Date of Award
Spring 5-20-2026
Document Type
Thesis
Degree Name
Master of Science (MS)
Department/Program
Forensic Science
Language
English
First Advisor or Mentor
Lissette Delgado-Cruzata
Second Reader
Mechthild Prinz
Third Advisor
Sai Casado Zapico
Abstract
Biogeographical ancestry (BGA) inference is an important tool in forensic science, providing supplemental information when comparison/reference DNA is not available for traditional DNA analyses. Insertion/deletion polymorphisms (INDELs) have been used in the last decade as ancestry-informative markers (AIMs) for BGA inference because they can be easily adapted to forensic-type samples and are determined using low cost and easy processing methods. Limited research has attempted to estimate ancestry and admixture in United States (U.S.) populations. This study evaluated the effectiveness of a 45- and 21- INDEL panel to measure population admixture proportions of four different origins (African, European, East Asian and Indigenous American) in five U.S. populations. Reference population data from 556 individuals included in the HGDP-CEPH panel were analyzed alongside U.S. population data from 15 individuals from New York, 61 Black individuals from the Southwest of the U.S., 99 White individuals from Utah, 64 Mexican Americans from California and 104 Puerto Ricans. Our results demonstrated that both the 45- and 21-INDEL panels successfully differentiated major continental ancestry groups and identified expected admixture patterns within U.S. populations. Latine/o/a populations exhibited the highest levels of admixture, while White and Black populations demonstrated comparatively greater genetic homogeneity. Results from New York samples showed complex admixture patterns. These findings support INDEL-based AIM panels as reliable tools for BGA inference, while emphasizing the need for expanded datasets within the U.S.
Recommended Citation
Martinez, Amanda, "Exploring Biogeographical Ancestry Inference of New York Residents Using a 45 INDEL Panel" (2026). CUNY Academic Works.
https://academicworks.cuny.edu/jj_etds/386
