High-throughput DNA Microarray Research Articles

DNA Microarray and Bioinformatic Analysis Reveals the Potential of Whale Oil in Enhancing Hair Growth in a C57BL/6 Mice Dorsal Skin Model.

Much research has been conducted to determine how hair regeneration is regulated, as this could provide therapeutic, cosmetic, and even psychological interventions for hair loss. The current study focused on the hair growth effect and effective utilization of fatty oil obtained from Bryde's whales through a high-throughput DNA microarray approach in conjunction with immunohistochemical observations. The research also examined the mechanisms and factors involved in hair growth. In an experiment using female C57BL/6J mice, the vehicle control group (VC: propylene glycol: ethanol: water), the positive control group (MXD: 3% minoxidil), and the experimental group (WO: 20% whale oil) were topically applied to the dorsal skin of the mouse. The results showed that 3% MXD and 20% WO were more effective than VC in promoting hair growth, especially 20% WO. Furthermore, in hematoxylin and eosin-stained dorsal skin tissue, an increase in the number of hair follicles and subcutaneous tissue thickness was observed with 20% WO. Whole-genome transcriptome analysis also confirmed increases for 20% WO in filaggrin (Flg), a gene related to skin barrier function; fibroblast growth factor 21 (Fgf21), which is involved in hair follicle development; and cysteine-rich secretory protein 1 (Crisp1), a candidate gene for alopecia areata. Furthermore, the results of KEGG pathway analysis indicated that 20% WO may have lower stress and inflammatory responses than 3% MXD. Therefore, WO is expected to be a safe hair growth agent.

Photothermal-Controlled Release of IL-4 in IL-4/PDA-Immobilized Black Titanium Dioxide (TiO2) Nanotubes Surface to Enhance Osseointegration: An In Vivo Study.

Host immune response has gradually been accepted as a critical factor in achieving successful implant osseointegration. The aim of this study is to create a favorable immune microenvironment by the dominant release of IL-4 during the initial few days after implant insertion to mitigate early inflammatory reactions and facilitate osseointegration. Herein, the B-TNT/PDA/IL-4 substrate was established by immobilizing an interleukin-4 (IL-4)/polydopamine (PDA) coating on a black TiO2 nanotube (B-TNT) surface, achieving on-demand IL-4 release under near infrared (NIR) irradiation. Gene Ontology (GO) enrichment analyses based on high-throughput DNA microarray data revealed that IL-4 addition inhibited osteoclast differentiation and function. Animal experiment results suggested that the B-TNT/PDA/IL-4+Laser substrate induced the least inflammatory, tartrate-resistant acid phosphatase, inducible nitric oxide synthase and the most CD163 positive cells, compared to the Ti group at 7 days post-implantation. In addition, 28 days post-implantation, micro-computed tomography results showed the highest bone volume/total volume, trabecular thickness, trabecular number and the lowest trabecular separation, while Hematoxylin-eosin and Masson-trichrome staining revealed the largest amount of new bone formation for the B-TNT/PDA/IL-4+Laser group. This study revealed the osteoimmunoregulatory function of the novel B-TNT/PDA/IL-4 surface by photothermal release of IL-4 at an early period post-implantation, thus paving a new way for dental implant surface modification.

Universal probe-based intermediate primer-triggered qPCR (UPIP-qPCR) for SNP genotyping

BackgroundThe detection and identification of single nucleotide polymorphism (SNP) is essential for determining patient disease susceptibility and the delivery of medicines targeted to the individual. At present, SNP genotyping technology includes Sanger sequencing, TaqMan-probe quantitative polymerase chain reaction (qPCR), amplification-refractory mutation system (ARMS)-PCR, and Kompetitive Allele-Specific PCR (KASP). However, these technologies have some disadvantages: the high cost of development and detection, long and time consuming protocols, and high false positive rates. Focusing on these limitations, we proposed a new SNP detection method named universal probe-based intermediate primer-triggered qPCR (UPIP-qPCR). In this method, only two types of fluorescence-labeled probes were used for SNP genotyping, thus greatly reducing the cost of development and detection for SNP genotyping.ResultsIn the amplification process of UPIP-qPCR, unlabeled intermediate primers with template-specific recognition functions could trigger probe hydrolysis and specific signal release. UPIP-qPCR can be used successfully and widely for SNP genotyping. The sensitivity of UPIP-qPCR in SNP genotyping was 0.01 ng, the call rate was more than 99.1%, and the accuracy was more than 99.9%. High-throughput DNA microarrays based on intermediate primers can be used for SNP genotyping.ConclusionThis novel approach is both cost effective and highly accurate; it is a reliable SNP genotyping method that would serve the needs of the clinician in the provision of targeted medicine.

