Molecular Ecology ResourcesGenomicsPeer-reviewed journal article
Generating high quality assemblies for genomic analysis of transposable elements
Filip WierzbickiiD, Florian SchwarziD, Odontsetseg Cannalonga, Robert KofleriD
Abstract
The advent of long-read sequencing holds great promise for research on transposable elements (TEs). Long reads may finally allow us to obtain reliable assemblies of repetitive regions, and thus shed light on many open questions in TE biology, such as the evolution of piRNA clusters, i.e., the master loci controlling TE activity. Currently, many different assembly strategies exist and it is not clear how to obtain the most suitable assemblies for TE research. In fact, it is not even clear how to best identify suitable assemblies as classic quality metrics such as BUSCO and NG50 are ignorant of TEs. To address these problems, we introduce four novel quality metrics that assess i) how well piRNA clusters are assembled (CUSCO) and ii) to which extent an assembly captures the TE landscape of an organism (TE abundance, SNPs and internal deletions). Using these novel metrics, we evaluate the effect of assemblers, polishing, read length, coverage, residual polymorphisms, and finally, identify suitable assembly strategies. Using an optimized approach, we provide high-quality assemblies for the two Drosophila melanogaster strains Canton-S and Pi2. Around 80% of the piRNA clusters were contiguously assembled in these two strains. Such high-quality assemblies will provide novel insights into the biology of TEs. It is, for example, an open question of whether piRNA clusters contain abundant presence/absence polymorphism of TE insertions, as expected when piRNA clusters are responsible for stopping TE invasions. A comparison of the sequences of our assembled piRNA clusters reveals that such polymorphisms are indeed abundantly found in clusters.
- organism: Drosophila
- assay: whole-genome sequencing
- research focus: genome assembly
- approach: statistical model
- Citations
- 27
- FWCI
- 1.65
- Field percentile
- top 15%
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