Listen to Genes: Dealing with Microarray Data in the Frequency Domain

Background

We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes.

Methodology

Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail.

Conclusions

We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers.     

Informatics enhanced SNP microarray analysis of 30 miscarriage samples compared to routine cytogenetics

Purpose

The metaphase karyotype is often used as a diagnostic tool in the setting of early miscarriage; however this technique has several limitations. We evaluate a new technique for karyotyping that uses single nucleotide polymorphism microarrays (SNP). This technique was compared in a blinded, prospective fashion, to the traditional metaphase karyotype.

Methods

Patients undergoing dilation and curettage for first trimester miscarriage between February and August 2010 were enrolled. Samples of chorionic villi were equally divided and sent for microarray testing in parallel with routine cytogenetic testing.

Results

Thirty samples were analyzed, with only four discordant results. Discordant results occurred when the entire genome was duplicated or when a balanced rearrangement was present. Cytogenetic karyotyping took an average of 29 days while microarray-based karytoyping took an average of 12 days.

Conclusions

Molecular karyotyping of POC after missed abortion using SNP microarray analysis allows for the ability to detect maternal cell contamination and provides rapid results with good concordance to standard cytogenetic analysis.     

Layered Signaling Regulatory Networks Analysis of Gene Expression Involved in Malignant Tumorigenesis of Non-Resolving Ulcerative Colitis via Integration of Cross-Study Microarray Profiles

Background

Ulcerative colitis (UC) was the most frequently diagnosed inflammatory bowel disease (IBD) and closely linked to colorectal carcinogenesis. By far, the underlying mechanisms associated with the disease are still unclear. With the increasing accumulation of microarray gene expression profiles, it is profitable to gain a systematic perspective based on gene regulatory networks to better elucidate the roles of genes associated with disorders. However, a major challenge for microarray data analysis is the integration of multiple-studies generated by different groups.

Methodology/Principal Findings

In this study, firstly, we modeled a signaling regulatory network associated with colorectal cancer (CRC) initiation via integration of cross-study microarray expression data sets using Empirical Bayes (EB) algorithm. Secondly, a manually curated human cancer signaling map was established via comprehensive retrieval of the publicly available repositories. Finally, the co-differently-expressed genes were manually curated to portray the layered signaling regulatory networks.

Results

Overall, the remodeled signaling regulatory networks were separated into four major layers including extracellular, membrane, cytoplasm and nucleus, which led to the identification of five core biological processes and four signaling pathways associated with colorectal carcinogenesis. As a result, our biological interpretation highlighted the importance of EGF/EGFR signaling pathway, EPO signaling pathway, T cell signal transduction and members of the BCR signaling pathway, which were responsible for the malignant transition of CRC from the benign UC to the aggressive one.

Conclusions

The present study illustrated a standardized normalization approach for cross-study microarray expression data sets. Our model for signaling networks construction was based on the experimentally-supported interaction and microarray co-expression modeling. Pathway-based signaling regulatory networks analysis sketched a directive insight into colorectal carcinogenesis, which was of significant importance to monitor disease progression and improve therapeutic interventions.     

Clustered gene expression changes flank targeted gene loci in knockout mice

Background

Gene expression profiling using microarrays is a powerful technology widely used to study regulatory networks. Profiling of mRNA levels in mutant organisms has the potential to identify genes regulated by the mutated protein.

Methodology/Principle Findings

Using tissues from multiple lines of knockout mice we have examined genome-wide changes in gene expression. We report that a significant proportion of changed genes were found near the targeted gene.

Conclusions/Significance

The apparent clustering of these genes was explained by the presence of flanking DNA from the parental ES cell. We provide recommendations for the analysis and reporting of microarray data from knockout mice     

Biphasic Functional Regulation in Hippocampus of Rat with Chronic Cerebral Hypoperfusion Induced by Permanent Occlusion of Bilateral Common Carotid Artery

Background

Chronic cerebral hypoperfusion induced by permanent occlusion of the bilateral common carotid artery (BCCAO) in rats has been commonly used for the study of Alzheimer’s disease and vascular dementia. Despite the apparent cognitive dysfunction in rats with BCCAO, the molecular markers or pathways involved in the pathological alternation have not been clearly identified.

Methods

Temporal changes (sham, 21, 35, 45, 55 and 70 days) in gene expression in the hippocampus of rats after BCCAO were measured using time-course microarray analysis. Gene Ontology (GO) and pathway analyses were performed to identify the functional involvement of temporally regulated genes in BCCAO.

