Geographic differentiation of polymorphism in the Plasmodium falciparum malaria vaccine candidate gene SERA5

SERA5 is regarded as a promising malaria vaccine candidate of the most virulent human malaria parasite Plasmodium falciparum. SERA5 is a 120 kDa abundantly expressed blood-stage protein containing a papain-like protease. Since substantial polymorphism in blood-stage vaccine candidates may potentially limit their efficacy, it is imperative to fully investigate polymorphism of the SERA5 gene (sera5). In this study, we performed evolutionary and population genetic analysis of sera5. The level of inter-species divergence (kS = 0.076) between P. falciparum and Plasmodium reichenowi, a closely related chimpanzee malaria parasite is comparable to that of housekeeping protein genes. A signature of purifying selection was detected in the proenzyme and enzyme domains. Analysis of 445 near full-length P. falciparum sera5 sequences from nine countries in Africa, Southeast Asia, Oceania and South America revealed extensive variations in the number of octamer repeat (OR) and serine repeat (SR) regions as well as substantial level of single nucleotide polymorphism (SNP) in non-repeat regions (2562 bp). Remarkably, a 14 amino acid sequence of SERA5 (amino acids 59-72) that is known to be the in vitro target of parasite growth inhibitory antibodies was found to be perfectly conserved in all 445 worldwide isolates of P. falciparum evaluated. Unlike other major vaccine target antigen genes such as merozoite surface protein-1, apical membrane antigen-1 or circumsporozoite protein, no strong evidence for positive selection was detected for SNPs in the non-repeat regions of sera5. A biased geographical distribution was observed in SNPs as well as in the haplotypes of the sera5 OR and SR regions. In Africa, OR- and SR-haplotypes with low frequency (<5%) and SNPs with minor allele frequency (<5%) were abundant and were mostly continent-specific. Consistently, significant genetic differentiation, assessed by the Wright's fixation index (FST) of inter-population variance in allele frequencies, was detected for SNPs and both OR- and SR-haplotypes among almost all parasite populations. The exception was parasite populations between Tanzania and Ghana, suggesting frequent gene flow in Africa. The present study points to the importance of investigating whether biased geographical distribution for SNPs and repeat variants in the OR and SR regions affect the reactivity of human serum antibodies to variants. (C) 2011 Elsevier Ltd. All rights reserved.

Gene expression during early somatic embryogenesis in Brazilian pine (Araucaria angustifolia (Bert) O. Ktze)

Brazilian pine (Araucaria angustifolia (Bert) O. Ktze) is the only native conifer species with economic importance in Brazil. Recently, due to intensive exploitation Brazilian pine was included in the official list of endangered Brazilian plants, under the "vulnerable" category. Biotechnology tools like somatic embryogenesis (SE) are potentially useful for mass clonal propagation and ex situ conservation strategies of commercial and endangered plant species. In spite of that, numerous obstacles still hamper the full application of SE technology for a wider range of species, including Brazilian pine. To enhance somatic embryogenesis in Brazilian pine and to gain a better understanding of the molecular events associated with somatic embryo development, we analyzed the steady-state transcript levels of genes known to regulate somatic embryogenesis using semiquantitative reverse transcription polymerase chain reaction (sqRT-PCR). These genes included Argonaute (AaAGO), Cup-shaped cotyledon1 (AaCUC), wushel-related WOX (AaWOX), a S-locus lectin protein kinase (AaLecK), Scarecrow- like (AaSCR), Vicilin 7S (AaVIC), Leafy Cotyledon 1 (AaLEC), and a Reversible glycosylated polypeptide (AaRGP). Expression patterns of these selected genes were investigated in embryogenic cultures undergoing different stages of embryogenesis, and all the way to maturation. Up-regulation of AaAGO, AaCUC, AaWOX, AaLecK, and AaVIC was observed during transition of somatic embryos from stage I to stage II. During the maintenance phase of somatic embryogenesis, expression of AaAGO and AaSCR, but not AaRPG and AaLEC genes was influenced by presence/ absence of plant growth regulators, both auxins and cytokinins. The results presented here provide new insights on the molecular mechanisms responsible for somatic embryo formation, and how selected genes may be used as molecular markers for Brazilian pine embryogenesis.

