Guidelines for Genome-Scale Analysis of Biological Rhythms

Michael E. Hughes, Katherine C. Abruzzi, Ravi Allada, Ron Anafi, Alaaddin Bulak Arpat, Gad Asher, Pierre Baldi, Charissa de Bekker, Deborah Bell-Pedersen, Justin Blau, Steve Brown, M. Fernanda Ceriani, Zheng Chen, Joanna C. Chiu, Juergen Cox, Alexander M. Crowell, Jason P. DeBruyne, Derk Jan Dijk, Luciano DiTacchio, Francis J. Doyle & 73 others Giles E. Duffield, Jay C. Dunlap, Kristin Eckel-Mahan, Karyn A. Esser, Garret A. FitzGerald, Daniel B. Forger, Lauren J. Francey, Ying Hui Fu, Frédéric Gachon, David Gatfield, Paul de Goede, Susan S. Golden, Carla Green, John Harer, Stacey Harmer, Jeff Haspel, Michael H. Hastings, Hanspeter Herzel, Erik D. Herzog, Christy Hoffmann, Christian Hong, Jacob J. Hughey, Jennifer M. Hurley, Horacio O. de la Iglesia, Carl Johnson, Steve A. Kay, Nobuya Koike, Karl Kornacker, Achim Kramer, Katja Lamia, Tanya Leise, Scott A. Lewis, Jiajia Li, Xiaodong Li, Andrew C. Liu, Jennifer J. Loros, Tami A. Martino, Jerome S. Menet, Martha Merrow, Andrew J. Millar, Todd Mockler, Felix Naef, Emi Nagoshi, Michael N. Nitabach, Maria Olmedo, Dmitri A. Nusinow, Louis J. Ptáček, David Rand, Akhilesh B. Reddy, Maria S. Robles, Till Roenneberg, Michael Rosbash, Marc D. Ruben, Samuel S.C. Rund, Aziz Sancar, Paolo Sassone-Corsi, Amita Sehgal, Scott Sherrill-Mix, Debra J. Skene, Kai Florian Storch, Joseph S. Takahashi, Hiroki R. Ueda, Han Wang, Charles Weitz, Pål O. Westermark, Herman Wijnen, Ying Xu, Gang Wu, Seung Hee Yoo, Michael Young, Eric Erquan Zhang, Tomasz Zielinski, John B. Hogenesch

Research output: Contribution to journalArticle

Abstract

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

Original languageEnglish (US)
Pages (from-to)380-393
Number of pages14
JournalJournal of Biological Rhythms
Volume32
Issue number5
DOIs
StatePublished - Oct 1 2017

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Periodicity
Genome
Guidelines
Synthetic Biology
Benchmarking
Clinical Medicine
Research Design
Research Personnel
RNA
Proteins

Keywords

  • biostatistics
  • ChIP-seq
  • circadian rhythms
  • computational biology
  • diurnal rhythms
  • functional genomics
  • guidelines
  • metabolomics
  • proteomics
  • RNA-seq
  • systems biology

ASJC Scopus subject areas

  • Physiology
  • Physiology (medical)

Cite this

Hughes, M. E., Abruzzi, K. C., Allada, R., Anafi, R., Arpat, A. B., Asher, G., ... Hogenesch, J. B. (2017). Guidelines for Genome-Scale Analysis of Biological Rhythms. Journal of Biological Rhythms, 32(5), 380-393. https://doi.org/10.1177/0748730417728663

Guidelines for Genome-Scale Analysis of Biological Rhythms. / Hughes, Michael E.; Abruzzi, Katherine C.; Allada, Ravi; Anafi, Ron; Arpat, Alaaddin Bulak; Asher, Gad; Baldi, Pierre; de Bekker, Charissa; Bell-Pedersen, Deborah; Blau, Justin; Brown, Steve; Ceriani, M. Fernanda; Chen, Zheng; Chiu, Joanna C.; Cox, Juergen; Crowell, Alexander M.; DeBruyne, Jason P.; Dijk, Derk Jan; DiTacchio, Luciano; Doyle, Francis J.; Duffield, Giles E.; Dunlap, Jay C.; Eckel-Mahan, Kristin; Esser, Karyn A.; FitzGerald, Garret A.; Forger, Daniel B.; Francey, Lauren J.; Fu, Ying Hui; Gachon, Frédéric; Gatfield, David; de Goede, Paul; Golden, Susan S.; Green, Carla; Harer, John; Harmer, Stacey; Haspel, Jeff; Hastings, Michael H.; Herzel, Hanspeter; Herzog, Erik D.; Hoffmann, Christy; Hong, Christian; Hughey, Jacob J.; Hurley, Jennifer M.; de la Iglesia, Horacio O.; Johnson, Carl; Kay, Steve A.; Koike, Nobuya; Kornacker, Karl; Kramer, Achim; Lamia, Katja; Leise, Tanya; Lewis, Scott A.; Li, Jiajia; Li, Xiaodong; Liu, Andrew C.; Loros, Jennifer J.; Martino, Tami A.; Menet, Jerome S.; Merrow, Martha; Millar, Andrew J.; Mockler, Todd; Naef, Felix; Nagoshi, Emi; Nitabach, Michael N.; Olmedo, Maria; Nusinow, Dmitri A.; Ptáček, Louis J.; Rand, David; Reddy, Akhilesh B.; Robles, Maria S.; Roenneberg, Till; Rosbash, Michael; Ruben, Marc D.; Rund, Samuel S.C.; Sancar, Aziz; Sassone-Corsi, Paolo; Sehgal, Amita; Sherrill-Mix, Scott; Skene, Debra J.; Storch, Kai Florian; Takahashi, Joseph S.; Ueda, Hiroki R.; Wang, Han; Weitz, Charles; Westermark, Pål O.; Wijnen, Herman; Xu, Ying; Wu, Gang; Yoo, Seung Hee; Young, Michael; Zhang, Eric Erquan; Zielinski, Tomasz; Hogenesch, John B.

