A comprehensive analysis of gene expression profiles in distal parts of the mouse renal tubule.

The distal parts of the renal tubule play a critical role in maintaining homeostasis of extracellular fluids. In this review, we present an in-depth analysis of microarray-based gene expression profiles available for microdissected mouse distal nephron segments, i.e., the distal convoluted tubule (DCT) and the connecting tubule (CNT), and for the cortical portion of the collecting duct (CCD; Zuber et al., Proc Natl Acad Sci USA 106:16523-16528, 2009). Classification of expressed transcripts in 14 major functional gene categories demonstrated that all principal proteins involved in maintaining the salt and water balance are represented by highly abundant transcripts. However, a significant number of transcripts belonging, for instance, to categories of G-protein-coupled receptors or serine/threonine kinases exhibit high expression levels but remain unassigned to a specific renal function. We also established a list of genes differentially expressed between the DCT/CNT and the CCD. This list is enriched by genes related to segment-specific transport functions and by transcription factors directing the development of the distal nephron or collecting ducts. Collectively, this in silico analysis provides comprehensive information about relative abundance and tissue specificity of the DCT/CNT and the CCD expressed transcripts and identifies new candidate genes for renal homeostasis.

Transcriptional regulation of metabolism.

Our understanding of metabolism is undergoing a dramatic shift. Indeed, the efforts made towards elucidating the mechanisms controlling the major regulatory pathways are now being rewarded. At the molecular level, the crucial role of transcription factors is particularly well-illustrated by the link between alterations of their functions and the occurrence of major metabolic diseases. In addition, the possibility of manipulating the ligand-dependent activity of some of these transcription factors makes them attractive as therapeutic targets. The aim of this review is to summarize recent knowledge on the transcriptional control of metabolic homeostasis. We first review data on the transcriptional regulation of the intermediary metabolism, i.e., glucose, amino acid, lipid, and cholesterol metabolism. Then, we analyze how transcription factors integrate signals from various pathways to ensure homeostasis. One example of this coordination is the daily adaptation to the circadian fasting and feeding rhythm. This section also discusses the dysregulations causing the metabolic syndrome, which reveals the intricate nature of glucose and lipid metabolism and the role of the transcription factor PPARgamma in orchestrating this association. Finally, we discuss the molecular mechanisms underlying metabolic regulations, which provide new opportunities for treating complex metabolic disorders.

The evolution of gene expression levels in mammalian organs.

Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.

Comparative modular analysis of gene expression in vertebrate organs.

ABSTRACT: BACKGROUND: The degree of conservation of gene expression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. RESULTS: Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. CONCLUSIONS: Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Semiquantitative RT-PCR measurement of gene expression in rat tissues including a correction for varying cell size and number

Background: Current methodology of gene expression analysis limits the possibilities of comparison between cells/tissues of organs in which cell size and/or number changes as a consequence of the study (e.g. starvation). A method relating the abundance of specific mRNA copies per cell may allow direct comparison or different organs and/or changing physiological conditions. Methods: With a number of selected genes, we analysed the relationship of the number of bases and the fluorescence recorded at a present level using cDNA standards. A lineal relationship was found between the final number of bases and the length of the transcript. The constants of this equation and those of the relationship between fluorescence and number of bases in cDNA were determined and a general equation linking the length of the transcript and the initial number of copies of mRNA was deduced for a given pre-established fluorescence setting. This allowed the calculation of the concentration of the corresponding mRNAs per g of tissue. The inclusion of tissue RNA and the DNA content per cell, allowed the calculation of the mRNA copies per cell. Results: The application of this procedure to six genes: Arbp, cyclophilin, ChREBP, T4 deiodinase 2, acetyl-CoA carboxylase 1 and IRS-1, in liver and retroperitoneal adipose tissue of food-restricted rats allowed precise measures of their changes irrespective of the shrinking of the tissue, the loss of cells or changes in cell size, factors that deeply complicate the comparison between changing tissue conditions. The percentage results obtained with the present methods were essentially the same obtained with the delta-delta procedure and with individual cDNA standard curve quantitative RT-PCR estimation. Conclusion: The method presented allows the comparison (i.e. as copies of mRNA per cell) between different genes and tissues, establishing the degree of abundance of the different molecular species tested.

