This study presents an in-silico pipeline for identifying single nucleotide polymorphisms (SNPs) and insertions or deletions (InDels) using RNA sequencing (RNA-seq) data. Genetic variations, such as SNPs and InDels, are vital for understanding genetic diversity and gene function. RNAseq is an efficient and cost-effective method for analysing these variations, enabling detailed examination of gene expression profiles and detection of differentially expressed transcripts. The pipeline involves converting RNA samples into cDNA libraries, followed by fragmentation and adapter ligation. The RNA-seq data undergoes rigorous quality control, read alignment, and variant calling using advanced bioinformatics tools. This approach allows for precise identification of SNPs and InDels, providing critical insights into gene regulation, protein structure, and evolutionary adaptation. By detailing the workflow from RNA extraction to variant annotation, this study underscores the utility of RNA-seq in genetic variation research. The integration of high-throughput sequencing technologies and sophisticated computational methods facilitates the identification of genetic variants, with significant applications in personalized medicine, disease research, and crop improvement. This study highlights RNAseq's potential to enhance our understanding of genetic diversity and its implications across various biological fields.