Determining significant fold differences in gene expression analysis

Intraperitoneal administration of human "Neo-Islets", 3-D organoids of mesenchymal stromal and pancreatic islet cells, normalizes blood glucose levels in streptozotocin-diabetic NOD/SCID mice: Significance for clinical trials

Globally, individuals with autoimmune Type 1 diabetes mellitus (T1DM) continue to depend for survival on insulin injections. While pancreas and intrahepatic pancreatic islet transplants can produce insulin-independence and ameliorate serious complications, both therapies depend on potentially toxic anti-rejection drugs. Furthermore, the scarcity of pancreas donors and islet transplant failures limit the general availability of such interventions. Recently, fetal and induced Pluripotent Stem Cells have been successfully differentiated to generate insulin producing β-like cells that generate euglycemia in diabetic mice. However, their clinical use still depends on anti-rejection drugs or immune-isolating encapsulation systems. We reported recently that allogeneic “Neo-Islets” (NI), 3-D organoids of Mesenchymal Stromal and Islet Cells are immune protected and permanently correct autoimmune diabetes in NOD mice by omental engraftment and endocrine cell redifferentiation. This new “endocrine pancreas” delivers islet hormones physiologically into the hepatic portal vein. Furthermore, treatment of insulin-dependent dogs with allogeneic canine NIs (ongoing FDA-approved Pilot Study) consistently improved glycemic control without the need for antirejection drugs. As there remains a critical need for curative therapies of T1DM, we engineered human NIs and tested their ability, after i.p. administration, to reestablish euglycemia in streptozotocin (STZ)-diabetic NOD/SCID mice. This diabetes model reproduces, in part, the clinical situation in which recipients of allogeneic biotherapies must take potent anti-rejection drugs that similarly create a life-long immune-compromised status. The present study demonstrates that human NI therapy (2x10e5/kg bw NIs/mouse) of STZ-diabetic NOD/SCID mice (n = 6), compared to controls (n = 6) significantly improved glycemic control, and most importantly, that a second dose given to the initial group normalized blood glucose levels long-term. Conclusion: Despite the limitations of the utilized diabetic NOD/SCID mouse model, the obtained data show that human NIs are curative, an observation that has high translational relevance and significantly supports the planned conduct of clinical trials with human NIs.

The complement cascade at the Utah microelectrode-tissue interface

Devices implanted within the central nervous system (CNS) are subjected to tissue reactivity due to the lack of biocompatibility between implanted material and the cells' microenvironment. Studies have attributed blood-brain barrier disruption, inflammation, and oxidative stress as main contributing factors that lead to electrode recording failure. The complement cascade is a part of the innate immunity that focuses on recognizing and targeting foreign objects; however, its role in the context of neural implants is substantially unknown. In this study, we implanted a non-functional 4x4 Utah microelectrode array (UEA) into the somatosensory cortex and studied the complement cascade via combined gene and immunohistochemistry quantification at acute (48-h), sub-acute (1-week), and early chronic (4-weeks) time points. The results of this study demonstrate the activation and continuation of the complement cascade at the electrode-tissue interface, illustrating the therapeutic potential of modulating the foreign body response via the complement cascade.

A gene expression signature of TREM2hi macrophages and γδ T cells predicts immunotherapy response

Identifying factors underlying resistance to immune checkpoint therapy (ICT) is still challenging. Most cancer patients do not respond to ICT and the availability of the predictive biomarkers is limited. Here, we re-analyze a publicly available single-cell RNA sequencing (scRNA-seq) dataset of melanoma samples of patients subjected to ICT and identify a subset of macrophages overexpressing TREM2 and a subset of gammadelta T cells that are both overrepresented in the non-responding tumors. In addition, the percentage of a B cell subset is significantly lower in the non-responders. The presence of these immune cell subtypes is corroborated in other publicly available scRNA-seq datasets. The analyses of bulk RNA-seq datasets of the melanoma samples identify and validate a signature - ImmuneCells.Sig - enriched with the genes characteristic of the above immune cell subsets to predict response to immunotherapy. ImmuneCells.Sig could represent a valuable tool for clinical decision making in patients receiving immunotherapy.