Transcriptomics of Mature Rice (Oryza Sativa L. Koshihikari) Seed under Hot Conditions by DNA Microarray Analyses

Higher temperature conditions during the final stages of rice seed development (seed filling and maturation) are known to cause damage to both rice yield and rice kernel quality. The western and central parts of Japan especially have seen record high temperatures during the past decade, resulting in the decrease of rice kernel quality. In this study, we looked at the rice harvested from a town in the central Kanto-plains (Japan) in 2010. The daytime temperatures were above the critical limits ranging from 34 to 38 °C at the final stages of seed development and maturity allowing us to investigate high-temperature effects in the actual field condition. Three sets of dry mature rice seeds (commercial), each with specific quality standards, were obtained from Japan Agriculture (JA Zen-Noh) branch in Ami-town of Ibaraki Prefecture in September 2010: grade 1 (top quality, labeled as Y1), grade 2 (medium quality, labeled as Y2), and grade 3 (out-of-grade or low quality, labeled as Y3). The research objective was to examine particular alterations in genome-wide gene expression in grade 2 (Y2) and grade 3 (Y3) seeds compared to grade 1 (Y1). We followed the high-temperature spike using a high-throughput omics-approach DNA microarray (Agilent 4 × 44 K rice oligo DNA chip) in conjunction with MapMan bioinformatics analysis. As expected, rice seed quality analysis revealed low quality in Y3 > Y2 over Y1 in taste, amylose, protein, and fatty acid degree, but not in water content. Differentially expressed gene (DEG) analysis from the transcriptomic profiling data revealed that there are more than one hundred upregulated (124 and 373) and downregulated (106 and 129) genes in Y2 (grade 2 rice seed) and Y3 (grade 3 rice seed), respectively. Bioinformatic analysis of DEGs selected as highly regulated differentially expressed (HRDE) genes revealed changes in function of genes related to metabolism, defense/stress response, fatty acid biosynthesis, and hormones. This research provides, for the first time, the seed transcriptome profile for the classified low grades (grade 2, and out-of-grade; i.e., grade 3) of rice under high-temperature stress condition.

Improved k-nearest neighbors approach for incomplete and contaminated gene expression datasets

With the rapid development of high-throughput DNA microarray technologies, researchers can measure expression profiles of thousands of genes simultaneously with low costs. These massive amounts of gene expression (GE) data often contain missing values or outliers due to various reasons of data generating process. Most of the statistical methods were developed based on complete dataset. As a result, for subsequent analysis using incomplete dataset, these methods strongly suffer and we cannot find our target. A numerous methods have been developed to impute missing values and they are available in the literature. Albeit, missing values imputation and outliers handling both are equally important for analyzing GE, most of the methods perform these tasks separately and produce misleading results. Therefore, in this paper, an attempt is made to develop a new hybrid approach which is robust against outliers and missing values, simultaneously. We demonstrate the performance of the proposed method in a comparison of popular missing value imputation method K-NN while performing feature selection using both simulated and real GE datasets. The Results obtain from simulated as well as real data studies show that the proposed method outperforms K-NN in presence of different percentages of missing values and outliers. On the other hand, in absence of outliers with missing values, the proposed method keeps equal performance with the other methods.
 J. bio-sci. 27: 31-41, 2019

Evaluation of the Vibrant DNA microarray for the high-throughput multiplex detection of enteric pathogens in clinical samples

