Motif-guided sparse decomposition of gene expression data for regulatory module identification

<p>Abstract</p> <p>Background</p> <p>Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated.</p> <p>Results</p> <p>We propose a novel approach, motif-guided sparse decomposition (mSD), to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1) transcription factor activity and (2) the strength of the predicted gene regulation event(s). Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer.</p> <p>Conclusion</p> <p>We have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD) of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The experimental results show that such a motif-guided strategy can provide context-specific regulatory modules in both yeast and breast cancer studies.</p

Fabrication of ciprofloxacin loaded alginate/cockle shell powder nanobiocomposite bone scaffold

Orthopedic implant infection is one of the most challenging issues in bone tissue engineering industry. Hence, local delivery of antibiotics incorporated into a fabricated bone scaffold possibly provides a more rapid bacteria inhibitory effect. In this study, pure ciprofloxacin loaded alginate/cockle shell powder nanobiocomposite bone scaffolds are fabricated with 5 wt% and 10 wt% ciprofloxacin respectively and tested for drug encapsulation, drug release and antibacterial properties towards common implant infecting bacterial strains (Staphylococcus aureus and Pseudomonas aeruginosa). Results from the studies showed a low drug encapsulation and drug release regardless of the concentration of drugs loaded with no significant differences noted (p<0.05). However, bacterial inhibition studies through direct contact and using eluted samples from drug release studies showed some inhibitory effects towards the growth of both bacterial strains tested. These findings were further justified with microscopy observations on biofilm and bacterial colony formation. Mineralization studies conducted additionally indicated that the scaffolds characteristics was not compromised due to drug loading. Although pure ciprofloxacin may not be the most suitable antibiotic to be incorporated into the nanobiocomposite bone scaffold, the study did provide some insight to the possible use of the scaffold for future drug delivery applications

Phase Transition in a One-Dimensional Extended Peierls-Hubbard Model with a Pulse of Oscillating Electric Field: I. Threshold Behavior in Ionic-to-Neutral Transition

Photoinduced dynamics of charge density and lattice displacements is calculated by solving the time-dependent Schr\"odinger equation for a one-dimensional extended Peierls-Hubbard model with alternating potentials for the mixed-stack organic charge-transfer complex, TTF-CA. A pulse of oscillating electric field is incorporated into the Peierls phase of the transfer integral. The frequency, the amplitude, and the duration of the pulse are varied to study the nonlinear and cooperative character of the photoinduced transition. When the dimerized ionic phase is photoexcited, the threshold behavior is clearly observed by plotting the final ionicity as a function of the increment of the total energy. Above the threshold photoexcitation, the electronic state reaches the neutral one with equidistant molecules after the electric field is turned off. The transition is initiated by nucleation of a metastable neutral domain, for which an electric field with frequency below the linear absorption peak is more effective than that at the peak. When the pulse is strong and short, the charge transfer takes place on the same time scale with the disappearance of dimerization. As the pulse becomes weak and long, the dimerization-induced polarization is disordered to restore the inversion symmetry on average before the charge transfer takes place to bring the system neutral. Thus, a paraelectric ionic phase is transiently realized by a weak electric field. It is shown that infrared light also induces the ionic-to-neutral transition, which is characterized by the threshold behavior.Comment: 24 pages, 11 figure

Dietary yeast influences ethanol sedation in Drosophila via serotonergic neuron function

Abuse of alcohol is a major clinical problem with far- reaching health consequences. Understanding the environmental and genetic factors that contribute to alcohol- related behaviors is a potential gateway for developing novel therapeutic approaches for patients that abuse the drug. To this end, we have used Drosophila melanogaster as a model to investigate the effect of diet, an environmental factor, on ethanol sedation. Providing flies with diets high in yeast, a routinely used component of fly media, increased their resistance to ethanol sedation. The yeast- induced resistance to ethanol sedation occurred in several different genetic backgrounds, was observed in males and females, was elicited by yeast from different sources, was readily reversible, and was associated with increased nutrient intake as well as decreased internal ethanol levels. Inhibition of serotonergic neuron function using multiple independent genetic manipulations blocked the effect of yeast supplementation on ethanol sedation, nutrient intake, and internal ethanol levels. Our results demonstrate that yeast is a critical dietary component that influences ethanol sedation in flies and that serotonergic signaling is required for the effect of dietary yeast on nutrient intake, ethanol uptake/elimination, and ethanol sedation. Our studies establish the fly as a model for diet- induced changes in ethanol sedation and raise the possibility that serotonin might mediate the effect of diet on alcohol- related behavior in other species.Flies fed a high yeast diet consume more nutrients, have decreased levels of internal ethanol when exposed to ethanol vapor and require longer exposure to ethanol to become sedated (ie, increased ST50). Our studies implicate serotonergic neurons as key regulators of nutrient consumption and therefore, the effect of dietary yeast on ethanol sedation in flies.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155987/1/adb12779.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155987/2/adb12779_am.pd

Arachis hypogaea gene expression atlas for fastigiata subspecies of cultivated groundnut to accelerate functional and translational genomics applications