Therapeutic hypothermia reduces cortical inflammation associated with utah array implants

OBJECTIVE

Neuroprosthetics hold tremendous promise to restore function through brain-computer interfaced devices. However, clinical applications of implantable microelectrodes remain limited given the challenges of maintaining neuronal signals for extended periods of time and with multiple biological mechanisms negatively affecting electrode performance. Acute and chronic inflammation, oxidative stress, and blood brain barrier disruption contribute to inconsistent electrode performance. We hypothesized that therapeutic hypothermia (TH) applied at the microelectrode insertion site will positively modulate both inflammatory and apoptotic pathways, promoting neuroprotection and improved performance in the long-term.

APPROACH

A custom device and thermoelectric system were designed to deliver controlled TH locally to the cortical implant site at the time of microelectrode array insertion and immediately following surgery. The TH paradigm was derived from in vivo cortical temperature measurements and finite element modeling of temperature distribution profiles in the cortex. Male Sprague-Dawley rats were implanted with non-functional Utah microelectrodes arrays (UMEA) consisting of 4 × 4 grid of 1.5 mm long parylene-coated silicon shanks. In one group, TH was applied to the implant site for two hours following the UMEA implantation, while the other group was implanted under normothermic conditions without treatment. At 48 h, 72 h, 7 d and 14 d post-implantation, mRNA expression levels for genes associated with inflammation and apoptosis were compared between normothermic and hypothermia-treated groups.

MAIN RESULTS

The custom system delivered controlled TH to the cortical implant site and the numerical models confirmed that the temperature decrease was confined locally. Furthermore, a one-time application of TH post UMEA insertion significantly reduced the acute inflammatory response with a reduction in the expression of inflammatory regulating cytokines and chemokines.

SIGNIFICANCE

This work provides evidence that acutely applied hypothermia is effective in significantly reducing acute inflammation post intracortical electrode implantation.

Interim report on the effective intraperitoneal therapy of insulin-dependent diabetes mellitus in pet dogs using "Neo-Islets," aggregates of adipose stem and pancreatic islet cells (INAD 012-776)

We previously reported that allogeneic, intraperitoneally administered “Neo-Islets,” composed of cultured pancreatic islet cells co-aggregated with high numbers of immunoprotective and cytoprotective Adipose-derived Stem Cells, reestablished, through omental engraftment, redifferentiation and splenic and omental up-regulation of regulatory T-cells, normoglycemia in autoimmune Type-1 Diabetic Non-Obese Diabetic (NOD) mice without the use of immunosuppressive agents or encapsulation devices. Based on these observations, we are currently testing this Neo-Islet technology in an FDA guided pilot study (INAD 012–776) in insulin-dependent, spontaneously diabetic pet dogs by ultrasound-guided, intraperitoneal administration of 2x10e5 Neo-Islets/kilogram body weight to metabolically controlled (blood glucose, triglycerides, thyroid and adrenal functions) and sedated animals. We report here interim observations on the first 4 canine Neo-Islet-treated, insulin-dependent pet dogs that are now in the early to intermediate-term follow-up phase of the planned 3 year study (> 6 months post treatment). Current results from this translational study indicate that in dogs, Neo-Islets appear to engraft, redifferentiate and physiologically produce insulin, and are rejected by neither auto- nor allo-immune responses, as evidenced by (a) an absent IgG response to the allogeneic cells contained in the administered Neo-Islets, and (b) progressively improved glycemic control that achieves up to a 50% reduction in daily insulin needs paralleled by a statistically significant decrease in serum glucose concentrations. This is accomplished without the use of anti-rejection drugs or encapsulation devices. No adverse or serious adverse events related to the Neo-Islet administration have been observed to date. We conclude that this minimally invasive therapy has significant translational relevance to veterinary and clinical Type 1 diabetes mellitus by achieving complete and at this point partial glycemic control in two species, i.e., diabetic mice and dogs, respectively.

