Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

Ana Jacinta-Fernandes; Joana M Xavier; Ramiro Magno; Joel G Lage; Ana-Teresa Maia

doi:10.1038/s41525-019-0112-9

Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

NPJ Genom Med. 2020 Feb 13:5:4. doi: 10.1038/s41525-019-0112-9. eCollection 2020.

Authors

Ana Jacinta-Fernandes^{1

2

3}, Joana M Xavier^{1

2

3}, Ramiro Magno^{2

3}, Joel G Lage^{1

2

3}, Ana-Teresa Maia^{1

2

3}

Affiliations

¹ 1Department of Biomedical Sciences and Medicine (DCBM), Universidade do Algarve, Faro, 8005-139 Portugal.
² 2Centre for Biomedical Research (CBMR), Universidade do Algarve, Faro, 8005-139 Portugal.
³ 3Algarve Biomedical Center (ABC), Universidade do Algarve, Faro, 8005-139 Portugal.

Abstract

Most breast cancer (BC) risk-associated single-nucleotide polymorphisms (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting microRNA (miRNA) genes and/or miRNA binding. To test this, we adapted two miRNA-binding prediction algorithms-TargetScan and miRanda-to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant ( $P \leq 5 \times 10^{- 8}$ ) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3'-untranslated regions of putative miRNA target genes were predicted to alter miRNA::mRNA (messenger RNA) pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and reinforce the role of miRNA-mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.

Keywords: Data mining; Risk factors.