Browsing by Author "Alkhnbashi, Omer S"
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Publication Genomics of rare diseases in the Greater Middle East.(2025-02-03) Chekroun, Ikram; Almarri, Mohamed A; Uddin, Mohammed; Alkhnbashi, Omer S; Ali, Fahad R; Alsheikh-Ali, Alawi; Abou Tayoun, Ahmad NThe Greater Middle East (GME) represents a concentrated region of unparalleled genetic diversity, characterized by an abundance of distinct alleles, founder mutations and extensive autozygosity driven by high consanguinity rates. These genetic hallmarks present a unique, yet vastly untapped resource for genomic research on Mendelian diseases. Despite this immense potential, the GME continues to face substantial challenges in comprehensive data collection and analysis. This Perspective highlights the region's unique position as a natural laboratory for genetic discovery and explores the challenges that have stifled progress thus far. Importantly, we propose strategic solutions, advocating for an all-inclusive research approach. With targeted investment and focused efforts, the latent genetic wealth in the GME can be transformed into a global hub for genomic research that will redefine and advance our understanding of the human genome.Publication SpacerPlacer: ancestral reconstruction of CRISPR arrays reveals the evolutionary dynamics of spacer deletions(2024-10-14) Alkhnbashi, Omer SBacteria employ CRISPR-Cas systems for defense by integrating invader-derived sequences, termed spacers, into the CRISPR array, which constitutes an immunity memory. While spacer deletions occur randomly across the array, newly acquired spacers are predominantly integrated at the leader end. Consequently, spacer arrays can be used to derive the chronology of spacer insertions. Reconstruction of ancestral spacer acquisitions and deletions could help unravel the coevolution of phages and bacteria, the evolutionary dynamics in microbiomes, or track pathogens. However, standard reconstruction methods produce misleading results by overlooking insertion order and joint deletions of spacers. Here, we present SpacerPlacer, a maximum likelihood-based ancestral reconstruction approach for CRISPR array evolution. We used SpacerPlacer to reconstruct and investigate ancestral deletion events of 4565 CRISPR arrays, revealing that spacer deletions occur 374 times more frequently than mutations and are regularly deleted jointly, with an average of 2.7 spacers. Surprisingly, we observed a decrease in the spacer deletion frequency towards both ends of the reconstructed arrays. While the resulting trailer-end conservation is commonly observed, a reduced deletion frequency is now also detectable towards the variable leader end. Finally, our results point to the hypothesis that frequent loss of recently acquired spacers may provide a selective advantage.