Nelson, M. G. | Search bioRxiv

bioRxiv2017

Genomic analysis of P elements in natural populations of Drosophila melanogaster

The Drosophila melanogaster P transposable element provides one of the best cases of horizontal transfer of a mobile DNA sequence in eukaryotes. Invasion of natural populations by the P element has led to a syndrome of phenotypes known as P-M hybrid dysgenesis that emerges when strains differing in their P element composition mate and produce offspring. Despite extensive research on many aspects of P element biology, many questions remain about the genomic basis of variation in P-M dysgenesis phenotypes in natural populations. Here we compare gonadal dysgenesis phenotypes and genomic P element predictions for isofemale strains obtained from three worldwide populations of D. melanogaster to illuminate the molecular basis of natural variation in cytotype status. We show that the number of predicted P element insertions in genome sequences from isofemale strains is highly correlated across different bioinformatics methods, but the absolute number of insertions per strain is sensitive to method and filtering strategies. Regardless of method used, we find that the number of euchromatic P element insertions predicted per strain varies significantly across populations, with strains from a North American population having fewer P element insertions than strains from populations sampled in Europe or Africa. Despite these geographic differences, numbers of euchromatic P element insertions are not strongly correlated with the degree of gonadal dysgenesis exhibited by an isofemale strain. Thus, variation in P element insertion numbers across different populations does not necessarily lead to corresponding geographic differences in gonadal dysgenesis phenotypes. Additionally, we show that pool-seq samples can uncover population differences in the number of P element insertions observed from isofemale lines, but that efforts to rigorously detect differences in the number of P elements across populations using pool-seq data must properly control for read depth per strain. Our work supports the view that euchromatic P element copy number is not sufficient to explain variation in gonadal dysgenesis across strains of D. melanogaster, and informs future efforts to decode the genomic basis of geographic and temporal differences in P element induced phenotypes.

genomics↗

bioRxiv2016

McClintock: An integrated pipeline for detecting transposable element insertions in whole genome shotgun sequencing data.

BackgroundTransposable element (TE) insertions are among the most challenging type of variants to detect in genomic data because of their repetitive nature and complex mechanisms of replication. Nevertheless, the recent availability of large resequencing datasets has spurred the development of many new methods to detect TE insertions in whole genome shotgun sequences. These methods generate output in diverse formats and have a large number of software and data dependencies, making their comparative evaluation challenging for potential users.\n\nResultsHere we develop an integrated bioinformatics pipeline for the detection of TE insertions in whole genome shotgun data, called McClintock (https://github.com/bergmanlab/mcclintock), that automatically runs and generates standardized output for multiple TE detection methods. We demonstrate the utility of the McClintock system by performing comparative evaluation of six TE detection methods using simulated and real genome data from the model microbal eukaryote, Saccharomyces cerevisiae. We find substantial variation among McClintock component methods in their ability to detect non-reference insertions in the yeast genome, but show that non-reference TEs at nearly all biologically-realistic locations can be detected in simulated data by combining multiple methods that use split-read and read-pair evidence. In general, our results reveal that split-read methods detect fewer non-reference TE insertions than read-pair methods, but generally have much higher positional accuracy. Analysis of a large sample of real yeast genomes reveals that most, but not all, McClintock component methods can recover known aspects of TE biology in yeast such as the transpositional activity status of families, tRNA gene target preferences, and target site duplication structure, albeit with varying levels of positional accuracy.\n\nConclusionsOur results suggest that no single TE detection method currently provides comprehensive detection of non-reference TEs, even in the context of a simplified model eukaryotic genome like S. cerevisiae. In spite of these limitations, the McClintock system provides a framework for testing, developing and integrating results from multiple TE detection methods to achieve this ultimate aim, as well as useful guidance for yeast researchers to select appropriate TE detection tools.

bioinformatics↗