Microbiota composition data of imago and larval stage of the anhydrobiotic midge.

The ability of larvae of a non-biting midge (Chironomidae) to withstand complete desiccation is a remarkable natural example of adaptation to extreme environment. In anhydrobiosis the larvae lose up to 99.2% of water and stay in a dry form until rainfall in natural environment or up to several decades in laboratory maintaining ability to restore activity soon after rehydration [1]. In the desiccated state, the larvae tolerate a variety of abiotic stresses, including high radiation exposure (7000Gry of Co gamma rays) [2]. Such a cross-resistance to desiccation and ionizing radiation is a characteristic of many anhydrobiotic organisms and believed to be based on similar molecular mechanisms. Microorganisms associated with the anhydrobiotic midge can also sustain desiccation and thus be radiation-resistant because desiccation-resistant prokaryotes are shown to be cross-resistant to ionizing radiation [3]. Microorganisms inhabiting larvae of the anhydrobiotic midge can also sustain desiccation and probably can sustain high doses of ionizing radiation. Therefore, it would be of interest to analyze the taxonomic and functional composition of microbiome of the anhydrobiotic midge. Sequencing data for the total DNA of anhydrobiotic organisms, which also contain reads derived from symbiotic microorganisms provide a promising opportunity to identify microorganisms with remarkable adaptation. It is known that at least some protective genes, such as late embryogenesis abundant (LEA) genes appeared in the genome of the midge by probable horizontal gene transfer from bacteria [1]. We performed shotgun sequencing of imago and larvae DNA samples using HiSeq 2000 and Genome Analyzer IIX System platforms. To assess microbiome diversity specific to anhydrobiotic midges, we analyzed Pool-seq data of the natural population of imago and Pool-seq data of final instar larvae. Data has been deposited in NCBI BioProject repository at NCBI under the accession number PRJNA659554 and consists of raw sequence data.