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Molecular and morphological evidence of a new species of Crassicutis Manter 1936 (Digenea), a parasite of cichlids in South America.

Camila PantojaTomás ScholzJosé Luis LuqueGerardo Pérez-Ponce de León
Published in: Parasitology research (2021)
A new species of Crassicutis Manter, 1936 (Digenea: Megaperidae) is described from the intestine of Satanoperca jurupari (Cichlidae) in the Amazon River basin, Brazil. The genus Crassicutis currently contains eight species. Crassicutis manteri n. sp. is morphologically very similar to Crassicutis cichlasomae Manter, 1936, a parasite of cichlids reported from Mexico, the Antilles, and Central and South America. Molecular data revealed that C. cichlasomae represents a species complex in Middle American cichlids. The new species can be readily distinguished from C. cichlasomae sensu lato, and the other congeners, by a combination of morphological traits such as a narrow, elongate mouth opening (versus spherical in other species), the tandem position of testes (symmetrical or oblique in most congeners), narrow body widening towards its posterior end (versus widely oval, leaf-like in other species), and short intestinal caeca ending close to the posterior end of the posterior testis (versus reaching more posteriorly in other species). Six novel sequences of 28S rDNA, ITS1, and cox1 were generated for two isolates of the new species. Sequences of the 28S rRNA gene were used to corroborate that Crassicutis is sister taxa of Homalometron Stafford, 1904. Mitochondrial DNA corroborated the distinction of the new species with previously sequenced congeners in Middle American cichlids; the interspecific divergence between the new species and the genetic lineages of C. cichlasomae was very high, varying between 23.7 and 27.2%. Biogeographical implications of our findings are briefly discussed including questionable validity of records of C. cichlasomae from South America.
Keyphrases
  • mitochondrial dna
  • genetic diversity
  • copy number
  • genome wide
  • gene expression
  • transcription factor
  • toxoplasma gondii
  • deep learning
  • electronic health record
  • big data
  • artificial intelligence