Hub-Centered Gene Network Reconstruction Using Automatic Relevance Determination

Network inference deals with the reconstruction of biological networks from experimental data. A variety of different reverse engineering techniques are available; they differ in the underlying assumptions and mathematical models used. One common problem for all approaches stems from the complexity of the task, due to the combinatorial explosion of different network topologies for increasing network size. To handle this problem, constraints are frequently used, for example on the node degree, number of edges, or constraints on regulation functions between network components. We propose to exploit topological considerations in the inference of gene regulatory networks. Such systems are often controlled by a small number of hub genes, while most other genes have only limited influence on the network's dynamic. We model gene regulation using a Bayesian network with discrete, Boolean nodes. A hierarchical prior is employed to identify hub genes. The first layer of the prior is used to regularize weights on edges emanating from one specific node. A second prior on hyperparameters controls the magnitude of the former regularization for different nodes. The net effect is that central nodes tend to form in reconstructed networks. Network reconstruction is then performed by maximization of or sampling from the posterior distribution. We evaluate our approach on simulated and real experimental data, indicating that we can reconstruct main regulatory interactions from the data. We furthermore compare our approach to other state-of-the art methods, showing superior performance in identifying hubs. Using a large publicly available dataset of over 800 cell cycle regulated genes, we are able to identify several main hub genes. Our method may thus provide a valuable tool to identify interesting candidate genes for further study. Furthermore, the approach presented may stimulate further developments in regularization methods for network reconstruction from data

Estimation of physician supply by specialty and the distribution impact of increasing female physicians in Japan

<p>Abstract</p> <p>Background</p> <p>Japan has experienced two large changes which affect the supply and distribution of physicians. They are increases in medical school enrollment capacity and in the proportion of female physicians. The purpose of this study is to estimate the future supply of physicians by specialty and to predict the associated impact of increased female physicians, as well as to discuss the possible policy implications.</p> <p>Methods</p> <p>Based on data from the 2004 and 2006 National Survey of Physicians, Dentists and Pharmacists, we estimated the future supply of physicians by specialty, using multistate life tables. Based on possible scenarios of the future increase in female physicians, we also estimated the supply of physicians by specialty.</p> <p>Results</p> <p>Even if Japan's current medical school enrollment capacity is maintained in subsequent years, the number of physicians per 1000 population is expected to increase from 2.2 in 2006 to 3.2 in 2036, which is a 46% increase from the current level. The numbers of obstetrician/gynecologists (OB/GYNs) and surgeons are expected to temporarily decline from their current level, whereas the number of OB/GYNs per 1000 births will still increase because of the declining number of births. The number of surgeons per 1000 population, even with the decreasing population, will decline temporarily over the next few years. If the percentage of female physicians continues to increase, the overall number of physicians will not be significantly affected, but in specialties with current very low female physician participation rates, such as surgery, the total number of physicians is expected to decline significantly.</p> <p>Conclusion</p> <p>At the current medical school enrollment capacity, the number of physicians per population is expected to continue to increase because of the skewed age distribution of physicians and the declining population in Japan. However, with changes in young physicians' choices of medical specialties and as the percentage of female physicians increases, patterns of physician supply will vary between specialties. Specialties less often chosen by young physicians and where males have dominated will face a decline in physician supply. These results highlight the necessity for developing a work environment that attracts female physicians to these types of specialties. This will also lead to improved gender equality in the workforce and more effective use of human resources.</p

Cerebellar Globular Cells Receive Monoaminergic Excitation and Monosynaptic Inhibition from Purkinje Cells

Inhibitory interneurons in the cerebellar granular layer are more heterogeneous than traditionally depicted. In contrast to Golgi cells, which are ubiquitously distributed in the granular layer, small fusiform Lugaro cells and globular cells are located underneath the Purkinje cell layer and small in number. Globular cells have not been characterized physiologically. Here, using cerebellar slices obtained from a strain of gene-manipulated mice expressing GFP specifically in GABAergic neurons, we morphologically identified globular cells, and compared their synaptic activity and monoaminergic influence of their electrical activity with those of small Golgi cells and small fusiform Lugaro cells. Globular cells were characterized by prominent IPSCs together with monosynaptic inputs from the axon collaterals of Purkinje cells, whereas small Golgi cells or small fusiform Lugaro cells displayed fewer and smaller spontaneous IPSCs. Globular cells were silent at rest and fired spike discharges in response to application of either serotonin (5-HT) or noradrenaline. The two monoamines also facilitated small Golgi cell firing, but only 5-HT elicited firing in small fusiform Lugaro cells. Furthermore, globular cells likely received excitatory monosynaptic inputs through mossy fibers. Because globular cells project their axons long in the transversal direction, the neuronal circuit that includes interplay between Purkinje cells and globular cells could regulate Purkinje cell activity in different microzones under the influence of monoamines and mossy fiber inputs, suggesting that globular cells likely play a unique modulatory role in cerebellar motor control

The effects of sleep deprivation, acute hypoxia, and exercise on cognitive performance: A multi-experiment combined stressors study

Introduction: Both sleep deprivation and hypoxia have been shown to impair executive function. Conversely, moderate intensity exercise is known to improve executive function. In a multi-experiment study, we tested the hypotheses that moderate intensity exercise would ameliorate any decline in executive function after i) three consecutive nights of partial sleep deprivation (PSD) (Experiment 1) and ii) the isolated and combined effects of a single night of total sleep deprivation (TSD) and acute hypoxia (Experiment 2). Methods: Using a rigorous randomised controlled crossover design, 12 healthy participants volunteered in each experiment (24 total, 5 females). In both experiments seven executive function tasks (2-choice reaction time, logical relations, manikin, mathematical processing, 1-back, 2-back, 3-back) were completed at rest and during 20 min semi-recumbent, moderate intensity cycling. Tasks were completed in the following conditions: before and after three consecutive nights of PSD and habitual sleep (Experiment 1) and in normoxia and acute hypoxia (FIO2 = 0.12) following one night of habitual sleep and one night of TSD (Experiment 2). Results: Although the effects of three nights of PSD on executive functions were inconsistent, one night of TSD (regardless of hypoxic status) reduced executive functions. Significantly, regardless of sleep or hypoxic status, executive functions are improved during an acute bout of moderate intensity exercise. Conclusion: These novel data indicate that moderate intensity exercise improves executive function performance after both PSD and TSD, regardless of hypoxic status. The key determinants and/or mechanism(s) responsible for this improvement still need to be elucidated. Future work should seek to identify these mechanisms and translate these significant findings into occupational and skilled performance settings

A Computational Mechanism for Unified Gain and Timing Control in the Cerebellum

Precise gain and timing control is the goal of cerebellar motor learning. Because the basic neural circuitry of the cerebellum is homogeneous throughout the cerebellar cortex, a single computational mechanism may be used for simultaneous gain and timing control. Although many computational models of the cerebellum have been proposed for either gain or timing control, few models have aimed to unify them. In this paper, we hypothesize that gain and timing control can be unified by learning of the complete waveform of the desired movement profile instructed by climbing fiber signals. To justify our hypothesis, we adopted a large-scale spiking network model of the cerebellum, which was originally developed for cerebellar timing mechanisms to explain the experimental data of Pavlovian delay eyeblink conditioning, to the gain adaptation of optokinetic response (OKR) eye movements. By conducting large-scale computer simulations, we could reproduce some features of OKR adaptation, such as the learning-related change of simple spike firing of model Purkinje cells and vestibular nuclear neurons, simulated gain increase, and frequency-dependent gain increase. These results suggest that the cerebellum may use a single computational mechanism to control gain and timing simultaneously

A Link among DNA Replication, Recombination, and Gene Expression Revealed by Genetic and Genomic Analysis of TEBICHI Gene of Arabidopsis thaliana

Spatio-temporal regulation of gene expression during development depends on many factors. Mutations in Arabidopsis thaliana TEBICHI (TEB) gene encoding putative helicase and DNA polymerase domains-containing protein result in defects in meristem maintenance and correct organ formation, as well as constitutive DNA damage response and a defect in cell cycle progression; but the molecular link between these phenotypes of teb mutants is unknown. Here, we show that mutations in the DNA replication checkpoint pathway gene, ATR, but not in ATM gene, enhance developmental phenotypes of teb mutants, although atr suppresses cell cycle defect of teb mutants. Developmental phenotypes of teb mutants are also enhanced by mutations in RAD51D and XRCC2 gene, which are involved in homologous recombination. teb and teb atr double mutants exhibit defects in adaxial-abaxial polarity of leaves, which is caused in part by the upregulation of ETTIN (ETT)/AUXIN RESPONSIVE FACTOR 3 (ARF3) and ARF4 genes. The Helitron transposon in the upstream of ETT/ARF3 gene is likely to be involved in the upregulation of ETT/ARF3 in teb. Microarray analysis indicated that teb and teb atr causes preferential upregulation of genes nearby the Helitron transposons. Furthermore, interestingly, duplicated genes, especially tandemly arrayed homologous genes, are highly upregulated in teb or teb atr. We conclude that TEB is required for normal progression of DNA replication and for correct expression of genes during development. Interplay between these two functions and possible mechanism leading to altered expression of specific genes will be discussed

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

The Human Phenotype Ontology in 2017.

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution