Species identification of protected carpet pythons suitable for degraded forensic samples

Sherryn Ciavaglia, Steve Donnellan, Julianne Henry, Adrian Linacre

    Research output: Contribution to journalArticle

    3 Citations (Scopus)

    Abstract

    In this paper we report on the identification of a section of mitochondrial DNA that can be used to identify the species of protected and illegally traded pythons of the genus Morelia. Successful enforcement of wildlife laws requires forensic tests that can identify the species nominated in the relevant legislation. The potentially degraded state of evidentiary samples requires that forensic investigation using molecular genetic species identification is optimized to interrogate small fragments of DNA. DNA was isolated from 35 samples of Morelia spilota from which the complete cytochrome b was sequenced. The ND6 gene was also sequenced in 32 of these samples. Additional DNA sequences were generated from 9 additional species of Morelia. The sequences were aligned by Geneious and imported into MEGA to create phylogenetic trees based on the entire complex of approximately 1,706 base pairs (bp). To mimic degraded DNA, which is usually found in forensic cases, short sub-sections of the full alignment were used to generate phylogenetic trees. The sub-sections that had the greatest DNA sequence information were in parts of the cytochrome b gene. Our results highlight that legislation is presently informed by inadequate taxonomy. We demonstrated that a 278 bp region of the cytochrome b gene recovered the topology of the phylogenetic tree found with the entire gene sequence and correctly identified species of Morelia with a high degree of confidence. The locus described in this report will assist in the successful prosecution of alleged illegal trade in python species.

    Original languageEnglish
    Pages (from-to)295-305
    Number of pages11
    JournalForensic Science, Medicine, and Pathology
    Volume10
    Issue number3
    DOIs
    Publication statusPublished - 2014

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