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 language | English (US) |
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Pages (from-to) | 380-393 |
Number of pages | 14 |
Journal | Journal of biological rhythms |
Volume | 32 |
Issue number | 5 |
DOIs | |
State | Published - Oct 1 2017 |
Funding
We thank members of the Hughes and Hogenesch labs for useful comments during the drafting of this article. We thank the organizers of the \u201CBig Data\u201D workshop during the 2016 meeting of the Society for Research on Biological Rhythms for providing the initial impetus for exploring the issues discussed herein. Work in the Hughes Lab is supported by an award from NIAMS (1R21AR069266) and start-up funds from the Department of Medicine at Washington University in St. Louis. The work of Pierre Baldi is supported in part by DARPA grant D17AP00002. Charissa de Bekker is supported by start-up funds from the Department of Biology at the University of Central Florida in Orlando, Florida. Justin Blau\u2019s laboratory is supported by National Institutes of Health (NIH) grant GM063911. Zheng Chen\u2019s lab is supported by the Robert A. Welch Foundation (AU-1731) and NIH/National Institute on Aging (R01AG045828). Work in Joanna Chiu\u2019s laboratory is supported by NIH R01 GM102225 and National Science Foundation (NSF) IOS 1456297. Alexander M. Crowell and Jay C. Dunlap are supported by R35GM118021 and by U01EB022546. Jason DeBruyne\u2019s lab is supported by National Institute of Neurological Disorders and Stroke (NINDS) U54 NS083932 and National Institute of General Medical Sciences (NIGMS) SC1 GM109861. Derk-Jan Dijk is supported by the Biotechnology and Biological Sciences Research Council and a Royal Society Wolfson Research Merit Award. Work in Giles Duffield\u2019s lab is supported by NIGMS (R01-GM087508) and the Eck Institute for Global Health. Work in Susan S. Golden\u2019s laboratory is supported by NIH award R35GM118290. Work in Carla Green\u2019s laboratory is supported by NIH grants R01GM112991, R01GM111387, and R01AG045795. Work in Stacey Harmer\u2019s laboratory is supported by NIH award R01GM069418 and NSF award IOS1238040. Work in Michael Hastings\u2019s lab is supported by the UK Medical Research Council (MC_ U105170643). Erik D. Herzog\u2019s lab is supported by NIH grants U01EB021956, R01NS095367, and R01GM104991. Work in the Hong laboratory is supported by the National Institute of Allergy and Infectious Diseases (U19AI116491). Work in the Hurley lab is supported by an award from National Institute of Biomedical Imaging and Bioengineering (1U01EB022546) and start-up funds from the Department of Biological Sciences at Rensselaer Polytechnic Institute. Horacio de la Iglesia is supported by NIH award R01 NS094211. Nobuya Koike is supported by JSPS KAKENHI grant JP26293048. Work in Achim Kramer\u2019s laboratory is supported by the Deutsche Forschungsgemeinschaft (SFB740/D2 and TRR186/A17). Related work in the Lamia lab is supported by an award from the National Institute of Diabetes and Digestive and Kidney Diseases (DK097164). Andrew C. Liu is supported by NIH grant NINDS R01NS054794. Jennifer J. Loros is supported by R35GM118022. Tami A. Martino\u2019s laboratory is supported by the Canadian Institutes of Health Research and the Heart and Stroke Foundation of Canada. Work in the Merrow lab is supported by a grant from the STW (Dutch Foundation for Technology and Science), the Volkswagen Foundation, and funds from the Ludwig-Maximilians University Munich. Work in the laboratory of Michael N. Nitabach is supported in part by NINDS, NIH (R01NS091070) and NIGMS, NIH (R01GM098931). Work in the Nusinow lab is supported by NSF grant IOS-1456796. Maria Olmedo is supported by the Ram\u00F3n y Cajal program of the Spanish Ministerio de Econom\u00EDa y Competitividad (RYC-2014-15551). Akhilesh B. Reddy is supported by the Wellcome Trust (100333/Z/12/Z) and the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001534), the U.K. Medical Research Council (FC001534), and the Wellcome Trust (FC001534). Maria Robles\u2019s lab is supported by start-up funds from the Ludwig-Maximiliam University, Munich, Germany. Samuel S. C. Rund is funded by the Royal Society (NF140517). Han Wang is funded by the grants from National Basic Research Program of China (973 Program; 2012CB947600) and the National Natural Science Foundation of China (31030062, 81570171, 81070455). P\u00E5l O. Westermark is funded by the Leibniz Institute for Farm Animal Biology. Herman Wijnen is funded by a Biotechnology and Biological Science Research Council grant BB/L023067/1 and EU Marie Sklodowska Curie Career Integration grant 618563. Seung-Hee Yoo\u2019s lab is supported by NIH/NIGMS (R01GM114424). John Hogenesch is supported by the NINDS (5R01NS05479).
Keywords
- ChIP-seq
- RNA-seq
- biostatistics
- circadian rhythms
- computational biology
- diurnal rhythms
- functional genomics
- guidelines
- metabolomics
- proteomics
- systems biology
ASJC Scopus subject areas
- Physiology
- Physiology (medical)