A comprehensive map of alternative polyadenylation in African American and European American lung cancer patients
Adriana Zingone,
Sanju Sinha,
Michael Ante,
Cu Nguyen,
Dalia Daujotyte,
Elise D. Bowman,
Neelam Sinha,
Khadijah A. Mitchell,
Qingrong Chen,
Chunhua Yan,
Phillipe Loher,
Daoud Meerzaman,
Eytan Ruppin and
Bríd M. Ryan ()
Additional contact information
Adriana Zingone: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute
Sanju Sinha: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute
Michael Ante: Lexogen GmbH
Cu Nguyen: Computational Genomics Research, Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute
Dalia Daujotyte: Lexogen GmbH
Elise D. Bowman: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute
Neelam Sinha: Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute
Khadijah A. Mitchell: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute
Qingrong Chen: Computational Genomics Research, Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute
Chunhua Yan: Computational Genomics Research, Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute
Phillipe Loher: Computational Medicine Center, Sidney Kimmel Medical College, Thomas Jefferson University
Daoud Meerzaman: Computational Genomics Research, Center for Biomedical Informatics and Information Technology (CBIIT), National Cancer Institute
Eytan Ruppin: Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute
Bríd M. Ryan: Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute
Nature Communications, 2021, vol. 12, issue 1, 1-12
Abstract:
Abstract Deciphering the post-transcriptional mechanisms (PTM) regulating gene expression is critical to understand the dynamics underlying transcriptomic regulation in cancer. Alternative polyadenylation (APA)—regulation of mRNA 3′UTR length by alternating poly(A) site usage—is a key PTM mechanism whose comprehensive analysis in cancer remains an important open challenge. Here we use a method and analysis pipeline that sequences 3′end-enriched RNA directly to overcome the saturation limitation of traditional 5′–3′ based sequencing. We comprehensively map the APA landscape in lung cancer in a cohort of 98 tumor/non-involved tissues derived from European American and African American patients. We identify a global shortening of 3′UTR transcripts in lung cancer, with notable functional implications on the expression of both coding and noncoding genes. We find that APA of non-coding RNA transcripts (long non-coding RNAs and microRNAs) is a recurrent event in lung cancer and discover that the selection of alternative polyA sites is a form of non-coding RNA expression control. Our results indicate that mRNA transcripts from EAs are two times more likely than AAs to undergo APA in lung cancer. Taken together, our findings comprehensively map and identify the important functional role of alternative polyadenylation in determining transcriptomic heterogeneity in lung cancer.
Date: 2021
References: Add references at CitEc
Citations:
Downloads: (external link)
https://www.nature.com/articles/s41467-021-25763-5 Abstract (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25763-5
Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/
DOI: 10.1038/s41467-021-25763-5
Access Statistics for this article
Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie
More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().