Results

Two major gene expression patterns were observed in the hippocampus of rats after BCCAO. One pattern, which was composed of 341 early up-regulated genes after the surgical procedure, was dominantly involved in immune-related biological functions (false discovery rate [FDR]<0.01). Another pattern composed of 182 temporally delayed down-regulated genes was involved in sensory perception such as olfactory and cognition functions (FDR<0.01). In addition to the two gene expression patterns, the temporal change of GO and the pathway activities using all differentially expressed genes also confirmed that an immune response was the main early change, whereas sensory functions were delayed responses. Moreover, we identified FADD and SOCS3 as possible core genes in the sensory function loss process using text-based mining and interaction network analysis.

Conclusions

The biphasic regulatory mechanism first reported here could provide molecular evidence of BCCAO-induced impaired memory in rats as well as mechanism of the development of vascular dementia.     

MicroRNA expression analysis: clinical advantage of propranolol reveals key microRNAs in myocardial infarction

Background

As playing important roles in gene regulation, microRNAs (miRNAs) are believed as indispensable involvers in the pathogenesis of myocardial infarction (MI) that causes significant morbidity and mortality. Working on a hypothesis that modulation of only some key members in the miRNA superfamily could benefit ischemic heart, we proposed a microarray based network biology approach to identify them with the recognized clinical effect of propranolol as a prompt.

Methods

A long-term MI model of rat was established in this study. The microarray technology was applied to determine the global miRNA expression change intervened by propranolol. Multiple network analyses were sequentially applied to evaluate the regulatory capacity, efficiency and emphasis of the miRNAs which dysexpression in MI were significantly reversed by propranolol.

Results

Microarray data analysis indicated that long-term propranolol administration caused 18 of the 31 dysregulated miRNAs in MI undergoing reversed expression, implying that intentional modulation of miRNA expression might show favorable effects for ischemic heart. Our network analysis identified that, among these miRNAs, the prime players in MI were miR-1, miR-29b and miR-98. Further finding revealed that miR-1 focused on regulation of myocyte growth, yet miR-29b and miR-98 stressed on fibrosis and inflammation, respectively.

Conclusion

Our study illustrates how a combination of microarray technology and functional protein network analysis can be used to identify disease-related key miRNAs.     

Arbuscular Mycorhizal Fungi Associated with the Olive Crop across the Andalusian Landscape: Factors Driving Community Differentiation

Background

In the last years, many olive plantations in southern Spain have been mediated by the use of self-rooted planting stocks, which have incorporated commercial AMF during the nursery period to facilitate their establishment. However, this was practised without enough knowledge on the effect of cropping practices and environment on the biodiversity of AMF in olive orchards in Spain.

Methodology/Principal Findings

Two culture-independent molecular methods were used to study the AMF communities associated with olive in a wide-region analysis in southern Spain including 96 olive locations. The use of T-RFLP and pyrosequencing analysis of rDNA sequences provided the first evidence of an effect of agronomic and climatic characteristics, and soil physicochemical properties on AMF community composition associated with olive. Thus, the factors most strongly associated to AMF distribution varied according to the technique but included among the studied agronomic characteristics the cultivar genotype and age of plantation and the irrigation regimen but not the orchard management system or presence of a cover crop to prevent soil erosion. Soil physicochemical properties and climatic characteristics most strongly associated to the AMF community composition included pH, textural components and nutrient contents of soil, and average evapotranspiration, rainfall and minimum temperature of the sampled locations. Pyrosequencing analysis revealed 33 AMF OTUs belonging to five families, with Archaeospora spp., Diversispora spp. and Paraglomus spp., being first records in olive. Interestingly, two of the most frequent OTUs included a diverse group of Claroideoglomeraceae and Glomeraceae sequences, not assigned to any known AMF species commonly used as inoculants in olive during nursery propagation.

Conclusions/Significance

Our data suggests that AMF can exert higher host specificity in olive than previously thought, which may have important implications for redirecting the olive nursery process in the future as well as to take into consideration the specific soils and environments where the mycorrhized olive trees will be established.     

Dietary monounsaturated Fatty acids intake and risk of skin photoaging

Background

Intake of monounsaturated fatty acids has been reported to reduce oxidative stress, insulin resistance and related inflammatory processes and may thus protect from skin photoaging. The objective of this study was to investigate the association between the risk of photoaging, monounsaturated fatty acids intake and the sources of monounsaturated fatty acids.

