Loci2Tissue: Ranking tissues by the e3xpression of disease-associated genes reveals insights of the underlying mechanisms of complex diseases and traits

Modern high throughput technologies routinely produce a large set of genomic loci of biological interest like genome-wide association studies (GWASs). Annotating the set of genomic loci may lead to new biological insights. However, available tools are limited.In this study, we developed a new bioinformatics software package named loci2tissue that aims to connect a set of input genomic loci to tissues and organs, thus providing annotation in terms of tissue-specific transcription regulation potential. This is achieved by utilizing multi-tissue expression quantitative trait loci (eQTLs) information provided by Genotype-Tissue Expression (GTEx) to connect genomic loci to genes in a tissue-specific manner. We then rank tissues based on the tissue-specific expression levels of these genes. When applying loci2tissue to sets of loci that harbor genetic variants linked to complex diseases, we are able to identify specific tissues involved in complex diseases or traits.Our analyses revealed interesting tissue-trait pairs. As examples, we found significant enrichment of visceral omental adipose tissue in Alzheimer’s disease and the hippocampus tissue in Parkinson’s disease. These results shed light on the underlying biology of many complex diseases and traits where the tissue is likely to be the source of pathogenesis.