DEEPOMICS FFPE, a deep neural network model, identifies DNA sequencing artifacts from formalin fixed paraffin embedded tissue with high accuracy.

Formalin-fixed, paraffin-embedded (FFPE) tissue specimens are routinely used in pathological diagnosis, but their large number of artifactual mutations complicate the evaluation of companion diagnostics and analysis of next-generation sequencing data. Identification of variants with low allele frequencies is challenging because existing FFPE filtering tools label all low-frequency variants as artifacts. To address this problem, we aimed to develop DEEPOMICS FFPE, an AI model that can classify a true variant from an artifact. Paired whole exome sequencing data from fresh frozen and FFPE samples from 24 tumors were obtained from public sources and used as training and validation sets at a ratio of 7:3. A deep neural network model with three hidden layers was trained with input features using outputs of the MuTect2 caller. Contributing features were identified using the SHapley Additive exPlanations algorithm and optimized based on training results. The performance of the final model (DEEPOMICS FFPE) was compared with those of existing models (MuTect filter, FFPolish, and SOBDetector) by using well-defined test datasets. We found 41 discriminating properties for FFPE artifacts. Optimization of property quantification improved the model performance. DEEPOMICS FFPE removed 99.6% of artifacts while maintaining 87.1% of true variants, with an F1-score of 88.3 in the entire dataset not used for training, which is significantly higher than those of existing tools. Its performance was maintained even for low-allele-fraction variants with a specificity of 0.995, suggesting that it can be used to identify subclonal variants. Different from existing methods, DEEPOMICS FFPE identified most of the sequencing artifacts in the FFPE samples while retaining more of true variants, including those of low allele frequencies. The newly developed tool DEEPOMICS FFPE may be useful in designing capture panels for personalized circulating tumor DNA assay and identifying candidate neoepitopes for personalized vaccine design. DEEPOMICS FFPE is freely available on the web ( http://deepomics.co.kr/ffpe ) for research.

Integrative Analysis of Gene Expression Data by RNA Sequencing for Differential Diagnosis of Acute Leukemia: Potential Application of Machine Learning.

BCR-ABL1-positive acute leukemia can be classified into three disease categories: B-lymphoblastic leukemia (B-ALL), acute myeloid leukemia (AML), and mixed-phenotype acute leukemia (MPAL). We conducted an integrative analysis of RNA sequencing (RNA-seq) data obtained from 12 BCR-ABL1-positive B-ALL, AML, and MPAL samples to evaluate its diagnostic utility. RNA-seq facilitated the identification of all p190 BCR-ABL1 with accurate splicing sites and a new gene fusion involving MAP2K2. Most of the clinically significant mutations were also identified including single-nucleotide variations, insertions, and deletions. In addition, RNA-seq yielded differential gene expression profile according to the disease category. Therefore, we selected 368 genes differentially expressed between AML and B-ALL and developed two differential diagnosis models based on the gene expression data using 1) scoring algorithm and 2) machine learning. Both models showed an excellent diagnostic accuracy not only for our 12 BCR-ABL1-positive cases but also for 427 public gene expression datasets from acute leukemias regardless of specific genetic aberration. This is the first trial to develop models of differential diagnosis using RNA-seq, especially to evaluate the potential role of machine learning in identifying the disease category of acute leukemia. The integrative analysis of gene expression data by RNA-seq facilitates the accurate differential diagnosis of acute leukemia with successful detection of significant gene fusion and/or mutations, which warrants further investigation.

A novel system-level approach using RNA-sequencing data identifies miR-30-5p and miR-142a-5p as key regulators of apoptosis in myocardial infarction.

This study identified microRNAs involved in myocardial infarction (MI) through a novel system-level approach using RNA sequencing data in an MI mouse model. This approach involved the extraction of DEGs and DEmiRs from RNA-seq data in sham and MI samples and the subsequent selection of two miRNAs: miR-30-5p (family) and miR-142a-5p, which were downregulated and upregulated in MI, respectively. Gene Set Enrichment Analysis (GSEA) using the predicted targets of the two miRNAs suggested that apoptosis is an essential gene ontology (GO)-associated term. In vitro functional assays using neonatal rat ventricular myocytes (NRVMs) demonstrated that miR-30-5p is anti-apoptotic and miR-142a-5p is pro-apoptotic. Luciferase assays showed that the apoptotic genes, Picalm and Skil, and the anti-apoptotic genes, Ghr and Kitl, are direct targets of miR-30-5p and miR-142a-5p, respectively. siRNA studies verified the results of the luciferase assays for target validation. The results of the system-level high throughput approach identified a pair of functionally antagonistic miRNAs and their targets in MI. This study provides an in-depth analysis of the role of miRNAs in the pathogenesis of MI which could lead to the development of therapeutic tools. The system-level approach could be used to identify miRNAs involved in variety of other diseases.