ABSTRACTBackgroundRapid detection of a wide range of etiologic agents is essential for appropriate treatment and control of gastrointestinal (GI) infections. A variety of microbial species including bacteria, viruses, parasites, and fungi have been recognized as diarrheagenic enteric pathogens. However, multiplex testing of various targets in a single reaction needs further improvement because of its limitation in species and throughput.ResultsThis study aims at developing and evaluating a DNA microarray-based qualitative multiplexed polymerase chain reaction (PCR) assay, Vibrant GI pathogen panel (GPP), for simultaneous detection of 27 enteric GI pathogenic targets (16 bacteria, 5 viruses, 4 parasites, and 2 fungi) directly from stool specimens. Limits of detection ranged from 102 to 104 cells/mL for bacteria, 102 to 103 cells/mL for parasites, 102 to 103 RNA copies/mL for viruses, and 102 to 103 cells/mL for fungi. Performance characteristics were determined using 27 Quantitative Genomic DNAs, 212 spiked stool specimens, 1067 clinical and archived stool specimens. Overall sensitivity was 95.9% (95% CI 92.4–98.1) and specificity was 100% (95% CI 99.9–100). Polymicrobial detections contained either two or three organisms was 20.2% (35/173) of positive clinical specimens and 3.3% (35/1055) of all clinical specimens.ConclusionThe Vibrant GPP is a comprehensive, high-throughput, and rapid DNA microarray to provide etiologic diagnosis of GI infections in the laboratory setting.

Acidobacteria Subgroups and Their Metabolic Potential for Carbon Degradation in Sugarcane Soil Amended With Vinasse and Nitrogen Fertilizers.

Acidobacteria is a predominant bacterial phylum in tropical agricultural soils, including sugarcane cultivated soils. The increased need for fertilizers due to the expansion of sugarcane production is a threat to the ability of the soil to maintain its potential for self-regulation in the long term, in witch carbon degradation has essential role. In this study, a culture-independent approach based on high-throughput DNA sequencing and microarray technology was used to perform taxonomic and functional profiling of the Acidobacteria community in a tropical soil under sugarcane (Saccharum spp.) that was supplemented with nitrogen (N) combined with vinasse. These analyses were conducted to identify the subgroup-level responses to chemical changes and the carbon (C) degradation potential of the different Acidobacteria subgroups. Eighteen Acidobacteria subgroups from a total of 26 phylogenetically distinct subgroups were detected based on high-throughput DNA sequencing, and 16 gene families associated with C degradation were quantified using Acidobacteria-derived DNA microarray probes. The subgroups Gp13 and Gp18 presented the most positive correlations with the gene families associated with C degradation, especially those involved in hemicellulose degradation. However, both subgroups presented low abundance in the treatment containing vinasse. In turn, the Gp4 subgroup was the most abundant in the treatment that received vinasse, but did not present positive correlations with the gene families for C degradation analyzed in this study. The metabolic potential for C degradation of the different Acidobacteria subgroups in sugarcane soil amended with N and vinasse can be driven in part through the increase in soil nutrient availability, especially calcium (Ca), magnesium (Mg), potassium (K), aluminum (Al), boron (B) and zinc (Zn). This soil management practice reduces the abundance of Acidobacteria subgroups, including those potentially involved with C degradation in this agricultural soil.

Comparison of Pathogenic Bacteria in Water and Fecal-Source Samples in the Kathmandu Valley, Nepal, Using High-Throughput DNA Microarray

Rapid population growth and unplanned urbanization are causing an insufficient drinking water supply, which is a major problem in the Kathmandu Valley, Nepal. People are therefore using groundwater for drinking, cooking, bathing, and laundry purposes [1].

