Navigation Links
Assortativity signatures of transcription factor networks contribute to robustness
Date:8/29/2014

Dartmouth researchers explored the type and number of connections in transcription factor networks (TFNs) to evaluate the role assortativity plays on robustness in a study published in PLOS Computational Biology in August. The study found that the assortativity signature contributes to a network's resilience against mutations.

"In simulations, it seems that varying the out-out assortativity of TFN models has a greater effect on robustness than varying any of the other three types of assortativity," said Dov A. Pechenick, PhD, lead author and former researcher at the Computational Genetics Laboratory at Dartmouth College, Hanover, NH. "We determined this by varying all four types of assortativity in the signature and then measuring robustness."

Transcription factors (TFs) are proteins that initiate and regulate the expression of a gene. To achieve their genetic mission, TFs also regulate one another's expression. Individual TFs connect to each other through connections that point in or out, forming a network. The direction of the coupling indicates regulatory control; an outbound connection by one TF stipulates its control over another, whereby it turns that TF on or off with respect to gene expression.

Many such connected pairings occur in a network, and their types determine a network's assortativity, which measures whether these pairings tend to occur between TFs that have similar numbers of connections. For example, when TFs in a pairing are likely to possess similar numbers of outgoing connections, out-out assortativity is high. If they are likely to possess very different numbers of incoming connections, in-in assortativity is low. Taken together, measures for the different kinds of assortativity create a signature. According to Pechenick, "There are four types of assortativity in directed networks, and the assortativity signature is a way of looking at all four at once."

Pechenick and his Dartmouth co-authors evaluated the assortativity signatures in published TFNs of 41 distinct human cell and tissue types and found that an above average number of connected TFs had similar numbers of outgoing connections (high out-out assortativity). Furthermore, this property, more so than the other three types of assortativity, seemed to be a predictor of robustness.

"Robustness is a measure of how resilient an overall pattern of TF gene expression is over time when confronted with mutations in the regulatory instructions of these TFs. If mutations tend to change the pattern, then robustness is low. If mutations tend to have no effect on the pattern, then robustness is high," said Pechenick.

This Dartmouth study was the first to look at the assortativity signatures of TFNs and their impact on robustness. "Results suggest that measuring the assortativity signature of a TFN can tell you something about its robustness," said Pechenick. "For researchers that wish to understand and simulate biological networks, these results indicate the importance of considering assortativity."


'/>"/>

Contact: Donna Dubuc
Donna.M.Dubuc@Dartmouth.edu
603-653-3615
The Geisel School of Medicine at Dartmouth
Source:Eurekalert

Related biology news :

1. Epigenetic signatures direct the repair potential of reprogrammed cells
2. Biosignatures distinguish between tuberculosis and sarcoidosis
3. Oncogenic signatures mapped in TCGA a guide for the development of personalized therapy
4. Signatures of selection inscribed on poplar genomes
5. Study demonstrates cells can acquire new functions through transcriptional regulatory network
6. Transcription factor Lyl-1 critical in producing early T-cell progenitors
7. NIH backs Rice University study of delay in gene transcription networks
8. Stay-at-home transcription factor prevents neurodegeneration
9. FASEB SRC announces: Mechanism and Regulation of Prokaryotic Transcription Conference
10. Transcription factor may protect against hepatic injury caused by hepatitis C and alcohol
11. System-wide analyses have underestimated the importance of transcription in animals
Post Your Comments:
*Name:
*Comment:
*Email:
(Date:1/21/2016)... PUNE, India , January 21, 2016 /PRNewswire/ ... According to a new market research report "Emotion ... Learning, and Others), Software Tools (Facial Expression, Voice ... and Regions - Global forecast to 2020", published ... Market is expected to reach USD 22.65 Billion ...
(Date:1/15/2016)... JUAN, Puerto Rico , Jan. 15, 2016 /PRNewswire/ ... companies big and small to find new ways to ... driven culture. iOS and Android ... device based on biometrics, transforming it into a hardware ... request that users swipe their fingerprint on their KodeKey ...
(Date:1/8/2016)... ANGELES and MANCHESTER, United Kingdom ... ("BBI"), a developer of innovative sensor-based diagnostic products, today announced ... financed by new and existing investors.  Proceeds from the financing ... SEM Scanner , a hand-held device for detecting early-stage pressure ... Ireland after receiving CE Mark approval. ...
Breaking Biology News(10 mins):
(Date:2/9/2016)... ... February 09, 2016 , ... With a presidential election in November ... Business Conference will bring together over 500 top healthcare leaders for a night and ... The conference, organized by MBA students of the University of Pennsylvania’s Wharton School, will ...
(Date:2/9/2016)... (PRWEB) , ... February 09, 2016 , ... Tunnell Consulting, ... Based in Paris, he will focus on acquiring new accounts and work closely ... , “Fred brings to our European clients more than 15 years ...
(Date:2/9/2016)... This market research report on the global ... of the market in terms of revenue (USD Million). ... the manufacture of microbiology culture media and related products. ... snapshot providing the overall information of various market segments ... also provides the overall information and data analysis of ...
(Date:2/8/2016)... BIOREM Inc. (TSXV: BRM) ("Biorem" or "the Company") today announced ... companies in the TSX Venture 50 TM . ... TSX Venture Exchange, in each of five major industry sectors ... life sciences, diversified industries and technology – based on a ... market cap growth, trading volume and analyst coverage. All data ...
Breaking Biology Technology: