Regulatory variation plays a crucial role in complex traits and diseases. Recent advances in genetic research have enabled the identification of genetic loci that influence traits ranging from growth in simple organisms to disease in humans. However, understanding how these loci affect traits remains a challenge. Expression quantitative trait loci (eQTLs) are genomic regions that influence gene expression levels. Studies of eQTLs have revealed how DNA sequence variations affect gene expression, which in turn influences physiological traits and disease risk. eQTLs can be classified based on their location relative to the gene they influence (local or distant) and their mode of action (cis or trans). Local eQTLs are typically located near the gene they influence and can act in cis, affecting expression in an allele-specific manner. Trans-eQTLs, on the other hand, act through diffusible factors and can influence gene expression from distant locations. Both types of eQTLs have been identified in various species, including humans, yeast, and model organisms. The study of eQTLs has also revealed the importance of regulatory variation in human disease. Many genetic variants associated with disease are located in non-coding regions and are not in linkage disequilibrium with coding exons. These variants likely influence gene expression through regulatory mechanisms. eQTLs can provide crucial links between genetic variants identified in genome-wide association studies (GWASs) and the biological processes they affect. Recent studies have shown that eQTLs can be found in a wide range of tissues and cell types, and that their effects can vary depending on the environment and genetic background. The identification of eQTLs in different tissues and cell types has provided insights into the complex relationship between gene expression variation and higher-order traits. These studies have also highlighted the importance of considering regulatory variation in the context of disease. Overall, the study of eQTLs has provided valuable insights into the molecular mechanisms underlying complex traits and diseases. As the field continues to advance, the integration of eQTL data with other types of genetic and molecular data will be essential for understanding the genetic basis of complex traits and diseases.Regulatory variation plays a crucial role in complex traits and diseases. Recent advances in genetic research have enabled the identification of genetic loci that influence traits ranging from growth in simple organisms to disease in humans. However, understanding how these loci affect traits remains a challenge. Expression quantitative trait loci (eQTLs) are genomic regions that influence gene expression levels. Studies of eQTLs have revealed how DNA sequence variations affect gene expression, which in turn influences physiological traits and disease risk. eQTLs can be classified based on their location relative to the gene they influence (local or distant) and their mode of action (cis or trans). Local eQTLs are typically located near the gene they influence and can act in cis, affecting expression in an allele-specific manner. Trans-eQTLs, on the other hand, act through diffusible factors and can influence gene expression from distant locations. Both types of eQTLs have been identified in various species, including humans, yeast, and model organisms. The study of eQTLs has also revealed the importance of regulatory variation in human disease. Many genetic variants associated with disease are located in non-coding regions and are not in linkage disequilibrium with coding exons. These variants likely influence gene expression through regulatory mechanisms. eQTLs can provide crucial links between genetic variants identified in genome-wide association studies (GWASs) and the biological processes they affect. Recent studies have shown that eQTLs can be found in a wide range of tissues and cell types, and that their effects can vary depending on the environment and genetic background. The identification of eQTLs in different tissues and cell types has provided insights into the complex relationship between gene expression variation and higher-order traits. These studies have also highlighted the importance of considering regulatory variation in the context of disease. Overall, the study of eQTLs has provided valuable insights into the molecular mechanisms underlying complex traits and diseases. As the field continues to advance, the integration of eQTL data with other types of genetic and molecular data will be essential for understanding the genetic basis of complex traits and diseases.