Mining Gene Expression Profile with Missing Values: An Integration of Kernel PCA and Robust Singular Values Decomposition

Background: Gene expression profiling and transcriptomics provide valuable information about the role of genes that are differentially expressed between two or more samples. It is always important and challenging to analyse High-throughput DNA microarray data with a number of missing values under various experimental conditions. </P><P> Objectives: Graphical data visualizations of the expression of all genes in a particular cell provide holistic views of gene expression patterns, which improve our understanding of cellular systems under normal and pathological conditions. However, current visualization methods are sensitive to missing values, which are frequently observed in microarray-based gene expression profiling, potentially affecting the subsequent statistical analyses. Methods: We addressed in this study the problem of missing values with respect to different imputation methods using gene expression biplot (GE biplot), one of the most popular gene visualization techniques. The effects of missing values for mining differentially expressed genes in gene expression data were evaluated using four well-known imputation methods: Robust Singular Value Decomposition (Robust SVD), Column Average (CA), Column Median (CM), and K-nearest Neighbors (KNN). Frobenius norm and absolute distances were used to measure the accuracy of the methods. Results: Three numerical experiments were performed using simulated data (i) and publicly available colon cancer (ii) and leukemia data (iii) to analyze the performance of each method. The results showed that CM and KNN performed better than Robust SVD and CA for identifying the index gene profile in the biplot visualization in both the simulation study and the colon cancer and leukemia microarray datasets. Conclusion: The impact of missing values on the GE biplot was smaller when the data matrix was imputed by KNN than by CM. This study concluded that KNN performed satisfactorily in generating a GE biplot in the presence of missing values in microarray data.

Morphological and transcriptional responses of Lycopersicon esculentum to hexavalent chromium in agricultural soil.

The carcinogenic, teratogenic, and mutagenic effects of hexavalent chromium (Cr[VI]) on living organisms through the food chain raise the immediate need to assess the potential toxicological impacts of Cr(VI) on human health. Therefore, the concentration-dependent responses of 12 Cr(VI)-responsive genes selected from a high-throughput Lycopersicon esculentum complementary DNA microarray were examined at different Cr concentrations. The results indicated that most of the genes were differentially expressed from 0.1 mg Cr/kg soil, whereas the lowest-observable-adverse-effect concentrations of Cr(VI) were 1.6 mg Cr/kg soil, 6.4 mg Cr/kg soil, 3.2 mg Cr/kg soil, and 0.4 mg Cr/kg soil for seed germination, root elongation, root biomass, and root morphology, respectively, implying that the transcriptional method was more sensitive than the traditional method in detecting Cr(VI) toxicity. Dose-dependent responses were observed for the relative expression of expansin (p = 0.778), probable chalcone-flavonone isomerase 3 (p = -0.496), and 12S seed storage protein CRD (p = -0.614); therefore, the authors propose the 3 genes as putative biomarkers in Cr(VI)-contaminated soil. Environ Toxicol Chem 2016;35:1751-1758. © 2015 SETAC.

Unraveling the Specific Ischemic Core and Penumbra Transcriptome in the Permanent Middle Cerebral Artery Occlusion Mouse Model Brain Treated with the Neuropeptide PACAP38.

Our group has been systematically investigating the effects of the neuropeptide pituitary adenylate-cyclase activating polypeptide (PACAP) on the ischemic brain. To do so, we have established and utilized the permanent middle cerebral artery occlusion (PMCAO) mouse model, in which PACAP38 (1 pmol) injection is given intracerebroventrically and compared to a control saline (0.9% sodium chloride, NaCl) injection, to unravel genome-wide gene expression changes using a high-throughput DNA microarray analysis approach. In our previous studies, we have accumulated a large volume of data (gene inventory) from the whole brain (ipsilateral and contralateral hemispheres) after both PMCAO and post-PACAP38 injection. In our latest research, we have targeted specifically infarct or ischemic core (hereafter abbreviated IC) and penumbra (hereafter abbreviated P) post-PACAP38 injections in order to re-examine the transcriptome at 6 and 24 h post injection. The current study aims to delineate the specificity of expression and localization of differentially expressed molecular factors influenced by PACAP38 in the IC and P regions. Utilizing the mouse 4 × 44 K whole genome DNA chip we show numerous changes (≧/≦ 1.5/0.75-fold) at both 6 h (654 and 456, and 522 and 449 up- and down-regulated genes for IC and P, respectively) and 24 h (2568 and 2684, and 1947 and 1592 up- and down-regulated genes for IC and P, respectively) after PACAP38 treatment. Among the gene inventories obtained here, two genes, brain-derived neurotrophic factor (Bdnf) and transthyretin (Ttr) were found to be induced by PACAP38 treatment, which we had not been able to identify previously using the whole hemisphere transcriptome analysis. Using bioinformatics analysis by pathway- or specific-disease-state focused gene classifications and Ingenuity Pathway Analysis (IPA) the differentially expressed genes are functionally classified and discussed. Among these, we specifically discuss some novel and previously identified genes, such as alpha hemoglobin stabilizing protein (Ahsp), cathelicidin antimicrobial peptide (Camp), chemokines, interferon beta 1 (Ifnb1), and interleukin 6 (Il6) in context of PACAP38-mediated neuroprotection in the ischemic brain. Taken together, the DNA microarray analysis provides not only a great resource for further study, but also reinforces the importance of region-specific analyses in genome-wide identification of target molecular factors that might play a role in the neuroprotective function of PACAP38.

