Browsing by Author "Mathabela, Nomfundo Mathabela"

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    Sequencing for high-risk type 1 diabetes genotypes in the South African black population using AmpliSeq Nanopore next generation sequencing
    (University of the Witwatersrand, Johannesburg, 2023) Mathabela, Nomfundo Mathabela; Ali, Stuart
    Introduction: Type 1 diabetes (T1D) is a chronic autoimmune disorder characterized by the destruction of the -cells of the pancreas, resulting in the inability to produce/maintain insulin. This results in an inability to maintain the blood glucose at homeostasis. Prolonged hyperglycaemia leads to micro- and macro-vascular complications. Thus, it is vital to diagnose and treat patients in a timely manner. It is important to identify individuals at increased risk of developing T1D allowing for appropriate follow ups. Numerous mutations/variants in specific genes confer an increased risk of T1D with the HLA gene accounting for approximately 40-50 % of the risk. Therefore, it is possible that by looking at genetic variation in T1D associated genes we can develop a tool that can determine the likelihood of an individual developing T1D. Study aims and objectives: The development, implementation, and validation of a Nanopore NGS method to sequence and genotype polymorphisms associated with T1D in a cohort of black South Africans which could be used to develop a genetic risk score (GRS) for T1D in this population. In addition, we aimed to compare sequencing results to two HLA genotypes obtained using PCR-RFLP. Method: Participants with T1D (n=19) and control participants (n=5) were genotyped for 12 T1D associated polymorphisms through Ampliseq Nanopore sequencing. In addition, Ion Torrent was used to confirm the Ampliseq Nanopore results. A bioinformatics pipeline that involves reference sequence generation using an in-house script, alignment of sequencing data with the reference sequence, filtering and variant calling was developed. A genetic risk score (GRS) was calculated for the participants. Participants (n=73) were genotyped by PCR-RFLP for the HLA rs2040410 and rs7454108 polymorphisms. Results: Sequencing samples individually was found to have a slightly higher Qscore than samples sequenced in multiplex (9.73 vs. 9.5). Samples sequenced individually had higher average reads (187.60 vs. 151.14 Mb), passed reads (41.47 vs. 25.99 Mb), and estimated bases (54.72 vs. 49.57 Mb) than those sequenced in multiplex. In addition, samples sequenced in a multiplex had higher average failed reads (475.58 Mb) in comparison to those sequenced individually (13.58 Mb). The average percentage difference in sequencing data generated using Ion Torrent compared to Nanopore was 5.67%. Variant calling produced average Phred-scale quality scores of 73.89 for standards (The Coriell Trio) and 89.77 for participants. The GRS calculator was not able to accurately predict which participants had T1D. Discussion and Conclusion: A next generation sequencing method and bioinformatics pipeline for the screening of participants for 645 T1D associated polymorphisms was investigated. The method combined two sequencing techniques i.e., Ion AmpliSeq and Nanopore sequencing to achieve this. The data can then be processed by in-house variant callers. With a larger sample group, this method will be useful for the investigation of genetic variants linked to T1D.