Transposable elements (TEs) are structural variants considered an important source of genetic diversity, which may arise in the transcriptome when TEs are transcribed in the same RNA molecule as genes, producing what we hereafter call chimeric transcripts. The presence of chimeric transcripts has been associated with adaptive traits in several species, but their identification remains hindered due to the lack of tools to detect them on a transcriptome-wide scale. Previous bioinformatics tools were developed to identify chimeric transcripts derived from TEs present in a reference genome. Nevertheless, different individuals/cells/strains might harbor different TE insertions generating such chimeric transcripts. Therefore, we have developed ChimeraTE, a pipeline that uses paired-end RNA-seq reads to identify chimeric transcripts with or without a reference genome, in a transcriptome-wide manner. ChimeraTE has two Modes: Mode 1 is a genome-guided approach that employs the canonical method of genome alignment, whereas Mode 2 identifies chimeric transcripts without a reference genome, being able to predict chimeras derived from fixed or polymorphic TEs. We have used both Modes with Illumina RNA-seq reads from ovarian tissues of Drosophila melanogaster wild-type strains, and found that ~3% of all genes generate chimeric transcripts. Approximately ~9% of all detected chimeras were absent from the D. melanogaster′s reference genome, corresponding to polymorphic insertions in the wild-type strains. ChimeraTE is the first pipeline with the ability to automatically uncover chimeric transcripts without a reference genome.
Herbivore diets are often generalistic, and communities of herbivores tend to share much of their diets. In the tropical lowlands of Malaysian Borneo, tens of different noncarnivorous land snail species are able to coexist in communities on limestone outcrops. We tried to answer the question whether diet differentiation plays a role in their coexistence. We show, with a large metabarcoding study of the plant diet from gut contents of 658 individual snails (from 26 species, with a focus on three of the most common species in the region), that the different snail species indeed share much of their plant diet, but that mean diet richness varies strongly among species (up to 15.3×). These differences are mostly explained by snail size, with larger snails having wider diets. Furthermore, phylogenetic analyses of the plant diet by individual snails showed signs of clustering in c. 28% of the individuals, possibly suggesting phylogenetic specialization, although such clustering was weak when diets were considered by species. We discuss how observed trends in diet richness and diet clustering could also be explained by random feeding, with larger species simply eating more or less specifically, and by other, noncompetitive interactions, such as snails avoiding desiccation. Our study shows how to efficiently put the power of metabarcoding to work in unravelling the complex community processes commonly encountered in tropical ecosystems and is thus of substantial relevance to both community ecologists and conservationists.
Classical ecological theory posits that species partition resources such that each species occupies a unique resource niche. In general, the availability of more resources allows more species to co‐occur. Thus, a strong relationship between communities of consumers and their resources is expected. However, correlations may be influenced by other layers in the food web, or by the environment. Here we show, by studying the relationship between communities of consumers (land snails) and individual diets (from seed plants), that there is in fact no direct, or at most a weak but negative, relationship. However, we found that the diversity of the individual microbiome positively correlates with both consumer community diversity and individual diet diversity in three target species. Moreover, these correlations were affected by various environmental variables, such as anthropogenic activity, habitat island size, and a possibly important nutrient source, guano runoff from nearby caves. Our results suggest that the microbiome and the environment explain the absence of correlations between diet and consumer community diversity. Hence, we advocate that microbiome inventories are routinely added to any community dietary analysis, which our study shows can be done with relatively little extra effort. Our approach presents the tools to quickly obtain an overview of the relationships between consumers and their resources. We anticipate our approach to be useful for ecologists and environmentalists studying different communities in a local food web.
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