Hypothalamic transcriptome analysis reveals the neuroendocrine mechanisms in controlling broodiness of Muscovy duck (Cairina moschata)

Broodiness, one of the maternal behaviors and instincts for natural breeding in birds, is an interesting topic in reproductive biology. Broodiness in poultry is characterized by persistent nesting, usually associated with cessation of egg laying. The study of avian broodiness is essential for bird conservation breeding and commercial poultry industry. In this study, we examined the hypothalamus transcriptome of Muscovy duck in three reproductive stages, including egg-laying anaphase (LA), brooding prophase (BP) and brooding metaphase (BM). Differences in gene expression during the transition from egg-laying to broodiness were examined, and 155, 379, 292 differently expressed genes (DEGs) were obtained by pairwise comparisons of LA-vs-BP, LA-vs-BM and BP-vs-BM, respectively (fold change≥1.5, P < 0.05). Gene Ontology Term (GO) enrichment analysis suggested a possible role of oxidative stress in the hypothalamus might invoke reproductive costs that potentially change genes expression. KEGG analysis revealed glutamatergic synapse, dopaminergic synapse, serotonergic synapse and GABAergic synapse pathway were significantly enriched, and regulator genes were identified. Eight gene expression patterns were illustrated by trend analysis and further clustered into three clusters. Additional six hub genes were identified through combining trend analysis and protein-protein interaction (PPI) analysis. Our results suggested that the cyclical mechanisms of reproductive function conversion include effects of oxidative stress, biosynthesis of neurotransmitters or their receptors, and interactions between glucocorticoids and thyroid hormones and regulatory genes. These candidate genes and biological pathways may be used as targets for artificial manipulation and marker-assisted breeding in the reproductive behavior.

Neuroinflammation, oxidative stress, and blood-brain barrier (BBB) disruption in acute Utah electrode array implants and the effect of deferoxamine as an iron chelator on acute foreign body response

The use of intracortical microelectrode arrays has gained significant attention in being able to help restore function in paralysis patients and study the brain in various neurological disorders. Electrode implantation in the cortex causes vasculature or blood-brain barrier (BBB) disruption and thus elicits a foreign body response (FBR) that results in chronic inflammation and may lead to poor electrode performance. In this study, a comprehensive insight into the acute molecular mechanisms occurring at the Utah electrode array-tissue interface is provided to understand the oxidative stress, neuroinflammation, and neurovascular unit (astrocytes, pericytes, and endothelial cells) disruption that occurs following microelectrode implantation. Quantitative real time polymerase chain reaction (qRT-PCR) was used to quantify the gene expression at acute time-points of 48-hr, 72-hr, and 7-days for factors mediating oxidative stress, inflammation, and BBB disruption in rats implanted with a non-functional 4 × 4 Utah array in the somatosensory cortex. During vascular disruption, free iron released into the brain parenchyma can exacerbate the FBR, leading to oxidative stress and thus further contributing to BBB degradation. To reduce the free iron released into the brain tissue, the effects of an iron chelator, deferoxamine mesylate (DFX), was also evaluated.

Blood brain barrier (BBB)-disruption in intracortical silicon microelectrode implants

Chronically implanted microelectrodes in the neural tissue elicit inflammatory responses that are time varying and have been shown to depend on multiple factors. Among these factors, blood brain barrier (BBB)-disruption has been hypothesized as one of the dominant factors resulting in electrode failure. A series of events that includes BBB and cell-membrane disruption occurs during electrode implantation that triggers multiple biochemical cascades responsible for microglial and astroglial activation, hemorrhage, edema, and release of pro-inflammatory neurotoxic cytokines that causes neuronal degeneration and dysfunction. Typically, microwire arrays and silicon probes are inserted slowly into the neural tissue whereas the silicon Utah MEAs (UMEA) are inserted at a high speed using a pneumatic inserter. In this work, we report the sequelae of electrode-implant induced cortical injury at various acute time points in UMEAs implanted in the brain tissue by quantifying the expression profile for key genes mediating the inflammatory response and tight junction (TJ) and adherens junction (AJ) proteins that form the BBB and are critical to the functioning of the BBB. Our results indicated upregulation of most pro-inflammatory genes relative to naïve controls for all time points. Expression levels for the genes that form the TJ and AJ were downregulated suggestive of BBB-dysfunction. Moreover, there was no significant difference between stab and implant groups suggesting the effects of UMEA insertion-related trauma in the brain tissue. Our results provide an insight into the physiological events related to neuroinflammation and BBB-disruption occurring at acute time-points following insertion of UMEAs.

