High-throughput genotype-based population structure analysis of selected buffalo breeds

India is considered as the home tract of some of the best buffalo breeds. However, the genetic structure of the Indian river buffalo is poorly understood. Hence, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds for selection and to design breeding strategies. In this study, we have analyzed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom Buffalo Genotyping Array. Diversity, as measured by expected heterozygosity, ranged from 0.364 in Surti to 0.384 in Murrah breed, and pair-wise F_ST values revealed the lowest genetic distance between Murrah and Nili-Ravi (0.0022), while the highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri, and Jaffarabadi in first two principal components and at K = 4, respectively, while remaining breeds were grouped together as a separate single cluster and admixed. Murrah and Mehsana showed early linkage disequilibrium (LD) decay, while Surti breed showed late decay. In LD blocks to quantitative trait locis (QTLs) concordance analysis, 4.65% of concordance was observed with 873 LD blocks overlapped with 2,330 QTLs. Overall, total 4,090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these single-nucleotide polymorphism (SNP) markers could differentiate phenotypically distinct breeds like Surti, Pandharpuri, and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.

A gene expression signature predicts recurrence-free survival in meningioma

BACKGROUND

Meningioma is the most common primary brain tumor and has a variable risk of local recurrence. While World Health Organization (WHO) grade generally correlates with recurrence, there is substantial within-grade variation of recurrence risk. Current risk stratification does not accurately predict which patients are likely to benefit from adjuvant radiation therapy (RT). We hypothesized that tumors at risk for recurrence have unique gene expression profiles (GEP) that could better select patients for adjuvant RT.

METHODS

We developed a recurrence predictor by machine learning modeling using a training/validation approach.

RESULTS

Three publicly available AffymetrixU133 gene expression datasets (GSE9438, GSE16581, GSE43290) combining 127 primary, non-treated meningiomas of all grades served as the training set. Unsupervised variable selection was used to identify an 18-gene GEP model (18-GEP) that separated recurrences. This model was validated on 62 primary, non-treated cases with similar grade and clinical variable distribution as the training set. When applied to the validation set, 18-GEP separated recurrences with a misclassification error rate of 0.25 (log-rank p=0.0003). 18-GEP was predictive for tumor recurrence [p=0.0008, HR=4.61, 95%CI=1.89-11.23)] and was predictive after adjustment for WHO grade, mitotic index, sex, tumor location, and Simpson grade [p=0.0311, HR=9.28, 95%CI=(1.22-70.29)]. The expression signature included genes encoding proteins involved in normal embryonic development, cell proliferation, tumor growth and invasion (FGF9, SEMA3C, EDNRA), angiogenesis (angiopoietin-2), cell cycle regulation (CDKN1A), membrane signaling (tetraspanin-7, caveolin-2), WNT-pathway inhibitors (DKK3), complement system (C1QA) and neurotransmitter regulation (SLC1A3, Secretogranin-II).

CONCLUSIONS

18-GEP accurately stratifies patients with meningioma by recurrence risk having the potential to guide the use of adjuvant RT.

Gene-expression Analysis Identifies Specific Patterns of Dysregulated Molecular Pathways and Genetic Subgroups of Human Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma comprises of a group of heterogeneous tumors of different etiologies. The multistep process of liver carcinogenesis involves various genetic and phenotypic alterations. The molecular pathways and driver mutations involved are still under investigation.

MATERIALS AND METHODS

DNA micorarray technology was used to identify differentially expressed genes between human hepatocarcinoma and non-tumorous liver tissues to establish a unique specific gene-expression profile independent of the underlying liver disease. The validity of this global gene-expression profile was tested for its robustness against biopsies from other liver entities (cirrhotic and non-cirrhotic liver) by diagnosing HCC in blinded samples.

RESULTS

Most of the consistently and strongly overexpressed genes were related to cell-cycle regulation and DNA replication [27 genes, e.g. cyclin B1, karyopherin alpha 2 (KPNA2), cyclin-dependent kinase 2 (CDC2)], G-protein depending signaling [e.g. Rac GTPase activating protein 1 (RACGAP1), Rab GTPase YPT1 homolog (RAB1), and ADP-ribosylation factor-like 2 (ARL2)] and extracellular matrix re-modelling or cytoskeleton structure [22 genes, e.g. serine proteinase inhibitor 1 kazal-type (SPINK1), osteopontin (OPN), secreted protein acidic and rich in cysteine (SPARC), collagen type 1 alpha2 (COL1A2), integrin alpha6 (ITGA6), and metalloproteinase 12 (MMP12)]. Furthermore, significantly differentially expressed genes (e.g. calcium-binding proteins, G-proteins, oncofetal proteins) in relation to tumor differentiation were detected using gene-expression analysis.

