Population analysis of complete mitogenomes for 334 samples from El Salvador.
Forensic Sci Int Genet
; 66: 102906, 2023 09.
Article
en En
| MEDLINE
| ID: mdl-37364481
ABSTRACT
The use of mitochondrial DNA (mtDNA) in the field of forensic genetics is widely spread mainly due to its advantages when identifying highly degraded samples. In this sense, massive parallel sequencing has made the analysis of the whole mitogenome more accessible, noticeably increasing the informativeness of mtDNA haplotypes. The civil war (1980-1992) in El Salvador caused many deaths and disappearances (including children) all across the country and the economic and social instability after the war forced many people to emigration. For this reason, different organizations have collected DNA samples from relatives with the aim of identifying missing people. Thus, we present a dataset containing 334 complete mitogenomes from the Salvadoran general population. To the best of our knowledge, this is the first publication of a nationwide forensic-quality complete mitogenome database of any Latin American country. We found 293 different haplotypes, with a random match probability of 0.0041 and 26.6 mean pairwise differences, which is similar to other Latin American populations, and which represent a marked improvement from the values obtained with just control region sequences. These haplotypes belong to 54 different haplogroups, being 91% of them of Native American origin. Over a third (35.9%) of the individuals carried at least a heteroplasmic site (excluding length heteroplasmies). Ultimately, the present database aims to represent mtDNA haplotype diversity in the general Salvadoran populations as a basis for the identification of people that disappeared during or after the civil war.
Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Genoma Mitocondrial
/
Genética de Población
País/Región como asunto:
America central
/
El salvador
Idioma:
En
Revista:
Forensic Sci Int Genet
Asunto de la revista:
GENETICA
/
JURISPRUDENCIA
Año:
2023
Tipo del documento:
Article