Reconstruction of transcriptional regulatory networks (TRNs) is a powerful approach to unravel the gene expression programs involved in healthy and disease states of a cell. However, these networks are usually reconstructed independent of the phenotypic (or clinical) properties of the samples. Therefore, they may confound regulatory mechanisms that are specifically related to a phenotypic property with more general mechanisms underlying the full complement of the analyzed samples. In this study, we develop a method called InPheRNo to identify \"phenotype-relevant\" TRNs. This method is based on a probabilistic graphical model that models the simultaneous effects of multiple transcription factors (TFs) on their target genes and the statistical relationship between the target genes\' expression and the phenotype. Extensive comparison of InPheRNo with related approaches using primary tumor samples of 18 cancer types from The Cancer Genome Atlas reveals that InPheRNo can accurately reconstruct cancer type-relevant TRNs and identify cancer driver TFs. In addition, survival analysis reveals that the activity level of TFs with many target genes could distinguish patients with poor prognosis from those with better prognosis.

Human transcriptome contains a large number of circular RNAs (circRNAs) that are mainly produced by back splicing of pre-mRNA. Here we describe a minigene reporter system containing a single exon encoding split GFP in reverse order, which can be efficiently back spliced to produce a circRNA encoding intact GFP gene. This simple reporter system can be adopted to study how different cis-elements and trans-factors affect circRNA production, and also can serve as a reliable system to measure the activity of IRES-mediated translation. Therefore this system can serve as a platform for mechanistic studies on the circRNA biogenesis and its function.

Thousands of genetic variants have been associated with complex traits through genome-wide association studies. However, the functional variants or mechanistic consequences remain elusive. Intermediate traits such as gene expression or protein levels are good proxies of the metabolic state of an organism. Proteome analysis especially can provide new insights into the molecular mechanisms of complex traits like obesity. The role of genetic variation in determining protein level variation has not been assessed in obesity. To address this, we design a large-scale protein quantitative trait locus (pQTL) analysis based on a set of 1129 proteins from 494 obese subjects before and after a weight loss intervention. This reveals 55 BMI-associated cis-pQTLs and trans-pQTLs at baseline and 3 trans-pQTLs after the intervention. We provide evidence for distinct genetic mechanisms regulating BMI-associated proteins before and after weight loss. Finally, by functional analysis, we identify and validate FAM46A as a trans regulator for leptin.

Regulated expression of the Ena1 Na+-ATPase is a crucial event for adaptation to high salt and/or alkaline pH stress in the budding yeast Saccharomyces cerevisiae. ENA1 expression is under the control of diverse signaling pathways, including that mediated by the calcium-regulatable protein phosphatase calcineurin and its downstream transcription factor Crz1. We present here a quantitative study of the expression of Ena1 in response to alkalinization of the environment and we analyze the contribution of Crz1 to this response. Experimental data and mathematical models substantiate the existence of two stress-responsive Crz1-binding sites in the ENA1 promoter and estimate that the contribution of Crz1 to the early response of the ENA1 promoter is about 60%. The models suggest the existence of a second input with similar kinetics, which would be likely mediated by high pH-induced activation of the Snf1 kinase.

Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.

BACKGROUND: The thioredoxin system maintains redox balance through the action of thioredoxin and thioredoxin reductase. Thioredoxin regulates the activity of various substrates, including those that function to counteract cellular oxidative stress. These include the peroxiredoxins, methionine sulfoxide reductase A and specific transcription factors. Of particular relevance is Redox Factor-1, which in turn activates other redox-regulated transcription factors.
METHODS: Experimentally defined transcription factor binding sites in the human thioredoxin and thioredoxin reductase gene promoters together with promoters of the major thioredoxin system substrates involved in regulating cellular redox status are discussed. An in silico approach was used to identify potential putative binding sites for these transcription factors in all of these promoters.
CONCLUSIONS: Our analysis reveals that many redox gene promoters contain the same transcription factor binding sites. Several of these transcription factors are in turn redox regulated. The ARE is present in several of these promoters and is bound by Nrf2 during various oxidative stress stimuli to upregulate gene expression. Other transcription factors also bind to these promoters during the same oxidative stress stimuli, with this redundancy supporting the importance of the antioxidant response. Putative transcription factor sites were identified in silico, which in combination with specific regulatory knowledge for that gene promoter may inform future experiments.
CONCLUSIONS: Redox proteins are involved in many cellular signalling pathways and aberrant expression can lead to disease or other pathological conditions. Therefore understanding how their expression is regulated is relevant for developing therapeutic agents that target these pathways.