Pathway profiles based on gene-set enrichment analysis in the honey bee Apis mellifera under brood rearing-suppressed conditions.

Perturbation of normal behaviors in honey bee colonies by any external factor can immediately reduce the colony's capacity for brood rearing, which can eventually lead to colony collapse. To investigate the effects of brood-rearing suppression on the biology of honey bee workers, gene-set enrichment analysis of the transcriptomes of worker bees with or without suppressed brood rearing was performed. When brood rearing was suppressed, pathways associated with both protein degradation and synthesis were simultaneously over-represented in both nurses and foragers, and their overall pathway representation profiles resembled those of normal foragers and nurses, respectively. Thus, obstruction of normal labor induced over-representation in pathways related with reshaping of worker bee physiology, suggesting that transition of labor is physiologically reversible. In addition, some genes associated with the regulation of neuronal excitability, cellular and nutritional stress and aggressiveness were over-expressed under brood rearing suppression perhaps to manage in-hive stress under unfavorable conditions.

Pan-cancer analysis of systematic batch effects on somatic sequence variations.

BACKGROUND: The Cancer Genome Atlas (TCGA) is a comprehensive database that includes multi-layered cancer genome profiles. Large-scale collection of data inevitably generates batch effects introduced by differences in processing at various stages from sample collection to data generation. However, batch effects on the sequence variation and its characteristics have not been studied extensively. RESULTS: We systematically evaluated batch effects on somatic sequence variations in pan-cancer TCGA data, revealing 999 somatic variants that were batch-biased with statistical significance (P < 0.00001, Fisher's exact test, false discovery rate ≤ 0.0027). Most of the batch-biased variants were associated with specific sample plates. The batch-biased variants, which had a unique mutational spectrum with frequent indel-type mutations, preferentially occurred at sites prone to sequencing errors, e.g., in long homopolymer runs. Non-indel type batch-biased variants were frequent at splicing sites with the unique consensus motif sequence 'TTDTTTAGTT'. Furthermore, some batch-biased variants occur in known cancer genes, potentially causing misinterpretation of mutation profiles. CONCLUSIONS: Our strategy for identifying batch-biased variants and characterising sequence patterns might be useful in eliminating false variants and facilitating correct interpretation of sequence profiles.

Deep sequencing-generated modules demonstrate coherent expression patterns for various cardiac diseases.

As sequencing technology rapidly develops, gene annotations have also become increasingly sophisticated with incorporation of information regarding the temporal-spatial context of alternative splicing patterns, developmental stages, and tissue specificity. The present study aimed to identify the heart-enriched genes based on next-generation sequencing data and to investigate the gene modules demonstrating coherent expression patterns for various cardiac disease-related perturbations. Seven gene modules, including 382 heart-enriched genes, were identified. At least two modules containing differentially expressed genes were experimentally confirmed to be highly sensitive to various cardiac diseases. Transcription factors regulating the gene modules were then analyzed based on knowledgebase information; the expression of eight transcription factors changed significantly during pressure-overload cardiac hypertrophy, suggesting possible regulation of the modules by the identified transcription factors. Collectively, our results contribute to the classification of heart-enriched genes and their modules and would aid in identification of the transcription factors involved in cardiac pathogenesis in the future.

miR-185 plays an anti-hypertrophic role in the heart via multiple targets in the calcium-signaling pathways.

