Framework for microRNA variant annotation and prioritization using human population and disease datasets.

TitleFramework for microRNA variant annotation and prioritization using human population and disease datasets.
Publication TypeJournal Article
Year of Publication2019
AuthorsOak, N, Ghosh, R, Huang, K-L, Wheeler, DA, Ding, L, Plon, SE
JournalHum Mutat
Volume40
Issue1
Pagination73-89
Date Published2019 Jan
ISSN1098-1004
KeywordsAnimals, Base Sequence, Conserved Sequence, Databases, Genetic, Disease, Exome Sequencing, Genetics, Population, Genome, Human, Germ-Line Mutation, Humans, MicroRNAs, Molecular Sequence Annotation, Neoplasms, Phylogeny, Vertebrates
Abstract

MicroRNA (miRNA) expression is frequently deregulated in human disease, in contrast, disease-associated miRNA mutations are understudied. We developed Annotative Database of miRNA Elements, ADmiRE, which combines multiple existing and new biological annotations to aid prioritization of causal miRNA variation. We annotated 10,206 mature (3,257 within seed region) miRNA variants from multiple large sequencing datasets including gnomAD (15,496 genomes; 123,136 exomes). The pattern of miRNA variation closely resembles protein-coding exonic regions, with no difference between intragenic and intergenic miRNAs (P = 0.56), and high confidence miRNAs demonstrate higher sequence constraint (P < 0.001). Conservation analysis across 100 vertebrates identified 765 highly conserved miRNAs that also have limited genetic variation in gnomAD. We applied ADmiRE to the TCGA PanCancerAtlas WES dataset containing over 10,000 individuals across 33 adult cancers and annotated 1,267 germline (rare in gnomAD) and 1,492 somatic miRNA variants. Several miRNA families with deregulated gene expression in cancer have low levels of both somatic and germline variants, e.g., let-7 and miR-10. In addition to known somatic miR-142 mutations in hematologic cancers, we describe novel somatic miR-21 mutations in esophageal cancers impacting downstream miRNA targets. Through the development of ADmiRE, we present a framework for annotation and prioritization of miRNA variation in disease datasets.

DOI10.1002/humu.23668
Alternate JournalHum Mutat
PubMed ID30302893
PubMed Central IDPMC6400659
Grant List5U01HG007436-03 / HG / NHGRI NIH HHS / United States
R01 CA138836 / CA / NCI NIH HHS / United States
R01-CA138836 / CA / NCI NIH HHS / United States
U41HG009649-01 / HG / NHGRI NIH HHS / United States
U41 HG009649 / HG / NHGRI NIH HHS / United States
U01 HG007436 / HG / NHGRI NIH HHS / United States
RP10189 / / Cancer Prevention and Research Institute of Texas / International

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