About CIRCA

Over the last two decades and together with our collaborators, our lab has created datasets, made databases, and built algorithms in wide use in the circadian community and beyond. This includes the Gene Atlas¹ and Gene Wiki^2,3, CircaDB⁴, and several algorithms including JTK⁵, PSEA⁶, MetaCycle⁷, and CYCLOPS⁸. In the spirit of open science, these resources and algorithms were made available and in use by thousands of researchers all over the world.

We’ve done the definitive work on the mammalian circadian transcriptome. In 2002, we showed that ∼10% of the mouse liver transcriptome was under clock control, including many key components of cellular pathways (e.g. HMG-CoA reductase)⁹. In 2009 using high resolution time sampling, we found 10x more clock regulated genes and hundreds of 2nd (12hr) and dozens of 3rd (8hr) harmonics of circadian transcription¹⁰. Later we showed that these harmonics depend on an intact circadian clock¹¹. In 2014, we completed the profiling of 12 mouse organs and showed that 43% of protein encoding genes and a majority of disease genes and drug targets are clock-regulated genes¹². Last year, we published CYCLOPS, an algorithm to extract periodicity from unordered, large scale data, and applied it to thousands of human liver, brain, lung, and cancer samples⁸. This year we used CYCLOPS to create a database of circadian transcriptional rhythms from 13 human organ systems¹³. These latter observations have clear implications for chronotherapy, timed dosing of drugs, to improve their therapeutic index in cancer, cardiovascular disease, and many other areas. To make these data available, we built CircaDB.

We have always felt that making data public is the right thing to do but not enough to catalyze real progress. To this end, with our colleagues Andy Su and Angel Pizarro, we created CircaDB. The goal of CircaDB is to allow everyday biologists to answer simple questions like, “what genes cycle in my organ of interest?”, “where does my gene cycle?” CircaDB allows these questions to be answer quickly and effectively, with link outs to Wikipedia, HomoloGene, Refseq, etc.. We put in sensible statistical defaults, but let users select their favorite algorithms^14,15, Q-value cutoff, phase range, or download the raw data. For the literati, we link to all the data in the About page, as well as to references for the algorithms used. The database is in use by hundreds of researchers all over the world without restriction. (I am a regular user as it is the most efficient way for me to answer these types of questions too.)

References

1. Su AI, Wiltshire T, Batalov S, Lapp H, Ching KA, Block D, Zhang J, Soden R, Hayakawa M, Kreiman G, Cooke MP, Walker JR, Hogenesch JB. A gene atlas of the mouse and human protein-encoding transcriptomes. Proc Natl Acad Sci U S A. 2004 Apr 20;101(16):6062–6067. PMCID: PMC395923   PubMed

2. Huss JW 3rd, Lindenbaum P, Martone M, Roberts D, Pizarro A, Valafar F, Hogenesch JB, Su AI. The Gene Wiki: community intelligence applied to human gene annotation. Nucleic Acids Res. 2010 Jan;38(Database issue):D633–9. PMCID: PMC2808918   PubMed

3. Hogenesch JB, Su AI. Clock gene wikis available: join the “long tail”. J Biol Rhythms. 2008 Oct;23(5):456–457. PMID: 18838611   PubMed

4. Pizarro A, Hayer K, Lahens NF, Hogenesch JB. CircaDB: a database of mammalian circadian gene expression profiles. Nucleic Acids Res. 2013 Jan;41(Database issue):D1009–13. PMCID: PMC3531170   PubMed

5. Hughes ME, Hogenesch JB, Kornacker K. JTK_CYCLE: an efficient nonparametric algorithm for detecting rhythmic components in genome-scale data sets. J Biol Rhythms. 2010 Oct;25(5):372–380. PMCID: PMC3119870   PubMed

6. Zhang R, Podtelezhnikov AA, Hogenesch JB, Anafi RC. Discovering Biology in Periodic Data through Phase Set Enrichment Analysis (PSEA). J Biol Rhythms. 2016 Jun;31(3):244–257. PMID: 26955841   PubMed

7. Wu G, Anafi RC, Hughes ME, Kornacker K, Hogenesch JB. MetaCycle: an integrated R package to evaluate periodicity in large scale data. Bioinformatics. 2016 Nov 1;32(21):3351–3353. PMCID: PMC5079475   PubMed

8. Anafi RC, Francey LJ, Hogenesch JB, Kim J. CYCLOPS reveals human transcriptional rhythms in health and disease. Proc Natl Acad Sci U S A. 2017 May 16;114(20):5312–5317. PMCID: PMC5441789   PubMed

