Some Investigation Into Gwas (Genome Wide Association Studies) and Post-gwas A Project Report Submitted in- Student Ready-project Formulation, Execution and Presentation Bts-421

Abstract

Genome-Wide Association Studies (GWAS) have revolutionized our understanding of the genetic basis of complex traits and diseases, identifying numerous genetic variants linked to conditions like type 2 diabetes, breast cancer, and schizophrenia. Utilizing high-throughput genotyping technologies and sophisticated statistical analyses, GWAS have pinpointed critical loci associated with various phenotypes. Despite these successes, GWAS face challenges, including missing heritability, suggesting the presence of additional genetic factors such as rare variants and gene-gene interactions that are not captured by conventional methods. Post-GWAS analyses, integrating functional genomics, epigenomics, and transcriptomics,are essential for annotating and validating findings, with techniques like eQTL mapping and CRISPR screens helping to elucidate causal mechanisms and identify therapeutic targets. Interdisciplinary collaborations and large-scale data sharing initiatives, exemplified by consortia such as the Wellcome Trust Case Control Consortium (WTCCC) and the Genetic Investigation of Anthropometric Traits (GIANT), enhance statistical power and ensure the generalizability of findings across diverse populations. The future of GWAS lies in leveraging machine learning and AI to detect complex genetic interactions and incorporating polygenic risk scores for personalized medicine. Addressing these challenges through integrative omics approaches, collaborations, and advanced computational methods will continue to shape the landscape of genetics research and pave the way for innovative approaches in personalized medicine and precision healthcare.