CONCLUSION

It is suggested that these significantly dysregulated genes are highly specific and potentially utilizable as prognostic markers and may lead to a better understanding of human hepatocarcinogenesis.

Aerobic exercise augments muscle transcriptome profile of resistance exercise

Recent reports suggest that aerobic exercise may boost the hypertrophic response to short-term resistance training. This study explored the effects of an acute aerobic exercise bout on the transcriptional response to subsequent resistance exercise. Ten moderately trained men performed ∼45 min cycling on one leg followed by 4 × 7 maximal knee extensions for each leg, 15 min later. Thus, one limb performed aerobic and resistance exercise (AE + RE) while the opposing leg did resistance exercise only (RE). Biopsies were obtained from the vastus lateralis muscle of each leg 3 h after the resistance exercise bout. Using DNA microarray, we analyzed differences [≥1.5-fold, false discovery rate (FDR) ≤10%] in gene expression profiles for the two modes of exercise. There were 176 genes up (127)- or downregulated (49) by AE + RE compared with RE. Among the most significant differentially expressed genes were established markers for muscle growth and oxidative capacity, novel cytokines, transcription factors, and micro-RNAs (miRNAs). The most enriched functional categories were those linked to carbohydrate metabolism and transcriptional regulation. Upstream analysis revealed that vascular endothelial growth factor, cAMP-response element-binding protein, Tet methylcytosine dioxygenase, and mammalian target of rapamycin were regulators highly activated by AE + RE, whereas JnK, NF-κβ, MAPK, and several miRNAs were inhibited. Thus, aerobic exercise alters the skeletal muscle transcriptional signature of resistance exercise to initiate important gene programs promoting both myofiber growth and improved oxidative capacity. These results provide novel insight into human muscle adaptations to diverse exercise modes and offer the very first genomic basis explaining how aerobic exercise may augment, rather than compromise, muscle growth induced by resistance exercise.

SNPchiMp v.3: integrating and standardizing single nucleotide polymorphism data for livestock species

BACKGROUND

In recent years, the use of genomic information in livestock species for genetic improvement, association studies and many other fields has become routine. In order to accommodate different market requirements in terms of genotyping cost, manufacturers of single nucleotide polymorphism (SNP) arrays, private companies and international consortia have developed a large number of arrays with different content and different SNP density. The number of currently available SNP arrays differs among species: ranging from one for goats to more than ten for cattle, and the number of arrays available is increasing rapidly. However, there is limited or no effort to standardize and integrate array- specific (e.g. SNP IDs, allele coding) and species-specific (i.e. past and current assemblies) SNP information.

RESULTS

Here we present SNPchiMp v.3, a solution to these issues for the six major livestock species (cow, pig, horse, sheep, goat and chicken). Original data was collected directly from SNP array producers and specific international genome consortia, and stored in a MySQL database. The database was then linked to an open-access web tool and to public databases. SNPchiMp v.3 ensures fast access to the database (retrieving within/across SNP array data) and the possibility of annotating SNP array data in a user-friendly fashion.

CONCLUSIONS

This platform allows easy integration and standardization, and it is aimed at both industry and research. It also enables users to easily link the information available from the array producer with data in public databases, without the need of additional bioinformatics tools or pipelines. In recognition of the open-access use of Ensembl resources, SNPchiMp v.3 was officially credited as an Ensembl E!mpowered tool. Availability at http://bioinformatics.tecnoparco.org/SNPchimp.

