Human mitochondrial DNA variabilitymultidisciplinary applications in the fields of forensic, medical and population genetics
- Cerezo Fernández, María
- Ángel Carracedo Álvarez Co-director
- Antonio Salas Ellacuriaga Co-director
Universidade de defensa: Universidade de Santiago de Compostela
Fecha de defensa: 01 de xullo de 2011
- María Victoria Lareu Huidobro Presidenta
- Paula Sánchez Diz Secretario/a
- María José Farfán Espuny Vogal
- Antonio Torroni Vogal
- Manuel López-Soto Vogal
Tipo: Tese
Resumo
The results of the present project indicate that the analysis of the mtDNA variation can be useful in medical, forensic, and population genetic studies. The particular features of the mtDNA, including high copy number, lack of recombination, and high average mutation rate; also determine its usefulness and limitations in genetic studies. For instance, the reconstruction of the phylogeny is straightforward because the lineages are passed through the matriline with the only changes generated by mutation. However, this is a single marker and only tells the history of female population, which not necessarily match the demography of the whole population. We have applied these principles to the analysis of several human populations, to the forensic field, and to some medical study. All of them have many aspects in common, indicating also the important interplay that should be always needed in all mtDNA studies. For instance, one cannot carry out a forensic or medical genetic study ignoring population variation patterns or the important heterogeneity that exists regarding site specific mutation rates. We have contributed to improve our knowledge of the variation in several African, European, and American populations. In this project we have also focussed our attention in several aspects of forensic interest, concerning the analysis of degraded and low DNA amount samples. And finally, we have tried to establish a necessary bridge between the different fields of research, indicating that proper quality standards can help to avoid false positives of instabilities in cancer studies, erroneous conclusions in forensic casework, or errors in datasets that could have consequences in population studies or indirectly in forensic or medical genetic ones.