Novel role for TRPC4 in regulation of macroautophagy by a small molecule in vascular endothelial cells

Macroautophagy (autophagy) is an important factor affecting the function of vascular endothelial cells (VECs) and must be tightly regulated in these cells. However, the precise mechanisms underlying this process, particularly in the presence of serum, remain obscure. In this study, we identified trans-3,5,4′-trimethoxystilbene (TMS) as a potent small molecule inducer of autophagy in human umbilical vascular endothelial cells (HUVECs) in the presence of serum. Using high-throughput DNA microarray and siRNA transfection technologies, we demonstrated that TMS induced autophagy by up-regulating the expression of the transient receptor potential canonical channel 4 (TRPC4), an important cation channel in HUVECs. In addition, the overexpression of TRPC4 by plasmid transfection also induced autophagy. Mechanistic studies revealed that the up-regulation of TRPC4 increased the intracellular Ca2+ concentration, which, in turn, activated the Ca2+/CaMKKβ/AMPK pathway, leading to mTOR inhibition and autophagy. Our study identifies a novel role for TRPC4 in the regulation of autophagy in VECs. TMS is a useful new tool for investigating the molecular mechanism of autophagy in VECs and may serve as a potential lead compound for developing a class of autophagy inducers to treat autophagy-related diseases.

Coordinated Regulation of Dendrite Arborization by Epigenetic Factors CDYL and EZH2

Dendritic arborization is one of the key determinants of precise circuits for information processing in neurons. Unraveling the molecular mechanisms underlying dendrite morphogenesis is critical to understanding the establishment of neuronal connections. Here, using gain- and loss-of-function approaches, we defined the chromodomain protein and transcription corepressor chromodomain Y-like (CDYL) protein as a negative regulator of dendrite morphogenesis in rat/mouse hippocampal neurons both in vitro and in vivo. Overexpressing CDYL decreased, whereas knocking it down increased, the dendritic complexity of the primary cultured rat neurons. High-throughput DNA microarray screening identified a number of CDYL downstream target genes, including the brain-derived neurotrophic factor (BDNF). Knock-down of CDYL in neuronal cells led to increased expression of BDNF, which is primarily responsible for CDYL's effects on dendrite patterns. Mechanistically, CDYL interacts with EZH2, the catalytic subunit of Polycomb Repressive Complex 2 (PRC2), directly and recruits the H3K27 methyltransferase activity to the promoter region of the BDNF gene. In doing so, CDYL and EZH2 coordinately restrict dendrite morphogenesis in an interdependent manner. Finally, we found that neural activity increased dendritic complexity through degradation of CDYL protein to unleash its inhibition on BDNF. These results link, for the first time, the epigenetic regulators CDYL and EZH2 to dendrite morphogenesis and might shed new light on our understanding of the regulation of the neurodevelopment.