Analysis of gene expression patterns in animals

During my PhD, my aim was to provide new tools to increase our capacity to analyse gene expression patterns, and to study on a large-scale basis the evolution of gene expression in animals. Gene expression patterns (when and where a gene is expressed) are a key feature in understanding gene function, notably in development. It appears clear now that the evolution of developmental processes and of phenotypes is shaped both by evolution at the coding sequence level, and at the gene expression level.Studying gene expression evolution in animals, with complex expression patterns over tissues and developmental time, is still challenging. No tools are available to routinely compare expression patterns between different species, with precision, and on a large-scale basis. Studies on gene expression evolution are therefore performed only on small genes datasets, or using imprecise descriptions of expression patterns.The aim of my PhD was thus to develop and use novel bioinformatics resources, to study the evolution of gene expression. To this end, I developed the database Bgee (Base for Gene Expression Evolution). The approach of Bgee is to transform heterogeneous expression data (ESTs, microarrays, and in-situ hybridizations) into present/absent calls, and to annotate them to standard representations of anatomy and development of different species (anatomical ontologies). An extensive mapping between anatomies of species is then developed based on hypothesis of homology. These precise annotations to anatomies, and this extensive mapping between species, are the major assets of Bgee, and have required the involvement of many co-workers over the years. My main personal contribution is the development and the management of both the Bgee database and the web-application.Bgee is now on its ninth release, and includes an important gene expression dataset for 5 species (human, mouse, drosophila, zebrafish, Xenopus), with the most data from mouse, human and zebrafish. Using these three species, I have conducted an analysis of gene expression evolution after duplication in vertebrates.Gene duplication is thought to be a major source of novelty in evolution, and to participate to speciation. It has been suggested that the evolution of gene expression patterns might participate in the retention of duplicate genes. I performed a large-scale comparison of expression patterns of hundreds of duplicated genes to their singleton ortholog in an outgroup, including both small and large-scale duplicates, in three vertebrate species (human, mouse and zebrafish), and using highly accurate descriptions of expression patterns. My results showed unexpectedly high rates of de novo acquisition of expression domains after duplication (neofunctionalization), at least as high or higher than rates of partitioning of expression domains (subfunctionalization). I found differences in the evolution of expression of small- and large-scale duplicates, with small-scale duplicates more prone to neofunctionalization. Duplicates with neofunctionalization seemed to evolve under more relaxed selective pressure on the coding sequence. Finally, even with abundant and precise expression data, the majority fate I recovered was neither neo- nor subfunctionalization of expression domains, suggesting a major role for other mechanisms in duplicate gene retention.

Evolution of gene expression in fire ants: the effects of developmental stage, caste, and species.

Ants provide remarkable examples of equivalent genotypes developing into divergent and discrete phenotypes. Diploid eggs can develop either into queens, which specialize in reproduction, or workers, which participate in cooperative tasks such as building the nest, collecting food, and rearing the young. In contrast, the differentiation between males and females generally depends upon whether eggs are fertilized, with fertilized (diploid) eggs giving rise to females and unfertilized (haploid) eggs giving rise to males. To obtain a comprehensive picture of the relative contributions of gender (sex), caste, developmental stage, and species divergence to gene expression evolution, we investigated gene expression patterns in pupal and adult queens, workers, and males of two species of fire ants, Solenopsis invicta and S. richteri. Microarray hybridizations revealed that variation in gene expression profiles is influenced more by developmental stage than by caste membership, sex, or species identity. The second major contributor to variation in gene expression was the combination of sex and caste. Although workers and queens share equivalent diploid nuclear genomes, they have highly distinctive patterns of gene expression in both the pupal and the adult stages, as might be expected given their extraordinary level of phenotypic differentiation. Overall, the difference in the proportion of differentially expressed genes was greater between workers and males than between workers and queens or queens and males, consistent with the fact that workers and males share neither gender nor reproductive capability. Moreover, between-species comparisons revealed that the greatest difference in gene expression patterns occurred in adult workers, a finding consistent with the fact that adult workers most directly experience the distinct external environments characterizing the different habitats occupied by the two species. Thus, much of the evolution of gene expression in ants may occur in the worker caste, despite the fact that these individuals are largely or completely sterile. Analyses of gene expression evolution revealed a combination of positive selection and relaxation of stabilizing selection as important factors driving the evolution of such genes.

