Nevertheless, currently they are believed to have been extensively involved in the evolution of primate genomes, especially from a regulatory perspective. Due to their recent activity they are also one of the primary sources of structural variants (SVs) in the human genome. By taking advantage of sequencing technologies and bioinformatics tools, recent surveys uncovered specific TE structural variants (TEVs) that gave rise to polymorphisms in human populations. When combined with RNA-seq data this information provides the opportunity to study the potential impact of TEs on gene expression in human.ResultsIn this work, we assessed the effects of the presence of specific TEs in cis on the expression of flanking genes by producing associations between polymorphic TEs and flanking gene expression levels in human lymphoblastoid cell lines. By using public data from the 1000 Genome Project and the Geuvadis consortium, we exploited an expression quantitative trait loci (eQTL) approach integrated with additional bioinformatics data mining analyses. We uncovered human loci enriched for common, less common and rare TEVs and identified 323 significant TEV-cis-eQTL associations. SINE-R/VNTR/Alus (SVAs) resulted the TE class with the strongest effects on gene expression. We also unveiled differential functional enrichments on genes associated to TEVs, genes associated to TEV-cis-eQTLs and genes associated to the genomic regions mostly enriched in TEV-cis-eQTLs highlighting, at multiple levels, the impact of TEVs on the host genome. Finally, we also identified polymorphic TEs putatively embedded in transcriptional units, proposing a novel mechanism in which TEVs may mediate individual-specific traits.ConclusionWe contributed to unveiling the effect of polymorphic TEs on transcription in lymphoblastoid cell lines.

Project description:UnlabelledBackgroundThe metagenomics approach allows the simultaneous sequencing of all genomes in an environmental sample. This results in high complexity datasets, where in addition to repeats and sequencing errors, the number of genomes and their abundance ratios are unknown. Recently developed next-generation sequencing (NGS) technologies significantly improve the sequencing efficiency and cost. On the other hand, they result in shorter reads, which makes the separation of reads from different species harder. Among the existing computational tools for metagenomic analysis, there are similarity-based methods that use reference databases to align reads and composition-based methods that use composition patterns (i.e., frequencies of short words or l-mers) to cluster reads. Similarity-based methods are unable to classify reads from unknown species without close references (which constitute the majority of reads). Since composition patterns are preserved only in significantly large fragments, composition-based tools cannot be used for very short reads, which becomes a significant limitation with the development of NGS. A recently proposed algorithm, AbundanceBin, introduced another method that bins reads based on predicted abundances of the genomes sequenced. However, it does not separate reads from genomes of similar abundance levels.ResultsIn this work, we present a two-phase heuristic algorithm for separating short paired-end reads from different genomes in a metagenomic dataset. We use the observation that most of the l-mers belong to unique genomes when l is sufficiently large. The first phase of the algorithm results in clusters of l-mers each of which belongs to one genome. During the second phase, clusters are merged based on l-mer repeat information. These final clusters are used to assign reads. The algorithm could handle very short reads and sequencing errors. It is initially designed for genomes with similar abundance levels and then extended to handle arbitrary abundance ratios. The software can be download for free at http://www.cs.ucr.edu/∼tanaseio/toss.htm.ConclusionsOur tests on a large number of simulated metagenomic datasets concerning species at various phylogenetic distances demonstrate that genomes can be separated if the number of common repeats is smaller than the number of genome-specific repeats. For such genomes, our method can separate NGS reads with a high precision and sensitivity.

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A novel method for identifying polymorphic transposable elements via scanning of high-throughput short reads.

Publications

A novel method for identifying polymorphic transposable elements via scanning of high-throughput short reads.

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