Pigeons: A Novel GUI Software for Analysing and Parsing High Density Heterologous Oligonucleotide Microarray Probe Level Data

Genomic DNA-based probe selection by using high density oligonucleotide arrays has recently been applied to heterologous species (Xspecies). With the advent of this new approach, researchers are able to study the genome and transcriptome of a non-model or an underutilised crop species through current state-of-the-art microarray platforms. However, a software package with a graphical user interface (GUI) to analyse and parse the oligonucleotide probe pair level data is still lacking when an experiment is designed on the basis of this cross species approach. A novel computer program called Pigeons has been developed for customised array data analysis to allow the user to import and analyse Affymetrix GeneChip^® probe level data through XSpecies. One can determine empirical boundaries for removing poor probes based on genomic hybridisation of the test species to the Xspecies array, followed by making a species-specific Chip Description File (CDF) file for transcriptomics in the heterologous species, or Pigeons can be used to examine an experimental design to identify potential Single-Feature Polymorphisms (SFPs) at the DNA or RNA level. Pigeons is also focused around visualization and interactive analysis of the datasets. The software with its manual (the current release number version 1.2.1) is freely available at the website of the Nottingham Arabidopsis Stock Centre (NASC).

Differences and similarities in the transcriptional profile of peripheral whole blood in early and late-onset preeclampsia: insights into the molecular basis of the phenotype of preeclampsiaa

OBJECTIVE

Preeclampsia (PE) can be sub-divided into early- and late-onset phenotypes. The pathogenesis of these two phenotypes has not been elucidated. To gain insight into the mechanisms of disease, the transcriptional profiles of whole blood from women with early- and late-onset PE were examined.

METHODS

A cross-sectional study was conducted to include women with: i) early-onset PE (diagnosed prior to 34 weeks, n=25); ii) late-onset PE (after 34 weeks, n=47); and iii) uncomplicated pregnancy (n=61). Microarray analysis of mRNA expression in peripheral whole blood was undertaken using Affymetrix microarrays. Differential gene expression was evaluated using a moderated t-test (false discovery rate <0.1 and fold change >1.5), adjusting for maternal white blood cell count and gestational age. Validation by real-time qRT-PCR was performed in a larger sample size [early PE (n=31), late PE (n=72) and controls (n=99)] in all differentially expressed genes. Gene ontology analysis and pathway analysis were performed.

RESULTS

i) 43 and 28 genes were differentially expressed in early- and late-onset PE compared to the control group, respectively; ii) qRT-PCR confirmed the microarray results for early and late-onset PE in 77% (33/43) and 71% (20/28) of genes, respectively; iii) 20 genes that are involved in coagulation (SERPINI2), immune regulation (VSIG4, CD24), developmental process (H19) and inflammation (S100A10) were differentially expressed in early-onset PE alone. In contrast, only seven genes that encoded proteins involved in innate immunity (LTF, ELANE) and cell-to-cell recognition in the nervous system (CNTNAP3) were differentially expressed in late-onset PE alone. Thirteen genes that encode proteins involved in host defense (DEFA4, BPI, CTSG, LCN2), tight junctions in blood-brain barrier (EMP1) and liver regeneration (ECT2) were differentially expressed in both early- and late-onset PE.

CONCLUSION

Early- and late-onset PE are characterized by a common signature in the transcriptional profile of whole blood. A small set of genes were differentially regulated in early- and late-onset PE. Future studies of the biological function, expression timetable and protein expression of these genes may provide insight into the pathophysiology of PE.

Discrete signal transduction pathway utilization by a neuropeptide (PACAP) and a cytokine (TNF-alpha) first messenger in chromaffin cells, inferred from coupled transcriptome-promoter analysis of regulated gene cohorts

Cultured bovine adrenal chromaffin cells (BCCs) are employed to study first messenger-specific signaling by cytokines and neurotransmitters occurring in the adrenal medulla following immune-related stress responses. Here, we show that the cytokine TNF-alpha, and the neuropeptide transmitter PACAP, acting through the TNFR2 and PAC1 receptors, activate distinct signaling pathways, with correspondingly distinct transcriptomic signatures in chromaffin cells. We have carried out a comprehensive integrated transcriptome analysis of TNF-alpha and PACAP gene regulation in BCCs using two microarray platforms to maximize transcript identification. Microarray data were validated using qRT-PCR. More than 90% of the transcripts up-regulated either by TNF-alpha or PACAP were specific to a single first messenger. The final list of transcripts induced by each first messenger was subjected to multiple algorithms to identify promoter/enhancer response elements for trans-acting factors whose activation could account for gene expression by either TNF-alpha or PACAP. Distinct groups of transcription factors potentially controlling the expression of TNF-alpha or PACAP-responsive genes were found: most of the genes up-regulated by TNF-alpha contained transcription factor binding sites for members of the Rel transcription factor family, suggesting TNF-alpha-TNFR2 signaling occurs mainly through the NF-KB signaling pathway. Surprisingly, EGR1 was predicted to be the primary transcription factor controlling PACAP-modulated genes, suggesting PACAP signaling to the nucleus occurs predominantly through ERK, rather than CREB activation. Comparison of TNFR2-dependent versus TNFR1-dependent gene induction, and EGR1-mediated transcriptional activation, may provide a pharmacological avenue to the unique pathways activated by the first messengers TNF-alpha and PACAP in neuronal and endocrine cells.