In: Journal of Biological Rhythms, Vol. 32, No. 5, 01.10.2017, p. 380-393.

Research output: Contribution to journalArticle

Hughes, ME, Abruzzi, KC, Allada, R, Anafi, R, Arpat, AB, Asher, G, Baldi, P, de Bekker, C, Bell-Pedersen, D, Blau, J, Brown, S, Ceriani, MF, Chen, Z, Chiu, JC, Cox, J, Crowell, AM, DeBruyne, JP, Dijk, DJ, DiTacchio, L, Doyle, FJ, Duffield, GE, Dunlap, JC, Eckel-Mahan, K, Esser, KA, FitzGerald, GA, Forger, DB, Francey, LJ, Fu, YH, Gachon, F, Gatfield, D, de Goede, P, Golden, SS, Green, C, Harer, J, Harmer, S, Haspel, J, Hastings, MH, Herzel, H, Herzog, ED, Hoffmann, C, Hong, C, Hughey, JJ, Hurley, JM, de la Iglesia, HO, Johnson, C, Kay, SA, Koike, N, Kornacker, K, Kramer, A, Lamia, K, Leise, T, Lewis, SA, Li, J, Li, X, Liu, AC, Loros, JJ, Martino, TA, Menet, JS, Merrow, M, Millar, AJ, Mockler, T, Naef, F, Nagoshi, E, Nitabach, MN, Olmedo, M, Nusinow, DA, Ptáček, LJ, Rand, D, Reddy, AB, Robles, MS, Roenneberg, T, Rosbash, M, Ruben, MD, Rund, SSC, Sancar, A, Sassone-Corsi, P, Sehgal, A, Sherrill-Mix, S, Skene, DJ, Storch, KF, Takahashi, JS, Ueda, HR, Wang, H, Weitz, C, Westermark, PO, Wijnen, H, Xu, Y, Wu, G, Yoo, SH, Young, M, Zhang, EE, Zielinski, T & Hogenesch, JB 2017, 'Guidelines for Genome-Scale Analysis of Biological Rhythms', Journal of Biological Rhythms, vol. 32, no. 5, pp. 380-393. https://doi.org/10.1177/0748730417728663
Hughes ME, Abruzzi KC, Allada R, Anafi R, Arpat AB, Asher G et al. Guidelines for Genome-Scale Analysis of Biological Rhythms. Journal of Biological Rhythms. 2017 Oct 1;32(5):380-393. https://doi.org/10.1177/0748730417728663
Hughes, Michael E. ; Abruzzi, Katherine C. ; Allada, Ravi ; Anafi, Ron ; Arpat, Alaaddin Bulak ; Asher, Gad ; Baldi, Pierre ; de Bekker, Charissa ; Bell-Pedersen, Deborah ; Blau, Justin ; Brown, Steve ; Ceriani, M. Fernanda ; Chen, Zheng ; Chiu, Joanna C. ; Cox, Juergen ; Crowell, Alexander M. ; DeBruyne, Jason P. ; Dijk, Derk Jan ; DiTacchio, Luciano ; Doyle, Francis J. ; Duffield, Giles E. ; Dunlap, Jay C. ; Eckel-Mahan, Kristin ; Esser, Karyn A. ; FitzGerald, Garret A. ; Forger, Daniel B. ; Francey, Lauren J. ; Fu, Ying Hui ; Gachon, Frédéric ; Gatfield, David ; de Goede, Paul ; Golden, Susan S. ; Green, Carla ; Harer, John ; Harmer, Stacey ; Haspel, Jeff ; Hastings, Michael H. ; Herzel, Hanspeter ; Herzog, Erik D. ; Hoffmann, Christy ; Hong, Christian ; Hughey, Jacob J. ; Hurley, Jennifer M. ; de la Iglesia, Horacio O. ; Johnson, Carl ; Kay, Steve A. ; Koike, Nobuya ; Kornacker, Karl ; Kramer, Achim ; Lamia, Katja ; Leise, Tanya ; Lewis, Scott A. ; Li, Jiajia ; Li, Xiaodong ; Liu, Andrew C. ; Loros, Jennifer J. ; Martino, Tami A. ; Menet, Jerome S. ; Merrow, Martha ; Millar, Andrew J. ; Mockler, Todd ; Naef, Felix ; Nagoshi, Emi ; Nitabach, Michael N. ; Olmedo, Maria ; Nusinow, Dmitri A. ; Ptáček, Louis J. ; Rand, David ; Reddy, Akhilesh B. ; Robles, Maria S. ; Roenneberg, Till ; Rosbash, Michael ; Ruben, Marc D. ; Rund, Samuel S.C. ; Sancar, Aziz ; Sassone-Corsi, Paolo ; Sehgal, Amita ; Sherrill-Mix, Scott ; Skene, Debra J. ; Storch, Kai Florian ; Takahashi, Joseph S. ; Ueda, Hiroki R. ; Wang, Han ; Weitz, Charles ; Westermark, Pål O. ; Wijnen, Herman ; Xu, Ying ; Wu, Gang ; Yoo, Seung Hee ; Young, Michael ; Zhang, Eric Erquan ; Zielinski, Tomasz ; Hogenesch, John B. / Guidelines for Genome-Scale Analysis of Biological Rhythms. In: Journal of Biological Rhythms. 2017 ; Vol. 32, No. 5. pp. 380-393.
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T1 - Guidelines for Genome-Scale Analysis of Biological Rhythms

