Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools. Good sae.g. Stable Isotope Labelling with Amino acids in cell Culture (SILAC), Isobaric Tag for Relative and Absolute (iTRAQ), Absolute Quantitation (AQUA), Multiple Reaction Monitoring (MRM), or Label-free quantification], which allow important large-scale phosphoproteomic studies [When combining the previously mentioned phosphoenrichments with Strong cation and anion exchange (SCX and SAX) or Hydrophilic interaction chromatography (HILIC), large-scale phosphoproteomic studies of interest can be carried out successfully . If the  studies -19Once the phosphorylation state of a protein, constitutive or associated to cancer disorders has been established by proteomics methods, a range of bioinformatics methods permits deeper study of its properties and contacts. Using sequence analysis, sequence comparison, virtual approaches of protein-protein, protein-ligand interaction or molecular dynamics simulations, initial physical information can be applied for the potential development of personalized approaches, aimed at the concept of personalized medicine. Bioinformatics covers a wide spectrum of techniques for the generation and use of beneficial information from structure, sequence or relationships among biological items  ,21. From2 and IMAC are capable of binding negatively charged phosphate groups from aqueous solutions. Simple and complex samples containing phosphopeptides and non-phosphorylated peptides are dissolved in an acidic solution to reduce the non-specific binding of acidic peptides (e.g. those containing aspartic acid and glutamic acid), and to stimulate the electrostatic interactions between the negatively charged peptides, mainly phosphopeptides, and the metal ions. The phosphopeptides isolated are eluted from the stationary phase using alkaline buffers [TiO buffers 2 and IMAC) have the drawback of binding acidic non-phosphorylated peptides (negatively charged peptides). Peptides containing acidic amino acid residues, glutamic acid and aspartic acid, can also bind to the metal ions. Ficarro et al (2002) circumvented this difficulty with IMAC (Fe3+) by converting acidic amino acid residues to methyl esters [et al [et al [3+) for the selective enrichment of phosphorylated peptides from model proteins when using 2,5-dihydroxybenzoic acid (DHB) with TiO2. In addition, more phosphopeptides are bound to the metal ions and more phosphopeptides can be eluted by using ammonium hydroxide as the eluent by use of glycolic acid in the loading buffer of TiO2 [Both resins  under acidic conditions whereas multi-phosphorylated peptides elute at high basic pH. Following SIMAC protocol, TiO2 allows capture of the unbound mono-phosphorylated peptides in the combined IMAC flow-through and washing steps [SIMAC allows enrichment of mono and multiply-phosphopeptides in a single experiment, and, from complex biological samples. Mono-phosphorylated peptides mainly elute from IMAC  procedure resulted in the observation of a higher number of phosphopeptides recovered. Phosphopeptides are precipitated by adding 0.5 M NaHPO4 and 2 M NH3OH to the peptide-mixture followed by 2 M CaCl2. The washed pellet (with 80 mM CaCl2) is dissolved in 5% of formic acid. Before isolating the phosphopeptides by IMAC (Fe3+), the resulting peptide-mixture is desalted via reversed phase chromatography (RP) [CPP consists of a pre-fractionation step in order to simplify and enrich phosphopeptides from complex samples. CPP coupled to two step IMAC (Fephy (RP) A positively charged analyte is attracted to a negatively charged solid-support, and a negatively charged analyte is attracted to a positively charged solid-support during SCX and SAX operations respectively. SCX and SAX has been successfully combined with IMAC and resulted in greater recovery and identification by MS of interesting phosphorylated peptides originating from yeast pheromone signalling pathway and membrane proteins respectively ,40HILIC consist of a liquid/liquid extraction system between the mobile and stationary phase. A water-rich layer on the surface of the stationary phase (polar) is formed; therefore a distribution of the analytes between these two layers will occur. Weak electrostatic mechanisms as well as hydrogen donor interactions between neutral polar molecules under high organic elution conditions occur during HILIC operations. Moreover, more polar compounds have stronger interaction with the stationary aqueous layer than less polar compounds, resulting in a stronger retention 2 and ZrO2, the negatively charged phosphopeptides are purified by their affinity to positively charged metal ions. However, some of these methods experience the problem of binding acidic, non-phosphorylated peptides. Ficarro et al [3+) by converting acidic peptides to methyl esters but increased the spectra complexity and required lyophilization of the sample, causing adsorptive losses of phosphopeptides in particular. TiO2 chromatography using DHB was introduced as a promising strategy by Larsen et al [2/DHB resulted in higher specificity and yield compared to IMAC (Fe3+) for the selective enrichment of phosphorylated peptides from model proteins . TiO2 offers increased capacity compared to IMAC resins in order to bind and elute mono-phosphorylated peptides. TiO2 exploits the same principle as IMAC, and is similarly prone to nonspecific retention of acidic nonphosphorylated peptides. However, when loading peptides in DHB, glycolic and phthalic acids, nonspecific binding to TiO2 is reduced, thereby improving phosphopeptide enrichment without chemical modification of the sample. SIMAC appeared as a phosphopeptide enrichment tool which exploits the properties of IMAC coupled to TiO2, thus facilitating more refined studies [Using IMAC, TiOro et al  bypasseden et al . TiO2/DH studies 2 [2. ZrO2 permits the isolation of single phosphorylated peptides in a more selective manner than TiO2 [Another phosphopeptide enrichment prior to mass spectrometric analysis is ZrO2  and its han TiO2 2 [e.g. kinases) do not bind so well to those resins. This is an important limitation concerning phosphoenrichment methods and is due to the low proportion of this kind of protein, or, their available amount binds to metal ions although not sufficiently so as to be detected by MS.Strategies which consist of fractionating and subsequently enriching phosphopeptides on a proteome wide scale are based on SCX/SAX and HILIC interaction chromatography. Calcium phosphate precipitation is also a useful pre-fractionation step to simplify and enrich phosphopeptides from complex samples which can be coupled to IMAC and TiO2 . Mainly The combination of SCX with IMAC has been proven, resulting in a huge number of phosphorylated residues identified (over 700 including Fus3p kinase). Although more than 100 signalling proteins and functional phosphorylation sites, including receptors, kinases and transcription factors, have been identified, it is clear that only a fraction of the phosphoproteome has been revealed e.g. HeLa samples), with the result of the identification of a large number of phosphorylated residues (around 1000) [Combinations of HILIC with IMAC have been proven in clinical studies (nd 1000) Improvement in methodologies to enrich for phosphorylated residues from kinases is clearly necessary. However, this is not straightforward for several reasons: the low abundance of those signalling molecules within cells, the stress/stimulation time-duration, as only a small fraction of phosphorylated kinases are available at any given time as a result of a stimulus and the time adaptation over signalling pathways 13C) instead of the normal carbon-12 (12C). When the cells are growing in this medium, they incorporate the heavy arginine into all of their proteins. All of the arginine containing peptides are now 6 Da heavier than their normal counterparts. The trick is that the proteins from both cell populations can be combined and analyzed together by MS. Pairs of chemically identical peptides of different stable-isotope composition can be differentiated via MS owing to their mass difference [SILAC is a technique based on MS that detects differences in protein abundance among samples using non-radioactive isotopic labelling. Two populations of cells are cultivated in cell culture. One of the cell populations is fed with growth medium containing normal amino acids. The second population is fed with growth medium containing amino acids labelled with stable (non-radioactive) heavy isotopes. For example, the medium can contain arginine labelled with six carbon-13 atoms . The fragmentation of the attached tag generates a low molecular mass reporter ion that can be used to relatively quantify the peptides and the proteins from which they originated. The signals of the reporter ions of each MS/MS spectrum allow for calculating the relative abundance (ratio) of the peptide(s) identified by this spectrum. In contrast to SILAC and AQUA (described below), it is during MS/MS experiments, that relative quantification of peptides takes place -50e.g. 10Daltons, due to the incorporation of a 13C6 and 15N4- arginine into the synthetic peptide, compared to the native peptide. The mass difference between the native and the synthetic peptide allows the mass spectrometer to differentiate between the two forms - both forms have the same chemical properties - resulting in the same chromatographic retention, ionization efficiency, and fragmentation distribution [AQUA was developed for the precise determination of protein expression and post-translational modification (PTM) levels. A peptide from a protein is constructed synthetically containing stable isotopes, and the AQUA peptide is the isotopically labelled synthetic peptide. The synthetic peptides can be synthesized with PTMs. The stable isotopes are incorporated into the AQUA peptide by using isotopically "heavy" amino acids during the synthesis process of the peptide of interest (native peptide). The synthetic peptide has a mass increase of ribution -53et al to identify and quantify tyrosine phosphorylated kinases for hundreds of nodes within a signalling network and across multiple experimental conditions. White et al.; Cox et al., and other relevant scientists [MRM requires that knowledge of the sequence of the protein be known in order to calculate precursor and fragment ion values, which can be used to trigger dependent ion scans in a qTRAP (hybrid triple quadrupole linear ion trap mass spectrometer). It can also be used to perform a precursor ion and neutral loss scan, to identify unknown phosphopeptides from a complex mixture, and is a powerful method for the identification and quantification of PTMs in proteins. Indeed, MRM has been used by White ientists ,49,54,5518O labelling is a label-free strategy that incorporates a stable isotope 18O-labelled ″universal″ reference sample as a comprehensive set of internal standards for analyzing large sample sets quantitatively. As a pooled sample, the 18O-labelled ″universal″ reference sample is spiked into each individually processed unlabelled biological sample and the peptide/protein abundances are quantified based on 16O/18O isotopic peptide pair abundance ratios that compare each unlabelled sample to the identical reference sample. This approach also allows for the direct application of label-free quantitation across the sample set simultaneously along with the labelling-approach  since each biological sample is unlabelled except for the labelled reference sample that is used as internal standard. The effectiveness of this approach for large-scale quantitative proteomics has been demonstrated by Qian et al 2009; Wong et al 2008 and other important scientists, giving relevant clues for malignant diseases [diseases ,57et al [Some drugs that bind to microtubules and block mitosis are ineffective in cancer treatment; others show inexplicable focal efficacy. The vinca alkaloids are useful for treating lymphoma, neuroblastoma and nephroblastomas, whereas taxol is useful for advanced breast cancer and ovarian cancer. It is not known why these drugs are not all equally effective nor is it known why they have different therapeutic value against different cancers. Steen et al  examinedDifferences in spindle checkpoint phosphorylation may reveal new features of the mitotic state. The ability to characterise drug candidates based on the spectrum of APC phosphorylations may facilitate the discrimination of the response of tumours to drugs and the identification of new means of checkpoint control.The authors suggested that the results of their study indicate that the term mitotic arrest is a misnomer: arrest is a dynamic state in which some cells enter apoptosis and other cells revert to interphase. The ability to observe biochemical events during arrest could be very important for understanding antiproliferative treatments.Exploring the dynamics of phosphorylation makes great demands on the accuracy of quantitation. Most MS-based quantitative approaches including SILAC and iTRAQ give relative data, meaning that one state of phosphorylation is determined relative to another phosphorylation state. These data can help to establish the kinetics of a pathway. These approaches allowed the measurement of specific quantitative changes in APC phosphorylation in cells arrested in nocodazole for varying periods. If these dynamics can be correlated with the process by which the arrested state is resolved, they may provide us with new tools to understand the mitotic process and to find more effective drug targets in cancer -61Development of drugs for specific biological pathways with increased specificity and reduced toxicity has validated the long-held belief in the cancer research community that a precise molecular understanding of cancer can result in cancer therapy.An example of cancer-specific drugs is the development of Herceptin - a monoclonal antibody against the HER2 receptor for breast cancer therapy. HER2 is an important target in cancer. HER2 overexpression increases tumour cell proliferation, invasiveness and predicts poor prognosis. Wolf-Yadlin and other scientists ,49,58-61et al (2011) [2 with reverse phase chromatography coupled to MS analysis. 