Molecular analysis of necrophagous diptera of the Iberian Peninsula

  1. Fuentes Lopez, Alberto
Supervised by:
  1. José Galián Albaladejo Director
  2. Elena Romera Lozano Director

Defence university: Universidad de Murcia

Fecha de defensa: 19 December 2018

Committee:
  1. José Serrano Marino Chair
  2. Deodalia Dias Secretary
  3. Daniel Martín Vega Committee member
Department:
  1. Zoology and Physical Anthropology

Type: Thesis

Abstract

This thesis is focused on the identification of Diptera with forensic interest in the Iberian Peninsula through barcoding techniques, other molecular techniques and geometric morphometric techniques. The identification of specimens is an essential step in forensic entomology studies. This identification would be used in the calculation of the post mortem interval (PMI), but with a wrong identification the result of this calculation could not be used in a judicial process. Sometimes, the state in which the samples are in the scene of a crime makes impossible to identify them by morphological techniques. Therefore, molecular techniques have become an essential tool in this type of studies. To develop the chapters of this thesis, we performed DNA extractions of multiple dipterous specimens with forensic interest collected in Spain and Portugal between 2012 and 2015. We sequenced the mitochondrial genes COI (for the analysis of barcoding) and 16S, and of the nuclear gene ITS2. Molecular identifications were performed comparing the sequences with the sequences present in the GenBank and BOLD databases through the BLAST and BIN tools respectively. The relationships among the identified species were analyzed by Neighbor-Joining phylogenetic trees and by haplotype networks. In addition, reconstruction of ancestral states methods for widely distributed species were applied. These analyzes were applied: to a wide range of species to know the diversity of Diptera species of the Iberian Peninsula (chapter I); to the family Sarcophagidae of special difficulty in its morphological identification (chapter II); to the Calliphora vicina species of wide distribution to know the relationship between its populations and its evolutionary history (chapter III); and to the species Lucilia ampullacea, Lucilia caesar and Lucilia illustris, considered sister species with difficulties for their morphological identification in poorly conserved samples (chapter IV). In addition, in this last chapter, geometric morphometric techniques were used to analyze the wings and heads of the specimens of these species. It was investigated if these techniques are useful for the identification of species and the differentiation of the populations in which they were collected. The information produced in this thesis increases and improves our knowledge about Diptera with forensic interest in the Iberian Peninsula. During the performing of this thesis, a total of 1398 new sequences were produced (669 of COI, 206 of 16S and 523 of ITS2). A project has been created in the BOLD database, called "Barcoding of Iberian Diptera", which will be very useful in future work. The usefulness of molecular tools, especially those of barcoding, for the identification of species has been corroborated. This includes some rename specimens due to erroneous previous morphological identifications, as well as the identification of Diptera collected by the scientific police of Alicante in forensic cases. In addition, the phylogeographic analysis showed that samples of forensic cases from Alcoy have local haplotypes. The analysis of the species C. vicina revealed that there is no biogeographic structure for any of the genes analyzed, confirming that geographic barriers are not enough to stop gene flow. The reconstruction of the ancestral states of this species showed serial colonizations among the populations, possibly linked to human activity. The species L. ampullacea, L. caesa and L. illustris were identified by molecular techniques and geometric morphometric techniques of wing and head. Both morphological structures were analyzed grouping the data by populations and revealed to be able to identify the provenance of the samples with these analyzes.