Center for Applied and Translational Genomics (CATG)

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A draft UAE-based Arab pangenome reference.
(2025-07-24) Nassir, Nasna; Almarri, Mohamed A; Kumail, Muhammad; Mohamed, Nesrin; Balan, Bipin; Hanif, Shehzad; AlObathani, Maryam; Jamalalail, Bassam; Elsokary, Hanan; Kondaramage, Dasuki; Shiyas, Suhana; Kosaji, Noor; Satsangi, Dharana; Suwaidi, Hanan Al; Albanna, Ammar; S Du Plessis, Stefan; Khansaheb, Hamda Hassan; Alsheikh-Ali, Alawi; Uddin, Mohammed
Pangenomes provide a robust and comprehensive portrayal of genetic diversity in humans, but Arab populations remain underrepresented. We present a preliminary UAE-based Arab Pangenome Reference (UPR) utilizing 53 individuals of diverse Arab ethnicities residing in the United Arab Emirates. We assembled nuclear and mitochondrial pangenomes using 35.27X high-fidelity long reads, 54.22X ultralong reads and 65.46X Hi-C reads. This approach yielded contiguous haplotype-phased de novo assemblies of exceptional quality, with an average N50 of 124.28 Mb. We discovered 111.96 million base pairs of previously uncharacterized euchromatic sequences absent from existing human pangenomes, the T2T-CHM13 and GRCh38 reference human genomes, and other public datasets. Moreover, we identified 8.94 million population-specific small variants and 235,195 structural variants within the Arab pangenome, not present in linear and pangenome references and public datasets. We detected 883 gene duplications, including the TATA-binding protein gene TAF11L5, which was uniquely duplicated across all Arab populations and that included 15.06% of genes associated with recessive diseases. By exploring the mitochondrial pangenome, we identified 1,436 bp of previously unreported sequences. Our study provides a valuable resource for future genetic research and genomic medicine initiatives in Arab population and other population with similar genetic backgrounds.
Genomic insights from a deeply phenotyped highly consanguineous neurodevelopmental disorders cohort.
(2024-09-26) Mohamed, Nesrin; Satsangi, Dharana; Hanif, Shehzad; Tambi, Richa; Nassir, Nasna; Uddin, Mohammed
Purpose: The genetic underpinning of neurodevelopmental disorders (NDDs) in diverse ethnic populations, especially those with high rates of consanguinity, remains largely unexplored. Here, we aim to elucidate genomic insight from 576 well-phenotyped and highly consanguineous (16%) NDD cohort.
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 N
The 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.
Gut matters in microgravity: potential link of gut microbiota and its metabolites to cardiovascular and musculoskeletal well-being
(2024-08) Soares, Nelson C
Abstract The gut microbiota and its secreted metabolites play a significant role in cardiovascular and musculoskeletal health and diseases. The dysregulation of the intestinal microbiota poses a significant threat to cardiovascular and skeletal muscle well-being. Nonetheless, the precise molecular mechanisms underlying these changes remain unclear. Furthermore, microgravity presents several challenges to cardiovascular and musculoskeletal health compromising muscle strength, endothelial dysfunction, and metabolic changes. The purpose of this review is to critically examine the role of gut microbiota metabolites on cardiovascular and skeletal muscle functions and dysfunctions. It also explores the molecular mechanisms that drive microgravity-induced deconditioning in both cardiovascular and skeletal muscle. Key findings in this review highlight that several alterations in gut microbiota and secreted metabolites in microgravity mirror characteristics seen in cardiovascular and skeletal muscle diseases. Those alterations include increased levels of Firmicutes/Bacteroidetes (F/B) ratio, elevated lipopolysaccharide levels (LPS), increased in para-cresol (p-cresol) and secondary metabolites, along with reduction in bile acids and Akkermansia muciniphila bacteria. Highlighting the potential, modulating gut microbiota in microgravity conditions could play a significant role in mitigating cardiovascular and skeletal muscle diseases not only during space flight but also in prolonged bed rest scenarios here on Earth.
Optimizing Large Language Models for Arabic Healthcare Communication: A Focus on Patient-Centered NLP Applications
(2024) Alkhnbashi, Omer S
Recent studies have highlighted the growing integration of Natural Language Processing (NLP) techniques and Large Language Models (LLMs) in healthcare. These technologies have shown promising outcomes across various healthcare tasks, especially in widely studied languages like English and Chinese. While NLP methods have been extensively researched, LLM applications in healthcare represent a developing area with significant potential. However, the successful implementation of LLMs in healthcare requires careful review and guidance from human experts to ensure accuracy and reliability. Despite their emerging value, research on NLP and LLM applications for Arabic remains limited particularly when compared to other languages. This gap is largely due to challenges like the lack of suitable training datasets, the diversity of Arabic dialects, and the language’s structural complexity. In this study, a panel of medical experts evaluated responses generated by LLMs, including ChatGPT, for Arabic healthcare inquiries, rating their accuracy between 85% and 90%. After fine tuning ChatGPT with data from the Altibbi platform, accuracy improved to a range of 87% to 92%. This study demonstrates the potential of LLMs in addressing Arabic healthcare queries especially in interpreting questions across dialects. It highlights the value of LLMs in enhancing healthcare communication within the Arabic-speaking world and points to a promising area for further research. This work establishes a foundation for optimizing NLP and LLM technologies to achieve greater linguistic and cultural adaptability in global healthcare settings.

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