Inhibition of DEPDC1A, a Bad Prognostic Marker in Multiple Myeloma, Delays Growth and Induces Mature Plasma Cell Markers in Malignant Plasma Cells

High throughput DNA microarray has made it possible to outline genes whose expression in malignant plasma cells is associated with short overall survival of patients with Multiple Myeloma (MM). A further step is to elucidate the mechanisms encoded by these genes yielding to drug resistance and/or patients’ short survival. We focus here on the biological role of the DEP (for Disheveled, EGL-10, Pleckstrin) domain contained protein 1A (DEPDC1A), a poorly known protein encoded by DEPDC1A gene, whose high expression in malignant plasma cells is associated with short survival of patients. Using conditional lentiviral vector delivery of DEPDC1A shRNA, we report that DEPDC1A knockdown delayed the growth of human myeloma cell lines (HMCLs), with a block in G2 phase of the cell cycle, p53 phosphorylation and stabilization, and p21Cip1 accumulation. DEPDC1A knockdown also resulted in increased expression of mature plasma cell markers, including CXCR4, IL6-R and CD38. Thus DEPDC1A could contribute to the plasmablast features of MMCs found in some patients with adverse prognosis, blocking the differentiation of malignant plasma cells and promoting cell cycle.

Comprehensive transcription analysis of human pathogenic fungus Penicillium marneffei in mycelial and yeast cells

Penicillium marneffei is a dimorphic fungus that responds to changes in temperature. We performed a comparative analysis of gene expression in mycelial- and yeast-phase P. marneffei cells using high-throughput DNA microarrays. A total of 1,884 differentially expressed genes with annotations in the gene ontology (GO) database were identified between P. marneffei mycelial and yeast cells. These differentially expressed genes mainly belong to 18 categories in the organism's ontology, including reproduction, immunity, metabolism, signaling, etc. Bioinformatics suggests that these differentially expressed genes may help explain the resistance to adverse environments and the virulence of P. marneffei. Nine genes from the results of the DNA microarray experiment were selected for further analysis with real-time quantitative PCR to validate the differential expression. Our data provide a global description of the transcriptional response accompanying adaptation to high temperature in yeast.

Development of a high-throughput DNA microarray for drug-resistant gene detection and its preliminary application

Most bacteria are resistant to a wide variety of antibiotics and other drugs, which decrease the effectiveness of clinical drug therapies. The present study developed a high-throughput DNA microarray for drug-resistant gene detection. A total of 115 specific oligonuclieotide probes with lengths of 42 nt to 45 nt and comparable Tm values were selected from 17 categories of drug-resistant genes in the National Center for Biotechnology Information database and were chemically synthesized. The entire bacterial DNA was extracted, randomly amplified, and labeled using Cy3-dCTP. The hybridization conditions of the microarray test were optimized to improve sensitivity and specificity. The drug-resistant genes were detected and genotyped using microarray analysis after hydration at 42°C for 4h with 2× hybridization solution. The microarray test sensitivity was 20ng/μL DNA. The performance of the microarray was validated using reference strains and clinical isolates. The results were consistent with direct DNA sequence analysis and drug susceptibility tests. The developed DNA microarray could be used to detect and screen drug-resistant bacteria rapidly and simultaneously. Thus, the present study could be helpful in effectively using antibiotics and controlling infectious diseases.

Advanced Immobilization and Amplification for High Performance Protein Chips

With the success of high-throughput DNA microarrays, protein biochips have been intensively investigated and broadly used in bioscience research, clinic diagnosis, drug discovery, and other applications. However, there is great need to significantly improve the sensitivity of protein chips, especially in early diagnosis. A major challenge of improving sensitivity is that protein detection does not have an effective amplification method, such as PCR for DNA microarrays. Construction of unique biofilms for efficient immobilization of protein probes and innovation of new amplification schemes could play a critical role in performance improvement of protein biochips. With dramatic developments in microfabrication, nanotechnologies, and biotechnologies, enormous progress has been made, particularly in improving biosensing sensitivity. This article reviews new advances in protein biochip technologies with emphasis on novel approaches for efficient probe immobilization and nanomaterials-assisted signal amplification for high performance protein chips. Prominent progress in integration of protein microarrays with microfluidic platforms is briefly discussed. The major challenges and perspectives on the future of protein biochips are also addressed.