Vitrification of primordial germ cells using whole embryos for gene-banking in loach, Misgurnus anguillicaudatus

In gene-banking, primordial germ cells (PGCs), which are embryonic precursor cells of germ cells, are useful for cryopreservation because PGCs have a potential to differentiate into both eggs and sperm via germ-line chimera. Here, we have established vitrification methods for PGCs cryopreservation using 12- to 17-somite stage embryos in loach, Misgurnus anguillicaudatus, which were dechorionated, removed their yolk and injected with green fluorescent protein (GFP) -nos1 3'UTR mRNA to visualize their PGCs. In order to optimize cryopreservation medium for vitrification, the toxicity of cryoprotectants was analyzed. Different concentrations (2, 3, 4, 5 m) of dimethyl sulfoxide (DMSO), methanol (MeOH), ethylene glycol (EG) and propylene glycol (PG) as cryoprotectants were tested. Then, 5 m DMSO showed significantly-high toxicity. Based on this information, combinations called DMP (2 m (14.2% [v/v]) DMSO, 2 m (8.1% [v/v]) MeOH and 2 m (14.4% [v/v]) PG), DP (2 m (14.2% [v/v]) DMSO and 4 m (28.7% [v/v]) PG) and DE (2.1 m (15% [v/v]) DMSO and 2.7 m (15% [v/v]) EG) were evaluated for their toxicities and efficacy of PGCs cryopreservation using two types of equilibration step: direct immersion of cryopreservation media (one-step) and serial exposure to half and full concentration of cryopreservation media (two-step). Viable PGCs were obtained from post-thaw embryos which were cryopreserved by DP and DE with both 1- and 2-step equilibrations. Despite DP showing the highest toxicity, it gave the highest survival rate of embryonic cells after cryopreservation. When PGCs recovered from vitrified embryos were transplanted into host embryos at the blastula stage, the transplanted PGCs were able to migrate to a host genital ridge similarly as endogenous PGCs. It suggests that our methods could be useful to create a germ-line chimera for the production of gametes from PGCs of cryopreserved embryos.

Evaluation of reference-based two-color methods for measurement of gene expression ratios using spotted cDNA microarrays

Abstract Background Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard. Results We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable. Conclusion RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

Abstract Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

GENE SET ENRICHMENT ANALYSIS MADE SIMPLE

Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, chose an appropriate cut-off, and create a list of candidate genes. This approach has been criticized for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, many of these methods seem overly complicated. Furthermore, the most popular method, Gene Set Enrichment Analysis (GSEA), is based on a statistical test known for its lack of sensitivity. In this paper we compare the performance of a simple alternative to GSEA.We find that this simple solution clearly outperforms GSEA.We demonstrate this with eight different microarray datasets.

Targeted gene transfer of hepatocyte growth factor to alveolar type II epithelial cells reduces lung fibrosis in rats

Inefficient alveolar wound repair contributes to the development of pulmonary fibrosis. Hepatocyte growth factor (HGF) is a potent growth factor for alveolar type II epithelial cells (AECII) and may improve repair and reduce fibrosis. We studied whether targeted gene transfer of HGF specifically to AECII improves lung fibrosis in bleomycin-induced lung fibrosis. A plasmid encoding human HGF expressed from the human surfactant protein C promoter (pSpC-hHGF) was designed, and extracorporeal electroporation-mediated gene transfer of HGF specifically to AECII was performed 7 days after bleomycin-induced lung injury in the rat. Animals were killed 7 days after hHGF gene transfer. Electroporation-mediated HGF gene transfer resulted in HGF expression specifically in AECII at biologically relevant levels. HGF gene transfer reduced pulmonary fibrosis as assessed by histology, hydroxyproline determination, and design-based stereology compared with controls. Our results indicate that the antifibrotic effect of HGF is due in part to a reduction of transforming growth factor-β(1), modulation of the epithelial-mesenchymal transition, and reduction of extravascular fibrin deposition. We conclude that targeted HGF gene transfer specifically to AECII decreases bleomycin-induced lung fibrosis and may therefore represent a novel cell-specific gene transfer technology to treat pulmonary fibrosis.

Application of in vivo induced antigen technology (IVIAT) to Bacillus anthracis.

In vivo induced antigen technology (IVIAT) is an immuno-screening technique that identifies bacterial antigens expressed during infection and not during standard in vitro culturing conditions. We applied IVIAT to Bacillus anthracis and identified PagA, seven members of a N-acetylmuramoyl-L-alanine amidase autolysin family, three P60 family lipoproteins, two transporters, spore cortex lytic protein SleB, a penicillin binding protein, a putative prophage holin, respiratory nitrate reductase NarG, and three proteins of unknown function. Using quantitative real-time PCR comparing RNA isolated from in vitro cultured B. anthracis to RNA isolated from BALB/c mice infected with virulent Ames strain B. anthracis, we confirmed induced expression in vivo for a subset of B. anthracis genes identified by IVIAT, including L-alanine amidases BA3767, BA4073, and amiA (pXO2-42); the bacteriophage holin gene BA4074; and pagA (pXO1-110). The exogenous addition of two purified putative autolysins identified by IVIAT, N-acetylmuramoyl-L-alanine amidases BA0485 and BA2446, to vegetative B. anthracis cell suspensions induced a species-specific change in bacterial morphology and reduction in viable bacterial cells. Many of the proteins identified in our screen are predicted to affect peptidoglycan re-modeling, and our results support significant cell wall structural remodeling activity during B. anthracis infection. Identification of L-alanine amidases with B. anthracis specificity may suggest new potential therapeutic targets.

