https://www.um.edu.mt/library/oar/handle/123456789/111132 2026-04-07T18:44:35Z 2026-04-07T18:44:35Z https://www.um.edu.mt/library/oar/handle/123456789/119660 2024-03-12T08:43:47Z 2022-01-01T00:00:00Z

Title: An annotation framework for variants that alter promoter transcription factor binding sites (nCODREG) Abstract: Transcriptional regulation is a complex biological process requiring the combined activity of numerous molecules, including transcription factors, cofactors and chromatin regulators. Transcription factors recognise and bind to short non-coding sequences known as motifs found in genes’ regulatory regions, such as promoter, enhancer and silencer regions. This allows transcription factors to modulate the recruitment and activation of RNA polymerase II, the multiprotein complex responsible for the transcription of all protein-coding genes. The presence of genetic variants in regulatory regions may disrupt transcription factor binding, culminating in altered gene expression and protein production. Indeed, genome-wide association studies (GWAS) have flagged several variants in regulatory regions associated with disease development and traits. Hence, the annotation of variants residing in regulatory sites has become increasingly important in genomic studies and disease interpretation. This study describes the implementation of an annotation framework for variants residing in gene promoter regions which may potentially create, delete or alter the binding affinity of transcription factor binding sites. Variants are annotated by querying a publicly available RESTful web-service called VEP, and a BioPython library called Bio.Motifs which computes the position weight matrix (PWM) scores from two locally saved motif collections called JASPAR and HOCOMOCO. The outcome is a list of promoter variants annotated with transcription factors which may be affected by the variants, and the expected binding ability at the variants’ site. Used together, the VEP and motif collections can strengthen the outcome of a particular variant. Results on our dataset show that on average 12% of Whole Exome Sequencing (WES) variant locations and 8.5% of Whole Genome Sequencing (WGS) locations flagged by VEP were also flagged by JASPAR’s motif collection. Compared to other motif finding tools, the implemented annotation framework automates the whole annotation process by building the required nucleotide sequences adjacent to the promoter variants, while ensuring the variants are always within the nucleotide sequence being scanned by the motifs. In addition, the annotation process is able to scale up according to the number of CPUs available on the running machine. Enabling multi-core execution on a 4-core processor resulted in a 66% decrease in execution time of the dataset compared to single-core execution, thus speeding up the annotation processing of millions of variants within high-throughput sequencing data files. Description: M.Sc.(Melit.)

2022-01-01T00:00:00Z https://www.um.edu.mt/library/oar/handle/123456789/111302 2023-07-05T11:01:09Z 2022-01-01T00:00:00Z

Title: Recalibration of minor alleles in the human reference sequence Abstract: The intrinsic problem of minor alleles occupying reference positions in the Human Reference Sequence build 37 may challenge the notion of accurate variant calling and result in variant misinterpretation in the clinical practice. In this research study, a bioinformatics pipeline, RecAl, was developed with the primary aim to detect all reference minor alleles and generate three VCF files during sample analysis. These files include the false-positive variants, the false-negative variants, and a separate corrected sample VCF file with the eliminated false-positive variants and incorporated false-negative variants. When the sample files were processed through RecAl, the percentage of false positives variants detected for an alternate allele frequency threshold of 0.90, 0.95 and 0.99 were 9.7%, 7.5% and 5.4% respectively. For the false negative variants, RecAl identified 0.013%, 0.007% and 0.005% respectively. Each of these variants were annotated using popular pathogenicity prediction tools including CADD (Kircher M et al., 2014), Polyphen-2 (Adzhubei I et al., 2010) and SIFT (Ng, P. and Henikoff, S., 2001). From the results, it was presented that 1.24% of the false-positive variants and 0.87% of the false-negative variants are deleterious with significant impact of sequence variation. Additionally, the list generated through RecAl for reference minor alleles was compared to the study carried out by Fuentes F et al., (2012) which focused on false-positive calls due to reference minor alleles in exome regions. From this evaluation, 90% of the variants matched which signifies that the problem of minor alleles occupying reference positions is still prevalent and the list of reference minor alleles generated by RecAl is reliable. Lastly, a comparative analysis of the reference minor alleles in the Human Reference build 37 was compared to the reference minor alleles in build 38 to assess how many reference minor alleles were corrected which resulted in only 9% being corrected. Description: M.Sc.(Melit.)

2022-01-01T00:00:00Z