Peripheral Blood Gene Expression Changes Associated With Primary Graft Dysfunction After Lung Transplantation

Recipient responses to primary graft dysfunction (PGD) after lung transplantation may have important implications to the fate of the allograft. We therefore evaluated longitudinal differences in peripheral blood gene expression in subjects with PGD. RNA expression was measured throughout the first transplant year in 106 subjects enrolled in the Clinical Trials in Organ Transplantation-03 study using a panel of 100 hypothesis-driven genes. PGD was defined as grade 3 in the first 72 posttransplant hours. Eighteen genes were differentially expressed over the first year based on PGD development, with significant representation from innate and adaptive immunity genes, with most differences identified very early after transplant. Sixteen genes were overexpressed in the blood of patients with PGD compared to those without PGD within 7 days of allograft reperfusion, with most transcripts encoding innate immune/inflammasome-related proteins, including genes previously associated with PGD. Thirteen genes were underexpressed in patients with PGD compared to those without PGD within 7 days of transplant, highlighted by T cell and adaptive immune regulation genes. Differences in gene expression present within 2 h of reperfusion and persist for days after transplant. Future investigation will focus on the long-term implications of these gene expression differences on the outcome of the allograft.

Cross-disorder comparative analysis of comorbid conditions reveals novel autism candidate genes

BACKGROUND

Numerous studies have highlighted the elevated degree of comorbidity associated with autism spectrum disorder (ASD). These comorbid conditions may add further impairments to individuals with autism and are substantially more prevalent compared to neurotypical populations. These high rates of comorbidity are not surprising taking into account the overlap of symptoms that ASD shares with other pathologies. From a research perspective, this suggests common molecular mechanisms involved in these conditions. Therefore, identifying crucial genes in the overlap between ASD and these comorbid disorders may help unravel the common biological processes involved and, ultimately, shed some light in the understanding of autism etiology.

RESULTS

In this work, we used a two-fold systems biology approach specially focused on biological processes and gene networks to conduct a comparative analysis of autism with 31 frequently comorbid disorders in order to define a multi-disorder subcomponent of ASD and predict new genes of potential relevance to ASD etiology. We validated our predictions by determining the significance of our candidate genes in high throughput transcriptome expression profiling studies. Using prior knowledge of disease-related biological processes and the interaction networks of the disorders related to autism, we identified a set of 19 genes not previously linked to ASD that were significantly differentially regulated in individuals with autism. In addition, these genes were of potential etiologic relevance to autism, given their enriched roles in neurological processes crucial for optimal brain development and function, learning and memory, cognition and social behavior.

CONCLUSIONS

Taken together, our approach represents a novel perspective of autism from the point of view of related comorbid disorders and proposes a model by which prior knowledge of interaction networks may enlighten and focus the genome-wide search for autism candidate genes to better define the genetic heterogeneity of ASD.

Integrated analysis identifies interaction patterns between small molecules and pathways

Previous studies have indicated that the downstream proteins in a key pathway can be potential drug targets and that the pathway can play an important role in the action of drugs. So pathways could be considered as targets of small molecules. A link map between small molecules and pathways was constructed using gene expression profile, pathways, and gene expression of cancer cell line intervened by small molecules and then we analysed the topological characteristics of the link map. Three link patterns were identified based on different drug discovery implications for breast, liver, and lung cancer. Furthermore, molecules that significantly targeted the same pathways tended to treat the same diseases. These results can provide a valuable reference for identifying drug candidates and targets in molecularly targeted therapy.

