ANALYSIS OF MUTATIONS USING ANCIENT DNA GENOMES TO UNDERSTAND PATHOGENIC EMERGENCE AND DISEASE EVOLUTION
Abstract
Paleogenomics, the study of ancient DNA, has revolutionized our comprehension of human history by providing access to genomic data spanning hundreds of thousands of years. High-throughput sequencing methods have enabled the retrieval of complete genome sequences from diverse ancient sources, allowing for the exploration of evolutionary, ecological, social, and environmental inquiries deep across time. The field of ancient genomes has experienced a trend in research due to next generation sequencing capabilities, facilitating the investigation of demographic structures, population histories, evolutionary processes, and disease adaptations. Studies in paleogenomics have shifted from sequencing archaic hominids to exploring the replacement of European hunter-gatherers by Neolithic farmers, revealing surprising genetic differences between ancient and modern populations. Ancient DNA analysis has shed light on human phenotypic diversity evolution through natural selection, particularly focusing on genetic markers like single nucleotide polymorphisms (SNPs) to understand disease pathogenicity and genetic variability. Research in paleogenomics has also delved into the evolutionary consequences of human adaptation to factors such as agricultural practices, environmental changes, and pathogens, providing insights into disease susceptibility and population history changes. Despite the wealth of discoveries from ancient genomes, there remains a Eurocentric bias, with limited studies on Arab populations in the Middle East and the Arabian Peninsula. This study aims to investigate how genomic changes over time influence present-day predispositions to metabolic disorders in the MENA region, tracking genetic variations' allele frequencies, comparing evolutionary mechanisms across different periods, and elucidating disease predispositions and resistances in MENA populations.
DOI/handle
http://hdl.handle.net/10576/56283Collections
- Biomedical Sciences [64 items ]