Biology subjects

Dzobo, K.

Publications and source records attributed to Dzobo, K..

4 recordsLinked to original sources

bioRxiv2024

Unveiling the role of Tdark genes in genetic diseases and phenotypes through bioinformatics-based functional enrichment and network analyses

In recent years, there has been growing interest in understanding the role of dark genes in genetic diseases and phenotypes. Despite their lack of functional characterisation, dark genes account for a significant portion of the human genome and are believed to play a role in regulating gene expression and cellular processes. We investigated the role of dark genes in genetic diseases and phenotypes by conducting integrative network analyses and functional enrichment studies across multiple large-scale molecular datasets. Our investigation revealed a predominant association of both dark and light genes with psoriasis. Furthermore, we found that the transcription factors UBTF and NFE2L2 are potential regulators of both dark and light genes associated with tuberculosis. In contrast, the transcription factors SUZ12 and TP63 are potential regulators of both dark and light genes associated with interstitial cystitis. Further network analysis of dark genes, including CALHM6, HCP5, PRRG4, DDX60L and RASA2, revealed a notably high weighted degree of association with genetic diseases and phenotypes. Moreover, our analysis revealed that numerous genetic diseases and phenotypes, including psoriasis, pick disease, tuberculosis, ulcerative colitis, interstitial cystitis, and Crohns disease, exhibited shared gene linkages. Additionally, we conducted a protein-protein interaction analysis to reveal 16 dark genes that encode hub proteins, including R3HDM2, RPUSD4, FASTKD5, and MRPL15, that could play a role in many genetic diseases and phenotypes, and are widely expressed across body tissues. Our findings contribute to the understanding of the genetic basis of diseases and provide potential therapeutic targets for future research. Identifying dysregulated dark genes in disease states can lead to new strategies for prevention, diagnosis, and treatment, thus advancing our understanding of disease mechanisms.

bioinformatics↗

bioRxiv2023

Racial Disparities in the Genetic Landscape of Acute Myeloid Leukaemia from The Cancer Genome Atlas: Insights from a Bioinformatics Analysis

Acute myeloid leukaemia (AML) is a heterogeneous disease with complex pathogenesis that affects hematopoietic stem cells. Ethnic and racial disparities have been reported to affect treatment and survival outcomes in AML patients. Here, we analysed clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) to investigate potential differences in the genetic landscape of AML between African and European individuals. We found several differentially expressed mRNA transcripts between the AML of Africans and Europeans. Notably, AML in African patients exhibited enrichment for several pathways, including signalling by G-protein-coupled receptors, oncostatin M, and codeine and morphine metabolism. In contrast, AML in European patients showed enrichment for pathways related to the glial cell-line derived neurotrophic factor/rearranged during transfection signalling axis, gamma-aminobutyric acid receptor activation, and ligand-gated ion transport channels. Additionally, kinase enrichment analysis identified shared and distinct kinases in AML among Africans and Europeans: Africans showed an enrichment of cyclin-dependent kinases, while Europeans exhibited an enrichment of ULK2, CSNK2B, and CAMK1. Our study highlights the potential importance of considering race when evaluating the genetic landscape of AML, which may improve treatment strategies for this disease.

bioinformatics↗

bioRxiv2023

Shedding Light on the Dark Genome: Insights into the Genetic, CRISPR-based, and Pharmacological Dependencies of Human Cancers and Disease Aggressiveness

Investigating the human genome is vital for identifying risk factors and devising effective therapies to combat genetic disorders and cancer. Despite the extensive knowledge of the "light genome", the poorly understood "dark genome" remains understudied. In this study, we integrated data from 20,412 protein-coding genes in Pharos and 8,395 patient-derived tumours from The Cancer Genome Atlas (TCGA) to examine the genetic and pharmacological dependencies in human cancers and their treatment implications. We discovered that dark genes exhibited high mutation rates in certain cancers, similar to light genes. By combining the drug response profiles of cancer cells with cell fitness post-CRISPR-mediated gene knockout, we identified the crucial vulnerabilities associated with both dark and light genes. Our analysis also revealed that tumours harbouring dark gene mutations displayed worse overall and disease-free survival rates than those without such mutations. Furthermore, dark gene expression levels significantly influenced patient survival outcomes. Our findings demonstrated a similar distribution of genetic and pharmacological dependencies across the light and dark genomes, suggesting that targeting the dark genome holds promise for cancer treatment. This study underscores the need for ongoing research on the dark genome to better comprehend the underlying mechanisms of cancer and develop more effective therapies.

bioinformatics↗

bioRxiv2020

An SNP variant MT1-MMP with a defect in its collagenolytic activity confers the fibrotic phenotype of Dupuytren's Disease

Dupuytrens Disease (DD) is a common fibroproliferative disease of the palmar fascia. We previously identified a strong association with a non-synonymous variant (rs1042704, pD273N) in MMP14 (encoding MT1-MMP). We investigated the functional consequences of this variant, and demonstrated that the variant MT1-MMP (MT1-N273) exhibits only 17% of cell surface collagenolytic activity compared to the ancestral enzyme (MT1-D273). Cells expressing both MT1-D273 and MT1-N273 in a 1:1 ratio, mimicking the heterozygous state, possess 38% of the collagenolytic activity compared to the cells expressing MT1-D273, suggesting that MT1-N273 acts in a dominant negative manner. Consistent with this hypothesis, patient-derived DD myofibroblasts expressing MT1-N273 demonstrated around 30% of full collagenolytic activity regardless of the heterozygous or homozygous state. 3D-molecular envelope modelling using small angle X-ray scattering demonstrated altered positioning of the catalytic domain within dimeric molecules. Taken together, our data suggest that rs1042704 directly contributes to the fibrotic phenotype of DD.

biochemistry↗