Methodology/Principal Findings

A cross sectional study was conducted within the framework of the SUVIMAX cohort. The survey included 1264 women and 1655 men aged between 45 and 60 years old. Dietary monounsaturated fatty acids intakes were estimated by dietary source through at least ten 24-h diet records completed during the first 2.5 years of the follow-up period. Severity of facial skin photoaging was graded by trained investigators at baseline during a clinical examination using a 6-grade scale illustrated by photographs. A lower risk of severe photoaging was associated with higher intakes of monounsaturated fatty acids from olive oil in both sexes. Strikingly, no association was found with intake of monounsaturated fatty acids from animal sources whether from dairy products, meat or processed meat.

Conclusion/Significance

These findings support the beneficial effect of dietary olive oil or healthy diet habits associated with olive oil consumption on the severity of facial photoaging.     

Centennial olive trees as a reservoir of genetic diversity

Background and Aims

Genetic characterization and phylogenetic analysis of the oldest trees could be a powerful tool both for germplasm collection and for understanding the earliest origins of clonally propagated fruit crops. The olive tree (Olea europaea L.) is a suitable model to study the origin of cultivars due to its long lifespan, resulting in the existence of both centennial and millennial trees across the Mediterranean Basin.

Methods

The genetic identity and diversity as well as the phylogenetic relationships among the oldest wild and cultivated olives of southern Spain were evaluated by analysing simple sequence repeat markers. Samples from both the canopy and the roots of each tree were analysed to distinguish which trees were self-rooted and which were grafted. The ancient olives were also put into chronological order to infer the antiquity of traditional olive cultivars.

Key Results

Only 9·6 % out of 104 a priori cultivated ancient genotypes matched current olive cultivars. The percentage of unidentified genotypes was higher among the oldest olives, which could be because they belong to ancient unknown cultivars or because of possible intra-cultivar variability. Comparing the observed patterns of genetic variation made it possible to distinguish which trees were grafted onto putative wild olives.

Conclusions

This study of ancient olives has been fruitful both for germplasm collection and for enlarging our knowledge about olive domestication. The findings suggest that grafting pre-existing wild olives with olive cultivars was linked to the beginnings of olive growing. Additionally, the low number of genotypes identified in current cultivars points out that the ancient olives from southern Spain constitute a priceless reservoir of genetic diversity.     

A Single Locus Is Responsible for Salinity Tolerance in a Chinese Landrace Barley (Hordeum vulgare L.)

Introduction

Salinity and waterlogging are two major abiotic stresses severely limiting barley production. The lack of a reliable screening method makes it very hard to improve the tolerance through breeding programs.

Methods

This work used 188 DH lines from a cross between a Chinese landrace variety, TX9425 (waterlogging and salinity tolerant), and a Japanese malting barley, Naso Nijo (waterlogging and salinity sensitive), to identify QTLs associated with the tolerance.

Results

Four QTLs were found for waterlogging tolerance. The salinity tolerance was evaluated with both a hydroponic system and in potting mixture. In the trial with potting mixture, only one major QTL was identified to associate with salinity tolerance. This QTL explained nearly 50% of the phenotypic variation, which makes it possible for further fine mapping and cloning of the gene. This QTL was also identified in the hydroponic experiment for different salt-related traits. The position of this QTL was located at a similar position to one of the major QTLs for waterlogging tolerance, indicating the possibility of similar mechanisms controlling both waterlogging and salinity tolerance.

Conclusion

The markers associated with the QTL provided a unique opportunity in breeding programs for selection of salinity and waterlogging tolerance.     

Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment

Motivation

The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1) dataset size (few subjects with respect to the number of features); 2) heterogeneity of the disease; 3) heterogeneity of experimental protocols and computational pipelines employed in the analysis. In this paper, we focus on the first two issues and assess, both on simulated (through an in silico regulation network model) and real clinical datasets, the consistency of candidate biomarkers provided by a number of different methods.

Methods

We extensively simulated the effect of heterogeneity characteristic of complex diseases on different sets of microarray data. Heterogeneity was reproduced by simulating both intrinsic variability of the population and the alteration of regulatory mechanisms. Population variability was simulated by modeling evolution of a pool of subjects; then, a subset of them underwent alterations in regulatory mechanisms so as to mimic the disease state.

Results

The simulated data allowed us to outline advantages and drawbacks of different methods across multiple studies and varying number of samples and to evaluate precision of feature selection on a benchmark with known biomarkers. Although comparable classification accuracy was reached by different methods, the use of external cross-validation loops is helpful in finding features with a higher degree of precision and stability. Application to real data confirmed these results.     

