Inference and Differential Analysis of Extended Core Networks: a way to study Anti-Sense Regulation

A key issue in bioinformatics is to decipher cell regulation mechanisms. By comparing networks observed in two different situations, differential network analysis enables to highlight differences that reveal specific cellular responses. The aim of our work is to study the role of natural anti-sense transcription on cellular regulation mechanisms. Our proposal is to build and compare networks obtained from two different sets of actors: the “usual” sense actors on one hand and the sense and anti-sense actors on the other hand. Our study only considers themost significant interactions, called an Extended Core Network; therefore our differential analysis identifies important interactions that are on the influence of anti-sense transcription. Our inference method of an Extended Core Network is inspired by C3NET, but whereas C3NET only computes one interaction per gene, we propose to consider the most significant interactions for each gene. We define the differential network analysis of two extended core networks inferred with and without anti-sense actors. This relies on change motifs that describe which gene-gene interactions of the extended core network are modified when we integrate anti-sense actors in the data. As our method ocuses on the most significant interactions, these motifs highlight the impact of anti-sense transcription. The networks motifs obtained by our workflow are then compared with assessed biological knowledge. The study reported in this paper is realized on transcriptional data from apple fruit in a context of fruit ripening; the change motifs revealed by our analysis are matched on a protein-protein interaction network and give a small set of interesting actors thatdeserve further biological investigation

Differential Network Analysis of Anti-sense Regulation

A challenging task in systems biology is to decipher cell regulation mechanisms. By comparing networks observed in two different situations, the differential network analysis approach enables to highlight interaction differences that reveal specific cellular responses. The aim of our work is to study the role of natural anti-sense transcription on cellular regulation mechanisms. Our proposal is to build and compare networks obtained from two different sets of actors: the “usual” sense actors on one hand and the sense and anti-sense actors on the other hand. Our study only considers the most significant interactions, called an Extended Core Network; therefore our differential analysis identifies important interactions that are impacted by anti-sense transcription. This paper first introduces our inference method of an Extended Core Network; this method is inspired by C3NET, but whereas C3NET only computes one interaction per gene, we propose to consider the most significant interactions for each gene. Secondly, we define the differential network analysis of two extended core networks inferred with and without anti-sense actors. On a local view, this analysis relies on change motifs that describe which genes have their most important interactions modified when the anti-sense transcripts are considered; they are called AS-impacted genes. Then from a more global view, we consider how the relationships between these AS-impacted genes are rewired in the network with anti-sense actors. Our analysis is performed by computing Steiner trees that represent minimal subnetworks connecting the AS-impacted genes. We show that the visualisation of these results help the biologists to identify interesting parts of the networks

Differential Functional Analysis and Change Motifs in Gene Networks to Explore the Role of Anti-sense Transcription

Several transcriptomic studies have shown the widespread existence of anti-sense transcription in cell. Anti-sense RNAs may be important actors in transcriptional control, especially in stress response processes. The aim of our work is to study gene networks, with the particularity to integrate in the process anti-sense transcripts. In this paper, we first present a method that highlights the importance of taking into account anti-sense data into functional enrichment analysis. Secondly, we propose the differential analysis of gene networks built with and without anti-sense actors in order to discover interesting change motifs that involve the anti-sense transcripts. For more reliability, our network comparison only studies the conservative causal part of a network, inferred by the C3NET method. Our work is realized on transcriptomic data from apple fruit

Live imaging of DORNRÖSCHEN and DORNRÖSCHEN-LIKE promoter activity reveals dynamic changes in cell identity at the microcallus surface of Arabidopsis embryonic suspensions

Key message Transgenic DRN::erGFP and DRNL::erGFP reporters access the window from explanting Arabidopsis embryos to callus formation and provide evidence for the acquisition of shoot meristem cell fates at the microcalli surface. Abstract The DORNRÖSCHEN (DRN) and DORNRÖSCHEN-LIKE (DRNL) genes encode AP2-type transcription factors, which are activated shortly after fertilisation in the zygotic Arabidopsis embryo. We have monitored established transgenic DRN::erGFP and DRNL::erGFP reporter lines using live imaging, for expression in embryonic suspension cultures and our data show that transgenic fluorophore markers are suitable to resolve dynamic changes of cellular identity at the surface of microcalli and enable fluorescence-activated cell sorting. Although DRN::erGFP and DRNL::erGFP are both activated in surface cells, their promoter activity marks different cell identities based on real-time PCR experiments and whole transcriptome microarray data. These transcriptome analyses provide no evidence for the maintenance of embryogenic identity under callus-inducing high-auxin tissue culture conditions but are compatible with the acquisition of shoot meristem cell fates at the surface of suspension calli

Transcription profiling of the chilling requirement for bud break in apples: a putative role for FLC-like genes.

doi:10.1093/jxb/erv0

A coumaroyl-ester-3-hydroxylase insertion mutant reveals the existence of nonredundant meta-hydroxylation pathways and essential roles for phenolic precursors in cell expansion and plant growth

Cytochromes P450 monooxygenases from the CYP98 family catalyze the meta-hydroxylation step in the phenylpropanoid biosynthetic pathway. The ref8 Arabidopsis (Arabidopsis thaliana) mutant, with a point mutation in the CYP98A3 gene, was previously described to show developmental defects, changes in lignin composition, and lack of soluble sinapoyl esters. We isolated a T-DNA insertion mutant in CYP98A3 and show that this mutation leads to a more drastic inhibition of plant development and inhibition of cell growth. Similar to the ref8 mutant, the insertion mutant has reduced lignin content, with stem lignin essentially made of p-hydroxyphenyl units and trace amounts of guaiacyl and syringyl units. However, its roots display an ectopic lignification and a substantial proportion of guaiacyl and syringyl units, suggesting the occurrence of an alternative CYP98A3-independent meta-hydroxylation mechanism active mainly in the roots. Relative to the control, mutant plantlets produce very low amounts of sinapoyl esters, but accumulate flavonol glycosides. Reduced cell growth seems correlated with alterations in the abundance of cell wall polysaccharides, in particular decrease in crystalline cellulose, and profound modifications in gene expression and homeostasis reminiscent of a stress response. CYP98A3 thus constitutes a critical bottleneck in the phenylpropanoid pathway and in the synthesis of compounds controlling plant development. CYP98A3 cosuppressed lines show a gradation of developmental defects and changes in lignin content (40% reduction) and structure (prominent frequency of p-hydroxyphenyl units), but content in foliar sinapoyl esters is similar to the control. The purple coloration of their leaves is correlated to the accumulation of sinapoylated anthocyanins