MicroRNA (miRNA) is an endogenous non-coding RNA species that either inhibits RNA translation or promotes degradation of target mRNAs. miRNAs often regulate cellular signaling by targeting multiple genes within the pathways. In the present study, using Gene Set Analysis, a useful bioinformatics tool to identify miRNAs with multiple target genes in the same pathways, we identified miR-185 as a key candidate regulator of cardiac hypertrophy. Using a mouse model, we found that miR-185 was significantly down-regulated in myocardial cells during cardiac hypertrophy induced by transverse aortic constriction. To confirm that miR-185 is an anti-hypertrophic miRNA, genetic manipulation studies such as overexpression and knock-down of miR-185 in neonatal rat ventricular myocytes were conducted. The results showed that up-regulation of miR-185 led to anti-hypertrophic effects, while down-regulation led to pro-hypertrophic effects, suggesting that miR-185 has an anti-hypertrophic role in the heart. Our study further identified Camk2d, Ncx1, and Nfatc3 as direct targets of miR-185. The activity of Nuclear Factor of Activated T-cell (NFAT) and calcium/calmodulin-dependent protein kinase II delta (CaMKIIδ) was negatively regulated by miR-185 as assessed by NFAT-luciferase activity and western blotting. The expression of phospho-phospholamban (Thr-17), a marker of CaMKIIδ activity, was also significantly reduced by miR-185. In conclusion, miR-185 effectively blocked cardiac hypertrophy signaling through multiple targets, rendering it a potential drug target for diseases such as heart failure.

Identification of tissue-enriched novel transcripts and novel exons in mice.

BACKGROUND: RNA sequencing (RNA-seq) has revolutionized the detection of transcriptomic signatures due to its high-throughput sequencing ability. Therefore, genomic annotations on different animal species have been rapidly updated using information from tissue-enriched novel transcripts and novel exons. RESULTS: 34 putative novel transcripts and 236 putative tissue-enriched exons were identified using RNA-Seq datasets representing six tissues available in mouse databases. RT-PCR results indicated that expression of 21 and 2 novel transcripts were enriched in testes and liver, respectively, while 31 of the 39 selected novel exons were detected in the testes or heart. The novel isoforms containing the identified novel exons exhibited more dominant expression than the known isoforms in heart and testes. We also identified an example of pathology-associated exclusion of heart-enriched novel exons such as Sorbs1 and Cluh during pressure-overload cardiac hypertrophy. CONCLUSION: The present study depicted tissue-enriched novel transcripts, a tissue-specific isoform switch, and pathology-associated alternative splicing in a mouse model, suggesting tissue-specific genomic diversity and plasticity.

Sumoylation regulates ER stress response by modulating calreticulin gene expression in XBP-1-dependent mode in Caenorhabditis elegans.

Excessive accumulation of unfolded proteins in the endoplasmic reticulum (ER) lumen causes ER stress, which induces a set of genes, including those encoding ER-resident chaperones, to relieve the detrimental effects and recover homeostasis. Calreticulin is a chaperone that facilitates protein folding in the ER lumen, and its gene expression is induced by ER stress in Caenorhabditis elegans. Sumoylation conjugates small ubiquitin-like modifier (SUMO) proteins with target proteins to regulate a variety of biological processes, such as protein stability, nuclear transport, DNA binding, and gene expression. In this study, we showed that C. elegans X-box-binding protein 1 (Ce-XBP-1), an ER stress response transcription factor, interacts with the SUMO-conjugating enzyme UBC-9 and a SUMOylation target. Our results indicated that abolishing sumoylation enhanced calreticulin expression in an XBP-1-dependent manner, and the resulting increase in calreticulin counteracted ER stress. Furthermore, sumoylation was repressed in C. elegans undergoing ER stress. Finally, RNAi against ubc-9 mainly affected the expression of genes associated with ER functions, such as lipid and organic acid metabolism. Our results suggest that sumoylation plays a regulatory role in ER function by controlling the expression of genes required for ER homeostasis in C. elegans.

Pressure-overload cardiac hypertrophy is associated with distinct alternative splicing due to altered expression of splicing factors.

Chronic pressure-overload cardiac hypertrophy is associated with an increased risk of morbidity/mortality, largely due to maladaptive remodeling and dilatation that progresses to dilated cardiomyopathy. Alternative splicing is an important biological mechanism that generates proteomic complexity and diversity. The recent development of next-generation RNA sequencing has improved our understanding of the qualitative signatures associated with alternative splicing in various biological conditions. However, the role of alternative splicing in cardiac hypertrophy is yet unknown. The present study employed RNA-Seq and a bioinformatic approach to detect the RNA splicing regulatory elements involved in alternative splicing during pressure-overload cardiac hypertrophy. We found GC-rich exonic motifs that regulate intron retention in 5' UTRs and AT-rich exonic motifs that are involved in exclusion of the AT-rich elements that cause mRNA instability in 3' UTRs. We also identified motifs in the intronic regions involved in exon exclusion and inclusion, which predicted splicing factors that bind to these motifs. We found, through Western blotting, that the expression levels of three splicing factors, ESRP1, PTB and SF2/ASF, were significantly altered during cardiac hypertrophy. Collectively, the present results suggest that chronic pressure-overload hypertrophy is closely associated with distinct alternative splicing due to altered expression of splicing factors.