Differential gene expression in tamoxifen-resistant breast cancer cells revealed by a new analytical model of RNA-Seq data

Resistance to tamoxifen (Tam), a widely used antagonist of the estrogen receptor (ER), is a common obstacle to successful breast cancer treatment. While adjuvant therapy with Tam has been shown to significantly decrease the rate of disease recurrence and mortality, recurrent disease occurs in one third of patients treated with Tam within 5 years of therapy. A better understanding of gene expression alterations associated with Tam resistance will facilitate circumventing this problem. Using a next generation sequencing approach and a new bioinformatics model, we compared the transcriptomes of Tam-sensitive and Tam-resistant breast cancer cells for identification of genes involved in the development of Tam resistance. We identified differential expression of 1215 mRNA and 513 small RNA transcripts clustered into ERα functions, cell cycle regulation, transcription/translation, and mitochondrial dysfunction. The extent of alterations found at multiple levels of gene regulation highlights the ability of the Tam-resistant cells to modulate global gene expression. Alterations of small nucleolar RNA, oxidative phosphorylation, and proliferation processes in Tam-resistant cells present areas for diagnostic and therapeutic tool development for combating resistance to this anti-estrogen agent.

Variability analysis of human plasma and cerebral spinal fluid reveals statistical significance of changes in mass spectrometry-based metabolomics data

Analytical and biological variability are issues of central importance to human metabolomics studies. Here both types of variation are examined in human plasma and cerebrospinal fluid (CSF) using a global liquid chromatography/mass spectrometry (LC/MS) metabolomics strategy. The platform shows small analytical variation with a median coefficient of variation (CV) of 15-16% for both plasma and CSF sample matrixes when the integrated area of each peak in the mass spectra is considered. Analysis of biological variation shows that human CSF has a median CV of 35% and plasma has a median CV of 46%. To understand the difference in CV between the biofluids, we compared plasma and CSF independently obtained from different healthy humans. Additionally, we analyzed another group of patients from whom we compared matched CSF and plasma (plasma and CSF obtained from the same human subject). A similar number of features was observed in both biofluids, although the majority of features appeared with greater intensity in plasma. More than a dozen metabolites shared between the human CSF and plasma metabolomes were identified based on accurate mass measurements, retention times, and MS/MS spectra. The fold change in these metabolites was consistent with the median biological CV determined for all peaks. The measured median biological CV together with analysis of intragroup variation of healthy individuals suggests that fold changes above 2 in metabolomics studies investigating plasma or CSF are statistically relevant with respect to the inherent variability of a healthy control group. These data demonstrate the reproducibility of the global metabolomics platform using LC/MS and reveal the robustness of the approach for biomarker discovery.

Missing value imputation for microarray gene expression data using histone acetylation information

Background

It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile analysis in bioinformatics. Although several methods have been suggested, their performances are not satisfactory for datasets with high missing percentages.

Results

The paper explores the feasibility of doing missing value imputation with the help of gene regulatory mechanism. An imputation framework called histone acetylation information aided imputation method (HAIimpute method) is presented. It incorporates the histone acetylation information into the conventional KNN(k-nearest neighbor) and LLS(local least square) imputation algorithms for final prediction of the missing values. The experimental results indicated that the use of acetylation information can provide significant improvements in microarray imputation accuracy. The HAIimpute methods consistently improve the widely used methods such as KNN and LLS in terms of normalized root mean squared error (NRMSE). Meanwhile, the genes imputed by HAIimpute methods are more correlated with the original complete genes in terms of Pearson correlation coefficients. Furthermore, the proposed methods also outperform GOimpute, which is one of the existing related methods that use the functional similarity as the external information.

Conclusion

We demonstrated that the using of histone acetylation information could greatly improve the performance of the imputation especially at high missing percentages. This idea can be generalized to various imputation methods to facilitate the performance. Moreover, with more knowledge accumulated on gene regulatory mechanism in addition to histone acetylation, the performance of our approach can be further improved and verified.

