The evolutionary origin of orphan genes

Gene evolution has long been thought to be primarily driven by duplication and rearrangement mechanisms. However, every evolutionary lineage harbours orphan genes that lack homologues in other lineages and whose evolutionary origin is only poorly understood. Orphan genes might arise from duplication and rearrangement processes followed by fast divergence; however, de novo evolution out of non-coding genomic regions is emerging as an important additional mechanism. This process appears to provide raw material continuously for the evolution of new gene functions, which can become relevant for lineage-specific adaptations.     

The impact of cellular networks on disease comorbidity

The impact of disease‐causing defects is often not limited to the products of a mutated gene but, thanks to interactions between the molecular components, may also affect other cellular functions, resulting in potential comorbidity effects. By combining information on cellular interactions, disease‐‐gene associations, and population‐level disease patterns extracted from Medicare data, we find statistically significant correlations between the underlying structure of cellular networks and disease comorbidity patterns in the human population. Our results indicate that such a combination of population‐level data and cellular network information could help build novel hypotheses about disease mechanisms.     

Prioritization of orphan disease-causing genes using topological feature and GO similarity between proteins in interaction networks

Identification of disease-causing genes among a large number of candidates is a fundamental challenge in human disease studies. However, it is still time-consuming and laborious to determine the real disease-causing genes by biological experiments. With the advances of the high-throughput techniques, a large number of protein-protein interactions have been produced. Therefore, to address this issue, several methods based on protein interaction network have been proposed. In this paper, we propose a shortest path-based algorithm, named SPranker, to prioritize disease-causing genes in protein interaction networks. Considering the fact that diseases with similar phenotypes are generally caused by functionally related genes, we further propose an improved algorithm SPGOranker by integrating the semantic similarity of GO annotations. SPGOranker not only considers the topological similarity between protein pairs in a protein interaction network but also takes their functional similarity into account. The proposed algorithms SPranker and SPGOranker were applied to 1598 known orphan disease-causing genes from 172 orphan diseases and compared with three state-of-the-art approaches, ICN, VS and RWR. The experimental results show that SPranker and SPGOranker outperform ICN, VS, and RWR for the prioritization of orphan disease-causing genes. Importantly, for the case study of severe combined immunodeficiency, SPranker and SPGOranker predict several novel causal genes.     

The orphan receptor ERRalpha interferes with steroid signaling

The estrogen receptor-related receptor α (ERRα) is an orphan member of the nuclear receptor superfamily that has been shown to interfere with the estrogen-signaling pathway. In this report, we demonstrate that ERRα also cross-talks with signaling driven by other steroid hormones. Treatment of human prostatic cells with a specific ERRα inverse agonist reduces the expression of several androgen-responsive genes, in a manner that does not involve perturbation of androgen receptor expression or activity. Furthermore, ERRα activates the expression of androgen response elements (ARE)-containing promoters, such as that of the prostate cancer marker PSA, in an ARE-dependent manner. In addition, promoters containing a steroid response element can be activated by all members of the ERR orphan receptor subfamily, and this, even in the presence of antisteroid compounds.     

The atypical orphan nuclear receptor DAX-1 interacts with orphan nuclear receptor Nur77 and represses its transactivation

DAX-1 (dosage-sensitive sex reversal adrenal hypoplasia congenital critical region on the X chromosome, gene 1) (NROB1) is an atypical member of the nuclear receptor family, which lacks the classical zinc finger DNA binding domain and acts as a coregulator of a number of nuclear receptors. In this study, we have found that DAX-1 is a novel coregulator of the orphan nuclear receptor Nur77 (NR4A1). We demonstrate that DAX-1 represses the Nur77 transactivation by transient transfection assays. Specific interaction between Nur77 and DAX-1 was detected by coimmunoprecipitation, yeast two-hybrid, and glutathione-S-transferase pull-down assays. The ligand binding domain of DAX-1 and the activation function-2 domain of Nur77 were determined as the direct interaction domains between DAX-1 and Nur77. In vitro competition binding assay showed that DAX-1 repressed Nur77 transactivation through the competition with steroid receptor coactivator-1 for the binding of Nur77. Moreover, DAX-1 repressed Nur77- and LH-dependent increase of cytochrome P450 protein 17 promoter activity in transient transfection assays. Furthermore, Nur77-mediated transactivation was significantly increased by down-regulation of DAX-1 expression with DAX-1 small interfering RNA in testicular Leydig cell line, K28. LH treatment induced a transient increase in Nur77 mRNA, whereas LH repressed DAX-1 expression in a time- and dose-dependent manner in K28 cells. In addition, immunohistochemical analysis showed the expression of Nur77 in mouse testicular Leydig cells. These results suggest that DAX-1 acts as a novel coregulator of the orphan nuclear receptor Nur77, and that the DAX-1 may play a key role in the regulation of Nur77-mediated steroidogenesis in testicular Leydig cells.     

The dynamic nature of contact networks in infectious disease epidemiology

Although contact network models have yielded important insights into infectious disease transmission and control throughout the last decade, researchers have just begun to explore the dynamic nature of contact patterns and their epidemiological significance. Most network models have assumed that contacts are static through time. Developing more realistic models of the social interactions that underlie the spread of infectious diseases thus remains an important challenge for both data gatherers and modelers. In this article, we review some recent data-driven and process-driven approaches that capture the dynamics of human contact, and discuss future challenges for the field.     