Exon 9 skipping of apoptotic caspase-2 pre-mRNA is promoted by SRSF3 through interaction with exon 8.

Alternative splicing plays an important role in gene expression by producing different proteins from a gene. Caspase-2 pre-mRNA produces anti-apoptotic Casp-2S and pro-apoptotic Casp-2L proteins through exon 9 inclusion or skipping. However, the molecular mechanisms of exon 9 splicing are not well understood. Here we show that knockdown of SRSF3 (also known as SRp20) with siRNA induced significant increase of endogenous exon 9 inclusion. In addition, overexpression of SRSF3 promoted exon 9 skipping. Thus we conclude that SRSF3 promotes exon 9 skipping. In order to understand the functional target of SRSF3 on caspase-2 pre-mRNA, we performed substitution and deletion mutagenesis on the potential SRSF3 binding sites that were predicted from previous reports. We demonstrate that substitution mutagenesis of the potential SRSF3 binding site on exon 8 severely disrupted the effects of SRSF3 on exon 9 skipping. Furthermore, with the approach of RNA pulldown and immunoblotting analysis we show that SRSF3 interacts with the potential SRSF3 binding RNA sequence on exon 8 but not with the mutant RNA sequence. In addition, we show that a deletion of 26nt RNA from 5' end of exon 8, a 33nt RNA from 3' end of exon 10 and a 2225nt RNA from intron 9 did not compromise the function of SRSF3 on exon 9 splicing. Therefore we conclude that SRSF3 promotes exon 9 skipping of caspase-2 pre-mRNA by interacting with exon 8. Our results reveal a novel mechanism of caspase-2 pre-mRNA splicing.

SC35 promotes splicing of the C5-V6-C6 isoform of CD44 pre-mRNA.

CD44 is a cell membrane glycoprotein that mediates the response of cells to their cellular microenvironment and regulates growth, survival, differentiation and motility. CD44 pre-mRNA contains 20 exons, 10 of which are alternatively spliced. Among the CD44 spliced variants, one of the V6 exon-containing isoforms, the V4-7 variant which contains variable exons 4, 5, 6 and 7, confers metastatic potential to non-metastatic cells. However, the splicing regulation of the V6 exon is not completely understood. SC35 is an arginine-serine rich protein that regulates alternative splicing of various pre-mRNAs. In the present study, we established a stable cell line which indicates inclusion or skipping of the V6 exon with the RFP or GFP signal. Using this stable cell line, we found that the V6 exon and flanking introns of CD44 pre-mRNA contained SC35 response elements that regulate V6 splicing. RT-PCR analyses of the endogenous CD44 splicing showed that SC35 promotes the production of the C5-V6-C6 isoform. shRNA knockdown of SC35 showed that reduced expression of SC35 decreased expression of the V6 exon-containing isoforms. Our results reveal a novel mechanism of CD44V6 splicing.

Identification of the dichotomous role of age-related LCK in calorie restriction revealed by integrative analysis of cDNA microarray and interactome.

Among the many experimental paradigms used for the investigation of aging, the calorie restriction (CR) model has been proven to be the most useful in gerontological research. Exploration of the mechanisms underlying CR has produced a wealth of data. To identify key molecules controlled by aging and CR, we integrated data from 84 mouse and rat cDNA microarrays with a protein-protein interaction network. On the basis of this integrative analysis, we selected three genes that are upregulated in aging but downregulated by CR and two genes that are downregulated in aging but upregulated by CR. One of these key molecules is lymphocyte-specific protein tyrosine kinase (LCK). To further confirm this result on LCK, we performed a series of experiments in vitro and in vivo using kidneys obtained from aged ad libitum-fed and CR rats. Our major significant findings are as follows: (1) identification of LCK as a key molecule using integrative analysis; (2) confirmation that the age-related increase in LCK was modulated by CR and that protein tyrosine kinase activity was decreased using a LCK-specific inhibitor; and (3) upregulation of LCK leads to NF-κB activation in a ONOO(-) generation-dependent manner, which is modulated by CR. These results indicate that LCK could be considered a target attenuated by the anti-aging effects of CR. Integrative analysis of cDNA microarray and interactome data are powerful tools for identifying target molecules that are involved in the aging process and modulated by CR.

Deep RNA sequencing reveals novel cardiac transcriptomic signatures for physiological and pathological hypertrophy.

Although both physiological hypertrophy (PHH) and pathological hypertrophy (PAH) of the heart have similar morphological appearances, only PAH leads to fatal heart failure. In the present study, we used RNA sequencing (RNA-Seq) to determine the transcriptomic signatures for both PHH and PAH. Approximately 13-20 million reads were obtained for both models, among which PAH showed more differentially expressed genes (DEGs) (2,041) than PHH (245). The expression of 417 genes was barely detectable in the normal heart but was suddenly activated in PAH. Among them, Foxm1 and Plk1 are of particular interest, since Ingenuity Pathway Analysis (IPA) using DEGs and upstream motif analysis showed that they are essential hub proteins that regulate the expression of downstream proteins associated with PAH. Meanwhile, 52 genes related to collagen, chemokines, and actin showed opposite expression patterns between PHH and PAH. MAZ-binding motifs were enriched in the upstream region of the participating genes. Alternative splicing (AS) of exon variants was also examined using RNA-Seq data for PAH and PHH. We found 317 and 196 exon inclusions and exon exclusions, respectively, for PAH, and 242 and 172 exon inclusions and exclusions, respectively for PHH. The AS pattern was mostly related to gains or losses of domains, changes in activity, and localization of the encoded proteins. The splicing variants of 8 genes (i.e., Fhl1, Rcan1, Ndrg2, Synpo, Ttll1, Cxxc5, Egfl7, and Tmpo) were experimentally confirmed. Multilateral pathway analysis showed that the patterns of quantitative (DEG) and qualitative (AS) changes differ depending on the type of pathway in PAH and PHH. One of the most significant changes in PHH is the severe downregulation of autoimmune pathways accompanied by significant AS. These findings revealed the unique transcriptomic signatures of PAH and PHH and also provided a more comprehensive understanding at both the quantitative and qualitative levels.

Alteration of the transcriptional profile of human embryonic kidney cells by transient overexpression of mouse TRPM7 channels.

BACKGROUND: TRPM7 is a cation channel containing a functional kinase domain. The functional activity of TRPM7 is essential for cell viability and growth, and its expression is up-regulated in certain pathological conditions, such as ischemia. METHODS: In order to assess the effects of TRPM7 activity on cellular gene expression, inducible HEK293 cell-lines harboring the wild-type mouse TRPM7 and a mutant lacking the kinase domain were established. The wild-type and the non-functional TRPM7 channels were induced transiently and the comparative changes in cellular transcription were investigated. RESULTS: From the genome-scale analysis using a human genome expression microarray, we identified 951 genes altered in transcription significantly and specifically by the expression of the functional TRPM7 channel. CONCLUSION: By analyzing the genes differentially expressed by TRPM7, we were able to provide potential target proteins and to delineate the cellular pathways affected by the channel function.

Revealing system-level correlations between aging and calorie restriction using a mouse transcriptome.

Although systems biology is a perfect framework for investigating system-level declines during aging, only a few reports have focused on a comprehensive understanding of system-level changes in the context of aging systems. The present study aimed to understand the most sensitive biological systems affected during aging and to reveal the systems underlying the crosstalk between aging and the ability of calorie restriction (CR) to effectively slow-down aging. We collected and analyzed 478 aging- and 586 CR-related mouse genes. For the given genes, the biological systems that are significantly related to aging and CR were examined according to three aspects. First, a global characterization by Gene Ontology (GO) was performed, where we found that the transcriptome (a set of genes) for both aging and CR were strongly related in the immune response, lipid metabolism, and cell adhesion functions. Second, the transcriptional modularity found in aging and CR was evaluated by identifying possible functional modules, sets of genes that show consistent expression patterns. Our analyses using the given functional modules, revealed systemic interactions among various biological processes, as exemplified by the negative relation shown between lipid metabolism and the immune response at the system level. Third, transcriptional regulatory systems were predicted for both the aging and CR transcriptomes. Here, we suggest a systems biology framework to further understand the most important systems as they age.