155 distinct phosphorylation sites in 77 mitochondrial phosphoproteins including 116 phosphoserine, 23 phosphothreonine and 16 phosphotyrosine residues were identified. They also assigned phosphorylation sites in mitochondrial proteins involved in amino acid degradation, importers and transporters, calcium homeostasis and apoptosis. Many of these mitochondrial phosphoproteins are substrates for protein kinase A, protein kinase C, casein kinase II and DNA-dependent protein kinase. The high number of phosphotyrosine residues suggests an important role for tyrosine phosphorylation in mitochondrial signalling. Many of the mitochondrial phosphoproteins are involved in oxidative phosphorylation, tricarboxylic acid cycle and lipid metabolism e.g. processes proposed to be involved in insulin resistance [Mitochondria play a central role in energy metabolism and cellular survival and consequently mitochondrial dysfunction is associated with a number of human pathologies. Mitochondrial dysfunction is linked to insulin resistance in humans with obesity and type 2 diabetes. Zhao l (2011)  studied sistance .et al (2009) [In this study  the mostl (2009)  successfl (2009) -71et al [et al (2007) using AQUA as a novel system of in situ quantitative protein analysis, studied the protein expression levels of phosphorylated Akt (p-Akt). Activation of Akt in tumours is mediated via several mechanisms including activation of cell membrane receptor tyrosine kinases such as EGFR and loss of phosphatase PTEN with dephosphorylation of phosphoinositol triphosphate. Ziwei et al discovered that Akt activation in oropharyngeal squamous cell carcinoma (OSCC) is associated with adverse patient outcome, indicating that Akt is a promising molecular target in oropharyngeal squamous cell carcinoma [White et al ,49 appliarcinoma et al [in vitro.White et al ,61 definet al [Hoffert et al  carried et al [They identified 714 phosphorylation sites on 223 unique phosphoproteins from inner medullary collecting duct samples treated short term with either calyculin A or vasopressin. Rinschen et al  studied Both ERK and JNK were able to phosphorylate residue S261 of aquaporin-2 in vitro, a site showing a decrease in phosphorylation in response to dDAVP in vivo. Their data support roles for multiple vasopressin V2-receptor-dependent signalling pathways in the vasopressin signalling network of collecting duct cells, involving several kinases not generally accepted to regulate collecting duct function. We should remark that Hoffert and co-workers carried out a very interesting research study, via a label-free quantitation strategy that measures phosphopeptide precursor ion abundances from extracted ion chromatograms (XIC).et al [2.The comparison of cellular phosphorylation levels for control, epidermal growth factor stimulus and growth factor combined with kinase inhibitors has been studied by Mann et al  using trThey evaluated the effects of kinase inhibitors on the entire cell signalling network. From thousands of phosphopeptides, less than 10% had a response pattern indicative of targets of U0126 and SB202190, two widely used MAPK inhibitors. They found that the 83% of the growth factor-induced phosphorylation events were affected by either or both inhibitors, showing quantitatively that early signalling processes are predominantly transmitted through the MAPK cascades. In contrast to MAPK inhibitors, dasatinib, a clinical drug directed against BCR-ABL, which is the cause of chronic myelogenous leukemia, affected nearly 1,000 phosphopeptides. Their assay is streamlined and could become a useful tool in kinase drug development.et al [Knowlton et al  conducteThey identified uncharacterized changes in tyrosine phosphorylation induced by CSF-1R in mammary epithelial cells as well as a set of candidate substrates dependent on SRC recruitment to CSF-1R. Many of these candidates may be direct SRC targets as the amino acids flanking the phosphorylation sites in these proteins are similar to known SRC kinase phosphorylation motifs. Their collection of substrates includes proteins involved in multiple cellular processes including cell-cell adhesion, endocytosis and signal transduction. Analyses of phosphoproteomic data from breast and lung cancer patient samples identified a subset of the SRC-dependent phosphorylation sites as being strongly correlated with SRC activation, which represent candidate markers of SRC activation downstream of receptor tyrosine kinases in human tumours.Integrins interact with extracellular matrix (ECM) and deliver intracellular signalling for cell proliferation, survival and motility. During tumour metastasis, integrin-mediated cell adhesion and migration on the ECM proteins are required for cancer cell survival and adaptation to the new microenvironment.et al [Chen Y et al  using SICorrect phosphorylation site assignment is a critical aspect of phosphoproteomic analysis. Large-scale phosphopeptide data sets that are generated through liquid chromatography-coupled tandem MS often contain hundreds or thousands of phosphorylation sites that require validation.et al [PhosphoScore is an open-source assignment program that is compatible with phosphopeptide data from multiple MS levels (MSn). It consists of an algorithm which takes into account the match quality and the normalized intensity of observed spectral peaks compared to a theoretical spectrum. It has been demonstrated by Ruttenberg et al  that Phohttp://ascore.med.harvard.edu/ascore.php). To distinguish the correct site(s) of phosphorylation for each phosphopeptide, automated site assignment is performed on MS2 data using the Ascore algorithm. It was used for an interesting research study of the phosphoprotein aquaporin-2 (AQP2) that was also quantified. This particular AQP2 peptide was identified from an MS3 spectrum and contained three unambiguously assigned phosphorylation sites: Ser-256, Ser-261, and Ser-264. A previous phosphoproteomic study by the same group included MS-based quantification of AQP2 at Ser-256 and Ser-261. The dramatic increase in abundance of this phosphopeptide in vasopressin-treated samples was consistent with increased phosphorylation of AQP2 at Ser-256 in response to vasopressin [Ascore consists of a statistical algorithm that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS2 spectra. Phosphorylation sites with an Ascore ≥ 19 (corresponding to > 99% certainty) are usually considered unambiguously assigned. The Ascore algorithm is compatible with MS2 spectra and phosphorylation sites from phosphopeptides found only at the MS3 level are assigned by manual examination of the spectra (opressin Next Generation Sequencing (NGS) has been recently used in a detailed study of genes involved in Colorectal Cancer (CRC) . As a maOnce mutations or phosphorylation of modified residues have been found in sequencing or proteomics studies, routine sequence-to-sequence and sequence-to-structure comparisons  are applied to obtain valuable information on the nature of the functional implications of the mutated residues in the protein context. Multiple alignments of proteins, and mainly those based on the comparison of experimentally obtained-three dimensional atomic structures , are a very valuable source of information related to the evolutionary strategies followed by the different members of a family of proteins to conserve or modify their functions and structures The analysis of structural alignments allows the detection of at least three types of regions or multiple alignment positions according to conservation:1. Conserved positions, usually key for function or structure maintenance.2. Tree-determinant residues, conserved only in protein subfamilies and related to family-specific active sites, substrate binding sites or protein-protein interaction surfaces. These sites contain essential information for the design of family-specific activator or inhibitor drugs .3. Positions that correspond to compensatory mutations that stabilize the mutations in one protein with changes in the other (correlated mutations). These sites are very effective for the detection of protein-protein interaction contacts , as theyAs a consequence of the sequence-to-structure comparison, and in absence of experimental crystal structures, the homology modelling methods, can develop a 3D model from a protein sequence based on the structures of a crystallized homologous protein. The method can only be applied to proteins having a common evolutionary origin, as only for proteins that are hypothesized to be homologous, this assertion implies that their three-dimensional structures are conserved to a greater extent than their primary structures. For cases where a good homology hypothesis cannot be supported, alternative methods can be applied in order to obtain a putative 3D structure. These procedures, known as "far-homology modelling" or "threading" methods, provide structures with lower confidence compared to those generated using homology modelling methods.Routine pipe-line for structural bioinformatics techniques used from structure identification to Molecular Dynamics analysis of the phosphorylated forms is summarized in Figure Information on the 3D structure of the active centre of a protein of interest and/or its natural ligands can be used as a basis for the design of effective drugs. This rational drug design is usually performed using multiple docking experiments in the active centre of the said protein, requiring the use of advanced software such as Autodock-4 , that alFinally, molecular dynamics (MD) techniques are commonly used to obtain refined models for protein structure, protein-protein and protein-ligand interactions.e.g. Src tyrosine kinase [Molecular dynamics is a computational simulation technique in which atoms within molecules are allowed to interact for a period of time according to the principles of physics. In the case of proteins, the relevant forces taken into account are the electrostatic interactions (attractive or repulsive), Van der Waals interactions, and the properties of the covalent bond . In general, simulation times for macromolecular protein complexes are up to 20 ns and the number of atoms of the simulated systems is in the order of up to 250,000, including solvent molecules. MD techniques have been used to simulate the individual behaviour of small protein or peptides , proteine kinase  or protee kinase )Figure aq-Gbg complex as initial template  will not cause important changes in the overall 3D structure of GRK2, but a consolidation of the "unphosphorylated" state, thus disturbing the protein-protein contact at this level. However, putative mutations such as S121D or S121E would generate a "constitutively phosphorylated-like state", stabilizing a reinforced interaction between the two polypeptides.From a clinical perspective, this result would indicate that the presence of a mutated Ser121 residue in GRK2 will produce different effects depending on the nature of the new residue. A conservative mutation ; DIGE 2-D: Fluorescence Difference Gel Electrophoresis; ECD: Electron Capture Dissociation; ESI: Electron Spray Ionization; ETD: Electron Transfer Dissociation; FT-ICR: Fourier transform-Ion Cyclotron Resonance; HILIC: Hydrophilic interaction chromatography; HPLC: High-performance liquid chromatography or high-pressure liquid chromatography; 3PO4 HPhosphoric acid; ICR: Ion Cyclotron Resonance; IMAC: Immobilized Metal Affinity Capture; IT: Ion Trap; iTRAQ: Isobaric Tag for Relative and Absolute Quantitation; kDa: kilodalton (molecular mass); LC: Liquid Chromatography; MALDI: Matrix-Assisted Laser Desorption/Ionization; MD: Molecular Dynamics; MOAC: Metal Oxide Affinity Chromatography; Mr: Relative molecular mass (dimensionless); MRM: Multiple reaction monitoring; MS: Mass Spectrometry; MSA: MultiStage Activation; MS/MS: tandem mass spectrometry; m/z: Mass to charge ratio; PID: Primary Immunodeficiencies; PTM: Post-Translational Modification; SILAC: Stable Isotope Labelling with Amino acid in cell Culture; SIMAC: Sequential Elution from IMAC; 2 TiOTitanium dioxide; TOF: Time Of Flight; 2ZrO: Zirconium dioxideThe authors declare that they have no competing interests.EL carried out the proteomics, phosphoproteomics and mass spectrometry studies for this review. JJW, JM and PGP carried out the bioinformatic studies for this review. IL and SMR carried out the clinical studies for this review. EL, JJW, IS, JM, PGP and SMR carried out these complementary studies in order to develop Clinical Phosphoproteomic-Bioinformatic research and publish this article. All authors read and approved the final manuscript.


Large-scale population sequencing studies provide a complete picture of human genetic variation within the studied populations. A key challenge is to identify, among the myriad alleles, those variants that have an effect on molecular function, phenotypes, and reproductive fitness. Most non-neutral variation consists of deleterious alleles segregating at low population frequency due to incessant mutation. To date, studies characterizing selection against deleterious alleles have been based on allele frequency  or ratio of polymorphism to divergence . Here, starting from Maruyama's theoretical prediction (Maruyama T (1974), Am J Hum Genet USA 6:669–673) that a (slightly) deleterious allele is, on average, younger than a neutral allele segregating at the same frequency, we devised an approach to characterize selection based on allelic age. Unlike existing methods, it compares sets of neutral and deleterious sequence variants at the same allele frequency. When applied to human sequence data from the Genome of the Netherlands Project, our approach distinguishes low-frequency coding non-synonymous variants from synonymous and non-coding variants at the same allele frequency and discriminates between sets of variants independently predicted to be benign or damaging for protein structure and function. The results confirm the abundance of slightly deleterious coding variation in humans. A key challenge in human genetics is to identify, among the multitude of genetic differences between individuals, those that have an effect on traits. Even though new genetic variants arise through mutation in each generation, most are present only in a small proportion of individuals because they have slightly negative effects on fitness. Detecting such slightly deleterious variants is a key challenge in analyzing how genetics influence human characteristics. In this paper, we test a theoretical prediction by Takeo Maruyama from 1974 that a slightly deleterious variant is, on average, younger than a neutral (non affecting fitness) variant present at the same population frequency. Thus our method detects selection by using estimated age of variants. We applied our method to human data from the Genome of the Netherlands Project, and we show that it distinguishes low-frequency protein-modifying variants from silent variants at the same population frequency and discriminates between sets of variants predicted to be benign or damaging for protein structure and function. Our results confirm the abundance of slightly deleterious protein-coding variation in humans. Most studies of deleterious genetic variation in humans have focused on the allele frequency spectrum and on the excess of rare alleles at functionally significant sites Under the assumption of constant population size and no dominance, mean allelic age conditional on population frequency is exactly symmetric with respect to direction of selection — beneficial and deleterious alleles with the same absolute value of the selection coefficient at the same frequency have identical mean ages.Thus, a profound consequence of Maruyama's theoretical prediction is that it enables statistical discrimination between classes of neutral and deleterious alleles even if the alleles are at the same population frequency. Approximating allelic age conditional on present allele frequency may provide a new way to quantify deleterious genetic variation, independent from analyses based on allele frequency distribution or polymorphism-to-divergence ratio. Conditional on current allele frequency, both allelic age and, in particular, time spent in the past at higher frequencies can be estimated by enumerating either mutation or recombination events after the first appearance of the allele in the population. Approaches based on comparison of allelic ages have been previously used to detect alleles under positive selection Some existing methods for estimating age use intra-allelic variability Here, using a new dataset of completely sequenced parent-child trios, we provide evidence that the “Maruyama effect”  can be observed in human genetic data. We introduce a statistic that is based on proximity of completely linked mutations at a lower frequency and recombination events. We demonstrate that this statistic can successfully discriminate between functional classes of human low-frequency derived allelic variants even if they are at the same frequency. This confirms the abundant selection against deleterious alleles in the human population.First, we recapitulated Maruyama's theory with diffusion approximation and simulations (see Methods) and confirm that neutral alleles at a given frequency are older than selected ones . A neutrquencies . The difBoth mean allelic age and mean sojourn times at each frequency are exactly symmetric with respect to the sign of selection coefficient. However, the symmetry is limited to the case of constant size population and no dominance. In a growing population the mean ages of deleterious and beneficial alleles of the same frequency differ (see Methods). The assumption of constant population size greatly simplifies the analysis of allelic ages under a standard diffusion approximation. However, the assumption of constant population size is clearly violated for the human population. To investigate the case of a growing population, we resorted to forward computer simulations (see Methods for exact details of demographic history). Computer simulations indicated that the difference between mean ages of deleterious and neutral alleles of the same frequency is present in a recently rapidly expanding population, though it is smaller than in the case of a constant-size population . The difWe have developed a statistical approach to discriminate between classes of neutral and deleterious alleles at the same frequency. The test statistic, which we call the Neighborhood-based Clock (NC) is defined as the logarithm of the minimal physical distance to the nearest completely linked allelic variant at a lower frequency or to the nearest detectable recombination event . TherefoTo assess whether the NC statistic can indeed discriminate between functional classes of human allelic variants, we analyzed coding variants discovered in the pilot data from the Genome of Netherlands project (GoNL). The pilot GoNL dataset (see Methods) consists of complete genomes of 47 parent-child trios, which enables accurate variant calling and haplotype phasing. Thus, the unique trio-based design of the GoNL dataset allowed us to compute NC statistics informed by family-based rather than population-based phasing, an especially important advantage for rare and low frequency alleles.We subdivided all coding variants into synonymous and non-synonymous (missense and nonsense). We further annotated the missense variants using PolyPhen-2 predictions as benign, possibly damaging, and probably damaging quencies . At minoWe estimate that 14.8% of non-synonymous alleles at minor allele count 2 are deleterious. At minor allele count 2 there are 3102 synonymous SNPs . In contrast, at minor allele count 2 there are 4335 non-synonymous alleles . Therefore, there is an enrichment of rare non-synonymous alleles compared to synonymous alleles. If we assume that all synonymous SNPs are selectively neutral, then we can treat their distribution as the neutral expectation. Therefore, there are Below, we focus primarily on low-frequency derived alleles . We note that, even though the theoretically predicted difference in age is greater for high-frequency deleterious variants , we expeThe NC statistic can discriminate between non-synonymous and synonymous SNPs at the same derived allele frequency  and bootLow-frequency ancestral alleles are expected to be much older than derived alleles at the same minor allele frequency. Those ancestral alleles date from before the human-chimpanzee divergence and each low-frequency ancestral allele corresponds to a high-frequency  derived allele. For example, an ancestral allele at minor allele frequency of 1% corresponds to a derived allele at population frequency of 99%. In agreement with this expectation, the NC statistic is, on average, much lower for ancestral variants than for derived variants .et al.As another independent test whether deleterious variants are on average younger than neutral alleles of the same frequency, we analyzed the fraction of population-specific SNPs. Because this analysis required data from multiple human populations, we used an entirely different data set, pilot data from the 1000 Genomes project (see Methods). We observed that non-synonymous SNPs, especially those predicted to be damaging, are more often population-specific  than synPCSK9 associated with reduction of LDL-cholesterol IFIH1 (I923V and H460R) associated with Type-I diabetes PCSK9 R46L variant and IFIH1 I923V variant are both younger than average according to the NC statistic . The IFIH1 H460R variant is a low-frequency ancestral allele and, accordingly, has low NC statistic (indicating old age), at 2.4 standard deviations lower than average for synonymous variants at the same minor allele count . These results suggest that although the NC statistic cannot be applied to pinpoint individual functional variants , it may have potential to enrich for groups of functional variants in burden association tests , using whole-genome sequencing at 12The data presented here include SNP genotypes in a pilot subset of 47 trios collected by the Genome of the Netherlands (GoNL) Project  were used and only those that had annotated phased genotypes.The NC test statistic was computed for variants at minor allele count of 2–6 separately. The statistic, for each coding variant, was computed as base-10 logarithm of the sum of the up- and down-stream physical distances to the closest recombination event (computed using the 4-gamete test The ancestral/derived states of variants were calculated using the ancestral reference human_ancestor_GRCh37_e59 provided with the 1000 Genomes project.P-values were computed using Mann-Whitney rank-sum test. P-values were 1-sided, with alternative hypotheses following younger age for non-synonymous variants. Effect sizes were calculated as standard deviations from the mean of the NC statistic for derived synonymous variants at a given minor allele count. Confidence intervals were computed using the percentile bootstrap method on 1000 bootstrap permutations of variant labels. Combined p-values were computed by meta-analysis using the Z-score method, weighted by sample size.