OBJECTIVE: To investigate genetic, molecular and functional aspects of human zona pellucida (ZP) in oocytes with an abnormal appearance.
METHODS: The study included three women with unexplained infertility whose oocytes had an abnormal ZP appearance and the mother and fertile sister of one of them. The coding exons and their flanking intron regions of the four ZP genes and the regulatory element for the ZP3 gene were sequenced. Immunofluorescence staining of discarded oocytes using monoclonal antibodies against recombinant human ZP glycoproteins and a hemizona assay were performed.
RESULTS: No new mutations were observed in the ZP1 (12 exons), ZP2 (19 exons), ZP3 (9 exons), ZP4 (12 exons) genes or in the ZP3 regulatory element of the three studied women. Sequencing of the genes revealed eight synonymous and non-synonymous reported polymorphisms only in ZP1, ZP2 and ZP3. Immunofluorescence staining of the discarded oocytes of two women showed clear and strong staining of the ZP1, ZP2 and ZP4 proteins, but weak staining of the ZP3 protein, although their ZP displayed normal sperm binding ability in the hemizona assay. Intracytoplasmic sperm injection yielded good pregnancy outcomes, even though few injected oocytes developed normally up to day 3.
CONCLUSIONS: The abnormal oocyte ZP appearance in the three study women may not have been due to the genetic changes in the ZP genes. Moreover, sperm binding was normal despite low ZP3 staining observed, suggesting that ZP3 profile may play a subordinate role in the reported cases. Our findings support previous studies which claim that abnormal oocyte morphology is not associated with a decrease in fertilization rates or birth outcomes in couples undergoing intracytoplasmic sperm injection.

Estrogen Receptor (ER) is a nuclear receptor that mediates the actions of estrogen and tamoxifen. ER is expressed in a major fraction of human breast cancers. Recently, genomic maps for estrogen- and tamoxifen-ER have been published. Interestingly, estrogen and tamoxifen induce similar genomic interactions and both ligands have been shown to use co-operating factors. The interactions of these co-operating factors within ER regions have impact both on ER-DNA interactions and gene expression regulated by estrogen and tamoxifen. Moreover, the study of chromatin changes induced by these factors has also provided significant insight into our understanding of ER transcriptional regulation. This methods review describes some functional genomic methods to study the influence of both ER ligands and ER co-operating factors. The analysis of protein-DNA interactions and chromatin changes can be explored by using classical and novel methods such as Chromatin Immunoprecipitation (ChIP) or Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE). This review also explores the properties of each of these methods and the advantages of combining them with high throughput sequencing.

Stochastic expression of genes produces heterogeneity in clonal populations of bacteria under identical conditions. We analyze and compare the behavior of the inducible lac genetic switch using well-stirred and spatially resolved simulations for Escherichia coli cells modeled under fast and slow-growth conditions. Our new kinetic model describing the switching of the lac operon from one phenotype to the other incorporates parameters obtained from recently published in vivo single-molecule fluorescence experiments along with in vitro rate constants. For the well-stirred system, investigation of the intrinsic noise in the circuit as a function of the inducer concentration and in the presence/absence of the feedback mechanism reveals that the noise peaks near the switching threshold. Applying maximum likelihood estimation, we show that the analytic two-state model of gene expression can be used to extract stochastic rates from the simulation data. The simulations also provide mRNA-protein probability landscapes, which demonstrate that switching is the result of crossing both mRNA and protein thresholds. Using cryoelectron tomography of an E. coli cell and data from proteomics studies, we construct spatial in vivo models of cells and quantify the noise contributions and effects on repressor rebinding due to cell structure and crowding in the cytoplasm. Compared to systems without spatial heterogeneity, the model for the fast-growth cells predicts a slight decrease in the overall noise and an increase in the repressors rebinding rate due to anomalous subdiffusion. The tomograms for E. coli grown under slow-growth conditions identify the positions of the ribosomes and the condensed nucleoid. The smaller slow-growth cells have increased mRNA localization and a larger internal inducer concentration, leading to a significant decrease in the lifetime of the repressor-operator complex and an increase in the frequency of transcriptional bursts.

Genome-wide association studies are providing exciting new insight into the genetics of complex disease, but oftentimes, the genomic regions associated with the trait of interest are large enough to contain several equally plausible candidate genes. Commonly, no obvious, putatively functional, polymorphisms are found to segregate. In most cases, therefore, functional evaluation of possible regulatory mechanisms is necessary to narrow the list of potential candidates. One approach to functional characterization of such variants is allelic expression (AE) profiling, which provides an assessment of transcriptional differences between two homologous transcripts. In AE, a heterozygous, transcribed single nucleotide polymorphism is used to quantify the relative transcript abundance between two gene copies. A ratio that differs significantly from 1:1 suggests that the sample may be heterozygous for a cis-acting regulatory allele. The pattern of observed cis-regulatory variation in the profiled candidate genes can thus narrow the list of candidates under an association signal substantially. In addition, AE is also an accessible and economical strategy, as it relies heavily upon standard techniques and equipment likely to be present in any disease-mapping laboratory.