Search

Morphologic and molecular data often lead to different hypotheses of phylogenetic relationships. Such incongruence has been found in the echinoderm class Echinoidea. In particular, the phylogenetic status of the order Clypeasteroida is not well resolved. Complete mitochondrial genomes are currently available for 29 echinoid species, but no clypeasteroid had been sequenced to date. DNA extracted from a single live individual of Sinaechinocyamus mai was sequenced with 10× Genomics technology. This first complete mitochondrial genome (mitogenome) for the order Clypeasteroida is 15,756 base pairs in length. Phylogenomic analysis based on 34 ingroup taxa belonging to nine orders of the class Echinoidea show congruence between our new genetic inference and published trees based on morphologic characters, but also includes some intriguing differences that imply the need for additional investigation.

Whole-genome doubling (WGD) is an early macro-evolutionary event in tumorigenesis, involving the doubling of an entire chromosome complement. However, its impact on breast cancer subtypes remains unclear. Here, we performed a comprehensive and quantitative analysis of WGD and its influence on breast cancer subtypes in patients from Taiwan and consequently highlight the genomic association between WGD and homologous recombination deficiency (HRD). A higher manifestation of WGD was reported in triple-negative breast cancer, conferring high chromosomal instability (CIN), while HER2 + tumors exhibited early WGD events, with widely varied CIN levels, compared to luminal-type tumors. An association of higher activity of de novo indel signature 2 with WGD and HRD in Taiwanese breast cancer patients was reported. A control test between WGD and pseudo non-WGD samples was further employed to support this finding. The study provides a better comprehension of tumorigenesis in breast cancer subtypes, thus assisting in personalized treatment. Wu, Hsieh et al. analyze Taiwanese breast cancer patient samples using whole-exome sequencing to examine the heterogeneity and homogeneity in the timing and dependencies of somatic aberrations across disease subtypes. The authors focus on somatic alterations and related features that correlate with whole genome doubling, including homologous recombination deficiencies.

Background Histology is a traditional way to classify subtypes of thymoma, because of low cost and convenience. Yet, due to the diverse morphology of thymoma, this method increases the complexity of histopathologic classification, and requires experienced experts to perform correct diagnosis. Therefore, in this study, we developed an alternative method by identifying protein biomarkers in order to assist clinical practitioners to make right classification of thymoma subtypes. Methods In total, 204 differentially expressed proteins in three subtypes of thymoma, AB, B2, and B3, were identified using mass spectrometry. Pathway analysis showed that the differentially expressed proteins in the three subtypes were involved in activation-related, signaling transduction-related and complement system-related pathways. To predict the subtypes of thymoma using the identified protein signatures, a support vector machine algorithm was used. Leave-one-out cross validation methods and receiver operating characteristic analysis were used to evaluate the predictive performance. Results The mean accuracy rates were > 80% and areas under the curve were ≧0.93 across these three subtypes. Especially, subtype B3 had the highest accuracy rate (96%) and subtype AB had the greatest area under the curve (0.99). One of the differentially expressed proteins COL17A2 was further validated using immunohistochemistry. Conclusions In summary, we identified specific protein signatures for accurately classifying subtypes of thymoma, which could facilitate accurate diagnosis of thymoma patients.

International audience; The use of phylogeny with uneven or limited taxon sampling may bias our interpretation of organismal evolution, for instance, the origin(s) of the deep-sea animals. The Mollusca is the second most speciose phylum, in which the Gastropoda forms the largest group. However, the currently proposed hypotheses of gastropod phylogeny are mainly based on part of their taxonomic diversity, notably on the large-sized and shallow-water species. In this study, we aimed at correcting this bias by reconstructing the phylogeny with new mitogenomes of deep-sea gastropods including Anatoma sp., Bathysciadiidae sp., Bayerotrochus teramachii, Calliotropis micraulax, Coccocrater sp., Cocculina subcompressa, Lepetodrilus guaymasensis, Peltospira smaragdina, Perotrochus caledonicus, Pseudococculinidae sp., and Shinkailepas briandi. This dataset provided the first reports of the mitogenomes for the Cocculiniformia, three vetigastropod superfamilies: Pleurotomarioidea, Lepetelloidea, and Scissurelloidea, and the neritimorph family Phenacolepadidae. The addition of deep-sea representatives also allowed us to evaluate the evolution of habitat use in gastropods. Our results showed a strongly supported sister-group relationship between the deep-sea lineages Cocculiniformia and Neomphalina. Within the Vetigastropoda, the Pleurotomarioidea was revealed as the sister-group of the remaining vetigastropods. Although this clade was presently restricted to the deep sea, fossil records showed that it has only recently invaded this habitat, thus suggesting that shallow waters was the ancestral habitat for the Vetigastropoda. The deep-sea Lepetelloidea and Lepetodriloidea formed a well-supported clade, with the Scissurelloidea sister to it, suggesting an early transition from shallow water to deep sea in this lineage. In addition, the switch between different chemosynthetic habitats was also observed in deep-sea gastropod lineages, notably in Neomphalina and Lepetelloidea. In both cases, the biogenic substrates appeared as the putative ancestral habitat, confirming the previously proposed hypothesis of a wooden-step to deep-sea vents scenario of evolution of habitat use for these taxa.