Exon array data analysis using Affymetrix power tools and R statistical software

The use of microarray technology to measure gene expression on a genome-wide scale has been well established for more than a decade. Methods to process and analyse the vast quantity of expression data generated by a typical microarray experiment are similarly well-established. The Affymetrix Exon 1.0 ST array is a relatively new type of array, which has the capability to assess expression at the individual exon level. This allows a more comprehensive analysis of the transcriptome, and in particular enables the study of alternative splicing, a gene regulation mechanism important in both normal conditions and in diseases. Some aspects of exon array data analysis are shared with those for standard gene expression data but others present new challenges that have required development of novel tools. Here, I will introduce the exon array and present a detailed example tutorial for analysis of data generated using this platform.

Gene-chip studies of adipogenesis-regulated microRNAs in mouse primary adipocytes and human obesity

BACKGROUND

Adipose tissue abundance relies partly on the factors that regulate adipogenesis, i.e. proliferation and differentiation of adipocytes. While components of the transcriptional program that initiates adipogenesis is well-known, the importance of microRNAs in adipogenesis is less well studied. We thus set out to investigate whether miRNAs would be actively modulated during adipogenesis and obesity.

METHODS

Several models exist to study adipogenesis in vitro, of which the cell line 3T3-L1 is the most well known, albeit not the most physiologically appropriate. Thus, as an alternative, we produced EXIQON microarray of brown and white primary murine adipocytes (prior to and following differentiation) to yield global profiles of miRNAs.

RESULTS

We found 65 miRNAs regulated during in vitro adipogenesis in primary adipocytes. We evaluated the similarity of our responses to those found in non-primary cell models, through literature data-mining. When comparing primary adipocyte profiles, with those of cell lines reported in the literature, we found a high degree of difference in 'adipogenesis' regulated miRNAs suggesting that the model systems may not be accurately representing adipogenesis. The expression of 10 adipogenesis-regulated miRNAs were studied using real-time qPCR and then we selected 5 miRNAs, that showed robust expression, were profiled in subcutaneous adipose tissue obtained from 20 humans with a range of body mass indices (BMI, range = 21-48, and all samples have U133+2 Affymetrix profiles provided). Of the miRNAs tested, mir-21 was robustly expressed in human adipose tissue and positively correlated with BMI (R2 = 0.49, p < 0.001).

CONCLUSION

In conclusion, we provide a preliminary analysis of miRNAs associated with primary cell in vitro adipogenesis and demonstrate that the inflammation-associated miRNA, mir-21 is up-regulated in subcutaneous adipose tissue in human obesity. Further, we provide a novel transcriptomics database of EXIQON and Affymetrix adipocyte profiles to facilitate data mining.

Genome-wide expression analysis of intra- and extraarticular connective tissue

In comparison to extraarticular ligaments and tendons, the intraarticular ligaments such as the anterior and posterior cruciates exhibit different biochemical, biomechanical, and viscoelastic properties and most importantly, differential abilities to heal after surgical repair. Little is known about the underlying basis for these differences, in large measure due to the paucity of molecular markers distinguishing different classes of tendons and ligaments. To date, there has been no systematic analysis of gene expression differences between different types of connective tissues. We used Affymetrix expression arrays to analyze the differences in gene expression levels between the anterior cruciate, posterior cruciate, and medial collateral ligaments, the patellar and Achilles tendons and the synovium. We have identified five clusters of gene cohorts displaying similar expression patterns. These clusters group into three categories including: (1) genes that are strongly expressed in all connective tissues compared to the synovium control tissue; (2) genes that distinguish intraarticular connective tissues from extraarticular connective tissues; and (3) a group of genes expressed in common by the patellar tendon and the synovium. Our analysis identifies a new marker of tendons and ligaments (fibin2), demonstrates molecular diversity between subtypes of tendons and ligaments, and indicates that the primary molecular subdivision among dense regular connective tissues is intra- versus extraarticular rather than ligament versus tendon.

