The landscape of long noncoding RNAs in the human transcriptome

Matthew K. Iyer; Yashar S. Niknafs; Rohit Malik; Udit Singhal; Anirban Sahu; Yasuyuki Hosono; Terrence R. Barrette; John R. Prensner; Joseph R. Evans; Shuang Zhao; Anton Poliakov; Xuhong Cao; Saravana M. Dhanasekaran; Yi Mi Wu; Dan R. Robinson; David G. Beer; Felix Y. Feng; Hariharan K. Iyer; Arul M. Chinnaiyan

doi:10.1038/ng.3192

The landscape of long noncoding RNAs in the human transcriptome

Matthew K. Iyer, Yashar S. Niknafs, Rohit Malik, Udit Singhal, Anirban Sahu, Yasuyuki Hosono, Terrence R. Barrette, John R. Prensner, Joseph R. Evans, Shuang Zhao, Anton Poliakov, Xuhong Cao, Saravana M. Dhanasekaran, Yi Mi Wu, Dan R. Robinson, David G. Beer, Felix Y. Feng, Hariharan K. Iyer, Arul M. Chinnaiyan^*

^*Corresponding author for this work

Anesthesiology

Research output: Contribution to journal › Article › peer-review

2252 Scopus citations

Abstract

Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.

Original language	English (US)
Pages (from-to)	199-208
Number of pages	10
Journal	Nature Genetics
Volume	47
Issue number	3
DOIs	https://doi.org/10.1038/ng.3192
State	Published - Feb 25 2015

Funding

We thank B. Palen and J. Hallum for technical assistance with the high-performance computing cluster, S. Roychowdhury for reviewing the manuscript, the University of Michigan DNA Sequencing Core for Sanger sequencing and K. Giles for critically reading the manuscript and for the submission of documents. This work was supported in part by US National Institutes of Health Prostate Specialized Program of Research Excellence grant P50 CA69568, Early Detection Research Network grant UO1 CA111275, US National Institutes of Health grants R01 CA132874 and RO1 CA154365 (D.G.B. and A.M.C.), and US Department of Defense grant PC100171 (A.M.C.). A.M.C. is supported by the Prostate Cancer Foundation and the Howard Hughes Medical Institute. A.M.C. is an American Cancer Society Research Professor and a Taubman Scholar of the University of Michigan. R.M. was supported by a Prostate Cancer Foundation Young Investigator Award and by US Department of Defense Post-Doctoral Fellowship W81XWH-13-1-0284. Y.S.N. is supported by a University of Michigan Cellular and Molecular Biology National Research Service Award Institutional Predoctoral Training Grant.

ASJC Scopus subject areas

Genetics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Iyer, M. K., Niknafs, Y. S., Malik, R., Singhal, U., Sahu, A., Hosono, Y., Barrette, T. R., Prensner, J. R., Evans, J. R., Zhao, S., Poliakov, A., Cao, X., Dhanasekaran, S. M., Wu, Y. M., Robinson, D. R., Beer, D. G., Feng, F. Y., Iyer, H. K., & Chinnaiyan, A. M. (2015). The landscape of long noncoding RNAs in the human transcriptome. Nature Genetics, 47(3), 199-208. https://doi.org/10.1038/ng.3192

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title = "The landscape of long noncoding RNAs in the human transcriptome",

abstract = "Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.",

author = "Iyer, {Matthew K.} and Niknafs, {Yashar S.} and Rohit Malik and Udit Singhal and Anirban Sahu and Yasuyuki Hosono and Barrette, {Terrence R.} and Prensner, {John R.} and Evans, {Joseph R.} and Shuang Zhao and Anton Poliakov and Xuhong Cao and Dhanasekaran, {Saravana M.} and Wu, {Yi Mi} and Robinson, {Dan R.} and Beer, {David G.} and Feng, {Felix Y.} and Iyer, {Hariharan K.} and Chinnaiyan, {Arul M.}",

note = "Funding Information: We thank B. Palen and J. Hallum for technical assistance with the high-performance computing cluster, S. Roychowdhury for reviewing the manuscript, the University of Michigan DNA Sequencing Core for Sanger sequencing and K. Giles for critically reading the manuscript and for the submission of documents. This work was supported in part by US National Institutes of Health Prostate Specialized Program of Research Excellence grant P50 CA69568, Early Detection Research Network grant UO1 CA111275, US National Institutes of Health grants R01 CA132874 and RO1 CA154365 (D.G.B. and A.M.C.), and US Department of Defense grant PC100171 (A.M.C.). A.M.C. is supported by the Prostate Cancer Foundation and the Howard Hughes Medical Institute. A.M.C. is an American Cancer Society Research Professor and a Taubman Scholar of the University of Michigan. R.M. was supported by a Prostate Cancer Foundation Young Investigator Award and by US Department of Defense Post-Doctoral Fellowship W81XWH-13-1-0284. Y.S.N. is supported by a University of Michigan Cellular and Molecular Biology National Research Service Award Institutional Predoctoral Training Grant.",

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Iyer, MK, Niknafs, YS, Malik, R, Singhal, U, Sahu, A, Hosono, Y, Barrette, TR, Prensner, JR, Evans, JR, Zhao, S, Poliakov, A, Cao, X, Dhanasekaran, SM, Wu, YM, Robinson, DR, Beer, DG, Feng, FY, Iyer, HK & Chinnaiyan, AM 2015, 'The landscape of long noncoding RNAs in the human transcriptome', Nature Genetics, vol. 47, no. 3, pp. 199-208. https://doi.org/10.1038/ng.3192

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AU - Malik, Rohit

AU - Singhal, Udit

AU - Sahu, Anirban

AU - Hosono, Yasuyuki

AU - Barrette, Terrence R.

AU - Prensner, John R.

AU - Evans, Joseph R.

AU - Zhao, Shuang

AU - Poliakov, Anton

AU - Cao, Xuhong

AU - Dhanasekaran, Saravana M.

AU - Wu, Yi Mi

AU - Robinson, Dan R.

AU - Beer, David G.

AU - Feng, Felix Y.

AU - Iyer, Hariharan K.

AU - Chinnaiyan, Arul M.

N1 - Funding Information: We thank B. Palen and J. Hallum for technical assistance with the high-performance computing cluster, S. Roychowdhury for reviewing the manuscript, the University of Michigan DNA Sequencing Core for Sanger sequencing and K. Giles for critically reading the manuscript and for the submission of documents. This work was supported in part by US National Institutes of Health Prostate Specialized Program of Research Excellence grant P50 CA69568, Early Detection Research Network grant UO1 CA111275, US National Institutes of Health grants R01 CA132874 and RO1 CA154365 (D.G.B. and A.M.C.), and US Department of Defense grant PC100171 (A.M.C.). A.M.C. is supported by the Prostate Cancer Foundation and the Howard Hughes Medical Institute. A.M.C. is an American Cancer Society Research Professor and a Taubman Scholar of the University of Michigan. R.M. was supported by a Prostate Cancer Foundation Young Investigator Award and by US Department of Defense Post-Doctoral Fellowship W81XWH-13-1-0284. Y.S.N. is supported by a University of Michigan Cellular and Molecular Biology National Research Service Award Institutional Predoctoral Training Grant.

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N2 - Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.

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The landscape of long noncoding RNAs in the human transcriptome

Abstract

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ASJC Scopus subject areas

UN SDGs

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