Uncoupling gene expression noise along the central dogma using genome engineered human cell lines

Quarton, Tyler; Kang, Taek Jin; Papakis, Vasileios; Nguyen, Khai T.; Nowak, Chance M.; Li, Yi; Bleris, Leonidas

doi:10.1093/nar/gkaa668

Cited by 28 publications

(43 citation statements)

References 49 publications

(20 reference statements)

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“…The stochasticity of gene expression is a well-known fact [70–78] and known to arise from the transcription machinery [79]. Post-transcriptional gene regulation is similarly well-known [80–85].…”

Section: Discussionmentioning

confidence: 99%

Identification ofFoxPcircuits involved in locomotion and object fixation inDrosophila

Palazzo

Rass

Brembs

2020

Preprint

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The FoxP family of transcription factors is necessary for operant self-learning, an evolutionary conserved form of motor learning. The expression pattern, molecular function and mechanisms of action of the Drosophila FoxP orthologue remain to be elucidated. By editing the genomic locus of FoxP with CRISPR/Cas9, we find that the three different FoxP isoforms are expressed in neurons, but not in glia and that not all neurons express all isoforms. Furthermore, we detect FoxP expression in, e.g., the protocerebral bridge, the fan shaped body and in motorneurons, but not in the mushroom bodies. Finally, we discover that FoxP expression during development, but not adulthood, is required for normal locomotion and landmark fixation in walking flies. While FoxP expression in the protocerebral bridge and motorneurons is involved in locomotion and landmark fixation, the FoxP gene can be deleted from dorsal cluster neurons and mushroom-body Kenyon cells without affecting these behaviors.

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Section: Discussionmentioning

confidence: 99%

Identification ofFoxPcircuits involved in locomotion and object fixation inDrosophila

Palazzo

Rass

Brembs

2020

Preprint

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“…Second, microbial communities are three-dimensional structures that play a crucial role in ecosystem functioning and are not directly assessed by gene presence [52]. Third, different levels of protein activity can be found in different species or among populations of the same species due to transcriptional or post-translational modifications [53]. Forth, temporal and spatial variability of environmental conditions and community dynamics need to be accounted for when demonstrating microbial interactions [50].…”

Section: Validation Of Putative Microbial Interaction Through Integramentioning

confidence: 99%

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Saraiva¹,

Worrich²,

Karakoç³

et al. 2021

Preprint

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Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used to define the building blocks to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.

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“…The dual-reporter method requires distinguishable measurements of transcripts or proteins from two independent and identically distributed reporter genes integrated into the same cell. In practice however, dual reporters rarely have identical dynamics, which is widely considered to be a significant challenge to interpreting experimental results (16). We show that, under certain conditions, the decomposition in Eq.…”

Section: Resolving Non-identifiabilitymentioning

confidence: 99%

“…Dual-reporter assays have been employed experimentally to study the noise contributed by both global and gene-specific effects (13–15). A particular challenge, however, is that dual reporters are rarely identically regulated (15, 16), and are not straightforward to set up in many systems. More recently, there have been some efforts in developing alternative methods for decomposing noise (16, 17).…”

Section: Introductionmentioning

confidence: 99%

“…A particular challenge, however, is that dual reporters are rarely identically regulated (15, 16), and are not straightforward to set up in many systems. More recently, there have been some efforts in developing alternative methods for decomposing noise (16, 17). Here we develop a direct generalisation of the original contribution of (2), that enables an analogous noise decomposition to be obtained from non-identical and not-necessarily independent reporters.…”

Section: Introductionmentioning

confidence: 99%

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Pathway dynamics can delineate the sources of transcriptional noise in gene expression

Ham

Jackson

Stumpf

2020

Preprint

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Single-cell expression profiling is destructive, giving rise to only static snapshots of cellular states. This loss of temporal information presents significant challenges in inferring dynamics from population data. Here we provide a formal analysis of the extent to which dynamic variability from within individual systems ("intrinsic noise") is distinguishable from variability across the population ("extrinsic noise"). Our results mathematically formalise observations that it is impossible to identify these sources of variability from the transcript abundance distribution alone. Notably, we find that systems subject to population variation invariably inflate the apparent degree of burstiness of the underlying process. Such identifiability problems can be remedied by the dual-reporter method, which separates the total gene expression noise into intrinsic and extrinsic contributions. This noise decomposition, however, requires strictly independent and identical gene reporters integrated into the same cell, which can be difficult to implement experimentally in many systems. Here we demonstrate mathematically that, in some cases, the same noise decomposition can be achieved at the transcriptional level with non-identical and not-necessarily independent reporters. We use our result to show that generic reporters lying in the same biochemical pathways (e.g. mRNA and protein) can replace dual reporters, enabling the noise decomposition to be obtained from only a single gene. Stochastic simulations are used to support our theory, and show that our "pathway-reporter" method compares favourably to the dual-reporter method.

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Uncoupling gene expression noise along the central dogma using genome engineered human cell lines

Cited by 28 publications

References 49 publications

Identification ofFoxPcircuits involved in locomotion and object fixation inDrosophila

Identification ofFoxPcircuits involved in locomotion and object fixation inDrosophila

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Pathway dynamics can delineate the sources of transcriptional noise in gene expression

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