A roadmap for zinc trafficking in the developing barley grain based on laser capture microdissection and gene expression profiling

Nutrients destined for the developing cereal grain encounter several restricting barriers on their path towards their final storage sites in the grain. In order to identify transporters and chelating agents that may be involved in transport and deposition of zinc in the barley grain, expression profiles have been generated of four different tissue types: the transfer cells, the aleurone layer, the endosperm, and the embryo. Cells from these tissues were isolated with the 'laser capture microdissection' technology and the extracted RNA was subjected to three rounds of T7-based amplification. The amplified RNA was subsequently hybridized to Affymetrix 22K Barley GeneChips. Due to the short average length of the amplified transcripts and the positioning of numerous probe sets at locations more than 400 base pairs (bp) from the poly(A)-tail, a normalization approach was used where the probe positions were taken into account. On the basis of the expression levels of a number of metal homeostasis genes, a working model is proposed for the translocation of zinc from the phloem to the storage sites in the developing grain.

Co-ordinated expression of amino acid metabolism in response to N and S deficiency during wheat grain filling

Increasing demands for productivity together with environmental concerns about fertilizer use dictate that the future sustainability of agricultural systems will depend on improving fertilizer use efficiency. Characterization of the biological processes responsible for efficient fertilizer use will provide tools for crop improvement under reduced inputs. Transcriptomic and metabolomic approaches were used to study the impact of nitrogen (N) and sulphur (S) deficiency on N and S remobilization from senescing canopy tissues during grain filling in winter wheat (Triticum aestivum). Canopy tissue N was remobilized effectively to the grain after anthesis. S was less readily remobilized. Nuclear magnetic resonance (NMR) metabolite profiling revealed significant effects of suboptimal N or S supply in leaves but not in developing grain. Analysis of amino acid pools in the grain and leaves revealed a strategy whereby amino acid biosynthesis switches to the production of glutamine during grain filling. Glutamine accumulated in the first 7 d of grain development, prior to conversion to other amino acids and protein in the subsequent 21 d. Transcriptome analysis indicated that a down-regulation of the terminal steps in many amino acid biosynthetic pathways occurs to control pools of amino acids during leaf senescence. Grain N and S contents increased in parallel after anthesis and were not significantly affected by S deficiency, despite a suboptimal N:S ratio at final harvest. N deficiency resulted in much slower accumulation of grain N and S and lower final concentrations, indicating that vegetative tissue N has a greater control of the timing and extent of nutrient remobilization than S.

The ABRF MARG microarray survey 2005: taking the pulse of the microarray field

Over the past several years, microarray technology has evolved into a critical component of any discovery-based program. Since 1999, the Association of Biomolecular Resource Facilities (ABRF) Microarray Research Group (MARG) has conducted biennial surveys designed to generate a profile of microarray service laboratories and, more importantly, an overview of technology development and implementation. Survey questions addressed instrumentation, protocols, staffing, funding, and work flow in a microarray facility. Presented herein are the results of the MARG 2005 survey; where possible, trends in the field are discussed and compared to data collected from previous surveys.

TAF4 inactivation in embryonic fibroblasts activates TGF beta signalling and autocrine growth

We have inactivated transcription factor TFIID subunit TBP-associated factor 4 (TAF4) in mouse embryonic fibroblasts. Mutant taf4(-/-) cells are viable and contain intact TFIID comprising the related TAF4b showing that TAF4 is not an essential protein. TAF4 inactivation deregulates more than 1000 genes indicating that TFIID complexes containing TAF4 and TAF4b have distinct target gene specificities. However, taf4(-/-) cell lines have altered morphology and exhibit serum-independent autocrine growth correlated with the induced expression of several secreted mitotic factors and activators of the transforming growth factor beta signalling pathway. In addition to TAF4 inactivation, many of these genes can also be induced by overexpression of TAF4b. A competitive equilibrium between TAF4 and TAF4b therefore regulates expression of genes controlling cell proliferation. We have further identified a set of genes that are regulated both by TAF4 and upon adaptation to serum starvation and which may be important downstream mediators of serum-independent growth. Our study also shows that TAF4 is an essential cofactor for activation by the retinoic acid receptor and CREB, but not for Sp1 and the vitamin D3 receptor.