Apoptotic killing of HIV-1-infected macrophages is subverted by the viral envelope glycoprotein

Viruses have evolved strategies to protect infected cells from apoptotic clearance. We present evidence that HIV-1 possesses a mechanism to protect infected macrophages from the apoptotic effects of the death ligand TRAIL (tumor necrosis factor–related apoptosis-inducing ligand). In HIV-1–infected macrophages, the viral envelope protein induced macrophage colony-stimulating factor (M-CSF). This pro-survival cytokine downregulated the TRAIL receptor TRAIL-R1/DR4 and upregulated the anti-apoptotic genes Bfl-1 and Mcl-1. Inhibition of M-CSF activity or silencing of Bfl-1 and Mcl-1 rendered infected macrophages highly susceptible to TRAIL. The anti-cancer agent Imatinib inhibited M-CSF receptor activation and restored the apoptotic sensitivity of HIV-1–infected macrophages, suggesting a novel strategy to curtail viral persistence in the macrophage reservoir.

Much of our understanding regarding mechanisms of HIV-1 persistence has been derived from studies with lymphocytes. However, mechanisms governing persistent infection of macrophages are less well understood. We investigated whether HIV-1 modulates macrophage function in a way that promotes their persist infection. We focused on a cytokine called macrophage colony-stimulating factor (M-CSF), because this pro-survival factor is induced upon infection by HIV-1. We found that the viral envelope gene was necessary for M-CSF induction of macrophages. M-CSF upregulated anti-apoptotic genes in macrophages and restricted the expression of the death receptor (tumor necrosis factor–related apoptosis-inducing ligand [TRAIL]-R1). As a consequence, HIV-1–infected macrophages were resistant to the apoptotic effects of TRAIL. If M-CSF was blocked by antibody or if the anti-apoptotic genes were silenced by RNA interference, the apoptotic sensitivity of HIV-1–infected macrophages was restored. Also, the anti-cancer drug Imatinib, which impairs activation of the M-CSF receptor, promoted the death of HIV-1–infected macrophages but not of uninfected macrophages. We believe that HIV-1 regulates M-CSF to extend macrophage survival and promote viral persistence in the host. Agents that interfere with M-CSF signaling, such as Imatinib, warrant further examination for activity against macrophage reservoirs in vivo.

A non-parametric approach to population structure inference using multilocus genotypes

Inference of population structure from genetic markers is helpful in diverse situations, such as association and evolutionary studies. In this paper, we describe a two-stage strategy in inferring population structure using multilocus genotype data. In the first stage, we use dimension reduction methods such as singular value decomposition to reduce the dimension of the data, and in the second stage, we use clustering methods on the reduced data to identify population structure. The strategy has the ability to identify population structure and assign each individual to its corresponding subpopulation. The strategy does not depend on any population genetics assumptions (such as Hardy-Weinberg equilibrium and linkage equilibrium between loci within populations) and can be used with any genotype data. When applied to real and simulated data, the strategy is found to have similar or better performance compared with STRUCTURE, the most popular method in current use. Therefore, the proposed strategy provides a useful alternative to analyse population data.

Analysis of gene expression in pathophysiological states: balancing false discovery and false negative rates

Nucleotide-microarray technology, which allows the simultaneous measurement of the expression of tens of thousands of genes, has become an important tool in the study of disease. In disorders such as malignancy, gene expression often undergoes broad changes of sizable magnitude, whereas in many common multifactorial diseases, such as diabetes, obesity, and atherosclerosis, the changes in gene expression are modest. In the latter circumstance, it is therefore challenging to distinguish the truly changing from non-changing genes, especially because statistical significance must be considered in the context of multiple hypothesis testing. Here, we present a balanced probability analysis (BPA), which provides the biologist with an approach to interpret results in the context of the total number of genes truly differentially expressed and false discovery and false negative rates for the list of genes reaching any significance threshold. In situations where the changes are of modest magnitude, sole consideration of the false discovery rate can result in poor power to detect genes truly differentially expressed. Concomitant analysis of the rate of truly differentially expressed genes not identified, i.e., the false negative rate, allows balancing of the two error rates and a more thorough insight into the data. To this end, we have developed a unique, model-based procedure for the estimation of false negative rates, which allows application of BPA to real data in which changes are modest.