Unraveling the ischemic brain transcriptome in a permanent middle cerebral artery occlusion mouse model by DNA microarray analysis

SUMMARYBrain ischemia, also termed cerebral ischemia, is a condition in which there is insufficient blood flow to the brain to meet metabolic demand, leading to tissue death (cerebral infarction) due to poor oxygen supply (cerebral hypoxia). Our group is interested in the protective effects of neuropeptides for alleviating brain ischemia, as well as the underlying mechanisms of their action. The present study was initiated to investigate molecular responses at the level of gene expression in ischemic brain tissue. To achieve this, we used a mouse permanent middle cerebral artery occlusion (PMCAO) model in combination with high-throughput DNA microarray analysis on an Agilent microarray platform. Briefly, the right (ipsilateral) and left (contralateral) hemispheres of PMCAO model mice were dissected at two time points, 6 and 24 hours post-ischemia. Total RNA from the ischemic (ipsilateral) hemisphere was subjected to DNA microarray analysis on a mouse whole genome 4x44K DNA chip using a dye-swap approach. Functional categorization using the gene ontology (GO, MGD/AMIGO) of numerous changed genes revealed expression pattern changes in the major categories of cellular process, biological regulation, regulation of biological process, metabolic process and response to stimulus. Reverse-transcriptase PCR (RT-PCR) analysis on randomly selected highly up- or downregulated genes validated, in general, the microarray data. Using two time points for this analysis, major and minor trends in gene expression and/or functions were observed in relation to early- and late-response genes and differentially regulated genes that were further classified into specific pathways or disease states. We also examined the expression of these genes in the contralateral hemisphere, which suggested the presence of bilateral effects and/or differential regulation. This study provides the first ischemia-related transcriptome analysis of the mouse brain, laying a strong foundation for studies designed to elucidate the mechanisms regulating ischemia and to explore the neuroprotective effects of agents such as target neuropeptides.

Seeking gene candidates responsible for developmental origins of health and disease

Human epidemiological evidence has led scientists to theorize that undernutrition during gestation is an important early origin of adult diseases. Animal models have successfully demonstrated that maternal diet could contribute to some adult diseases. Undernutrition is perceived harmful in pregnant women, whereas calorie restriction is a strategy proven to extend healthy and maximum lifespan in adult. This diagrammatically opposite effect of nutritional condition might provide us with hints to search for genes underlying health conditions. Here, we have initiated a study examining the effect of undernutrition on maternal and fetal livers, utilizing high-throughput DNA microarray analysis for screening genome-wide changes in their transcriptomes. Briefly, pregnant mice were exposed to food deprivation (FD) on gestation day (GD) 17, and cesarean section was performed on GD18. Control mice were supplied with chow ad libitum until sacrifice. Total RNA extracted from mother and fetal livers for each control and treatment (FD) was analyzed with an Agilent mouse whole genome DNA chip. A total of 3058 and 3126 up- (>1.5-fold) and down- (<0.75-fold) regulated genes, and 1475 and 1225 up- (>1.5-fold) and down- (<0.75-fold) regulated genes showed differential expression at the mRNA level, in the maternal and fetal livers, respectively. Interestingly, 103 genes up-regulated in the mother were down-regulated in the fetus, whereas 108 down-regulated maternal genes were up-regulated in the fetus; these 211 genes are potential candidates related to longevity or health. The role of some of these genes, in context of the proposed mechanisms for developmental origins of health and disease is discussed.

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

BackgroundThe wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets.MethodsUnsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA) and nonnegative matrix factorization (NMF) are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles.ResultsIn our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and the biological analysis of the identified significant genes and their related pathways demonstrated that these genes play a prominent role in AD and relate the activation patterns to AD phenotypes. It is validated that the combination of these two methods is efficient.ConclusionsUnsupervised matrix factorization methods provide efficient tools to analyze high-throughput microarray dataset. According to the facts that different unsupervised approaches explore correlations in the high-dimensional data space and identify relevant subspace base on different hypotheses, integrating these methods to explore the underlying biological information from microarray dataset is an efficient approach. By combining the significant genes identified by both ICA and NMF, the biological analysis shows great efficient for elucidating the molecular taxonomy of Alzheimer’s disease and enable better experimental design to further identify potential pathways and therapeutic targets of AD.