Myotis species having higher levels of activity in stands of high-severity burn. Larger-bodied bats, typically adapted to more open habitat, showed no response to fire. We found differential use of riparian and upland habitats among the phonic groups, yet no interaction of habitat type by fire severity was found. Extent of high-severity fire damage in the landscape had no effect on activity of bats in unburned sites suggesting no landscape effect of fire on foraging site selection and emphasizing stand-scale conditions driving bat activity. Results from this fire in mixed-conifer forests of California suggest that bats are resilient to landscape-scale fire and that some species are preferentially selecting burned areas for foraging, perhaps facilitated by reduced clutter and increased post-fire availability of prey and roosts.Wildlife response to natural disturbances such as fire is of conservation concern to managers, policy makers, and scientists, yet information is scant beyond a few well-studied groups . We examined the effects of wildfire severity on bats, a taxon of high conservation concern, at both the stand (<1 ha) and landscape scale in response to the 2002 McNally fire in the Sierra Nevada region of California, USA. One year after fire, we conducted surveys of echolocation activity at 14 survey locations, stratified in riparian and upland habitat, in mixed-conifer forest habitats spanning three levels of burn severity: unburned, moderate, and high. Bat activity in burned areas was either equivalent or higher than in unburned stands for all six phonic groups measured, with four groups having significantly greater activity in at least one burn severity level. Evidence of differentiation between fire severities was observed with some  Martes pennanti) and spotted owl  in western North America is mediated by disturbance history, primarily fire and human management Disturbance-habitat dynamics are widely understood to play central roles in the conservation of animal populations. For example, the provision of heterogeneous late-successional habitat for species of conservation concern like fisher ; Jeffrey, ponderosa, and sugar pine ; and incense cedar  We conducted our study in the Sequoia and Inyo National Forests in the southern Sierra Nevada of California, USA , and high-severity  burn in riparian and upland forests to assess how activity differed in relation to burn-status and habitat type . Burned Surveys were conducted from July through August, 2003, one year after the fire; this corresponds to a timeframe when female bats are reproductive and resource requirements highest We sampled unburned and burned areas simultaneously to minimize variation in echolocation activity, as bat activity is known to vary temporally due to prey availability and weather conditions http://www.hoarybat.com) was used to visually classify bat calls to species and phonic groups. We could not categorize all calls to species due to similarities in calls among species with similar call morphology. We partitioned calls into one of six phonic groups based on call characteristics , fringed myotis , and long-eared myotis . The remaining three phonic groups consisted of species which are not reliably identified by the uniqueness of their call morphology and were categorized based on the terminal frequency of the call sweep, including LB25, MY50, and MY40. Bats in the LB25 group are “large-bodied” species with narrowband echolocation calls terminating at approximately 25 KHz, assumed to represent Mexican free-tailed bats, (Tadarida brasiliensis), big brown bats (Eptesicus fuscus), hoary bats (Lasiurus cinereus), and silver-haired bats (Lasionycteris noctivagans). Bats in the MY50 (50 KHz range) group represent Yuma myotis (Myotis yumanensis) and California myotis . Bats in the MY40 (40 KHz range) group represent little brown bat (Myotis lucifugus), long-legged myotis (Myotis volans), and small-footed myotis (Myotis ciliolabrum). Call classifications were made by a single person to minimize observer bias.Analook , low severity (fire-caused crown scorch affected <40% overstory canopy foliage), moderate-severity (crown scorch of 40–89% of forest canopy) or high-severity (crown scorch or loss of 90% of canopy) based on USFS vegetation burn-severity maps F-tests of maximum likelihood ratios, and thus only present results of additive models.Acoustic detectors do not detect all bat species equally, leading to under-representation of some species in surveys To assess how fire at the landscape scale affects bat activity, we analyzed unburned sites to identify differences relative to the extent of high-severity fire damage within a 2 km radius. This scale was selected based on previous studies detecting landscape-scale effects of forest disturbance on other vertebrates M. thysanodes, MY40) showed differing response to fire severity with positive response to high-severity fire and neutral response to moderate-severity  demonstrated increasing magnitude of response with severity, two groups , and two groups (LB25 and M. evotis) showed no response  and peaked e.g. . Our datresponse . We encoMounting evidence suggests that fire-prone forests and associated fauna are often resilient to stand-replacing fire The wildfire-landscape mosaic did not affect bat activity in unburned stands for any of the six phonic groups. Some stands had up to 30% of the surrounding landscape within a 2 km radius burned with stand replacement fire. Despite this, activity was neither higher (due to immigration of species preferring unburned conditions) nor lower (due to emigration to favored habitat conditions elsewhere), suggesting that bat communities do not respond to forest landscape condition in a manner similar to that documented for territorial birds following fire Baetis spp., and Simuliidae) M. yumanensis with documented prey preferences for emergent insects Insect response to fire has been studied in a range of settings with well-documented neutral to positive impacts on a several taxa of flying insects The positive response of bats to fire broadly mirrors a range of bird species adapted to foraging in open conditions and not dependent on live conifer foliage for foraging or nesting substrates. Despite the broad parallels found in this study with avian post-fire response, further work exploring a broader range of post-fire conditions is necessary such as time since fire and influence of pre-fire forest condition in multiple forest types. This research reflects the first documented taxa-specific response of bats to a single wildfire. Further work to investigate response of bats on other wildfires and in other fire-sensitive ecosystems at varying stages of succession is needed to broaden the scope of inference from our results, as other research investigating avian and reptile responses to fire at multiple spatial scales in non-forested habitats of Australia have found late-successional conditions favored by birds Our results support the emerging perspective that naturally generated early successional habitats are essential on the landscape for a broad range of taxa and that processes like wildfire are instrumental in their maintenance. Our results, in conjunction with the only other peer-reviewed study on bat response to wildfire Figure S1Distribution of bat activity by phonic group in relation to burn severity. Natural log-transformed boxplot and dot plots of each phonic group by level of disturbance  among (A) Myotis thysanodes = MYTH; (B) “large-bodied” species in the 25 KHz range = LB25; (C) Myotis evotis = MYEV; (D) Antrozous pallidus = ANPA; (E) Myotis species in the 50 KHz range = MY50; and (F) Myotis species in the 40 KHz range = MY40.(TIF)Click here for additional data file.Table S1Acoustic survey information summarized for 14 survey locations with paired detectors deployed at each location in different habitats designated by habitat type (upland and riparian).(DOCX)Click here for additional data file.Table S2Modeling results for effects of fire severity and habitat on bat phonic group activity one year after wildfire in mixed-conifer forest, California, USA.(DOCX)Click here for additional data file.Table S3Modeling results for the effect of landscape-scale fire on bat activity in unburned forest in mixed-conifer forest one year post-fire, California, USA.(DOCX)Click here for additional data file.


In the Cancer Genome Atlas (TCGA) project, gene expression of the same set of samples is measured multiple times on different microarray platforms. There are two main advantages to combining these measurements. First, we have the opportunity to obtain a more precise and accurate estimate of expression levels than using the individual platforms alone. Second, the combined measure simplifies downstream analysis by eliminating the need to work with three sets of expression measures and to consolidate results from the three platforms.We propose to use factor analysis (FA) to obtain a unified gene expression measure (UE) from multiple platforms. The UE is a weighted average of the three platforms, and is shown to perform well in terms of accuracy and precision. In addition, the FA model produces parameter estimates that allow the assessment of the model fit.http://tcga-data.nci.nih.gov/docs/publications/unified_expression/.The R code is provided in  The Cancer Genome Atlas (TCGA) project This article addresses the problem of combining gene expression measures for the same set of samples from multiple platforms. A combined measure is desirable because 1) we get a more reliable estimate by using more information, and 2) downstream analysis can be carried out on a single set of expression measures rather than multiple. As shown in Our method was used to generate the unified expression measures for TCGA glioblastoma multiforme (GBM) data, which was used in Verhaak et al Here, we propose to use factor analysis to address this problem. The main advantage of using factor analysis to combine concomitant expression measures is that it gives each platform a weight depending on how well its measurements correlate with the rest of the platforms and therefore has the ability to down-weight a problematic platform. The underlying gene expression level is reflected in the measurements obtained from each of the platforms and is thought of as the latent variable in the factor analysis model. Factor analysis has previously been used in the single-platform setting as a summarization method for Affymetrix U133 platforms Factor analysis can be applied in two ways. One is to first summarize the expression measures within each platform and apply factor analysis to the platform summaries. We call this gene-level FA. This method requires the gene of interest to be measured on at least three platforms simultaneously. The second method, probe-level FA, applies factor analysis directly to probe-level measurements across all platforms. This eliminates the requirement of having at least three platforms measure a given gene and can provide estimates for all genes that are measured on any of the platforms. Factor analysis as we do it requires more samples than platforms, and is best when the number of samples greatly exceeds the number of platforms. Our approach will not apply in a setting such as the MAQC project We have applied both gene-level and probe-level FA to integrate the expression measures from U133, Exon and Agilent arrays for TCGA GBM and ovarian tumor samples. We use expression levels measured from digital sequencing (DGE) experiments on a subset of these samples as our gold standard to evaluate the performance of our FA models, as digital sequencing has been shown to be highly reproducible and accurate in identifying differentially expressed genes We compare the performances of gene-level and probe-level FAs to each of the three platforms alone, as well as gene-level and probe-level averages in terms of precision and accuracy. We find that gene-level FA and gene-level average are the top performers when evaluated by several criteria across all genes, followed by probe-level FA. Our simulation study further shows that gene-level FA has a clear advantage over gene-level average when two platforms are giving good expression measurements and the third is mis-behaving. This result is confirmed when we look at the subset of such genes in the TCGA ovarian data set.We have applied the proposed FA models to 246 GBM samples and 175 ovarian samples available through TCGA. This paper focuses on the ovarian data set where digital sequencing data is available for 31 of the 175 samples, which we use as a gold standard to evaluate our methods. Each sample is measured on three microarray platforms: U133, Exon and Agilent. Probes from the three platforms are mapped to a transcript database compiled from RefSeq and GenBank as described in A thorough presentation of the factor analysis model can be found in andIt turns out that the right hand side of (2) is equal to In order to obtain unified expression measures for a given gene using Thomson's factor score, we need to estimate the parameters and the maximum likelihood estimates of the parameters Thomson's factor score says that the unified expression measure is a weighted average of the observed expression measures from the We obtain the same unified expression measure even if the The factor analysis model is implemented using the R package We find that factor analysis gives unified expression measures that are highly correlated with well-performing platforms when a gene is expressed and has a reasonable dynamic range across samples. When a gene is expressed at background levels or has constant expression levels across samples, we cannot get a good estimate of the covariance matrix for that gene, and the factor analysis model will not produce helpful results. However, these are genes that are not of interest in most cases. By combining multiple platforms, discordant measures from one platform can be rescued by concordant measurements from the other two platforms. In these situations, the factor model gives a more reliable estimate than simply averaging measurements from all the platforms.This section is organized as follows. We first describe the model fit for gene-level FA and probe-level FA by showing a few genes that are representative of the different situations, followed by a comparison of gene-level FA and probe-level FA. We then systematically evaluate the performance of our FA models in terms of precision (variance) and accuracy (bias) by first comparing them to five other gene expression summaries across all genes: gene-level averages of the three platforms, probe-level averages across all probes from the three platforms, and the three expression measures from the three platforms. The accuracy of gene-level FA and gene-level averages is then further compared using a simulation study, the results of which are then confirmed in the TCGA ovarian data set.We illustrate the model fit in different situations using four genes, shown in FHL1, When pair-wise correlations between platforms are high . Despite these differences, 75% of the genes have gene-level and probe-level FA correlations greater than 0.8 . There ac ranges . After t85B gene , where g85B gene . Based oTo combine gene expression measures from several platforms, the naive method would be to take the mean of the standardized gene-level summaries of each platform. An alternative would be to take the mean of the probe-level data from all platforms, or use gene-level summaries from one of the platforms. Therefore we have seven gene expression summaries: gene-level averages, probe-level averages, RMA summaries of U133 arrays, RMA summaries of Exon arrays, gene summaries of Agilent arrays, gene-level FA and probe-level FA. We now evaluate these seven gene expression summaries in terms of precision (variance) and accuracy (bias). For precision, we use the nine sets of replicate samples in our data and compare the variability of the seven gene expression summaries. For accuracy, we use digital sequencing data on 31 of the ovarian tumor samples as our gold standard. Note that notations used in this section is independent of those in the There are 9 sets of replicate samples: 06-0137 (2), 06-0138 (2), 06-0145 (4), 06-0154 (2), 06-0156 (3), 06-0168 (2), 06-0176 (2), 06-0208 (2) and 06-0211 (2). For a given gene, let Next-generation sequencing is emerging as an attractive alternative to microarrays for measuring gene expression levels. Instead of relying on hybridization of predetermined probes to target transcripts, the new sequencing technologies count the number of reads mapped to genes of interest, and thus eliminate issues with cross hybridization and background signals. Studies find that gene expression measured from next- generation sequencing is highly replicable and that its performance in identifying differentially expressed genes is highly concordant with qRT-PCR We use median-normalized Illumina DGE gene count data for 31 of the ovarian tumor samples as our reference for expression levels. Processing of the DGE data is described in As a first step to assess how well array gene expression summaries resemble that of DGE data, we compute the sum of squared differences between standardized array summaries and standardized logwhere Instead of quantifying absolute gene expression levels, we often use microarrays to compare the expression levels of two groups by estimating a fold change for each gene. Here we obtain two distinct groups of sizes 7 and 24 from the 31 samples by consensus clustering ectively , represewhere ummaries , which iPoisson regression models have been shown to work well across technical strata for digital sequencing data atistics , possibllimmaWe would like to test whether the log fold change between the two groups specified in section is significantly different from 0. Rather than relying on methods based on the Poisson distribution, we use and 0.94 .We use DGE data on 31 of the ovarian tumor samples to assess the accuracy of gene expression measurements from three microarray platforms, their simple averages, and the proposed unified expression measures. We find that the gene-level FA is the closest to the expression measures generated from DGE when evaluated by the sum of squared differences between standardized array summaries and standardized logWhen looking across all the genes common to all three platforms, it appears that gene-level FA and gene-level average perform comparably. We perform a simulation study to evaluate their behaviors more systematically. Based on the results of this simulation study, we identify a subset of genes for which gene-level FA shows an advantage over gene-level average in TCGA ovarian data set.We simulate gene expression data for 200 samples according to the FA model described in equation (1) as follows:The true gene expression levels For a given configuration of Generate Determine Get estimates of Repeat 200 times for each configuration of We see that gene-level FA has a clear advantage over the average when two of the In general, the average is less sensitive than FA. The FA takes advantage of the two good platforms when it is clear that the third platform should be down-weighted, but can also produce worse estimates than the average when the situation is less clear.With more insight from our simulation study, we now look at a subset of genes where two of the array platforms have better than 0.5 correlations with DGE and the third platform has a correlation of 0.4 or less with DGE. There are 892 genes that fall into this category. We find that the gene-level FA has an advantage over the average in terms of distances to the expression level measured by DGE for this subset of genes, while they remain comparable in precision, fold-change and identification of DE genes (data not shown).We propose to use the factor analysis model to produce a unified gene expression measure from three different microarray platforms  when the same set of samples is measured on each. Factor analysis is a natural method to use since it takes the covariance structure of the three platforms into account and estimates the unobserved variable as a weighted average of the three observed variables. This estimate is linear in the observed variables, albeit one with estimated coefficients.The main advantage of the proposed factor analysis model is that it down-weights problematic platforms and therefore gives better estimates than a simple average. This is shown clearly in simulations (subplots 1 to 6). With real data, we do not expect the factor analysis model to show a drastic improvement over the simple average simply because the fraction of genes where one platform is misbehaving is small. However, when this does happen, the gene-level FA produces estimates that are more accurate than the simple average . The othIDH1, EGFR, PDGFRA and NF1. Interestingly, the classifier cross-validation errors were reduced when gene-level FA expression levels were used, compared to training the classifier models on data from any of the three separate platforms. Reduction in cross-validation error has been shown to be a property of less noisy data The unified expression measures generated from the FA model was successfully used in a recent analysis of TCGA GBM expression profiles http://tcga-data.nci.nih.gov/docs/publications/unified_expression/. The factor analysis model may be further improved to produce good estimates when the correlation matrix is poorly estimated, which usually occurs for genes with a small dynamic range. An approach that allows us to borrow information from genes with well-estimated correlation matrices could improve the estimates for such genes.TCGA is expected to produce expression profiles on three platforms on a total of 1,500 tumor samples of GBM, ovarian serous adenocarcinoma and lung squamous carcinoma, to which FA will be applied to produce unified expression estimates and will be made available at Figure S1Correlation of gene-level summaries among the three platforms per gene.(TIF)Click here for additional data file.Figure S2Estimated (TIF)Click here for additional data file.Figure S3Estimated (TIF)Click here for additional data file.Figure S4GBM data. Gene SLC36A1: Gene-level summaries.(TIF)Click here for additional data file.Figure S5Gene SLC36A1: Gene-level summaries.(TIF)Click here for additional data file.Figure S6Correlations for 53 genes with one bad (TIF)Click here for additional data file.Figure S7Heywood cases. Red dots are genes in which Heywood cases occur.(TIF)Click here for additional data file.Figure S8Bootstrap SE of (TIF)Click here for additional data file.Figure S9Genes with large bootstrap SE of (TIF)Click here for additional data file.Figure S10Number of probes per gene on each platform. Figures reflect the number of unique probes on the Agilent array, each usually duplicated 2 to 3 times.(TIF)Click here for additional data file.Figure S11Pairwise probe correlations for gene FHL1 stratified into three within-platform groups and three between-platform groups. FHL1 has 55 U133 probes, 52 exon probes, and 3 Agilent probes. Therefore there are (TIF)Click here for additional data file.Figure S12Gene FHL1: probe-level (TIF)Click here for additional data file.Figure S13Pairwise probe correlations for gene SLC36A1 stratified into three within-platform groups and three between-platform groups. SLC36A1 has 11 U133 probes, 49 exon probes, and 2 Agilent probes. Therefore there are (TIF)Click here for additional data file.Figure S14Gene SLC36A1: probe-level (TIF)Click here for additional data file.Figure S15Histogram of 11,864 correlations between matching gene-level and probe-level gene expression estimates.(TIF)Click here for additional data file.Figure S16Genes with low correlation between probe-level FA and gene-level FA. Red dots are genes whose correlation between probe-level FA and gene-level FA estimates are below (TIF)Click here for additional data file.Figure S17Gene CCD85B. Probe-level FA strongly influenced by Exon array because of its large number of probes.(TIF)Click here for additional data file.Figure S18Correlations between gene-level FA and DGE, and correlations between probe-level FA and DGE for 30 genes with low probe-level and gene-level FA correlations. These genes have reasonable expression levels and dynamic ranges, and are not Heywood cases.(TIF)Click here for additional data file.Figure S19Consensus clustering of the 31 ovarian samples. Samples 1 to 7 form cluster 1 (C1) and samples 8 to 31 form cluster 2 (C2).(TIF)Click here for additional data file.Figure S20QQ-plot of (TIF)Click here for additional data file.Table S1Number of genes with varying (PDF)Click here for additional data file.Table S2Percentage of small (PDF)Click here for additional data file.Table S3Number of genes with varying (PDF)Click here for additional data file.File S1File describing the processing of DGE data.(PDF)Click here for additional data file.File S2R code.(TXT)Click here for additional data file.


Primary bone lymphoma (PBL) is a relatively uncommon entity. However, involvement of the cranial vault is an unusual manifestation of aggressive non-Hodgkin’s lymphoma. We report the case of a 42-year old immunocompetent woman who presented with an enlarging mass involving the right parietal bone. Magnetic resonance imaging (MRI) of the brain revealed an expansive tumor that affects the right parietal bone. Computed tomographic (CT) scans of the abdomen, chest and pelvis were negative for lymphadenopathy or organomegaly. Biopsy of the mass showed diffuse large B-cell non-Hodgkin’s lymphoma confirmed by immunohistochemical study. The patient had a complete response after 4 cycles of chemotherapy followed by external beam radiotherapy. After a follow-up of more than 9 months the patient is still in good local control without distant metastasis. The aim of our work is to report a case of Primary bone lymphoma of the cranial vault with good response to treatment combining sequential chemotherapy and radiotherapy. Primary bone lymphoma (PBL) represents about 5% of all non-Hodgkin lymphomas (NHL) and 3% of all bone malignancies . The femA 42-year old immunocompetent woman presented with a 10-month history of enlarging mass involving the right parietal bone without history of trauma. Physical examination showed a localized mass of 8 × 6 cm in diameter, in the right parietal region. There was no erythema and it was firm and slightly tender. The remainder of the examination was unremarkable; in particular no lymphadenopathy and no abdominal masses were felt.Neurological examination was normal. MRI of the brain revealed an expansive tumor (11 × 5 cm) affecting the right parietal bone, including the scalp . There wBiopsy of the mass with histopathology analysis showed diffuse architecture with mixture of large cleaved (centroblastic/centrocytic) and large noncleaved (centroblastic monomorphous) cells. The cytoplasm was scanty. The tumor cells did stain for CD20, CD79a and bcl2 protein. The proliferating fraction, as detected by Ki67 was high (more than 80% of neoplastic cells). The CD3 T-cell marker was negative. The immunohistochemical tests confirmed the diagnosis of large B-cell lymphoma . Based uThe diagnosis of PBL is more definite in patients who present with isolated bone localisations of lymphoma without other sites of involvement. Most series show a male preponderance, higher likelihood of early-stage disease presentation, and a median age of presentation in the fifth or sixth decade. Involvement of the cranial vault is an unusual manifestation of non-Hodgkin’s lymphoma in patients without HIV infection. Only fourteen patients with non-HIV related primary cranial vault lymphoma have been reported in the literature -15. Our Despite the increasing number of primary bone lymphoma and recent therapeutic advances, several questions still remain unanswered about the optimal management of these tumors. We believe that four cycles of a chemotherapeutic regimen (RCHOP) followed by involved field radiotherapy is the appropriate regimen for patients with primary localized cranial vault lymphoma. Furthermore, exclusive irradiation should be proposed for isolated cases. The prognosis is uncertain, but either direct cerebral invasion or leptomeningeal seeding should indicate a less favorable prognosis .This case demonstrates that PBL must be kept in mind in the differential diagnosis of primary lesions in the skull. Chemotherapy followed by involved field irradiation, appears to be an adapted therapy.The authors declare that they have no competing interests.ZF: performed literature review, the composition of this case report and manuscript writing. IL-MA: conception and design collection and assembly of data. BK: analyse and interpretation of anatomo-pathology findings. SB-HM- HE: analyse and interpretation of data, manuscript writing. All authors read and approved the final version of the manuscript.


Host defense peptides (HDPs) are an evolutionarily conserved component of the innate immune response found in all living species. They possess antimicrobial activities against a broad range of organisms including bacteria, fungi, eukaryotic parasites, and viruses. HDPs also have the ability to enhance immune responses by acting as immunomodulators. We discovered a new family of HDPs derived from pathogenic helminth (worms) that cause enormous disease in animals and humans worldwide. The discovery of these peptides was based on their similar biochemical and functional characteristics to the human defense peptide LL-37. We propose that these new peptides modulate the immune response via molecular mimicry of mammalian HDPs thus providing a mechanism behind the anti-inflammatory properties of helminth infections. Host defense peptides (HDPs) are conserved in all living species as a primitive component of the innate immune response  over acidic amino acids  peptide of 37 residues with a molecular mass of 4.5 kDa. It adopts an amphipathic α-helix structure and possesses a broad spectrum antimicrobial activity. This peptide is contained within an inactive secreted precursor protein termed hCAP-18  which is cleaved by endogenous serine proteinase three to release the C-terminal active 37-residue peptide , eosinophils, mast cells, and basophils, all of which can produce various types of Th2-type cytokines  2-type dominated immune response. Th2-type immunity is typically characterized by an increase in the levels of interleukin-4 (IL-4) and other Th2-type cytokines , activation and expansion of CD4A further important dimension in helminth infection is the differentiation of alternatively activated macrophages (aaMφs) under the influence of Th2-type cytokines. While aaMφs are recruited to the site of infection and are implicated as functional effectors, they also have strong anti-inflammatory properties and highly express genes whose functions relate to the repair of extracellular matrices, wound healing and fibrosis. The overall outcome of a helminth infection may then be an environment with down-regulated proinflammatory responsiveness, activated damage repair mechanisms and a tightly controlled development of Th2 anti-parasite effector responses  to release a C-terminal fragment. The 34-residue C-terminal peptide of FhHDM-1 contains a 21-residue amphipathic helix which exhibits a marked structural parallel with the bioactive human LL-37 peptide. The amphipathic helix of LL-37 anchors the peptide to phospholipid membranes through interaction with hydrophobic face . The HDMs were termed following their characterization: they exhibit similar functional and biochemical properties to the human defense peptides, defensins and cathelicidins. To date, the best studied HDM is the 8 kDa protein FhHDM-1) secreted by the trematode,  secretedSchistosoma mansoni (a trematode that resides in the mesenteric vein) and F. hepatica (a trematode that lives in the bile ducts) cause damages leading to the systemic movement of bacteria (Ogunrinade and Adegoke, Salmonella sp, is frequent (Melhem and Loverde, It is well known that intestinal injury and systemic endotoxemia are two factors leading to morbidity in helminth infected mice (Herbert et al., HDPs are an evolutionarily conserved component of the innate immune response and are found among all classes of life. They have been demonstrated to possess antimicrobial activities on a broad range of organism, killing Gram negative and Gram positive bacteria, mycobacteria, enveloped viruses, fungi and even transformed or cancerous cells. It also appears that HDPs have the ability to enhance immunity by functioning as immunomodulators. The discovery of a family of defense peptides that is conserved amongst medically-important trematode pathogens has raised the question of their utility for helminths. Why would parasitic worms need HDPs? Helminth parasites are master regulators of immune responses in order to ensure life-long persistence in the host. One strategy of immune regulation is the secretion of a wide range of immunoregulatory molecules, which are able to target various host cells and alter them to induce a highly directed host response known as a “modified Th2-type response.” Our recent finding of a family of HDMs that modulate the immune response via molecular mimicry of HDPs provides a common mechanism for the anti-inflammatory properties of helminth infection (Robinson et al., The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


An important challenge in biology has been to understand how cell-type-specific expression programs are orchestrated through regulated access to chromatin. Knowledge of the interaction between noncoding RNAs (ncRNAs) and chromatin regulators has the potential to help answer such questions, but how ncRNAs target chromatin regulators to specific sites in the genome is not well understood. Recently, Jeon and Lee proposed that DNA-binding proteins act as a bridge between ncRNAs and their target sites in chromatin. In this minireview, we examine their findings and place them in the wider context of how chromatin regulator-RNA complexes are targeted to specific sites in chromatin. A number of noncoding RNAs (ncRNAs) have been demonstrated to play a role in transcriptional or chromatin regulation through their interaction with chromatin-modifying enzymes and transcription factors. Some of these RNAs can be visualised to be associated with specific loci, most strikingly the coating of the inactive X chromosome (Xi) by X inactive-specific transcript (Xist) RNA. Modulation of a number of ncRNAs leads to changes in the targeting of regulatory complexes to specific genomic sites. Mechanisms must therefore be in operation that direct ncRNA-protein complexes to specific sites in the genome.Xic) of the future Xi and progressively coats the chromosome. This is accompanied by the appearance of repressive chromatin modifications, including those catalysed by polycomb repressive complex 2 (PRC2). Xist RNA has been proposed to play a direct role in the recruitment of PRC2 through protein-RNA interaction [in situ hybridization and RT-PCR to distinguish between endogenous and transgenic Xist expression [Xic and Xist RNA, Jeon and Lee found that Xist and YY1 interact in cells and that YY1 interacts with the Xist repeat C region in vitro. Consistent with this finding, an earlier study conducted at the Lee laboratory showed that targeting the C region with locked nucleic acid (LNA) oligonucleotides caused displacement of Xist from the Xi [Xic by simultaneously binding to Xist DNA and RNA [Dosage compensation in female mammals is achieved by silencing one copy of the two X chromosomes, termed 'X-chromosome inactivation' (XCI). The long ncRNA Xist is the key factor in initiating this process . Xist ispression . Transgem the Xi . On the  and RNA   methylation at HOXD and several other sites in the genome in trans [The mechanism identified by Jeon and Lee  may be rin trans . HOTAIR in trans . Authorsin trans  and 'capin trans , respectin trans . The autHOXA locus and interacts with mixed-lineage leukaemia (MLL) H3K4 methyltransferase complexes through WD repeat-containing protein 5 (WDR5) [HOTTIP into contact with downstream parts of HOXA, and it has been proposed that this allows HOTTIP RNA to target WDR5-MLL to downstream genes [trans, including those on different chromosomes.Another potential mechanism involved in the targeting of ncRNAs to distant DNA target sites is the proximity between loci induced by chromosomal looping Figure . The lon5 (WDR5) . Chromosam genes . Chromosam genes -14. Knocam genes . One cou0, and in vitro gel shift and protection assays suggest that it forms a triplex structure with the T0 DNA sequence. In addition to allowing the RNA to associate with rRNA promoters, this triplex structure is recognised by DNMT3B and is required for DNA methylation [Direct interactions between RNA and DNA sequences also provide a potential mechanism by which ncRNAs target chromatin regulators to specific sites Figure . Short phylation . Whethercis as it is being transcribed (Figure cis, and the RNAs directly interact with PRC2 in vitro and in cells [RNA can target transcriptional regulator proteins in d Figure . The 60-in cells .Growing evidence suggests that ncRNAs play an important role in chromatin and transcriptional regulation. How these ncRNAs are localised to specific sites in chromatin is not yet clear, but common themes may be emerging. Jeon and Lee's study  outlinesRT-PCR: reverse transcriptase polymerase chain reaction.The authors declare that they have no competing interests.AK and RGJ wrote this review together, and both read and approved the final manuscript.


Astragalus membranaceus Bunge, a medicinal herb used for cardiovascular diseases (CVD). In this work, we investigated the therapeutic mechanisms of AGS-IV at a network level by computer-assisted target identification with the in silico inverse docking program (INVDOCK). Targets included in the analysis covered all signaling pathways thought to be implicated in the therapeutic actions of all CVD drugs approved by US FDA. A total of 39 putative targets were identified. Three of these targets, calcineurin (CN), angiotensin-converting enzyme (ACE), and c-Jun N-terminal kinase (JNK), were experimentally validated at a molecular level. Protective effects of AGS-IV were also compared with the CN inhibitor cyclosporin A (CsA) in cultured cardiomyocytes exposed to adriamycin. Network analysis of protein-protein interactions (PPI) was carried out with reference to the therapeutic profiles of approved CVD drugs. The results suggested that the therapeutic effects of AGS-IV are based upon a combination of blocking calcium influx, vasodilation, anti-thrombosis, anti-oxidation, anti-inflammation and immune regulation.Astragaloside IV (AGS-IV) is a main active ingredient of  Astragalus membranaceus Bunge, the dried root of a low shrub, has been widely prescribed in traditional Chinese medicine (TCM) for the treatment of cardiovascular disorders. Over 25% of the 90 recipes in the 2010 edition of the Chinese Pharmacopoeia for cardiovascular diseases (CVD) contain Astragalus membranaceus Bunge.Astragalus membranaceus Bunge In vivo animal studies have shown that AGS-IV is protective against isoproterenol-induced myocardial injury In vitro experiments suggested that AGS-IV could improve post-ischemic heart function and ameliorate reperfusion arrhythmias in vivoAstragaloside IV (AGS-IV) is one of the main active compounds of Dysfunctions of multiple genes and/or their products are implicated in the pathogenesis of complex chronic diseases  in silico program INVDOCK In this study, we attempted to investigate the therapeutic mechanism of Astragaloside IV against CVD using a network-based methodology that integrates data of drugs, targets and pathways. The CVD is a series of diseases with complex etiology involving multiple biological processes or pathways For each of the 120 pathways owning CVD drug targets, we computed the p-values according to the definition of pathway enrichment, respectively. As there are different statistic methods to calculate this value, we adopted three strategies: distinct protein enrichment of CVD drug targets, protein node enrichment of CVD drug targets and CVD drug enrichment (see Methods section for details). The analysis generated 33 pathways  with at least one p-value<0.05 . The sigSmall-molecule drugs generally function by binding to proteins and/or nucleic acids. Ligand-protein inverse docking is one approach to search for multiple putative protein targets. Base on the 33 key CVD-associated pathways identified by enrichment analysis, we used INVDOCK The candidate 3D dataset included all known information for the 1,619 proteins in the 33 key pathways . The 3D structure of AGS-IV  was entePutative complexes of AGS-IV with calcineurin (CN) and cyclophilin (Cyp) are shown in The Gene Ontology (GO) terms of the 39 putative protein targets, their implications for CVD therapy, and corresponding references are listed in An altered balance in the biological action of vasodilator and vasoconstrictor molecules is associated with hypertension.Abnormity in blood coagulation cascade may lead to thrombosis.Calcium ions are key intracellular messengers in the cardiovascular system. Proteins that mediate calcium fluxes in the heart and vascular smooth muscle initiate excitation-contraction coupling.MAP kinase signal transduction pathway has been reported to play a crucial role in many aspects of cardiovascular responses Normal cardiac growth and exercise-induced hypertrophy were found to be regulated by the PI3K/Akt pathway to a high extent Small G proteins have shown to be implicated in regulation of endothelial function, smooth muscle cell contraction, proliferation, and migration, as well as cardiomyocyte hypertrophy Cardiac injury is known to activate innate immune mechanisms initiating an inflammatory reaction, and cardiac repair following myocardial infarction is related with immune response Oxidative stress is associated with many forms of cardiovascular diseases. Increased production of reactive species in vascular tissues may play an important role in hypertension, vascular remodeling after angioplasty, atherosclerosis, myocardial infarction, and ischemic stroke A comprehensive literature search in PubMed showed that 27 of the 33 proteins aforementioned were reported as drug targets or potential targets for CVD treatment see . All butCN, ACE and JNK were validated experimentally for two reasons. First, there is ample literature support for important role of these proteins in CVD. Second, these three proteins are readily available.50 of 403 nM  with AGS-IV (0.10∼1.02 µM) for 24 h. As mentioned earlier, INVDOCK predicted that AGS-IV binds to CN in the same pattern as CsA does. Hence CsA (80 µg/L) was added as positive control. Then, CN activities were determined by the CN activity assay kit. Our results indicate that AGS-IV inhibited CN activity with an ICf 403 nM . The IC550 of 268 nM. IC50 of the reference drug enalapril is 1.94 nM To validate the inhibition of ACE by AGS-IV, we incubated cultured endothelial cells from human umbilical veins (HUVEC) with AGS-IV. Considering our result that AGS-IV docks into the same binding pocket of ACE as ACE inhibitors captopril and enalaprilat Inflammation plays a critical role in CVD. Toll-like receptor (TLR) signaling is involved in the pathological process of inflammation in vascular smooth muscle cells (VSMCs) Pathological cardiac hypertrophy is a response to a variety of primary conditions such as hypertension, myocardial hypoxia, ischemia and infarction, and is associated with heart failure, arrhythmia and increased risk of heart attack. Previous studies indicated that blocking CN could alleviate cardiac hypertrophy 50 for CsA and AGS-IV was 365 nM (Lactate dehydrogenase(LDH), an enzyme existed in all cells, could be used as an index of cytotoxic effect, for releasing into the culture supernatant after the injury. We determined the activity of LDH leaking into the medium from ADR-injuried cardiomyocytes treated by AGS-IV or CsA respectively. Our experiments suggested that AGS-IV and CsA inhibited ADR-induced release of lactate dehydrogenase (LDH) from cultured cells to the medium in a concentration-dependent manner. The ECs 365 nM  and 1.36s 365 nM , respectBcl-2 exerts a survival function in response to a wide range of apoptotic stimuli by inhibiting mitochondrial cytochrome c release; whereas Bax is a key component of apoptosis induction via mitochondrial stress. The Bcl-2/Bax ratio is commonly used to measure the impact of drugs on the apoptotic process. An increase in the ratio suggests a protective effect against apoptosis In the last section we verified the direct inhibition of AGS-IV on CVD associated active proteins CN, ACE and JNK, here we examined the protective function of AGS-IV on ADR-induced injury in cardiomyocytes. We referred to these two experiments as protein and cellular level experiments, respectively. In To understand the relationship among the putative targets of AGS-IV, we mapped the 39 proteins onto the protein-protein interaction network of the human genome. We successfully identified 37 proteins and found that 34 of them can be linked into one sub-network either through direct interactions or with only one intermediate protein, suggesting that most of the targets are located in the neighborhood of each other in the human protein network. The proximity of proteins in the interactome indicates that they share common functions. To identify the functions of this network between targets, we next applied a simulated annealing algorithm Astragalus membranaceus has been widely used in TCM for stroke patients, and a previous clinical investigation suggested that Astragalus membranaceus may be beneficial for the treatment of acute cerebral infarction in vivo experiments suggested that AGS-IV could significantly reduce the volume of heart and brain infarctions It would be interesting to bridge AGS-IV and existing FDA-approved CVD drugs via their common drug targets. This is expected to provide alternative insights for deducing the therapeutic mechanism of AGS-IV. Among the 39 putative targets of AGS-IV identified in this study, seven are known targets of approved CVD drugs. We searched the DrugBank database and found 23 approved CVD drugs that share common targets with AGS-IV. We extracted all of the targets of these 23 drugs and used this information to construct a drug-target network . The antACE inhibitors are widely used in the treatment of cardiovascular diseases, including congestive heart failure, coronary artery disease and hypertension. The drug-target network for AGS-IV also includes a group of ACE inhibitors. Based on these results, we speculate that the cardioprotective effect of AGS-IV may be partially due to its inhibition of ACE. By blocking ACE, ACE inhibitors decrease the level of angiotensin II, a vasoconstrictor and a negative feedback mediator of renin activity. Our earlier experimental study found that AGS-IV dilates aortic vessels through angiotensin II inhibition The network we constructed for AGS-IV includes three statin drugs (ATC code C10AA). However, the primary target of statins  is not a target for AGS-IV. Two local anesthetics, lidocaine and dibucaine (ATC code C05AD), share two common targets with AGS-IV: EGFR and CALM1. But the targets are apparently not relevant to the therapeutic action of AGS-IV.2+ influx accumulation is implicated in the pathogenesis of ischemic and reperfusion injury 2+ and CALM to the regulatory and catalytic subunits, respectively To get an overall picture of the interplay between AGS-IV's targets and CVD therapy-associated pathways, we mapped the 39 putative protein targets of AGS-IV onto the 33 key pathways associated with CVD therapy and found that they appeared in 30 out of the 33 key pathways. A target-pathway network for