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Mohammed Uddin

Long-read sequencing improves detection of non-coding structural variations

About Mohammed Uddin

Mohammed Uddin is a human geneticist with a research focus on the genetics of neurodevelopmental and rare disorders. Mohammed completed his masters in computer science and a Ph.D. in molecular genetics that enabled him to integrate both computational and cellular biology of the brain. Mohammed did his postdoctoral fellowship at The Hospital for Sick Children (SickKids) in Toronto, Canada, and received the international Banting Fellowship in 2015 by the Canadian Institutes for Health Research (CIHR). His current research interest primarily focuses on the application of single cell genomis, AI, and CRISPR technology to identify genetic etiology of neurodevelopmental disorders.


Whole-genome sequencing (WGS) techniques play a critical role in investigating structural variations in the genome to understand the genetic aspect of a disease. In autism spectrum disorders (ASD), studies typically concentrate on investigating pathogenic variations contributing to a proband’s condition in the protein-coding region, while a substantially larger non-coding region is neglected. Moreover, current short-read sequencing tools are incapable of detecting large and complex genomic variations. In this talk, I will present our results on the detection of structural variation in a family with triplets impacted by ASD. Comparing with other WGS technology, nanopore sequencing identified significantly large number of SVs in non-coding region of the genome.

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Mohammed Uddin

Mohammed Uddin