Regulation of human (adrenal) androgen biosynthesis-New insights from novel throughput technology studies

Androgens are precursors for sex steroids and are predominantly produced in the human gonads and the adrenal cortex. They are important for intrauterine and postnatal sexual development and human reproduction. Although human androgen biosynthesis has been extensively studied in the past, exact mechanisms underlying the regulation of androgen production in health and disease remain vague. Here, the knowledge on human androgen biosynthesis and regulation is reviewed with a special focus on human adrenal androgen production and the hyperandrogenic disorder of polycystic ovary syndrome (PCOS). Since human androgen regulation is highly specific without a good animal model, most studies are performed on patients harboring inborn errors of androgen biosynthesis, on human biomaterials and human (tumor) cell models. In the past, most studies used a candidate gene approach while newer studies use high throughput technologies to identify novel regulators of androgen biosynthesis. Using genome wide association studies on cohorts of patients, novel PCOS candidate genes have been recently described. Variant 2 of the DENND1A gene was found overexpressed in PCOS theca cells and confirmed to enhance androgen production. Transcriptome profiling of dissected adrenal zones established a role for BMP4 in androgen synthesis. Similarly, transcriptome analysis of human adrenal NCI-H295 cells identified novel regulators of androgen production. Kinase p38α (MAPK14) was found to phosphorylate CYP17 for enhanced 17,20 lyase activity and RARB and ANGPTL1 were detected in novel networks regulating androgens. The discovery of novel players for androgen biosynthesis is of clinical significance as it provides targets for diagnostic and therapeutic use.

Breast cancer risk and heterocyclic amines and effect modification by NAT gene polymorphisms

Breast cancer is the most common cancer in women in the United States and is a leading cause of cancer-related deaths (1). Recently, dietary heterocyclic amines (HCAs) have been proposed to be a risk factor for breast cancer (2). This study uses the data collected for a case-control study conducted at the M.D. Anderson Cancer Center to assess the association between breast cancer risk and HCAs {2-amino-1-methyl-6-phenylimidazole [4,5-b] pyridine (PhIP), 2-amino-3,8-dimethylimidazo [4,5-f] quinoxaline (MeIQx), 2-amino-3,4,8-trimethylimidazo [4,5-f] quinoxaline (DiMeIQx) and mutagenicity of HCAs} and to examine if this association is modified by genetic polymorphisms of N-acetyl transferases (NAT1/NAT2). The NAT1/2 genotype was determined using Taqman technology. HCAs were estimated by using a meat preparation questionnaire on meat type, cooking method, and doneness, combined with a quantitative HCA database. Three hundred and fifty patients with breast cancer attending the Diagnostic Radiology Clinic at M. D. Anderson Cancer Center and fulfilling the eligibility criteria were compared to three hundred and fifty patients attending the same clinic for benign breast lesions to answer these questions. Logistic regression models were used to control for known risk factors and showed no statistically significant association between breast cancer versus benign breast cancer lesions and dietary intake of heterocyclic amines. There was no clear difference in their effect after subgroup analyses in different acetylator strata of NAT1/2 and no statistical interactions were found between NAT1/2 genotypes and HCAs, suggesting no effect modification by NAT1/2 acetylator status. These results suggest the need for further research to analyze if these null associations were because of the benign breast lesions sharing the risk factors with breast cancer or any other factors which haven't been explored yet.^

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

Gene Expression Profiling in Limb-Girdle Muscular Dystrophy 2A

Limb-girdle muscular dystrophy type 2A (LGMD2A) is a recessive genetic disorder caused by mutations in calpain 3 (CAPN3). Calpain 3 plays different roles in muscular cells, but little is known about its functions or in vivo substrates. The aim of this study was to identify the genes showing an altered expression in LGMD2A patients and the possible pathways they are implicated in. Ten muscle samples from LGMD2A patients with in which molecular diagnosis was ascertained were investigated using array technology to analyze gene expression profiling as compared to ten normal muscle samples. Upregulated genes were mostly those related to extracellular matrix (different collagens), cell adhesion (fibronectin), muscle development (myosins and melusin) and signal transduction. It is therefore suggested that different proteins located or participating in the costameric region are implicated in processes regulated by calpain 3 during skeletal muscle development. Genes participating in the ubiquitin proteasome degradation pathway were found to be deregulated in LGMD2A patients, suggesting that regulation of this pathway may be under the control of calpain 3 activity. As frizzled-related protein (FRZB) is upregulated in LGMD2A muscle samples, it could be hypothesized that β-catenin regulation is also altered at the Wnt signaling pathway, leading to an incorrect myogenesis. Conversely, expression of most transcription factor genes was downregulated (MYC, FOS and EGR1). Finally, the upregulation of IL-32 and immunoglobulin genes may induce the eosinophil chemoattraction explaining the inflammatory findings observed in presymptomatic stages. The obtained results try to shed some light on identification of novel therapeutic targets for limb-girdle muscular dystrophies