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Contrasting genetic and morphological differentiation among geographical lineages of a stenotopic miniature rasborine, Boraras maculatus, in Peninsular Malaysia.

Yi Qing FamJamsari Amirul Firdaus JamaluddinAbdullah Halim Muhammad-RasulMohd Lokman Ilham-NorhakimNik Fadzly N RoselySébastien Lavoué
Published in: Journal of fish biology (2023)
The variability of the stenotopic miniature rasborine Boraras maculatus (Cypriniformes: Danionidae: Rasborinae) across acidic-water habitats of Peninsular Malaysia was investigated using two molecular markers (the mitochondrial COI gene and the nuclear rhodopsin gene), as well as morphological evidence. Molecular phylogenetic analyses revealed differentiation among populations of B. maculatus in Peninsular Malaysia with the distinction of four allopatric lineages. Each of them was recognized as a putative species by automatic species delimitations methods. These lineages diverged from each other between 7.4 and 1.9 million years ago. A Principal Component Analysis (PCA) was conducted to examine the multivariate variation of 11 morphometric measurements among three of these lineages. PCA results showed significant overlap in morphological characteristics among these lineages. Additionally, a photo-based machine learning approach failed to fully differentiate these lineages, suggesting limited morphological differentiation. Boraras maculatus represents a case of morphological stasis in a stenotopic miniature species. Strong habitat preference coupled with long-term habitat fragmentation, may explain why each lineage of B. maculatus has a restricted distribution and did not disperse to other regions within and outside of Peninsular Malaysia, despite ample possibilities when the Sunda shelf was emerged and drained by large paleodrainages for most of the past 7 million years. The conservation status of Boraras maculatus and its peat swamp habitats is discussed, and it is concluded that peat swamps comprise several evolutionary units. Each of these units is considered a conservation unit and deserves appropriate protection. This article is protected by copyright. All rights reserved.
Keyphrases
  • machine learning
  • genome wide
  • climate change
  • copy number
  • oxidative stress
  • genetic diversity
  • gene expression
  • deep learning
  • artificial intelligence
  • transcription factor
  • high resolution