Comparative modular analysis of gene expression in vertebrate development

The focus of my PhD research was the concept of modularity. In the last 15 years, modularity has become a classic term in different fields of biology. On the conceptual level, a module is a set of interacting elements that remain mostly independent from the elements outside of the module. I used modular analysis techniques to study gene expression evolution in vertebrates. In particular, I identified ``natural'' modules of gene expression in mouse and human, and I showed that expression of organ-specific and system-specific genes tends to be conserved between such distance vertebrates as mammals and fishes. Also with a modular approach, I studied patterns of developmental constraints on transcriptome evolution. I showed that none of the two commonly accepted models of the evolution of embryonic development (``evo-devo'') are exclusively valid. In particular, I found that the conservation of the sequences of regulatory regions is highest during mid-development of zebrafish, and thus it supports the ``hourglass model''. In contrast, events of gene duplication and new gene introduction are most rare in early development, which supports the ``early conservation model''. In addition to the biological insights on transcriptome evolution, I have also discussed in detail the advantages of modular approaches in large-scale data analysis. Moreover, I re-analyzed several studies (published in high-ranking journals), and showed that their conclusions do not hold out under a detailed analysis. This demonstrates that complex analysis of high-throughput data requires a co-operation between biologists, bioinformaticians, and statisticians.

The neuronal monocarboxylate transporter MCT2: its regulation by BDNF and its role in learning and memory

Glucose has been considered the major, if not the exclusive, energy substrate for the brain. But under certain physiological and pathological conditions other substrates, namely monocarboxylates (lactate, pyruvate and ketone bodies), can contribute significantly to satisfy brain energy demands. These monocarboxylates need to be transported across the blood-brain barrier or out of astrocytes into the extracellular space and taken up into neurons. It has been shown that monocarboxylates are transported by a family of proton-linked transporters called monocarboxylate transporters (MCTs). In the central nervous system, MCT2 is the predominant neuronal isoform and little is known about the regulation of its expression. Noradrenaline (NA), insulin and IGF-1 were previously shown to enhance the expression of MCT2 in cultured cortical neurons via a translational mechanism. Here we demonstrate that the well known brain neurotrophic factor BDNF enhances MCT2 protein expression in cultured cortical neurons and in synaptoneurosome preparations in a time- and concentrationdependent manner without affecting MCT2 mRNA levels. We observed that BDNF induced MCT2 expression by activation of MAPK as well as PI3K/Akt/mTOR signaling pathways. Furthermore, we investigated the possible post-transcriptional regulation of MCT2 expression by a neuronal miRNA. Then, we demonstrated that BDNF enhanced MCT2 expression in the hippocampus in vivo, in parallel with some post-synaptic proteins such as PSD95 and AMPA receptor GluR2/3 subunits, and two immediate early genes Arc and Zif268 known to be expressed in conditions related to synaptic plasticity. In the last part, we demonstrated in vivo that a downregulation of hippocampal MCT2 via silencing with an appropriate lentiviral vector in mice caused an impairment of working memory without reference memory deficit. In conclusion, these results suggest that regulation of neuronal monocarboxylate transporter MCT2 expression could be a key event in the context of synaptic plasticity, allowing an adequate energy substrate supply in situations of altered synaptic efficacy. - Le glucose représente le substrat énergétique majeur pour le cerveau. Cependant, dans certaines conditions physiologiques ou pathologiques, le cerveau a la capacité d'utiliser des substrats énergéiques appartenant à la classe des monocarboxylates (lactate, pyruvate et corps cétoniques) afin de satisfaire ses besoins énergétiques. Ces monocarboxylates doivent être transportés à travers la barrière hématoencéphalique mais aussi hors des astrocytes vers l'espace extracellulaire puis re-captés par les neurones. Leur transport est assuré par une famillle de transporteurs aux monocarboxylates (MCTs). Dans le système nerveux central, les neurones expriment principalement l'isoforme MCT2 mais peu d'informations sont disponibles concernant la régulation de son expression. Il a été montré que la noradrénaline, l'insuline et l'IGF-1 induisent l'expression de MCT2 dans des cultures de neurones corticaux par un mécanisme traductionnel. Dans cette étude nous démontrons dans un premier temps que le facteur neurotrophique BDNF augmente l'expression de MCT2 à la fois dans des cultures de neurones corticaux et dans les préparations synaptoneurosomales selon un décours temporel et une gamme de concentrations propre. Aucun changement n'a été observé concernant les niveaux d'ARNm de MCT2. Nous avons observé que le BDNF induisait l'expression de MCT2 par l'activation simultanée des voies de signalisation MAPK et PI3K/Akt/mTOR. De plus, nous nous sommes intéressés à une potentielle régulation par les micro-ARNs de la synthèse de MCT2. Ensuite, nous avons démontré que le BDNF induit aussi l'expression de MCT2 dans l'hippocampe de la souris en parallèle avec d'autres protéines post-synaptiques telles que PSD95 et GluR2/3 et avec deux « immediate early genes » tels que Arc et Zif268 connus pour être exprimés dans des conditions de plasticité synaptique. Dans un dernier temps, nous avons démontré qu'une diminution d'expression de MCT2 induite par le biais d'un siRNA exprimé via un vecteur lentiviral dans l'hippocampe de souris générait des déficits de mémoire de travail sans affecter la mémoire de référence. En conclusion, ces résultats nous suggèrent que le transporteur aux monocarboxylates neuronal MCT2 serait essentiel pour l'apport énergétique du lactate pour les neurones dans des conditions de haute activité neuronale comme c'est le cas pendant les processus de plasticité synaptique.