Precision epidemiology using genomic technologies allows for a more targeted approach to COVID-19 control and treatment at individual and population level, and is the urgent need of the day. It enables identification of patients who may be at higher risk than others to COVID-19-related mortality, due to their genetic architecture, or who might respond better to a COVID-19 treatment. The COVID-19 virus, similar to SARS-CoV, uses the ACE2 receptor for cell entry and employs the cellular serine protease TMPRSS2 for viral S protein priming. This study aspires to present a multi-omics view of how variations in the ACE2 and TMPRSS2 genes affect COVID-19 infection and disease progression in affected individuals. It reports, for both genes, several variant and gene expression analysis findings, through (i) comparison analysis over single nucleotide polymorphisms (SNPs), that may account for the difference of COVID-19 manifestations among global sub-populations; (ii) calculating prevalence of structural variations (copy number variations (CNVs) / insertions), amongst populations; and (iii) studying expression patterns stratified by gender and age, over all human tissues. This work is a good first step to be followed by additional studies and functional assays towards informed treatment decisions and improved control of the infection rate.

RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few R/Bioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source R/Bioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include: six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both R/Bioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (https://bioconductor.org/packages/release/bioc/html/RNASeqR.html)., Comment: 10 pages, 5 figures

Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs (MIR181B1 and MIR103A1) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3, may be mania state-specific markers. Additionally, four genes showed a nominal p-value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14, PYHIN1, UTRN, and DMXL2, and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine-cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness.

Disseminated castration-resistant prostate cancer (CRPC) is a common disease in men that is characterized by limited survival and resistance to androgen-deprivation therapy. The increase in human epidermal growth factor receptor 2 (HER2) signaling contributes to androgen receptor activity in a subset of patients with CRPC; however, enigmatically, HER2-targeted therapies have demonstrated a lack of efficacy in patients with CRPC. Aberrant glycosylation is a hallmark of cancer and involves key processes that support cancer progression. Using transcriptomic analysis of prostate cancer data sets, histopathologic examination of clinical specimens, and in vivo experiments of xenograft models, we reveal in this study a coordinated increase in glycan-binding protein, galectin-4, specific glycosyltransferases of core 1 synthase, glycoprotein- N-acetylgalactosamine 3-β-galactosyltransferase 1 (C1GALT1) and ST3 beta-galactoside α-2,3-sialyltransferase 1 (ST3GAL1), and resulting mucin-type O-glycans during the progression of CRPC. Furthermore, galectin-4 engaged with C1GALT1-dependent O-glycans to promote castration resistance and metastasis by activating receptor tyrosine kinase signaling and cancer cell stemness properties mediated by SRY-box 9 (SOX9). This galectin-glycan interaction up-regulated the MYC-dependent expression of C1GALT1 and ST3GAL1, which altered cellular mucin-type O-glycosylation to allow for galectin-4 binding. In clinical prostate cancer, high-level expression of C1GALT1 and galectin-4 together predict poor overall survival compared with low-level expression of C1GALT1 and galectin-4. In summary, MYC regulates abnormal O-glycosylation, thus priming cells for binding to galectin-4 and downstream signaling, which promotes castration resistance and metastasis.-Tzeng, S.-F., Tsai, C.-H., Chao, T.-K., Chou, Y.-C., Yang, Y.-C., Tsai, M.-H., Cha, T.-L., Hsiao, P.-W. O-Glycosylation-mediated signaling circuit drives metastatic castration-resistant prostate cancer.

Distinct microRNA (miRNA) and mRNA signatures were reported in nucleophosmin (NPM1)-mutated acute myeloid leukemia (AML). However, it remains unknown whether the mutation participates in the dynamic interaction between miRNA and mRNA. In this study, we aimed to investigate the role of NPM1 mutation in modulating miRNA-mRNA regulation (MMR). From the sample-paired miRNA/mRNA microarrays of 181 de novo AML patients, we found that MMR was dynamic and could be affected by NPM1 mutation. By a systematic framework, we identified 493 NPM1 mutation-modulated MMR pairs, where the strength of MMR was significantly attenuated in patients carrying NPM1 mutations, compared to those with wild-type NPM1. These miRNAs/mRNAs were associated with pathways implicated in cancer and known functions of NPM1 mutation. Such modulation of MMR was validated in two independent cohorts as well as in cells with different NPM1 mutant burdens. Furthermore, we showed that the regulatory strength of nine MMR pairs could predict patients' outcomes. Combining these pairs, a scoring system was proposed and shown to predict survival in discovery and validation data sets, independent of other known prognostic factors. Our study provides novel biological insights into the role of NPM1 mutation as a modulator of MMR, based on which a novel prognostic marker is proposed in AML.