Identification of mouse heart transcriptomic network sensitive to various heart diseases.

Exploring biological systems from highly complex datasets is an important task for systems biology. The present study examined co-expression dynamics of mouse heart transcriptome by spectral graph clustering (SGC) to identify a heart transcriptomic network. SGC of microarray data produced 17 classified biological conditions (called condition spectrum, CS) and co-expression patterns by generating bi-clusters. The results showed dynamic co-expression patterns with a modular structure enriched in heart-related CS (CS-1 and -13) containing abundant heart-related microarray data. Consequently, a mouse heart transcriptomic network was constructed by clique analysis from the gene clusters exclusively present in the heart-related CS; 31 cliques were used for constructing the network. The participating genes in the network were closely associated with important cardiac functions (e. g., development, lipid and glycogen metabolisms). Online Mendelian Inheritance in Man (OMIM) database indicates that mutations of the genes in the network induced serious heart diseases. Many of the tested genes in the network showed significantly altered gene expression in an animal model of hypertrophy. The results suggest that the present approach is critical for constructing a heart-related transcriptomic network and for deducing important genes involved in the pathogenesis of various heart diseases.

Comprehensive identification and characterization of novel cardiac genes in mouse.

Comprehensive understanding of the molecular and physiological events occurring in cardiac muscle requires identification of unknown genes expressed in this tissue. We analyzed the mouse cardiac muscle UniGene library containing 827 gene-oriented transcript clusters, predicting that 19% of these genes are unknown. We systematically identified 15 authentic novel genes abundantly expressed in cardiac muscle. Northern blot analysis revealed transcriptional characteristics of the genes, such as transcript size and presence of isoforms. Transfection assays performed using various cell lines including mouse cardiac muscle cells provided information on the cellular characteristics of the novel proteins. Using correlation analysis, we identified co-regulated genes from previously reported microarray data sets. Our in silico and in vitro data suggest that a number of the novel genes are implicated in calcium metabolism, mitochondrial functions and gene transcription. In particular, we obtained new and direct evidence that one of the novel proteins is a calcium-binding protein. Taken together, we identified and characterized a number of novel cardiac genes by integrative approach. Our inclusive data establish a firm basis for future investigation into the cardiac gene network and functions of these genes.

Gene profiling during regression of pressure overload-induced cardiac hypertrophy.

Regression of cardiac hypertrophy and improvement of the functional capacity of failing hearts have reportedly been achieved by mechanical unloading in cardiac work. In this study, cardiac hypertrophy was first induced in rats by transverse aortic constriction and then mechanically unloaded by relieving the constriction after significant cardiac hypertrophy had developed. Hypertrophy was significantly regressed at the cellular and molecular levels at day 1, 3, and 7 after constriction relief. Gene profiling analysis revealed that 52 genes out of 9,911 genes probed on a gene array were specifically upregulated during the early regression period. Among these regression-induced genes, Eyes absent 2 (eya2) was of particular interest because it is a transcriptional cofactor involved in mammalian organogenesis as well as Drosophila eye development. Adenovirus-mediated overexpression of eya2 in rat neonatal cardiomyocytes completely abrogated phenylephrine-induced development of cardiomyocyte hypertrophy as determined by cell size, sarcomere rearrangement and fetal gene re-expression. Our data strongly suggest that transcriptional programs distinct from those mediating cardiac hypertrophy may be operating during the regression of hypertrophy, and eya2 may be a key regulator of one of these programs.

HCNet: a database of heart and calcium functional network.

SUMMARY: The Heart and Calcium functional Network (HCNet) database is a collection of functional gene modules calculated from the microarray data compendium available from the GEO database. It is a specialized database designed to assist experimentalists for cardiac calcium signaling research by providing the pre-calculated gene clusters and their potential correlation network in heart. In the current release of HCNet, 57 functional modules from 786 target genes obtained by a bi-clustering analysis of 381 microarray datasets are available. Detailed information of the clusters such as expression profiles, network diagrams is provided in two categories, heart-specific genes and heart-specific genes along with calcium toolkit genes. Overrepresented gene ontological categories and transcription factors in each cluster are also provided to infer the biological implications of the detected functional modules. AVAILABILITY: HCNet is available at http://sbrg2.gist.ac.kr/hcnet.