Interactome networks and human disease

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.     

Translational disease interpretation with molecular networks

Molecular networks are being used to reconcile genotypes and phenotypes by integrating medical information. In this context, networks will be instrumental for the interpretation of disease at the personalized medicine level.     

The mammalian orphan nuclear receptors: orphans as cellular guardians

In classical endocrinology, receptors are molecules that bind a hormone or a ligand to transduce signal within a target cell. Later, however, many intracellular receptors have been discovered in mammals, which have not been shown to bind endogenous ligands and are now are referred as “orphan receptors.” The orphan receptors share high degree of structural and functional homology with the classical nuclear receptors (NRs) and are now part of the NR superfamily and therefore referred as orphan nuclear receptors (ONRs). Interestingly, however, ONR members are not evolutionarily or functionally linked and they form a highly diverse group within the NR superfamily. In mammals, ONRs exhibit great functional diversity and majority of them are expressed in a tissue-specific fashion. In the past one decade, functional studies have revealed that they are mediators of multitude of crucial metabolic, developmental, reproductive, and immunological functions in mammals. Emerging studies also indicate the role of ONRs in the onset of several complex human diseases and hence they may be potential candidates for therapeutic drug targeting in the future.     

The mammalian orphan nuclear receptors: orphans as cellular guardians

In classical endocrinology, receptors are molecules that bind a hormone or a ligand to transduce signal within a target cell. Later, however, many intracellular receptors have been discovered in mammals, which have not been shown to bind endogenous ligands and are now are referred as "orphan receptors." The orphan receptors share high degree of structural and functional homology with the classical nuclear receptors (NRs) and are now part of the NR superfamily and therefore referred as orphan nuclear receptors (ONRs). Interestingly, however, ONR members are not evolutionarily or functionally linked and they form a highly diverse group within the NR superfamily. In mammals, ONRs exhibit great functional diversity and majority of them are expressed in a tissue-specific fashion. In the past one decade, functional studies have revealed that they are mediators of multitude of crucial metabolic, developmental, reproductive, and immunological functions in mammals. Emerging studies also indicate the role of ONRs in the onset of several complex human diseases and hence they may be potential candidates for therapeutic drug targeting in the future.     

Distribution of orphan metabolic activities

A significant fraction (30-40%) of known metabolic activities is currently orphan. Although orphan activities have been biochemically characterized, we do not know a single gene responsible for these reactions in any organism. The problem of orphan activities represents one of the major challenges of modern biochemistry. We analyze the distribution of orphans across biochemical space, through years of enzymatic characterization, and by biological organisms. We find that orphan metabolic activities have been accumulating for many decades. They are widely distributed across enzymatic functional space and metabolic network neighborhoods. Although orphans are relatively more abundant in less studied species, over half of orphan reactions have been experimentally characterized in more than one organism. Shrinking the space of orphan activities will likely require a close collaboration between computational and experimental laboratories.     

The signaling hubs at the crossroad of longevity and age-related disease networks

The established human age-related disease proteins (ARDPs) and longevity-associated proteins (LAPs) together with their first-order interacting partners form scale-free networks which significantly overlap. About half of the common proteins are involved in signal transduction. These proteins are strongly interconnected and in turn form a common signaling network which comprises over 40% of all hubs (proteins with multiple interactions) in the human interactome. Along with the insulin pathway, the common signaling network is remarkably enriched with the focal adhesion and adherens junction proteins whose relation to the control of lifespan is yet to be fully addressed. The examples of such candidate proteins include several hubs, focal adhesion kinase PTK2 and the extracellular proteins fibronectin FN1, paxillin PXN, and vinculin VCL. The results of the network-based analysis highlight the potential importance of these pathways, especially hubs, in linking the human longevity and age-related diseases.     

Drug repositioning for orphan diseases

The need and opportunity to discover therapeutics for rare or orphan diseases are enormous. Due to limited prevalence and/or commercial potential, of the approximately 6000 orphan diseases (defined by the FDA Orphan Drug Act as <200 000 US prevalence), only a small fraction (5%) is of interest to the biopharmaceutical industry. The fact that drug development is complicated, time-consuming and expensive with extremely low success rates only adds to the low rate of therapeutics available for orphan diseases. An alternative and efficient strategy to boost the discovery of orphan disease therapeutics is to find connections between an existing drug product and orphan disease. Drug Repositioning or Drug Repurposing--finding a new indication for a drug--is one way to maximize the potential of a drug. The advantages of this approach are manifold, but rational drug repositioning for orphan diseases is not trivial and poses several formidable challenges--pharmacologically and computationally. Most of the repositioned drugs currently in the market are the result of serendipity. One reason the connection between drug candidates and their potential new applications are not identified in an earlier or more systematic fashion is that the underlying mechanism 'connecting' them is either very intricate and unknown or indirect or dispersed and buried in an ever-increasing sea of information, much of which is emerging only recently and therefore is not well organized. In this study, we will review some of these issues and the current methodologies adopted or proposed to overcome them and translate chemical and biological discoveries into safe and effective orphan disease therapeutics.