Dataset Information

Support for multiple classes of local expression clusters in Drosophila melanogaster, but no evidence for gene order conservation.

ABSTRACT:

Background

Gene order in eukaryotic genomes is not random, with genes with similar expression profiles tending to cluster. In yeasts, the model taxon for gene order analysis, such syntenic clusters of non-homologous genes tend to be conserved over evolutionary time. Whether similar clusters show gene order conservation in other lineages is, however, undecided. Here, we examine this issue in Drosophila melanogaster using high-resolution chromosome rearrangement data.

Results

We show that D. melanogaster has at least three classes of expression clusters: first, as observed in mammals, large clusters of functionally unrelated housekeeping genes; second, small clusters of functionally related highly co-expressed genes; and finally, as previously defined by Spellman and Rubin, larger domains of co-expressed but functionally unrelated genes. The latter are, however, not independent of the small co-expression clusters and likely reflect a methodological artifact. While the small co-expression and housekeeping/essential gene clusters resemble those observed in yeast, in contrast to yeast, we see no evidence that any of the three cluster types are preserved as synteny blocks. If anything, adjacent co-expressed genes are more likely to become rearranged than expected. Again in contrast to yeast, in D. melanogaster, gene pairs with short intergene distance or in divergent orientations tend to have higher rearrangement rates. These findings are consistent with co-expression being partly due to shared chromatin environment.

Conclusions

We conclude that, while similar in terms of cluster types, gene order evolution has strikingly different patterns in yeasts and in D. melanogaster, although recombination is associated with gene order rearrangement in both.

SUBMITTER: Weber CC

PROVIDER: S-EPMC3129673 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Publications

Support for multiple classes of local expression clusters in Drosophila melanogaster, but no evidence for gene order conservation.

Weber Claudia C CC Hurst Laurence D LD

Genome biology 20110317 3

<h4>Background</h4>Gene order in eukaryotic genomes is not random, with genes with similar expression profiles tending to cluster. In yeasts, the model taxon for gene order analysis, such syntenic clusters of non-homologous genes tend to be conserved over evolutionary time. Whether similar clusters show gene order conservation in other lineages is, however, undecided. Here, we examine this issue in Drosophila melanogaster using high-resolution chromosome rearrangement data.<h4>Results</h4>We sho ...[more]

PMID: 21414197

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Project description:Animal genomes are parasitized by a horde of transposable elements (TEs) whose mutagenic activity can have catastrophic consequences. The piRNA pathway is a conserved mechanism to repress TE activity in the germline via a specialized class of small RNAs associated with effector Piwi proteins called piwi-associated RNAs (piRNAs). piRNAs are produced from discrete genomic regions called piRNA clusters (piCs). While piCs are generally enriched for TE sequences and the molecular processes by which they are transcribed and regulated are relatively well understood in Drosophila melanogaster , much less is known about the origin and evolution of piCs in this or any other species. To investigate piC evolution, we use a population genomics approach to compare piC activity and sequence composition across 8 geographically distant strains of D. melanogaster with high quality long-read genome assemblies. We perform extensive annotations of ovary piCs and TE content in each strain and test predictions of two proposed models of piC evolution. The 'de novo' model posits that individual TE insertions can spontaneously attain the status of a small piC to generate piRNAs silencing the entire TE family. The 'trap' model envisions large and evolutionary stable genomic clusters where TEs tend to accumulate and serves as a long-term "memory" of ancient TE invasions and produce a great variety of piRNAs protecting against related TEs entering the genome. It remains unclear which model best describes the evolution of piCs. Our analysis uncovers extensive variation in piC activity across strains and signatures of rapid birth and death of piCs in natural populations. Most TE families inferred to be recently or currently active show an enrichment of strain-specific insertions into large piCs, consistent with the trap model. By contrast, only a small subset of active LTR retrotransposon families is enriched for the formation of strain-specific piCs, suggesting that these families have an inherent proclivity to form de novo piCs. Thus, our findings support aspects of both 'de novo' and 'trap' models of piC evolution. We propose that these two models represent two extreme stages along an evolutionary continuum, which begins with the emergence of piCs de novo from a few specific LTR retrotransposon insertions that subsequently expand by accretion of other TE insertions during evolution to form larger 'trap' clusters. Our study shows that piCs are evolutionarily labile and that TEs themselves are the major force driving the formation and evolution of piCs.

Project description:BACKGROUND:While the genomes of hundreds of organisms have been sequenced and good approaches exist for finding protein encoding genes, an important remaining challenge is predicting the functions of the large fraction of genes for which there is no annotation. Large gene expression datasets from microarray experiments already exist and many of these can be used to help assign potential functions to these genes. We have applied Support Vector Machines (SVM), a sigmoid fitting function and a stratified cross-validation approach to analyze a large microarray experiment dataset from Drosophila melanogaster in order to predict possible functions for previously un-annotated genes. A total of approximately 5043 different genes, or about one-third of the predicted genes in the D. melanogaster genome, are represented in the dataset and 1854 (or 37%) of these genes are un-annotated. RESULTS:39 Gene Ontology Biological Process (GO-BP) categories were found with precision value equal or larger than 0.75, when recall was fixed at the 0.4 level. For two of those categories, we have provided additional support for assigning given genes to the category by showing that the majority of transcripts for the genes belonging in a given category have a similar localization pattern during embryogenesis. Additionally, by assessing the predictions using a confidence score, we have been able to provide a putative GO-BP term for 1422 previously un-annotated genes or about 77% of the un-annotated genes represented on the microarray and about 19% of all of the un-annotated genes in the D. melanogaster genome. CONCLUSIONS:Our study successfully employs a number of SVM classifiers, accompanied by detailed calibration and validation techniques, to generate a number of predictions for new annotations for D. melanogaster genes. The applied probabilistic analysis to SVM output improves the interpretability of the prediction results and the objectivity of the validation procedure.

Dataset Information

Support for multiple classes of local expression clusters in Drosophila melanogaster, but no evidence for gene order conservation.

Background

Results

Conclusions

Publications

Support for multiple classes of local expression clusters in Drosophila melanogaster, but no evidence for gene order conservation.

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