Robustness of transcriptional regulatory program influences gene expression variability

Transcriptomic analysis reveals the rareness of genetic assimilation of gene expression in environmental adaptations

Genetic assimilation is the evolutionary process by which an environmentally induced phenotype becomes genetically encoded and constitutive. Genetic assimilation has been proposed as a concluding step in environmental adaptation, but its prevalence has not been systematically investigated. Analyzing transcriptomic data collected upon reciprocal transplant, we address this question in the experimental evolution, domestication, or natural evolution of seven diverse species. We find that genetic assimilation of environment-induced gene expression is the exception rather than the rule and that substantially more genes retain than lose their expression plasticity upon organismal adaptations to new environments. The probability of genetic assimilation of gene expression decreases with the expression level and number of transcription factors controlling the gene, suggesting that genetic assimilation results primarily from passive losses of gene regulations that are not mutationally robust. Hence, for gene expression, our findings argue against the purported generality or importance of genetic assimilation to environmental adaptation.

Resilience, plasticity and robustness in gene expression during aging in the brain of outbred deer mice

BACKGROUND

Genes that belong to the same network are frequently co-expressed, but collectively, how the coordination of the whole transcriptome is perturbed during aging remains unclear. To explore this, we calculated the correlation of each gene in the transcriptome with every other, in the brain of young and older outbred deer mice (P. leucopus and P. maniculatus).

RESULTS

In about 25 % of the genes, coordination was inversed during aging. Gene Ontology analysis in both species, for the genes that exhibited inverse transcriptomic coordination during aging pointed to alterations in the perception of smell, a known impairment occurring during aging. In P. leucopus, alterations in genes related to cholesterol metabolism were also identified. Among the genes that exhibited the most pronounced inversion in their coordination profiles during aging was THBS4, that encodes for thrombospondin-4, a protein that was recently identified as rejuvenation factor in mice. Relatively to its breadth, abolishment of coordination was more prominent in the long-living P. leucopus than in P. maniculatus but in the latter, the intensity of de-coordination was higher.

CONCLUSIONS

There sults suggest that aging is associated with more stringent retention of expression profiles for some genes and more abrupt changes in others, while more subtle but widespread changes in gene expression appear protective. Our findings shed light in the mode of the transcriptional changes occurring in the brain during aging and suggest that strategies aiming to broader but more modest changes in gene expression may be preferrable to correct aging-associated deregulation in gene expression.

Topological clustering of regulatory genes confers pathogenic tolerance to cassava brown streak virus (CBSV) in cassava

Robustness, a naïve property of biological systems, enables organisms to maintain functions during perturbation and is crucial for improving the resilience of crops to prevailing stress conditions and diseases, guaranteeing food security. Most studies of robustness in crops have focused on genetic superiority based upon individual genes, overlooking the collaborative actions of multiple responsive genes and the regulatory network topology. This research aims to uncover patterns of gene cooperation leading to organismal robustness by studying the topology of gene co-expression networks (GCNs) of both CBSV virus resistant and susceptible cassava cultivars. The resulting GCNs show higher topological clustering of cooperative genes in the resistant cultivar, suggesting that the network architecture is central to attaining robustness. Despite a reduction in the number of hub genes in the resistant cultivar following the perturbation, essential biological functions contained in the network were maintained through neighboring genes that withstood the shock. The susceptible cultivar seemingly coped by inducing more gene actions in the network but could not maintain the functions required for plant growth. These findings underscore the importance of regulatory network architecture in ensuring phenotypic robustness and deepen our understanding of transcriptional regulation.

Multiplexed Gene Expression Tuning with Orthogonal Synthetic Gene Circuits

Understanding the individual and joint contribution of multiple protein levels toward a phenotype requires precise and tunable multigene expression control. Here we introduce a pair of mammalian synthetic gene circuits that linearly and orthogonally control the expression of two reporter genes in mammalian cells with low variability in response to chemical inducers introduced into the growth medium. These gene expression systems can be used to simultaneously probe the individual and joint effects of two gene product concentrations on a cellular phenotype in basic research or biomedical applications.

A set of AP2-like genes is associated with inflorescence branching and architecture in domesticated rice

Rice yield is influenced by inflorescence size and architecture, and inflorescences from domesticated rice accessions produce more branches and grains. Neither the molecular control of branching nor the developmental differences between wild and domesticated rice accessions are fully understood. We surveyed phenotypes related to branching, size, and grain yield across 91 wild and domesticated African and Asian accessions. Characteristics related to axillary meristem identity were the main phenotypic differences between inflorescences from wild and domesticated accessions. We used whole transcriptome sequencing in developing inflorescences to measure gene expression before and after the transition from branching axillary meristems to determinate spikelet meristems. We identified a core set of genes associated with axillary meristem identity in Asian and African rice, and another set associated with phenotypic variability between wild and domesticated accessions. AP2/EREBP-like genes were enriched in both sets, suggesting that they are key factors in inflorescence branching and rice domestication. Our work has identified new candidates in the molecular control of inflorescence development and grain yield, and provides a detailed description of the effects of domestication on phenotype and gene expression.

