Local genetic context shapes the function of a gene regulatory network

Staroń, Anna; Tomasek, Kathrin; Carter, Caroline Caruso; Sonnleitner, Elisabeth; Kavčič, Bor; Paixão, Tiago; Guet, Călin C.

doi:10.7554/elife.65993

Cited by 23 publications

(16 citation statements)

References 90 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, our findings are consistent with divergent supercoiling competition, but the effect size is small (Figure 6 ). Genetic interference effects can be further complicated by transcription units without completely insulating terminators ( 61 ). Subtleties in the exact genetic construct design and spacing are likely responsible for variations in effect size reported between and within studies.…”

Section: Discussionmentioning

confidence: 99%

Genetic context effects can override canonical cis regulatory elements in Escherichia coli

Scholz

Lindeboom

Freddolino

2022

Nucleic Acids Research

View full text Add to dashboard Cite

Recent experiments have shown that in addition to control by cis regulatory elements, the local chromosomal context of a gene also has a profound impact on its transcription. Although this chromosome-position dependent expression variation has been empirically mapped at high-resolution, the underlying causes of the variation have not been elucidated. Here, we demonstrate that 1 kb of flanking, non-coding synthetic sequences with a low frequency of guanosine and cytosine (GC) can dramatically reduce reporter expression compared to neutral and high GC-content flanks in Escherichia coli. Natural and artificial genetic context can have a similarly strong effect on reporter expression, regardless of cell growth phase or medium. Despite the strong reduction in the maximal expression level from the fully-induced reporter, low GC synthetic flanks do not affect the time required to reach the maximal expression level after induction. Overall, we demonstrate key determinants of transcriptional propensity that appear to act as tunable modulators of transcription, independent of regulatory sequences such as the promoter. These findings provide insight into the regulation of naturally occurring genes and an independent control for optimizing expression of synthetic biology constructs.

show abstract

Section: Discussionmentioning

confidence: 99%

Genetic context effects can override canonical cis regulatory elements in Escherichia coli

Scholz

Lindeboom

Freddolino

2022

Nucleic Acids Research

View full text Add to dashboard Cite

show abstract

“…It is not clear yet to what extent regulatory interactions between the regulons of certain TFs overlap with one another within the cell's regulatory network. For example, it is challenging to predict whether two TFs within distinct regulatory networks are neutral with respect to one another, or if they exhibit positive or negative synergies ( 10 ). Some multilayered regulatory networks are clearly subject to regulatory cross-talk, a situation where one TF could affect the regulatory loop of another TF ( 11–13 ).…”

Section: Introductionmentioning

confidence: 99%

Molecular basis for lethal cross-talk between two unrelated bacterial transcription factors - the regulatory protein of a restriction-modification system and the repressor of a defective prophage

Wiśniewska

Wons

Potrykus

et al. 2022

Nucleic Acids Research

View full text Add to dashboard Cite

Bacterial gene expression depends on the efficient functioning of global transcriptional networks, however their interconnectivity and orchestration rely mainly on the action of individual DNA binding proteins called transcription factors (TFs). TFs interact not only with their specific target sites, but also with secondary (off-target) sites, and vary in their promiscuity. It is not clear yet what mechanisms govern the interactions with secondary sites, and how such rewiring affects the overall regulatory network, but this could clearly constrain horizontal gene transfer. Here, we show the molecular mechanism of one such off-target interaction between two unrelated TFs in Escherichia coli: the C regulatory protein of a Type II restriction-modification system, and the RacR repressor of a defective prophage. We reveal that the C protein interferes with RacR repressor expression, resulting in derepression of the toxic YdaT protein. These results also provide novel insights into regulation of the racR-ydaST operon. We mapped the C regulator interaction to a specific off-target site, and also visualized C protein dynamics, revealing intriguing differences in single molecule dynamics in different genetic contexts. Our results demonstrate an apparent example of horizontal gene transfer leading to adventitious TF cross-talk with negative effects on the recipient's viability. More broadly, this study represents an experimentally-accessible model of a regulatory constraint on horizontal gene transfer.

show abstract

“…GRN inference remains a challenging task because of the inherent complexity of transcriptional regulation, as well as the high dimensionality and noise in biological datasets. Furthermore, GRNs are dynamic and context-specific [2,3], i.e. some regulatory processes are active only in certain cell types, tissues, conditions, or in response to specific stimuli.…”

Section: Introductionmentioning

confidence: 99%

Inference of differential gene regulatory networks from gene expression data using boosted differential trees

Galindez

List

Baumbach

et al. 2022

Preprint

View full text Add to dashboard Cite

Diseases can be caused by molecular perturbations that induce specific changes in regulatory interactions and their coordinated expression, also referred to as network rewiring. However, the detection of complex changes in regulatory connections remains a challenging task and would benefit from the development of novel non-parametric approaches. We developed a new ensemble method called BoostDiff (boosted differential regression trees) to infer a differential network discriminating between two conditions. BoostDiff builds an adaptively boosted (AdaBoost) ensemble of differential trees with respect to a target condition. To build the differential trees, we propose differential variance improvement as a novel splitting criterion. Variable importance measures derived from the resulting models are used to reflect changes in gene expression predictability and to build the output differential networks. BoostDiff outperforms existing differential network methods on simulated data evaluated in two different complexity settings. We then demonstrate the power of our approach when applied to real transcriptomics data in COVID-19 and Crohn's disease. BoostDiff identifies context-specific networks that are enriched with genes of known disease-relevant pathways and complements standard differential expression analyses. BoostDiff is available at https://github.com/gihannagalindez/boostdiff_inference .

show abstract

Local genetic context shapes the function of a gene regulatory network

Cited by 23 publications

References 90 publications

Genetic context effects can override canonical cis regulatory elements in Escherichia coli

Genetic context effects can override canonical cis regulatory elements in Escherichia coli

Molecular basis for lethal cross-talk between two unrelated bacterial transcription factors - the regulatory protein of a restriction-modification system and the repressor of a defective prophage

Inference of differential gene regulatory networks from gene expression data using boosted differential trees

Contact Info

Product

Resources

About