Spatio-temporal and developmental stage-specific transcriptome analysis plays a crucial role in systems biology-based improvement of any species. In this context, we report here the Arachis hypogaea gene expression atlas (AhGEA) for the world’s widest cultivated subsp. fastigiata based on RNA-seq data using 20 diverse tissues across five key developmental stages. Approximately 480 million paired-end filtered reads were generated followed by identification of 81 901 transcripts from an early-maturing, high-yielding, drought-tolerant groundnut variety, ICGV 91114. Further, 57 344 genome-wide transcripts were identified with ≥1 FPKM across different tissues and stages. Our in-depth analysis of the global transcriptome sheds light into complex regulatory networks namely gravitropism and photomorphogenesis, seed development, allergens and oil biosynthesis in groundnut. Importantly, interesting insights into molecular basis of seed development and nodulation have immense potential for translational genomics research. We have also identified a set of stable expressing transcripts across the selected tissues, which could be utilized as internal controls in groundnut functional genomics studies. The AhGEA revealed potential transcripts associated with allergens, which upon appropriate validation could be deployed in the coming years to develop consumer-friendly groundnut varieties. Taken together, the AhGEA touches upon various important and key features of cultivated groundnut and provides a reference for further functional, comparative and translational genomics research for various economically important traits

Effects of Lattice and Molecular Phonons on Photoinduced Neutral-to-Ionic Transition Dynamics in Tetrathiafulvalene-pp-Chloranil

For electronic states and photoinduced charge dynamics near the neutral-ionic transition in the mixed-stack charge-transfer complex tetrathiafulvalene-$p$-chloranil (TTF-CA), we review the effects of Peierls coupling to lattice phonons modulating transfer integrals and Holstein couplings to molecular vibrations modulating site energies. The former stabilizes the ionic phase and reduces discontinuities in the phase transition, while the latter stabilizes the neutral phase and enhances the discontinuities. To reproduce the experimentally observed ionicity, optical conductivity and photoinduced charge dynamics, both couplings are quantitatively important. In particular, strong Holstein couplings to form the highly-stabilized neutral phase are necessary for the ionic phase to be a Mott insulator with large ionicity. A comparison with the observed photoinduced charge dynamics indicates the presence of strings of lattice dimerization in the neutral phase above the transition temperature.Comment: 9 pages, 7 figures, accepted for publication in J. Phys. Soc. Jp

The problem of a metal impurity in an oxide: ab-initio study of electronic and structural properties of Cd in Rutile TiO2

In this work we undertake the problem of a transition metal impurity in an oxide. We present an ab-initio study of the relaxations introduced in TiO2 when a Cd impurity replaces substitutionally a Ti atom. Using the Full-Potential Linearized-Augmented-Plane-Wave method we obtain relaxed structures for different charge states of the impurity and computed the electric-field gradients (EFGs) at the Cd site. We find that EFGs, and also relaxations, are dependent on the charge state of the impurity. This dependence is very remarkable in the case of the EFG and is explained analyzing the electronic structure of the studied system. We predict fairly anisotropic relaxations for the nearest oxygen neighbors of the Cd impurity. The experimental confirmation of this prediction and a brief report of these calculations have recently been presented [P.R.L. 89, 55503 (2002)]. Our results for relaxations and EFGs are in clear contradiction with previous studies of this system that assumed isotropic relaxations and point out that no simple model is viable to describe relaxations and the EFG at Cd in TiO2 even approximately.Comment: 11 pages, 8 figures, Revtex 4, published in Physical Review

Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping

Background: Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers. Results: An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90–9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program. Conclusion: This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties

A clinical prediction rule for diagnosing human infections with avian influenza A(H7N9) in a hospital emergency department setting

BACKGROUND: Human infections with avian influenza A(H7N9) virus are associated with severe illness and high mortality. To better inform triage decisions of hospitalization and management, we developed a clinical prediction rule for diagnosing patients with A(H7N9) and determined its predictive performance. METHODS: Clinical details on presentation of adult patients hospitalized with either A(H7N9)(n = 121) in China from March to May 2013 or other causes of acute respiratory infections (n = 2,603) in Jingzhou City, China from January 2010 through September 2012 were analyzed. A clinical prediction rule was developed using a two-step coefficient-based multivariable logistic regression scoring method and evaluated with internal validation by bootstrapping. RESULTS: In step 1, predictors for A(H7N9) included male sex, poultry exposure history, and fever, haemoptysis, or shortness of breath on history and physical examination. In step 2, haziness or pneumonic consolidation on chest radiographs and leukopenia were also associated with a higher probability of A(H7N9). The observed risk of A(H7N9) was 0.3% for those assigned to the low-risk group and 2.5%, 4.3%, and 44.0% for tertiles 1 through 3, respectively, in the high-risk group. This prediction rule achieved good model performance, with an optimism-corrected sensitivity of 0.93, a specificity of 0.80, and an area under the receiver-operating characteristic curve of 0.96. CONCLUSIONS: A simple decision rule based on data readily obtainable in the setting of patients' first clinical presentations from the first wave of the A/H7N9 epidemic in China has been developed. This prediction rule has achieved good model performance in predicting their risk of A(H7N9) infection and should be useful in guiding important clinical and public health decisions in a timely and objective manner. Data to be gathered with its use in the current evolving second wave of the A/H7N9 epidemic in China will help to inform its performance in the field and contribute to its further refinement.published_or_final_versio