Open main menu

Cis-regulatory module (CRM) is a stretch of DNA, usually 100–1000 DNA base pairs in length,[1] where a number of transcription factors can bind and regulate expression of nearby genes and regulate their transcription rates. They are labeled as cis because they are typically located on the same DNA strand as the genes they control as opposed to trans, which refers to effects on genes not located on the same strand or farther away, such as transcription factors.[1] One cis-regulatory element can regulate several genes,[2] and conversely, one gene can have several cis-regulatory modules.[3]Cis-regulatory modules carry out their function by integrating the active transcription factors and the associated co-factors at a specific time and place in the cell where this information is read and an output is given.[4]


Gene-regulation functionEdit

Diagram showing at which stages in the DNA-mRNA-protein pathway expression can be controlled

Cis-regulatory modules are one of several types of functional regulatory elements. Regulatory elements are binding sites for transcription factors, which are involved in gene regulation.[1] Cis-regulatory modules perform a large amount of developmental information processing.[1] Cis-regulatory modules are non-random clusters at their specified target site that contain transcription factor binding sites.[1]

The original definition presented cis-regulatory modules as enhancers of cis-acting DNA, which increased the rate of transcription from a linked promoter.[4] However, this definition has changed to define cis-regulatory modules as a DNA sequence with transcription factor binding sites which are clustered into modular structures, including -but not limited to- locus control regions, promoters, enhancers, silencers, boundary control elements and other modulators.[4]

Cis-regulatory modules can be divided into three classes; enhancers, which regulate gene expression positively;[1] insulators, which work indirectly by interacting with other nearby cis-regulatory modules; and [1] silencers that turn off expression of genes.[1]

The design of cis-regulatory modules is such that transcription factors and epigenetic modifications serve as inputs, and the output of the module is the command given to the transcription machinery, which in turn determines the rate of gene transcription or whether it is turned on or off.[1] There are two types of transcription factor inputs: those that determine when the target gene is to be expressed and those that serve as functional drivers, which come into play only during specific situations during development.[1] These inputs can come from different time points, can represent different signal ligands, or can come from different domains or lineages of cells. However, a lot still remains unknown.

Additionally, the regulation of chromatin structure and nuclear organization also play a role in determining and controlling the function of cis-regulatory modules.[4] Thus gene-regulation functions (GRF) provide a unique characteristic of a cis-regulatory module (CRM), relating the concentrations of transcription factors (input) to the promoter activities (output). The challenge is to predict GRFs. This challenge still remains unsolved. In general, gene-regulation functions do not use Boolean logic,[2] although in some cases the approximation of the Boolean logic is still very useful.

The Boolean logic assumptionEdit

Within the assumption of the Boolean logic, principles guiding the operation of these modules includes the design of the module which determines the regulatory function. In relation to development, these modules can generate both positive and negative outputs. The output of each module is a product of the various operations performed on it. Common operations include "OR" logic gate – This design indicates that in an output will be given when either input is given [3]. "AND" logic gate – In this design two different regulatory factors are necessary to make sure that a positive output results.[1] "Toggle Switches" – This design occurs when the signal ligand is absent while the transcription factor is present; this transcription factor ends up acting as a dominant repressor. However, once the signal ligand is present the transcription factor's role as repressor is eliminated and transcription can occur.[1]

Other Boolean logic operations can occur as well, such as sequence specific transcriptional repressors, which when they bind to the cis-regulatory module lead to an output of zero. Additionally, besides influence from the different logic operations, the output of a "cis"-regulatory module will also be influenced by prior events.[1] 4) Cis-regulatory modules must interact with other regulatory elements. For the most part, even with the presence of functional overlap between cis-regulatory modules of a gene, the modules' inputs and outputs tend to not be the same.[1]

While the assumption of Boolean logic is important for systems biology, detailed studies show that in general the logic of gene regulation is not Boolean.[2] This means, for example, that in the case of a cis-regulatory module regulated by two transcription factors, experimentally determined gene-regulation functions can not be described by the 16 possible Boolean functions of two variables. Non-Boolean extensions of the gene-regulatory logic have been proposed to correct for this issue.[2]

Identification and computational predictionEdit

Besides experimentally determining CRMs, there are various bioinformatics algorithms for predicting them. Most algorithms try to search for significant combinations of transcription factor binding sites (DNA binding sites) in promoter sequences of co-expressed genes.[5] More advanced methods combine the search for significant motifs with correlation in gene expression datasets between transcription factors and target genes.[6] Both methods have been implemented, for example, in the ModuleMaster. Other programs created for the identification and prediction of cis-regulatory modules include:

INSECT 2.0 [7] is a web server that allows to search Cis-regulatory modules in a genome-wide manner. The program relies on the definition of strict restrictions among the Transcription Factor Binding Sites (TFBSs) that compose the module in order to decrease the false positives rate. INSECT is designed to be user-friendly since it allows automatic retrieval of sequences and several visualizations and links to third-party tools in order to help users to find those instances that are more likely to be true regulatory sites. INSECT 2.0 algorithm was previously published and the algorithm and theory behind it explained in [8]

Stubb uses hidden Markov models to identify statistically significant clusters of transcription factor combinations. It also uses a second related genome to improve the prediction accuracy of the model.[9]

Bayesian Networks use an algorithm that combines site predictions and tissue-specific expression data for transcription factors and target genes of interest. This model also uses regression trees to depict the relationship between the identified cis-regulatory module and the possible binding set of transcription factors.[10]

CRÈME examine clusters of target sites for transcription factors of interest. This program uses a database of confirmed transcription factor binding sites that were annotated across the human genome. A search algorithm is applied to the data set to identify possible combinations of transcription factors, which have binding sites that are close to the promoter of the gene set of interest. The possible cis-regulatory modules are then statistically analyzed and the significant combinations are graphically represented [11]

Active cis-regulatory modules in a genomic sequence have been difficult to identify. Problems in identification arise because often scientists find themselves with a small set of known transcription factors, so it makes it harder to identify statistically significant clusters of transcription factor binding sites.[9] Additionally, high costs limit the use of large whole genome tiling arrays.[10]


Cis-regulatory modules can be characterized by the information processing that they encode and the organization of their transcription factor binding sites. Additionally, cis-regulatory modules are also characterized by the way they affect the probability, proportion, and rate of transcription.[4] Highly cooperative and coordinated cis-regulatory modules are classified as enhanceosomes.[4] The architecture and the arrangement of the transcription factor binding sites are critical because disruption of the arrangement could cancel out the function.[4] Functional flexible cis-regulatory modules are called billboards. Their transcriptional output is the summation effect of the bound transcription factors.[4] Enhancers affect the probability of a gene being activated, but have little or no effect on rate.[4] The Binary response model acts like an on/off switch for transcription. This model will increase or decrease the amount of cells that transcribe a gene, but it does not affect the rate of transcription.[4] Rheostatic response model describes cis-regulatory modules as regulators of the initiation rate of transcription of its associated gene.[4]

Mode of actionEdit

Cis-regulatory modules can regulate their target genes over large distances. Several models have been proposed to describe the way that these modules may communicate with their target gene promoter.[4] These include the DNA scanning model, the DNA sequence looping model and the facilitated tracking model. In the DNA scanning model, the transcription factor and cofactor complex form at the cis-regulatory module and then continues to move along the DNA sequence until it finds the target gene promoter.[4] In the looping model, the transcription factor binds to the cis-regulatory module, which then causes the looping of the DNA sequence and allows for the interaction with the target gene promoter. The transcription factor-cis-regulatory module complex causes the looping of the DNA sequence slowly towards the target promoter and forms a stable looped configuration.[4] The facilitated tracking model combines parts of the two previous models.

