Abstract
Repeat elements are important components of eukaryotic genomes. One limitation in our understanding of repeat elements is that most analyses rely on reference genomes that are incomplete and often contain missing data in highly repetitive regions that are difficult to assemble. To overcome this problem we develop a new method, REPdenovo, which assembles repeat sequences directly from raw shotgun sequencing data. REPdenovo can construct various types of repeats that are highly repetitive and have low sequence divergence within copies. We show that REPdenovo is substantially better than existing methods both in terms of the number and the completeness of the repeat sequences that it recovers. The key advantage of REPdenovo is that it can reconstruct long repeats from sequence reads. We apply the method to human data and discover a number of potentially new repeats sequences that have been missed by previous repeat annotations. Many of these sequences are incorporated into various parasite genomes, possibly because the filtering process for host DNA involved in the sequencing of the parasite genomes failed to exclude the host derived repeat sequences. REPdenovo is a new powerful computational tool for annotating genomes and for addressing questions regarding the evolution of repeat families. The software tool, REPdenovo, is available for download at https://github.com/Reedwarbler/REPdenovo.
Highlights
IntroductionIn particular mammalian genomes, consist of large amounts of repeat elements
Most genomes, and in particular mammalian genomes, consist of large amounts of repeat elements
By comparing with repeat annotations stored in existing repeat libraries and latest long human sequence reads, we identify and validate a set of potentially novel repeats in the human genome that are not included in existing repeat annotations
Summary
In particular mammalian genomes, consist of large amounts of repeat elements. Transposable elements (TEs) are perhaps the most well-known. They are believed to constitute 25% to 40% of most mammalian genomes [2,3,4,5] and can amplify themselves in the genome using various mechanisms, typically involving RNA intermediates. There are several existing computational approaches for finding TEs from short sequence reads [13, 14]. The method in [14] assumes a reference genome is available, and finds repeats from sequence reads using the reference. One can use short reads to assemble a reference genome. Repetitive regions are usually more difficult to assemble This leads to reduced power for repeat analysis if one uses the assembled reference genome for the purpose of repeat finding
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