The influence of muscle type and dystrophin deficiency on murine expression profiles

The phenotypic differences among Duchenne muscular dystrophy patients, mdx mice, and mdx(5cv) mice suggest that despite the common etiology of dystrophin deficiency, secondary mechanisms have a substantial influence on phenotypic severity. The differential response of various skeletal muscles to dystrophin deficiency supports this hypothesis. To explore these differences, gene expression profiles were generated from duplicate RNA targets extracted from six different skeletal muscles (diaphragm, soleus, gastrocnemius, quadriceps, tibialis anterior, and extensor digitorum longus) from wild-type, mdx, and mdx(5cv) mice, resulting in 36 data sets for 18 muscle samples. The data sets were compared in three different ways: (1) among wild-type samples only, (2) among all 36 data sets, and (3) between strains for each muscle type. The molecular profiles of soleus and diaphragm separate significantly from the other four muscle types and from each other. Fiber-type proportions can explain some of these differences. These variations in wild-type gene expression profiles may also reflect biomechanical differences known to exist among skeletal muscles. Further exploration of the genes that most distinguish these muscles may help explain the origins of the biomechanical differences and the reasons why some muscles are more resistant than others to dystrophin deficiency.

A method for cross-species gene expression analysis with high-density oligonucleotide arrays

DNA microarrays have been widely used in gene expression analysis of biological processes. Due to a lack of sequence information, the applications have been largely restricted to humans and a few model organisms. Presented within this study are results of the cross-species hybridization with Affymetrix human high-density oligonucleotide arrays or GeneChip using distantly related mammalian species; cattle, pig and dog. Based on the unique feature of the Affymetrix GeneChip where every gene is represented by multiple probes, we hypothesized that sequence conservation within mammals is high enough to generate sufficient signals from some of the probes for expression analysis. We demonstrated that while overall hybridization signals are low for cross-species hybridization, a few probes of most genes still generated signals equivalent to the same-species hybridization. By masking the poorly hybridized probes electronically, the remaining probes provided reliable data for gene expression analysis. We developed an algorithm to select the reliable probes for analysis utilizing the match/mismatch feature of GeneChip. When comparing gene expression between two tissues using the selected probes, we found a linear correlation between the cross-species and same-species hybridization. In addition, we validated cross-species hybridization results by quantitative PCR using randomly selected genes. The method shown herein could be applied to both plant and animal research.

Global analysis of gene expression patterns during disuse atrophy in rat skeletal muscle

Muscular inactivity leads to atrophy, weakness, and decreased fatigue resistance. In order to provide a window into the dynamic processes that underlie muscle atrophy, we performed global gene expression analysis of rat soleus muscles using Affymetrix GeneChips at 1, 4, 7 and 14 days of hindlimb unloading. Expression of 309 known genes was significantly changed by at least 2-fold (212 upregulated, 97 downregulated). K-means clustering was used to divide these genes into co-regulated clusters based on the similarity of temporal expression patterns. This allowed the development of a timeline of the atrophy process with respect to the behaviour of genes in a broad array of functional categories. Regulatory genes were often upregulated early, in either a transient or sustained manner, but they also populated clusters with later patterns of activation, suggesting different phases of molecular adaptations. Other early events were the activation of ubiquitination genes and downregulation of protein chaperones. In comparison, clusters representing slightly delayed activation patterns included genes involved in fast contraction, glycolysis, translational inhibition, oxidative stress, protein degradation, and amino acid catabolism. Downregulated genes exhibited fewer unique expression patterns and included structural and regulatory genes of the extracellular matrix and cytoskeleton, and genes that define a slow-oxidative phenotype. Other novel findings include the tight co-activation of proteasome subunit and ubiquitination genes, differential regulation of serine proteases and serine protease inhibitors, and the identification of transcriptional, signalling, growth and cell cycle genes that probably play a role in the atrophy process. The present work has uncovered temporal patterns of gene expression that highlight the molecular processes that underlie muscle atrophy and provide new avenues for study.