Cis-regulatory module in gene regulatory networkEdit

The function of a gene regulatory network depends on the architecture of the nodes, whose function is dependent on the multiple cis-regulatory modules.[1] The layout of cis-regulatory modules can provide enough information to generate spatial and temporal patterns of gene expression.[1] During development each domain, where each domain represents a different spatial regions of the embryo, of gene expression will be under the control of different cis-regulatory module(s).[1] The design of regulatory modules help in producing feedback, feed forward, and cross-regulatory loops.[12]

See alsoEdit


  1. ^ a b c d e f g h i j k l m n o p q Davidson EH (2006). The Regulatory Genome: Gene Regulatory Networks in Development and Evolution. Elsevier. pp. 1–86.
  2. ^ a b c d Teif V.B. (2010). "Predicting Gene-Regulation Functions: Lessons from Temperate Bacteriophages". Biophysical Journal. 98 (7): 1247–56. doi:10.1016/j.bpj.2009.11.046. PMC 2849075. PMID 20371324.
  3. ^ Ben-Tabou de-Leon S, Davidson EH (2007). "Gene regulation: gene control network in development". Annu Rev Biophys Biomol Struct. 36: 191–212. doi:10.1146/annurev.biophys.35.040405.102002. PMID 17291181.
  4. ^ a b c d e f g h i j k l m n Jeziorska DM, Jordan KW, Vance KW (2009). "A systems biology approach to understanding cis-regulatory module function". Semin. Cell Dev. Biol. 20: 856–862. doi:10.1016/j.semcdb.2009.07.007.
  5. ^ Aerts, S.; et al. (2003). "Computational detection of cis-regulatory modules". Bioinformatics. 19 Suppl 2: ii5–14. doi:10.1093/bioinformatics/btg1052. PMID 14534164.
  6. ^ Wrzodek, Clemens; Schröder, Adrian; Dräger, Andreas; Wanke, Dierk; Berendzen, Kenneth W.; Kronfeld, Marcel; Harter, Klaus; Zell, Andreas (2010). "ModuleMaster: A new tool to decipher transcriptional regulatory networks". Biosystems. Ireland: Elsevier. 99 (1): 79–81. doi:10.1016/j.biosystems.2009.09.005. ISSN 0303-2647. PMID 19819296.
  7. ^ Parra RG, Rohr CO, Koile D, Perez-Castro C, Yankilevich P (2015). "INSECT 2.0: a web-server for genome-wide cis-regulatory modules prediction". Bioinformatics. 32: 1229–31. doi:10.1093/bioinformatics/btv726. PMID 26656931.
  8. ^ Rohr CO, Parra RG, Yankilevich P, Perez-Castro C (2013). "INSECT: IN-silico SEarch for Co-occurring Transcription factors". Bioinformatics. 29: 2852–8. doi:10.1093/bioinformatics/btt506. PMID 24008418.
  9. ^ a b Sinha S, Liang Y, Siggia E (2006). "Stubb: a program for discovery and analysis of cis-regulatory modules". Nucleic Acids Res. 34 (Web Server issue): W555–W559. doi:10.1093/nar/gkl224. PMC 1538799. PMID 16845069.
  10. ^ a b Chen X, Blanchette M (2007). "Comparing sequences without using alignments: application to HIV/SIV subtyping". BMC Bioinformatics. 8: 1–17. doi:10.1186/1471-2105-8-1. PMC 1766362. PMID 17199892.
  11. ^ Sharan R, Ben-Hur A, Loots GG, Ovcharenko I (2004). "CREME: Cis-Regulatory Module Explorer for the human genome". Nucleic Acids Res. 32 (Web Server issue): W253–W256. doi:10.1093/nar/gkh385. PMC 441523. PMID 15215390.
  12. ^ Li E, Davidson EH (2009). "Building Developmental Gene Regulatory Networks". Birth Defects Res. 87 (2): 123–130. doi:10.1002/bdrc.20152. PMC 2747644. PMID 19530131.

External linksEdit