9. Panda S, Antoch MP, Miller BH, Su AI, Schook AB, Straume M, Schultz PG, Kay SA, Takahashi JS, Hogenesch JB. Coordinated transcription of key pathways in the mouse by the circadian clock. Cell. 2002 May 3;109(3):307–320. PMID: 12015981   PubMed

10. Hughes ME, DiTacchio L, Hayes KR, Vollmers C, Pulivarthy S, Baggs JE, Panda S, Hogenesch JB. Harmonics of circadian gene transcription in mammals. PLoS Genet. 2009 Apr;5(4):e1000442. PMCID: PMC2654964   PubMed

11. Hughes ME, Hong H-K, Chong JL, Indacochea AA, Lee SS, Han M, Takahashi JS, Hogenesch JB. Brain-specific rescue of Clock reveals system-driven transcriptional rhythms in peripheral tissue. PLoS Genet. 2012 Jul 26;8(7):e1002835. PMCID: PMC3405989   PubMed

12. Zhang R, Lahens NF, Ballance HI, Hughes ME, Hogenesch JB. A circadian gene expression atlas in mammals: implications for biology and medicine. Proc Natl Acad Sci U S A. 2014 Nov 11;111(45):16219–16224. PMCID: PMC4234565   PubMed

13. Ruben MD, Wu G, Smith DF, Schmidt RE, Francey LJ, Lee YY, Anafi RC, Hogenesch JB. A database of tissue-specific rhythmically expressed human genes has potential applications in circadian medicine. Sci Transl Med. 2018 Sep 12;10(458). PMID: 30209245   PubMed   Sci Transl Med

14. Glynn EF, Chen J, Mushegian AR. Detecting periodic patterns in unevenly spaced gene expression time series using Lomb–Scargle periodograms. Bioinformatics. Oxford University Press; 2006 Feb 1;22(3):310–316.   PubMed

15. de Lichtenberg U, Jensen LJ, Fausbøll A, Jensen TS, Bork P, Brunak S. Comparison of computational methods for the identification of cell cycle-regulated genes. Bioinformatics. 2005 Apr 1;21(7):1164–1171. PMID: 15513999   PubMed

Data references

Dataset	Paper	Source
Cosinor regression output for 13 human tissues	Ruben et al., Sci Transl Med, 2018	download data
Human GTEx collections of RNA-seq	GTEx consortium, Nat. Genet, 2013	GTEx Portal
Mouse 12 organs 1.0ST 2014	Zhang and Lahens et al., PNAS, 2014	GSE54652
Mouse Liver 48 hour Hughes 2009	Hughes et al., PLoS Genetics, 2009	GSE11923
Mouse Pituitary 48 hour Hughes 2009	Hughes et al., PLoS Genetics, 2009	download data
Mouse NIH 3T3 Immortalized Cell Line 48 hour Hughes 2009	Hughes et al., PLoS Genetics, 2009	GSE11922
Human U2 OS Hughes 2009	Hughes et al., PLoS Genetics, 2009	GSE13949
Mouse Wild Type Liver	Miller et al., WT and Clock livers, 2007	GSE3748
Mouse Wild Type Muscle	Andrews et al., WT and Clock skeletal muscle	GSE3748
Mouse Liver Panda 2002	Panda et al., Cell, 2002	download data
Mouse SCN MAS4 Panda 2002	Panda et al., Cell, 2002	download data
Mouse SCN gcrma Panda 2002	Panda et al., Cell, 2002	download data
Mouse Aorta MU74v2	Rudic et al., PLoS Biology, 2004	GSE414
Mouse Kidney MU74v2	Rudic et al., PLoS Biology, 2004	GSE414
Mouse Distal Colon 2008	Hoogerwerf et al., Gastroenterology, 2008	GSE10644
Mouse Macrophages DD 2010	Keller et al., Proc Natl Acad Sci U S A, 2009	GSE25585

Links

Hogenesch Lab

Su Lab

Hughes Lab

Anafi Lab

Requesting Addition of New Data Sets

Researchers can request that a particular data set be added by submitting an issue at our project page hosted at Github.

Source Code

Circadb is open source Ruby on Rails application and available under github.com/circadb. Circadb is licensed under the GNU General Public License (GPL-2.0).

Recent updates

Update - 9/12/2018	14 human tissues are added to the database
Update - 8/13/2015	Two new datasets: "Mouse SCN" and "Mouse spleen" are now available
Update - 6/9/2014	We added two new datasets: "Mouse Macrophages" and "Mouse Heart LD"
Update - 9/27/2013	RNA-seq data is now available for all Mouse 1.OST experiments
Update - 9/23/2013	Wildcard search is now enabled
Update - 5/16/2013	Mouse Distal Colon data sets added to CircaDB.