these targets and pathways is illustrated in Systems biology and network pharmacology are attracting increasing attention in drug discovery. In contrast to the classical strategy of targeting individual proteins, network-based approach considers the overall effects produced by multiple targets, including network robustness The current study conducted a network-level investigation for the therapeutic mechanisms of AGS-IV on CVD. To maintain a reasonable level of reliability without substantially sacrificing statistical power, we focused on the 33 key pathways known to be affected by majority of FDA-approved CVD drugs. We used a flexible ligand-protein inverse docking program, INVDOCK, to pinpoint proteins with which AGS-IV may potentially interact. We are not presently able to identify potential target proteins without an existing 3D structure. Among the 39 potential targets predicted from an analysis of the crystal structures of 1,619 proteins, 69% have been reported in the literature as known or potential targets for CVD drugs. Three proteins  with the strongest literature support were experimentally verified. These results suggest that target prediction based on protein candidates selected from key CVD related pathways is a sound approach in identifying drug targets.50 of AGS-IV against purified CN and ACE was approximately two orders higher than CsA and enalapril, respectively. Considering the fact that AGS-IV is a naturally-occurring substance, such results are not surprising. At the whole cell level (adriamycin-induced LDH release from cultured cardiomyocytes), however, AGS-IV is only 3.7 fold less potent than CsA. The much stronger activity of AGS-IV at the cell level suggested synergistic action among multiple targets. Our experiments validated the network-based mathematical models, and suggested that partial inhibition of multiple targets can be more efficient than potent inhibition of a single target A recent study suggested that both AGS-IV and the ACE inhibitor quinapril could improve cardiac function in a rat model of chronic heart failure Our network analysis suggests that the therapeutic effects of AGS-IV are likely achieved by modulation of a combination of targets in a modular pattern. Of particular interest are target proteins at the crosstalk sites among the multiple pathways that participate in calcium, MAPK, VEGF signaling . This allows AGS-IV to intervene in multiple pathways involved in CVD via limited number of targets.The network-based systems biology strategy described in this paper could be an effective approach for elucidating the protein relationships within and between comprehensive pathways in complex diseases and their treatment. In our knowledge, this study is the first to employ a network-based computational approach in systematic search of potential CVD-related drug targets for a natural compound and to illustrate its underlying molecular mechanism based on the various network associations. Also, the multiple mechanisms identified in this study could be valuable for designing new network-based multi-target CVD drugs or for proposing combinations of drug treatment for CVD.Data about drugs and targets were downloaded from the DrugBank database Pathway data was downloaded from the FTP service of KEGG in vivo, in vitro, or yeast two-hybrid experiments.Protein-protein interaction data were downloaded from the HPRD database  INVDOCK software We first constructed a protein-protein interaction network for human genome based on the HPRD data and mapped all putative targets of AGS-IV onto this network. Then we applied the Steiner minimal tree algorithm A drug-target network is defined as a bipartite network for the drug-target associations consisting of two disjoint sets of nodes We first mapped all the protein targets of the drugs under study onto the KEGG pathways k of a node is the number of edges linked to that node. The degree distribution p(k) of a network is the frequency of occurrence of nodes with degree k, . It has been reported that degree distributions of most real world networks including biological networks obey power law. Such distribution suggests that most nodes in the network (corresponding to entities of the system under study) only influence limited number of nodes, while a small number of nodes interact with quite plenty of nodes thus play key roles in the system In a network, the degree i.e., the pathway can be regarded as significantly regulated by CVD drugs. We defined three types of pathway enrichment as follows:We used pathway enrichment analysis Type I enrichment: Distinct CVD drug targets are significantly enriched in the pathway.Type II enrichment: Regulating points of CVD drug targets are significantly enriched in the pathway. This type of enrichment is defined to identify pathways that are regulated by few distinct protein targets but at many positions, that is, one target appears at multiple positions of the same pathway.Type III enrichment: CVD drugs are significantly enriched in the pathway.r is the number of clusters, i and j. The maximum modularity metric corresponds to the partition that comprises as many as within-module links and as few as possible inter-module links.We applied the simulated annealing algorithm Astragalus membranaceus (Fisch) Bunge to a 99.2% purity  and dissolved in DMSO. The calcineurin assay kit was purchased from Nanjing Jiancheng Bioengineering Institute (NJBI) . Phenylephrine (PE), cyclosporin A (CsA) and enalapril maleate (EM) were purchased from Sigma-Aldrich . Anti-phospho-JNK mAb, anti-JNK mAb, and their respective horseradish peroxidase-coupled secondary antibodies were purchased from Santa Cruz . All other reagents were purchased from Sigma .Dulbecco's modified Eagle's medium (DMEM) media, fetal bovine serum and 0.25% trypsin-EDTA for the cell culture were purchased from Invitrogen . AGS-IV (lot no. 030510) was extracted from 2 atmosphere. The cells were seeded onto six-well plates or 35-mm dishes and cultured to a near confluent condition. Primary VSMC (<4 passages) were used.All research involving animals complied with protocols approved by the Animal Care and Use Committee in Second Military Medical University. The medial layer of the thoracic aorta from 7-day-old Wistar rats was extracted and cultured in DMEM containing 5% FBS at 37°C in a 5% COThe activity of calcineurin was determined using a calcineurin activity assay kit as described in the manufacturer's protocol. The RII-phosphopeptide (BioMol) was used as a highly specific substrate for calcineurin. The detection of free inorganic phosphate released from RII by calcineurin was based on the malachite green dye reaction. Reactions were terminated after 30 min, and absorption was determined by UV spectroscopy at 660 nm. The activity was corrected for protein concentration. Calcineurin activity was expressed as percentage relative to the PBS control.The ACE activity of human endothelial cells  was determined by the rate of production of hippuric acid from the synthetic tripeptide substrate hippuryl-L-histidyl-L-leucine (HHL) according to previously published methods VSMCs were plated in 6-well plates and incubated with either AGS-IV (800 µg/L) or PBS for 30 min. After stimulation with 100 ng/L LPS for 10 or 20 min, the cells were lysed and phosphorylated JNK was detected by Western blotting. JNK activation was normalized to β-actin.Cells were lysed with M-PER protein extraction reagent  supplemented with protease inhibitor cocktail and protein concentrations in the extracts were measured by a bicinchoninic acid (BCA) assay (Pierce). Forty micrograms of the protein was used either for immunoprecipitation or subjected to sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE) and transferred onto nitrocellulose membranes. The β-actin content of each sample was determined to demonstrate equal protein loading.We applied a well-documented improved anchorage velocity-dependent separation method to separate and purify the cardiomyocytes 5 cells/ml. Twenty four h later, cardiomyocytes were incubated with different concentrations of CsA  or AS-IV  for 1 h, then stimulated with adriamycin (ADR) (4.5 µg/ml) for 24 h.Cardiomyocytes were seeded into a 12-well culture plate at a density of 1∼5×10The activity of LDH in the culture supernatant of drug-treated cardiomyocytes was determined using an LDH activity assay kit .Figure S1Log-log plots for degree distribution of pathway nodes in target-pathway network (a) and drug-pathway network (b) for FDA-approved small molecule CVD drugs. Distribution of pathway nodes in both of the networks obeyed power laws.(TIF)Click here for additional data file.Figure S2Comparison of percentage of distinct protein targets and regulating points for cardiovascular targets significantly enriched pathways (P<0.05). Pathways permuted decreasingly according to percentage. (a) Type I enrichment pathways: enrichment of distinct CVD drug targets (b) Type II enrichment pathways: enrichment of CVD drug target nodes. Pathway names are listed in (TIF)Click here for additional data file.Figure S3Comparison of percentage of FDA-approved drugs acting on cardiovascular drugs significantly enriched pathways (P<0.05). Pathways permuted decreasingly according to percentage. Pathway names are listed in (TIF)Click here for additional data file.Figure S4Chemical structure and 3D molecular structure of Astragaloside IV. (a) Chemical structure of AGS-IV. (b) 3D molecular structure of AGS-IV. Grey, red, and white colors represent carbon, oxygen and hydrogen atom, respectively.(TIF)Click here for additional data file.Table S1List of 33 KEGG pathways that are significantly regulated by CVD drugs.(PDF)Click here for additional data file.Table S2Putative therapeutic targets of AGS-IV identified from INVDOCK search of candidate protein 3D structure data set. PDB ID is the identification number for a protein in the PDB. Target Class: AC: target for approved CVD drugs; A: target for approved drugs of other classes; E: target for experimental drugs; U: protein not applied as target. The properties of proteins with no references were obtained from the Uniprot database. Proteins that have been reported in the literature as associated with CVD therapy are indicated in bold.(PDF)Click here for additional data file.