AU - Hughes, Michael E.

AU - Abruzzi, Katherine C.

AU - Allada, Ravi

AU - Anafi, Ron

AU - Arpat, Alaaddin Bulak

AU - Asher, Gad

AU - Baldi, Pierre

AU - de Bekker, Charissa

AU - Bell-Pedersen, Deborah

AU - Blau, Justin

AU - Brown, Steve

AU - Ceriani, M. Fernanda

AU - Chen, Zheng

AU - Chiu, Joanna C.

AU - Cox, Juergen

AU - Crowell, Alexander M.

AU - DeBruyne, Jason P.

AU - Dijk, Derk Jan

AU - DiTacchio, Luciano

AU - Doyle, Francis J.

AU - Duffield, Giles E.

AU - Dunlap, Jay C.

AU - Eckel-Mahan, Kristin

AU - Esser, Karyn A.

AU - FitzGerald, Garret A.

AU - Forger, Daniel B.

AU - Francey, Lauren J.

AU - Fu, Ying Hui

AU - Gachon, Frédéric

AU - Gatfield, David

AU - de Goede, Paul

AU - Golden, Susan S.

AU - Green, Carla

AU - Harer, John

AU - Harmer, Stacey

AU - Haspel, Jeff

AU - Hastings, Michael H.

AU - Herzel, Hanspeter

AU - Herzog, Erik D.

AU - Hoffmann, Christy

AU - Hong, Christian

AU - Hughey, Jacob J.

AU - Hurley, Jennifer M.

AU - de la Iglesia, Horacio O.

AU - Johnson, Carl

AU - Kay, Steve A.

AU - Koike, Nobuya

AU - Kornacker, Karl

AU - Kramer, Achim

AU - Lamia, Katja

AU - Leise, Tanya

AU - Lewis, Scott A.

AU - Li, Jiajia

AU - Li, Xiaodong

AU - Liu, Andrew C.

AU - Loros, Jennifer J.

AU - Martino, Tami A.

AU - Menet, Jerome S.

AU - Merrow, Martha

AU - Millar, Andrew J.

AU - Mockler, Todd

AU - Naef, Felix

AU - Nagoshi, Emi

AU - Nitabach, Michael N.

AU - Olmedo, Maria

AU - Nusinow, Dmitri A.

AU - Ptáček, Louis J.

AU - Rand, David

AU - Reddy, Akhilesh B.

AU - Robles, Maria S.

AU - Roenneberg, Till

AU - Rosbash, Michael

AU - Ruben, Marc D.

AU - Rund, Samuel S.C.

AU - Sancar, Aziz

AU - Sassone-Corsi, Paolo

AU - Sehgal, Amita

AU - Sherrill-Mix, Scott

AU - Skene, Debra J.

AU - Storch, Kai Florian

AU - Takahashi, Joseph S.

AU - Ueda, Hiroki R.

AU - Wang, Han

AU - Weitz, Charles

AU - Westermark, Pål O.

AU - Wijnen, Herman

AU - Xu, Ying

AU - Wu, Gang

AU - Yoo, Seung Hee

AU - Young, Michael

AU - Zhang, Eric Erquan

AU - Zielinski, Tomasz

AU - Hogenesch, John B.

PY - 2017/10/1

Y1 - 2017/10/1

N2 - Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

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KW - ChIP-seq

KW - circadian rhythms

KW - computational biology

KW - diurnal rhythms

KW - functional genomics

KW - guidelines

KW - metabolomics

KW - proteomics

KW - RNA-seq

KW - systems biology

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