No budget mitogenomics: Assembling 14 new mitogenomes for the ant subfamily Pseudomyrmecinae from public data

Abstract

The advent of Next Generation Sequencing has reduced sequencing costs and increased genomic projects from a huge amount of organismal taxa, generating an unprecedented amount of genomic datasets publicly available. Often, only a tiny fraction of outstanding relevance of the genome data produced by researchers is used in their works. This fact allows the data generated to be recycled in further projects worldwide. The assembly of complete mitogenomes is frequently overlooked though it is useful to understand evolutionary relationships among taxa, especially those presenting poor mtDNA sampling at the level of genera and families. This is exactly the case for ants (Hymenoptera:Formicidae) and more specifically for the subfamily Pseudomyrmecinae, a group of arboreal ants with several cases of convergent coevolution without any complete mitochondrial sequence available. In this work, we assembled, annotated and performed comparative genomics analyses of 14 new complete mitochondria from Pseudomyrmecinae species relying solely on public datasets available from the Sequence Read Archive (SRA). We used all complete mitogenomes available for ants to study the gene order conservation and also to generate two phylogenetic trees using both (i) concatenated set of 13 mitochondrial genes and (ii) the whole mitochondrial sequences. Even though the tree topologies diverged subtly from each other (and from previous studies), our results confirm several known relationships and generate new evidences for sister clade classification inside Pseudomyrmecinae clade. We also performed a synteny analysis for Formcidae and identified possible sites in which nucleotidic insertions happened in mitogenomes of pseudomyrmecine ants. Using a data mining/bioinformatics approach, the current work increased the number of complete mitochondrial genomes available for ants from 15 to 29, demonstrating the unique potential of public databases for mitogenomics studies. The wide applications of mitogenomes in research and presence of mitochondrial data in different public dataset types makes the “no budget mitogenomics” approach ideal for comprehensive molecular studies, especially for subsampled taxa.