{"doi":"10.3390/ijms232012493","title":"IsomiR-eQTL: A Cancer-Specific Expression Quantitative Trait Loci Database of miRNAs and Their Isoforms","abstract":"<jats:p>The identification of expression quantitative trait loci (eQTL) is an important component in efforts to understand how genetic variants influence disease risk. MicroRNAs (miRNAs) are short noncoding RNA molecules capable of regulating the expression of several genes simultaneously. Recently, several novel isomers of miRNAs (isomiRs) that differ slightly in length and sequence composition compared to their canonical miRNAs have been reported. Here we present isomiR-eQTL, a user-friendly database designed to help researchers find single nucleotide polymorphisms (SNPs) that can impact miRNA (miR-eQTL) and isomiR expression (isomiR-eQTL) in 30 cancer types. The isomiR-eQTL includes a total of 152,671 miR-eQTLs and 2,390,805 isomiR-eQTLs at a false discovery rate (FDR) of 0.05. It also includes 65,733 miR-eQTLs overlapping known cancer-associated loci identified through genome-wide association studies (GWAS). To the best of our knowledge, this is the first study investigating the impact of SNPs on isomiR expression at the genome-wide level. This database may pave the way for researchers toward finding a model for personalised medicine in which miRNAs, isomiRs, and genotypes are utilised.</jats:p>","journal":"International Journal of Molecular Sciences","year":2022,"id":652026,"datarank":0.26876392038420827,"base_score":1.791759469228055,"endowment":1.791759469228055,"self_citation_contribution":0.26876392038420827,"citation_network_contribution":0.0,"self_endowment_contribution":0.26876392038420827,"citer_contribution":0.0,"corpus_percentile":41.5,"corpus_rank":7900,"citation_count":5,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1580461,"name":"Paul Whatmore","orcid":null,"position":1,"is_corresponding":false},{"id":1107566,"name":"Samaneh Farashi","orcid":"0000-0001-6383-4203","position":2,"is_corresponding":false},{"id":1176939,"name":"Roberto A. Barrero","orcid":"0000-0002-7735-665X","position":3,"is_corresponding":false},{"id":240079,"name":"Jyotsna Batra","orcid":"0000-0003-4646-6247","position":4,"is_corresponding":false},{"id":1003109,"name":"Afshin Moradi","orcid":"0000-0003-1544-0992","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"IsomiR-eQTL: A Cancer-Specific Expression Quantitative Trait Loci Database of miRNAs and Their Isoforms","abstract":"<jats:p>The identification of expression quantitative trait loci (eQTL) is an important component in efforts to understand how genetic variants influence disease risk. MicroRNAs (miRNAs) are short noncoding RNA molecules capable of regulating the expression of several genes simultaneously. Recently, several novel isomers of miRNAs (isomiRs) that differ slightly in length and sequence composition compared to their canonical miRNAs have been reported. Here we present isomiR-eQTL, a user-friendly database designed to help researchers find single nucleotide polymorphisms (SNPs) that can impact miRNA (miR-eQTL) and isomiR expression (isomiR-eQTL) in 30 cancer types. The isomiR-eQTL includes a total of 152,671 miR-eQTLs and 2,390,805 isomiR-eQTLs at a false discovery rate (FDR) of 0.05. It also includes 65,733 miR-eQTLs overlapping known cancer-associated loci identified through genome-wide association studies (GWAS). To the best of our knowledge, this is the first study investigating the impact of SNPs on isomiR expression at the genome-wide level. This database may pave the way for researchers toward finding a model for personalised medicine in which miRNAs, isomiRs, and genotypes are utilised.</jats:p>","is_dataset_classified":null,"base_score":1.791759469228055,"endowment":1.791759469228055,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"36293349","pmcid":"PMC9604134","openalex_id":"https://openalex.org/W4306765284","authors":[],"funders":[{"funder_name":"Advance Queensland Industry Research Fellowship","grant_id":"","title":null},{"funder_name":"National Health and Medical Research Council Career Development Fellowship","grant_id":"","title":null},{"funder_name":"Queensland University of Technology Postgraduate Research Award","grant_id":"","title":null}],"total_grants":3,"fwci":0.3363,"citation_percentile":0.49210008,"influential_citations":0,"citation_trend":[{"year":2024,"count":3},{"year":2025,"count":1},{"year":2026,"count":1}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://www.mdpi.com/1422-0067/23/20/12493/pdf?version=1666099602","host_type":"journal"},{"url":"https://www.mdpi.com/1422-0067/23/20/12493/pdf?version=1666099602","host_type":"publisher"},{"url":"https://www.mdpi.com/1422-0067/23/20/12493/pdf","host_type":"publisher"},{"url":"https://doi.org/10.3390/ijms232012493","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/36293349","host_type":"repository"},{"url":"https://doaj.org/article/130d193e2fb94cdcb3af37bf8aaa5c47","host_type":"repository"},{"url":"https://dx.doi.org/10.3390/ijms232012493","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9604134","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC9604134","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC9604134?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["MicroRNA in disease regulation","Cancer-related molecular mechanisms research","RNA modifications and cancer"],"mesh_terms":["Humans","Neoplasms","Protein Isoforms","Polymorphism, Single Nucleotide","MicroRNAs","Quantitative Trait Loci","Genome-Wide Association Study"],"keywords":["Expression quantitative trait loci","Single-nucleotide polymorphism","Biology","Quantitative trait locus","Genome-wide association study","microRNA","Computational biology","Genetics","Genetic association","Gene","Genotype","miRNA","Gwas","Isomir","Mir-eqtl","Isomir-eqtl"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"refsnp"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-10T11:36:18.573732Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}