The role of the genome in experience-dependent plasticity: Extending the analogy of the genomic action potential

Our past experiences shape our current and future behavior. These experiences must leave some enduring imprint on our brains, altering neural circuits that mediate behavior and contributing to our individual differences. As a framework for understanding how experiences might produce lasting changes in neural circuits, Clayton [D. F. Clayton, Neurobiol. Learn. Mem. 74, 185-216 (2000)] introduced the concept of the genomic action potential (gAP)-a structured genomic response in the brain to acute experience. Similar to the familiar electrophysiological action potential (eAP), the gAP also provides a means for integrating afferent patterns of activity but on a slower timescale and with longer-lasting effects. We revisit this concept in light of contemporary work on experience-dependent modification of neural circuits. We review the "Immediate Early Gene" (IEG) response, the starting point for understanding the gAP. We discuss evidence for its involvement in the encoding of experience to long-term memory across time and biological levels of organization ranging from individual cells to cell ensembles and whole organisms. We explore distinctions between memory encoding and homeostatic functions and consider the potential for perpetuation of the imprint of experience through epigenetic mechanisms. We describe a specific example of a gAP in humans linked to individual differences in the response to stress. Finally, we identify key objectives and new tools for continuing research in this area.

Functional redundancy of transcription factors explains why most binding targets of a transcription factor are not affected when the transcription factor is knocked out

Background

Biologists are puzzled by the extremely low percentage (3%) of the binding targets of a yeast transcription factor (TF) affected when the TF is knocked out, a phenomenon observed by comparing the TF binding dataset and TF knockout effect dataset.

Results

This study gives a plausible biological explanation of this counterintuitive phenomenon. Our analyses find that TFs with high functional redundancy show significantly lower percentage than do TFs with low functional redundancy. This suggests that functional redundancy may lead to one TF compensating for another, thus masking the TF knockout effect on the binding targets of the knocked-out TF. In addition, we show that seven classes of genes (lowly expressed genes, TATA box-less genes, genes containing a nucleosome-free region immediately upstream of the transcriptional start site (TSS), genes with low transcriptional plasticity, genes with a low number of bound TFs, genes with a low number of TFBSs, and genes with a short average distance of TFBSs to the TSS) are insensitive to the knockout of their promoter-binding TFs, providing clues for finding other biological explanations of the surprisingly low percentage of the binding targets of a TF affected when the TF is knocked out.

Conclusions

This study shows that one property of TFs (functional redundancy) and seven properties of genes (expression level, TATA box, nucleosome, transcriptional plasticity, the number of bound TFs, the number of TFBSs, and the average distance of TFBSs to the TSS) may be useful for explaining a counterintuitive phenomenon: most binding targets of a yeast transcription factor are not affected when the transcription factor is knocked out.

Gene expression profiling for targeted cancer treatment

INTRODUCTION

There is certain degree of frustration and discontent in the area of microarray gene expression data analysis of cancer datasets. It arises from the mathematical problem called 'curse of dimensionality,' which is due to the small number of samples available in training sets, used for calculating transcriptional signatures from the large number of differentially expressed (DE) genes, measured by microarrays. The new generation of causal reasoning algorithms can provide solutions to the curse of dimensionality by transforming microarray data into activity of a small number of cancer hallmark pathways. This new approach can make feature space dimensionality optimal for mathematical signature calculations.

AREAS COVERED

The author reviews the reasons behind the current frustration with transcriptional signatures derived from DE genes in cancer. He also provides an overview of the novel methods for signature calculations based on differentially variable genes and expression regulators. Furthermore, the authors provide perspectives on causal reasoning algorithms that use prior knowledge about regulatory events described in scientific literature to identify expression regulators responsible for the differential expression observed in cancer samples.

EXPERT OPINION

The author advocates causal reasoning methods to calculate cancer pathway activity signatures. The current challenge for these algorithms is in ensuring quality of the knowledgebase. Indeed, the development of cancer hallmark pathway collections, together with statistical algorithms to transform activity of expression regulators into pathway activity, are necessary for causal reasoning to be used in cancer research.

Identifying aging-related genes in mouse hippocampus using gateway nodes

Background

High-throughput studies continue to produce volumes of metadata representing valuable sources of information to better guide biological research. With a stronger focus on data generation, analysis models that can readily identify actual signals have not received the same level of attention. This is due in part to high levels of noise and data heterogeneity, along with a lack of sophisticated algorithms for mining useful information. Networks have emerged as a powerful tool for modeling high-throughput data because they are capable of representing not only individual biological elements but also different types of relationships en masse. Moreover, well-established graph theoretic methodology can be applied to network models to increase efficiency and speed of analysis. In this project, we propose a network model that examines temporal data from mouse hippocampus at the transcriptional level via correlation of gene expression. Using this model, we formally define the concept of “gateway” nodes, loosely defined as nodes representing genes co-expressed in multiple states. We show that the proposed network model allows us to identify target genes implicated in hippocampal aging-related processes.

Results

By mining gateway genes related to hippocampal aging from networks made from gene expression in young and middle-aged mice, we provide a proof-of-concept of existence and importance of gateway nodes. Additionally, these results highlight how network analysis can act as a supplement to traditional statistical analysis of differentially expressed genes. Finally, we use the gateway nodes identified by our method as well as functional databases and literature to propose new targets for study of aging in the mouse hippocampus.

Conclusions

This research highlights the need for methods of temporal comparison using network models and provides a systems biology approach to extract information from correlation networks of gene expression. Our results identify a number of genes previously implicated in the aging mouse hippocampus related to synaptic plasticity and apoptosis. Additionally, this model identifies a novel set of aging genes previously uncharacterized in the hippocampus. This research can be viewed as a first-step for identifying the processes behind comparative experiments in aging that is applicable to any type of temporal multi-state network.