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Non-coding RNAs underlie genetic predisposition to breast cancer

Authors :
Moradi Marjaneh, M
Beesley, J
O'Mara, TA
Mukhopadhyay, P
Koufariotis, LT
Kazakoff, S
Hussein, N
Fachal, L
Bartonicek, N
Hillman, KM
Kaufmann, S
Sivakumaran, H
Smart, CE
McCart Reed, AE
Ferguson, K
Saunus, JM
Lakhani, SR
Barnes, DR
Antoniou, AC
Dinger, ME
Waddell, N
Easton, DF
Dunning, AM
Chenevix-Trench, G
Edwards, SL
French, JD
Moradi Marjaneh, M
Beesley, J
O'Mara, TA
Mukhopadhyay, P
Koufariotis, LT
Kazakoff, S
Hussein, N
Fachal, L
Bartonicek, N
Hillman, KM
Kaufmann, S
Sivakumaran, H
Smart, CE
McCart Reed, AE
Ferguson, K
Saunus, JM
Lakhani, SR
Barnes, DR
Antoniou, AC
Dinger, ME
Waddell, N
Easton, DF
Dunning, AM
Chenevix-Trench, G
Edwards, SL
French, JD
Publication Year :
2020

Abstract

Background: Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear. Results: Using targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants. Conclusions: We have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits.

Details

Database :
OAIster
Publication Type :
Electronic Resource
Accession number :
edsoai.on1183379006
Document Type :
Electronic Resource