Changes in microRNA expression profile in hippocampus during the acquisition and extinction of cocaine-induced conditioned place preference in rats

Background

MicroRNA (miRNA) emerges as important player in drug abuse. Yet, their expression profile in neurological disorder of cocaine abuse has not been well characterized. Here, we explored the changes of miRNA expression in rat hippocampus following repeated cocaine exposure and subsequent abstinence from cocaine treatment.

Results

Conditioned place preference (CPP) procedure was used to assess the acquisition and extinction of cocaine-seeking behavior in rats. MiRNA microarray was performed to examine miRNAs levels in rat hippocampus. Quantitative RT-PCR was conducted to further confirm results in microarray study. Finally, bioinformatic predictions were made to suggest potential target genes of cocaine-responsive miRNA in this study. MiRNA array found that 34 miRNA levels were changed in rat hippocampus while acquiring cocaine CPP and 42 miRNAs levels were altered after the cocaine-induced CPP were extinguished, as compared to normal controls. The findings from qRT-PCR study support results from microarray analysis.

Conclusions

The current study demonstrated dynamic changes in miRNA expression in rat hippocampus during the acquisition and extinction of cocaine-induced CPP. Some miRNAs which have been previously reported to be involved in brain disorders and drug abuse, including miR-133b, miR-134, miR-181c, miR-191, miR-22, miR-26b, miR-382, miR-409-3p and miR-504, were found to be changed in their expression following repeated cocaine exposure and subsequent abstinence from cocaine treatment. These findings may extend our understanding of the regulatory network underlying cocaine abuse and may provide new targets for the future treatment of drug abuse.     

Transcriptomic Meta-Analysis of Multiple Sclerosis and Its Experimental Models

Background

Multiple microarray analyses of multiple sclerosis (MS) and its experimental models have been published in the last years.

Objective

Meta-analyses integrate the information from multiple studies and are suggested to be a powerful approach in detecting highly relevant and commonly affected pathways.

Data sources

ArrayExpress, Gene Expression Omnibus and PubMed databases were screened for microarray gene expression profiling studies of MS and its experimental animal models.

Study eligibility criteria

Studies comparing central nervous system (CNS) samples of diseased versus healthy individuals with n >1 per group and publically available raw data were selected.

Material and Methods

Included conditions for re-analysis of differentially expressed genes (DEGs) were MS, myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis (EAE) in rats, proteolipid protein-induced EAE in mice, Theiler’s murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD), and a transgenic tumor necrosis factor-overexpressing mouse model (TNFtg). Since solely a single MS raw data set fulfilled the inclusion criteria, a merged list containing the DEGs from two MS-studies was additionally included. Cross-study analysis was performed employing list comparisons of DEGs and alternatively Gene Set Enrichment Analysis (GSEA).

Results

The intersection of DEGs in MS, EAE, TMEV-IDD, and TNFtg contained 12 genes related to macrophage functions. The intersection of EAE, TMEV-IDD and TNFtg comprised 40 DEGs, functionally related to positive regulation of immune response. Over and above, GSEA identified substantially more differentially regulated pathways including coagulation and JAK/STAT-signaling.

Conclusion

A meta-analysis based on a simple comparison of DEGs is over-conservative. In contrast, the more experimental GSEA approach identified both, a priori anticipated as well as promising new candidate pathways.     

Connective Tissue Growth Factor in Regulation of RhoA Mediated Cytoskeletal Tension Associated Osteogenesis of Mouse Adipose-Derived Stromal Cells

Background

Cytoskeletal tension is an intracellular mechanism through which cells convert a mechanical signal into a biochemical response, including production of cytokines and activation of various signaling pathways.

Methods/Principal Findings

Adipose-derived stromal cells (ASCs) were allowed to spread into large cells by seeding them at a low-density (1,250 cells/cm²), which was observed to induce osteogenesis. Conversely, ASCs seeded at a high-density (25,000 cells/cm²) featured small cells that promoted adipogenesis. RhoA and actin filaments were altered by changes in cell size. Blocking actin polymerization by Cytochalasin D influenced cytoskeletal tension and differentiation of ASCs. To understand the potential regulatory mechanisms leading to actin cytoskeletal tension, cDNA microarray was performed on large and small ASCs. Connective tissue growth factor (CTGF) was identified as a major regulator of osteogenesis associated with RhoA mediated cytoskeletal tension. Subsequently, knock-down of CTGF by siRNA in ASCs inhibited this osteogenesis.

Conclusions/Significance

We conclude that CTGF is important in the regulation of cytoskeletal tension mediated ASC osteogenic differentiation.