Login / Signup

Evaluating the monophyly of Mammillaria series Supertextae (Cactaceae).

Cristian R CervantesSilvia Hinojosa-AlvarezAna WegierUlises RosasSalvador Arias
Published in: PhytoKeys (2021)
Mammillaria (Cactaceae) taxonomy has been historically problematic due to the morphological variability and sympatry of the species. This has led to several proposals for infrageneric classification, including subgeneric, section and series categories. Mammillaria ser. Supertextae is one of 15 series and is made up of a variable set of species that are mainly distributed in southern Mexico and Central America. However, the phylogenetic relationships within M. ser. Supertextae and its relationship to other Mammillaria taxa are far from fully understood. Here we attempt to elucidate these relationships using complete terminal sampling and newly obtained chloroplast marker sequences and comparing them to Mammillaria species sequences from GenBank. Our phylogenetic analyses showed that M. ser. Supertextae comprises a well-supported monophyletic group that diverged approximately 2.1 Mya and has M. ser. Polyacanthae as its sister group; however, relationships within M. ser. Supertextae remain unresolved. The topology obtained within M. ser. Supertextae must also be interpreted under the distribution shared by these taxa, but it is difficult to differentiate ancestral polymorphisms from possible introgression, given the short time elapsed and the markers used. Our results show that the infrageneric units of M. haageana and M. albilanata can be considered independent evolutionary units. We also suggest that the relationship between M. haageana and M. albilanata is convoluted because their distribution overlaps (mainly towards southern Mexico), with genetic differences that possibly indicate they represent more than two taxonomic entities. One possible explanation is that there could still be gene flow between these taxa, and we might be witnessing an ongoing speciation process.
Keyphrases
  • genome wide
  • genetic diversity
  • machine learning
  • deep learning
  • dna methylation
  • copy number
  • gene expression