Evolution of gene expression changes in newborn rats after mechanical ventilation with reversible intubation

Résumant mon travail de thèse, l'article qui suit décrit un nouveau modèle animal servant à étudier l'impact combiné d'une ventilation mécanique (VM), d'une oxygénothérapie et d'une inflammation sur des poumons immatures. Cette étude permet, pour la première fois, de mesurer l'expression de gènes à distance d'une VM pour en analyser la cinétique. La VM représente un traitement intégral dans la prise en charge de prématurés. Sauvant des vies, elle est cependant non-physiologique et décrite comme nocive à court et à long terme, empêchant le bon développement pulmonaire. Nombreuses études se sont intéressées à l'impact immédiat de la VM sur les poumons, mais il n'existe à ce jour aucun modèle de rongeur pour en analyser les effets tardifs. Par analogie avec la clinique, nous avons créé un modèle avec un animal dont le stade développemental pulmonaire est comparable aux prématurés humains et consistant en une oxygénothérapie, une VM modérée avec intubation non chirurgicale, similaire à la pratique quotidienne, et un contexte inflammatoire mimant celui de chorioamnionite dans lequel bien des prématurés naissent. Nous avons ensuite réalisé une extubation pour permettre une période de rétablissement, puis fait des analyses et sur le plan structurel par histologie conventionnelle et en 3D, et sur le plan biologique, par analyse de l'expression de gènes et de protéines. Ce travail a permis de valider ce nouveau modèle comme outil de recherche pour réaliser des mesures à distance d'une VM chez des rats nouveau-nés. Comparant ces mesures à celles prises à la fin de la VM, nous observons: une augmentation initiale et transitoire des médiateurs impliqués dans la cascade inflammatoire dont le corrélat histologique est une maladie inflammatoire pulmonaire et, tardivement, une altération plus développementale de la structure pulmonaire avec diminution de l'alvéolarisation. Ceci pourrait être en partie dû à une expression asynchrone de gènes décrits comme importants pour la formation des alvéoles (matrix metalloproteinase 9, elastine). Offrant une nouvelle approche pour la recherche pulmonaire chez les rongeurs, ce modèle servira comme futur outil pour approfondir nos connaissances de la physiopathologie conduisant aux altérations structurelles retrouvées dans les poumons d'anciens prématurés soumis à une VM (dysplasie broncho-pulmonaire), pour tester l'influence de certains traitements (p.ex. surfactant) et pour étudier les effets de la VM en l'appliquant à des modèles transgéniques.

