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Microsatellites are short, repetitive DNA sequences that can rapidly expand and contract due to slippage during DNA replication. Despite their impacts on transcription, genome structure, and disease, relatively little is known about the evolutionary dynamics of these short sequences across long evolutionary periods. To address this gap in our knowledge, we performed comparative analyses of 304 available insect genomes. We investigated the impact of sequence assembly methods and assembly quality on the inference of microsatellite content, and we explored the influence of chromosome type and number on the tempo and mode of microsatellite evolution across one of the most speciose clades on the planet. Diploid chromosome number had no impact on the rate of microsatellite evolution or the amount of microsatellite content in genomes. We found that centromere type (holocentric or monocentric) is not associated with a difference in the amount of microsatellite content; however, in those species with monocentric chromosomes, microsatellite content tends to evolve faster than in species with holocentric chromosomes.

Microsatellites are repetitive DNA sequences usually found in non-coding regions of the genome. Their quantification and analysis have applications in fields from population genetics to evolutionary biology. As genome assemblies become commonplace, the need for software that can facilitate analyses has never been greater. In particular, R packages that can analyze genomic data are particularly important since this is one of the most popular software environments for biologists. We created an R package, micRocounter, to quantify microsatellites. We have optimized our package for speed, accessibility, and portability, making the automated analysis of large genomic data sets feasible. Computationally intensive algorithms were built in C++ to increase speed. Tests using benchmark datasets show a 200-fold improvement in speed over existing software. A moderately sized genome of 500 Mb can be processed in under 50 sec. Results are output as an object in R increasing accessibility and flexibility for practitioners.

Stenotrophomonas maltophilia is an opportunistic bacterium that is commonly associated with respiratory infections in immunocompromised patients, including cystic fibrosis patients. In this report, we introduce the complete genome sequence of S. maltophilia podophage Pepon, which is a T7-like phage closely related to the previously reported phage Ponderosa.

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