Transcriptome Analysis Identified Gene Regulation Networks in Soybean Leaves Perturbed by the Coronatine Toxin

The non-host specific Pseudomonas syringae phytotoxin Coronatine (COR) causes chlorosis and promotes toxicity by inducing physiological changes in plants. We performed transcriptome analysis to better understand plants' transcriptional and metabolic response to COR. Toward this end, mock-treated and COR-treated soybean plants were analyzed by RNA-Seq. A total of 4,545 genes were differentially expressed between the two treatments, of which 2,170 were up-regulated whereas 2,375 were down-regulated in COR treated samples. Gene annotation and pathway analysis conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases revealed that the differential genes were involved in photosynthesis, jasmonic acid (JA) synthesis, signal transduction, and phenylpropane metabolism. This study will provide new insights into COR mediated responses and extend our understanding of COR function in plants.

Introducing Trait Networks to Elucidate the Fluidity of Organismal Evolution Using Palaeontological Data

Explaining the evolution of animals requires ecological, developmental, paleontological, and phylogenetic considerations because organismal traits are affected by complex evolutionary processes. Modeling a plurality of processes, operating at distinct time-scales on potentially interdependent traits, can benefit from approaches that are complementary treatments to phylogenetics. Here, we developed an inclusive network approach, implemented in the command line software ComponentGrapher, and analyzed trait co-occurrence of rhinocerotoid mammals. We identified stable, unstable, and pivotal traits, as well as traits contributing to complexes, that may follow to a common developmental regulation, that point to an early implementation of the postcranial Bauplan among rhinocerotoids. Strikingly, most identified traits are highly dissociable, used repeatedly in distinct combinations and in different taxa, which usually do not form clades. Therefore, the genes encoding these traits are likely recruited into novel gene regulation networks during the course of evolution. Our evo-systemic framework, generalizable to other evolved organizations, supports a pluralistic modeling of organismal evolution, including trees and networks.

Evolutionary constraints in regulatory networks defined by partial order between phenotypes

Gene regulation networks allow organisms to adapt to diverse environmental niches. However, the constraints underlying the evolution of regulatory phenotypes remain ill-defined both theoretically and experimentally. Here, we show that the concept of partial order identifies such constraints, and test the predictions by experimentally evolving an engineered signal-integrating network in multiple environments. We find that populations: 1) expand in fitness space along the Pareto-optimal front predicted by conflicts in regulatory demands, by fine-tuning binding affinities within the network, 2) expand beyond this constraint by changes in the network structure, thus allowing access to new fitness domains. Strikingly, the constraint predictions are based on whether the network output increases or decreases in response to the different signals, and do not require information on the network architecture or underlying genetics. Overall, our findings show that limited knowledge on current regulatory phenotypes can provide predictions on future evolutionary constraints.

Traces of transposable elements in genome dark matter co-opted by flowering gene regulation networks

1AbstractTransposable elements (TEs) are mobile, repetitive DNA sequences that make the largest contribution to genome bulk. They thus contribute to the so-called “dark matter of the genome”, the part of the genome in which nothing is immediately recognizable as biologically functional.We developed a new method, based on k-mers, to identify degenerate TE sequences. With this new algorithm, we detect up to 10% of the A. thaliana genome as derived from as yet unidentified TEs, bringing the proportion of the genome known to be derived from TEs up to 50%. A significant proportion of these sequences overlapped conserved non-coding sequences identified in crucifers and rosids, and transcription factor binding sites. They are overrepresented in some gene regulation networks, such as the flowering gene network, suggesting a functional role for these sequences that have been conserved for more than 100 million years, since the spread of flowering plants in the Cretaceous.

Current Advances on the Important Roles of Enhancer RNAs in Gene Regulation and Cancer

Revealing the gene regulation networks governing cancer initiation and development is necessary while it remains uncompleted. In recent years, enhancers have been reported to be widely transcribed, resulting in the generation of enhancer RNAs (eRNAs). Previous studies have reported that eRNAs are a subclass of long noncoding RNAs (lncRNAs), which play a critical role in gene regulation and cancer development. These eRNAs can promote enhancer-promoter (E-P) looping formation by binding to other protein factors or propel expression of downstream protein-coding gene. In this review, we have focused on the characteristics of eRNAs and illustrated the biological function and potential mechanism of eRNAs in regulating gene expression and cancer development.