Regulation of the expression of NADP-malic enzyme by UV-B, red and far-red light in maize seedlings

The induction of nicotinamide adenine dinucleotide phosphate-malic enzyme (NADP-ME) in etiolated maize (Zea mays) seedlings by UV-B and UV-A radiation, and different levels of photosynthetically active radiation (PAR, 400-700 nm) was investigated by measuring changes in activity, protein quantity and RNA levels as a function of intensity and duration of exposure to the different radiations. Under low levels of PAR, exposure to UV-B radiation but not UV-A radiation for 6 to 24 h caused a marked increase in the enzyme levels similar to that observed under high PAR in the absence of UV-B. UV-B treatment of green leaves following a 12-h dark period also caused an increase in NADP-ME expression. Exposure to UV-B radiation for only 5 min resulted in a rapid increase of the enzyme, followed by a more gradual rise with longer exposure up to 6 h. Low levels of red light for 5 min or 6 h were also effective in inducing NADP-ME activity equivalent to that obtained with UV-B radiation. A 5-min exposure to far-red light following UV-B or red light treatment reversed the induction of NADP-ME, and this effect could be eliminated by further treatment with UV-B or red light. These results indicate that physiological levels of UV-B radiation can have a positive effect on the induction of this photosynthetic enzyme. The reducing power and pyruvate generated by the activity of NADP-ME may be used for respiration, in cellular repair processes and as substrates for fatty acid synthesis required for membrane repair.

Changes in cell shape and desmin intermediate filament distribution are associated with down-regulation of desmin expression in C2C12 myoblasts grown in the absence of extracellular Ca2+

Desmin is the main intermediate filament (IF) protein of muscle cells. In skeletal muscle, desmin IFs form a scaffold that interconnects the entire contractile apparatus with the subsarcolemmal cytoskeleton and cytoplasmic organelles. The interaction between desmin and the sarcolemma is mediated by a number of membrane proteins, many of which are Ca2+-sensitive. In the present study, we analyzed the effects of the Ca2+ chelator EGTA (1.75 mM) on the expression and distribution of desmin in C2C12 myoblasts grown in culture. We used indirect immunofluorescence microscopy and reverse transcription polymerase chain reaction (RT-PCR) to analyze desmin distribution and expression in C2C12 cells grown in the presence or absence of EGTA. Control C2C12 myoblasts showed a well-spread morphology after a few hours in culture and became bipolar when grown for 24 h in the presence of EGTA. Control C2C12 cells showed a dense network of desmin from the perinuclear region to the cell periphery, whereas EGTA-treated cells showed desmin aggregates in the cytoplasm. RT-PCR analysis revealed a down-regulation of desmin expression in EGTA-treated C2C12 cells compared to untreated cells. The present results suggest that extracellular Ca2+ availability plays a role in the regulation of desmin expression and in the spatial distribution of desmin IFs in myoblasts, and is involved in the generation and maintenance of myoblast cell shape.

Potential Urinary miRNA Biomarker Candidates for the Accurate Detection of Prostate Cancer among Benign Prostatic Hyperplasia Patients

MicroRNAs (miRNAs) are a class of short (similar to 22nt), single stranded RNA molecules that function as post-transcriptional regulators of gene expression. MiRNAs can regulate a variety of important biological pathways, including: cellular proliferation, differentiation and apoptosis. Profiling of miRNA expression patterns was shown to be more useful than the equivalent mRNA profiles for characterizing poorly differentiated tumours. As such, miRNA expression "signatures" are expected to offer serious potential for diagnosing and prognosing cancers of any provenance. The aim of this study was to investigate the potential of using deregulation of urinary miRNAs in order to detect Prostate Cancer (PCa) among Benign Prostatic Hyperplasia (BPH). To identify the miRNA signatures specific for PCa, miRNA expression profiling of 8 PCa patients, 12 BPH patients and 10 healthy males was carried out using whole genome expression profiling. Differential expression of two individual miRNAs between healthy males and BPH patients was detected and found to possibly target genes related to PCa development and progression. The sensitivity and specificity of miR-1825 for detecting PCa among BPH individuals was found to be 60% and 69%, respectively. Whereas, the sensitivity and specificity of miR-484 were 80% and 19%, respectively. Additionally, the sensitivity and specificity for miR-1825/484 in tandem were 45% and 75%, respectively. The proposed PCa miRNA signatures may therefore be of great value for the accurate diagnosis of PCa and BPH. This exploratory study has identified several possible targets that merit further investigation towards the development and validation of diagnostically useful, non-invasive, urine-based tests that might not only help diagnose PCa but also possibly help differentiate it from BPH.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.