Gene expression comparison of biopsies from Duchenne muscular dystrophy (DMD) and normal skeletal muscle

The primary cause of Duchenne muscular dystrophy (DMD) is a mutation in the dystrophin gene leading to the absence of the corresponding RNA transcript and protein. Absence of dystrophin leads to disruption of the dystrophin-associated protein complex and substantial changes in skeletal muscle pathology. Although the histological pathology of dystrophic tissue has been well documented, the underlying molecular pathways remain poorly understood. To examine the pathogenic pathways and identify new or modifying factors involved in muscular dystrophy, expression microarrays were used to compare individual gene expression profiles of skeletal muscle biopsies from 12 DMD patients and 12 unaffected control patients. Two separate statistical analysis methods were used to interpret the resulting data: t test analysis to determine the statistical significance of differential expression and geometric fold change analysis to determine the extent of differential expression. These analyses identified 105 genes that differ significantly in expression level between unaffected and DMD muscle. Many of the differentially expressed genes reflect changes in histological pathology. For instance, immune response signals and extracellular matrix genes are overexpressed in DMD muscle, an indication of the infiltration of inflammatory cells and connective tissue. Significantly more genes are overexpressed than are underexpressed in dystrophic muscle, with dystrophin underexpressed, whereas other genes encoding muscle structure and regeneration processes are overexpressed, reflecting the regenerative nature of the disease.

Microarray optimizations: increasing spot accuracy and automated identification of true microarray signals

In this paper, fluorescent microarray images and various analysis techniques are described to improve the microarray data acquisition processes. Signal intensities produced by rarely expressed genes are initially correctly detected, but they are often lost in corrections for background, log or ratio. Our analyses indicate that a simple correlation between the mean and median signal intensities may be the best way to eliminate inaccurate microarray signals. Unlike traditional quality control methods, the low intensity signals are retained and inaccurate signals are eliminated in this mean and median correlation. With larger amounts of microarray data being generated, it becomes increasingly more difficult to analyze data on a visual basis. Our method allows for the automatic quantitative determination of accurate and reliable signals, which can then be used for normalization. We found that a mean to median correlation of 85% or higher not only retains more data than current methods, but the retained data is more accurate than traditional thresholds or common spot flagging algorithms. We have also found that by using pin microtapping and microvibrations, we can control spot quality independent from initial PCR volume.

Identification of genes expressed with temporal-spatial restriction to developing cerebellar neuron precursors by a functional genomic approach

Hedgehog pathway activation is required for proliferation of cerebellar granule cell neuron precursors during development and is etiologic in certain cerebellar tumors. To identify genes expressed specifically in granule cell neuron precursors, we used oligonucleotide microarrays to analyze regulation of 13,179 genes/expressed sequence tags in heterogeneous primary cultures of neonatal mouse cerebellum that respond to the mitogen Sonic hedgehog. In conjunction, we applied experiment-specific noise models to render a gene-by-gene robust indication of up-regulation in Sonic hedgehog-treated cultures. Twelve genes so identified were tested, and 10 (83%) showed appropriate expression in the external granular layer (EGL) of the postnatal day (PN) 7 cerebellum and down-regulation by PN 15, as verified by in situ hybridization. Whole-organ profiling of the developing cerebellum was carried out from PN 1 to 30 to generate a database of temporal gene regulation profiles (TRPs). From the database an algorithm was developed to capture the TRP typical of EGL-specific genes. The "TRP-EGL" accurately predicted expression in vivo of an additional 18 genes/expressed sequence tags with a sensitivity of 80% and a specificity of 88%. We then compared the positive predictive value of our analytical procedure with other widely used methods, as verified by the TRP-EGL in silico. These findings suggest that replicate experiments and incorporation of noise models increase analytical specificity. They further show that genome-wide methods are an effective means to identify stage-specific gene expression in the developing granule cell lineage.