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The scuttle flies (Diptera: Phoridae) of Iran with the description of Mahabadphora aesthesphora as a new genus and species.

Roya Namaki-KhamenehSamad KhaghaniniaR Henry L DisneyNaseh Maleki-Ravasan
Published in: PloS one (2021)
Scuttle flies (Diptera: Phoridae) are mega-diverse and often synanthropic insects that play superb roles in various ecosystems. Identification of this group of insects is challenging due to their small size, morphological identification difficulties, niche diversity, and lack of taxonomic keys. To pave the way, an in-depth investigation was directed toward the scuttle flies in Iran using morphological and molecular data. A dichotomous key was also developed to identify the genus and species of the phorids reported in the country. The faunistic findings revealed the presence of about 22,000 (13,903 male and 8,097 female) phorid materials organized into 11 genera. Megaselia species (n = 13768), made up about 99% of the specimens studied. Moreover, 71 morphologically defined species belonging to nine genera were molecularly characterized using COI, 28S rRNA, and Arginine kinase datasets. Excluding four Megaselia Rondani, 1856 species, our results specified that morphologically delimited species were in agreement with the molecular analyses inferred from the COI/28S rRNA and COI/Arginine kinase sequences with genetic distances and phylogenetic trees. According to the results of the present study and previously published data, the Phoridae recorded for Iran are a total of 97 species that are ordered in 13 genera and three subfamilies, including Chonocephalinae, Metopininae and Phorinae. By comparing the known world phorid genera, a new monotypic genus of scuttle flies, Mahabadphora aesthesphora gen. nov., sp. nov., was identified based on its morphological and molecular characteristics and included in an updated key. Our results could comprehensively determine the taxonomic status of scuttle flies in Iran, scrutinize their phylogenetic structures and facilitate their identification.
Keyphrases
  • genetic diversity
  • nitric oxide
  • climate change
  • drosophila melanogaster
  • single cell
  • mass spectrometry
  • deep learning
  • protein kinase
  • bioinformatics analysis
  • artificial intelligence