Discovery of novel biomarkers by microarray analysis of peripheral blood mononuclear cell gene expression in benzene-exposed workers

Benzene is an industrial chemical and component of gasoline that is an established cause of leukemia. To better understand the risk benzene poses, we examined the effect of benzene exposure on peripheral blood mononuclear cell (PBMC) gene expression in a population of shoe-factory workers with well-characterized occupational exposures using microarrays and real-time polymerase chain reaction (PCR). PBMC RNA was stabilized in the field and analyzed using a comprehensive human array, the U133A/B Affymetrix GeneChip set. A matched analysis of six exposed-control pairs was performed. A combination of robust multiarray analysis and ordering of genes using paired t-statistics, along with bootstrapping to control for a 5% familywise error rate, was used to identify differentially expressed genes in a global analysis. This resulted in a set of 29 known genes being identified that were highly likely to be differentially expressed. We also repeated these analyses on a smaller subset of 508 cytokine probe sets and found that the expression of 19 known cytokine genes was significantly different between the exposed and the control subjects. Six genes were selected for confirmation by real-time PCR, and of these, CXCL16, ZNF331, JUN, and PF4 were the most significantly affected by benzene exposure, a finding that was confirmed in a larger data set from 28 subjects. The altered expression was not caused by changes in the makeup of the PBMC fraction. Thus, microarray analysis along with real-time PCR confirmation reveals that altered expressions of CXCL16, ZNF331, JUN, and PF4 are potential biomarkers of benzene exposure.

A comparison of cDNA, oligonucleotide, and Affymetrix GeneChip gene expression microarray platforms

We have conducted a study to compare the variability in measured gene expression levels associated with three types of microarray platforms. Total RNA samples were obtained from liver tissue of four male mice, two each from inbred strains A/J and C57BL/6J. The same four samples were assayed on Affymetrix Mouse Genome Expression Set 430 GeneChips (MOE430A and MOE430B), spotted cDNA microarrays, and spotted oligonucleotide microarrays using eight arrays of each type. Variances associated with measurement error were observed to be comparable across all microarray platforms. The MOE430A GeneChips and cDNA arrays had higher precision across technical replicates than the MOE430B GeneChips and oligonucleotide arrays. The Affymetrix platform showed the greatest range in the magnitude of expression levels followed by the oligonucleotide arrays. We observed good concordance in both estimated expression level and statistical significance of common genes between the Affymetrix MOE430A GeneChip and the oligonucleotide arrays. Despite their apparently high precision, cDNA arrays showed poor concordance with other platforms.

Development and production of an oligonucleotide MuscleChip: use for validation of ambiguous ESTs

BACKGROUND

We describe the development, validation, and use of a highly redundant 120,000 oligonucleotide microarray (MuscleChip) containing 4,601 probe sets representing 1,150 known genes expressed in muscle and 2,075 EST clusters from a non-normalized subtracted muscle EST sequencing project (28,074 EST sequences). This set included 369 novel EST clusters showing no match to previously characterized proteins in any database. Each probe set was designed to contain 20-32 25 mer oligonucleotides (10-16 paired perfect match and mismatch probe pairs per gene), with each probe evaluated for hybridization kinetics (Tm) and similarity to other sequences. The 120,000 oligonucleotides were synthesized by photolithography and light-activated chemistry on each microarray.

RESULTS

Hybridization of human muscle cRNAs to this MuscleChip (33 samples) showed a correlation of 0.6 between the number of ESTs sequenced in each cluster and hybridization intensity. Out of 369 novel EST clusters not showing any similarity to previously characterized proteins, we focused on 250 EST clusters that were represented by robust probe sets on the MuscleChip fulfilling all stringent rules. 102 (41%) were found to be consistently "present" by analysis of hybridization to human muscle RNA, of which 40 ESTs (39%) could be genome anchored to potential transcription units in the human genome sequence. 19 ESTs of the 40 ESTs were furthermore computer-predicted as exons by one or more than three gene identification algorithms.

CONCLUSION

Our analysis found 40 transcriptionally validated, genome-anchored novel EST clusters to be expressed in human muscle. As most of these ESTs were low copy clusters (duplex and triplex) in the original 28,000 EST project, the identification of these as significantly expressed is a robust validation of the transcript units that permits subsequent focus on the novel proteins encoded by these genes.