Lung adenocarcinoma possesses distinct patterns of EGFR/KRAS mutations between East Asian and Western, male and female patients. However, beyond the well-known EGFR/KRAS distinction, gender and ethnic specific molecular aberrations and their effects on prognosis remain largely unexplored. Association modules capture the dependency of an effector molecular aberration and target gene expressions. We established association modules from the copy number variation (CNV), DNA methylation and mRNA expression data of a Taiwanese female cohort. The inferred modules were validated in four external datasets of East Asian and Caucasian patients by examining the coherence of the target gene expressions and their associations with prognostic outcomes. Modules 1 (cis-acting effects with chromosome 7 CNV) and 3 (DNA methylations of UBIAD1 and VAV1) possessed significantly negative associations with survival times among two East Asian patient cohorts. Module 2 (cis-acting effects with chromosome 18 CNV) possessed significantly negative associations with survival times among the East Asian female subpopulation alone. By examining the genomic locations and functions of the target genes, we identified several putative effectors of the two cis-acting CNV modules: RAC1, EGFR, CDK5 and RALBP1. Furthermore, module 3 targets were enriched with genes involved in cell proliferation and division and hence were consistent with the negative associations with survival times. We demonstrated that association modules in lung adenocarcinoma with significant links of prognostic outcomes were ethnic and/or gender specific. This discovery has profound implications in diagnosis and treatment of lung adenocarcinoma and echoes the fundamental principles of the personalized medicine paradigm.

Small RNAs (sRNAs) play important roles in plants under stress conditions. However, limited research has been performed on the sRNAs involved in plant wound responses. In the present study, a novel wounding-induced sRNA, sRNA8105, was identified in sweet potato (Ipomoea batatas cv. Tainung 57) using microarray analysis. It was found that expression of sRNA8105 increased after mechanical wounding. Furthermore, Dicer-like 1 (DCL1) is required for the sRNA8105 precursor (pre-sRNA8105) to generate 22 and 24 nt mature sRNA8105. sRNA8105 targeted the first intron of IbMYB1 (MYB domain protein 1) before RNA splicing, and mediated RNA cleavage and DNA methylation of IbMYB1. The interaction between sRNA8105 and IbMYB1 was confirmed by cleavage site mapping, agro-infiltration analyses, and use of a transgenic sweet potato over-expressing pre-sRNA8105 gene. Induction of IbMYB1-siRNA was observed in the wild-type upon wounding and in transgenic sweet potato over-expressing pre-sRNA8105 gene without wounding, resulting in decreased expression of the whole IbMYB1 gene family, i.e. IbMYB1 and the IbMYB2 genes, and thus directing metabolic flux toward biosynthesis of lignin in the phenylpropanoid pathway. In conclusion, sRNA8105 induced by wounding binds to the first intron of IbMYB1 RNA to methylate IbMYB1, cleave IbMYB1 RNA, and trigger production of secondary siRNAs, further repressing the expression of the IbMYB1 family genes and regulating the phenylpropanoid pathway.

Microarray transcriptome study in cancer has been commonly used to investigate tumorigenic mechanisms. The unique growth pattern of spontaneous regression (SR) after progressive (P) growth in canine transmissible venereal tumor (CTVT) provides a valuable cancer model to study the genome-wide differences in samples between the two stages of growth. In this study, Affymetrix analysis was performed based on the canine genome to compare the gene expression profiles of CTVT P- and SR-phase tumors. A total of 459 (278 up-regulated and 181 down-regulated) genes were identified as being differentially-expressed during the SR phase by the 2-fold method. Further analysis of these genes revealed that the expression of three genes associated with IL-6 production -TIMD-4, GPNMB and PLTP - was significantly higher in SR-phase tumors than in P-phase tumors; these results were also confirmed by real time RT-PCR in tumor tissues of beagles. In addition, we found that Th17-related genes were over-expressed in the SR phase, suggesting autoimmune responses involvement in tumor regression. Although the interaction between CTVT and host immunity were partially investigated in previous studies, our results enable us to gain new insight into the genes and possible mechanisms involved in tumor regression and reveal potentially useful targets for cancer therapy.

Bamboos are ecologically and economically important grasses, and are distinguished by their rapid growth. To identify genes associated with bamboo growth, PCR-based mRNA differential display was used to clone genes that were differentially expressed in various tissues of bamboo (Bambusa oldhamii) shoots at different growth stages. In total, 260 different cDNA sequences were obtained. These genes displayed complex expression profiles across the different tissues and growth stages as revealed by a cDNA microarray analysis. Notable among them were genes that were temporally up-regulated or down-regulated in the internode-containing region of rapidly elongating shoots. These genes might participate in the rapid elongation of the bamboo culm. Of the 36 up-regulated and 46 down-regulated genes, 16 genes and 8 genes, respectively, were predicted to encode hypothetical proteins or were unknown sequences. Aside from these, genes involved in hormonal signaling and homeostasis, stress responses, peptide processing and signaling and lignin biosynthesis composed most of the up-regulated genes; genes involved in DNA replication, nucleic acid binding and signal transduction were highly represented among the down-regulated genes. These results suggested that genes associated with plant hormonal signaling and homeostasis, peptide signaling, reactive oxygen species signaling and homeostasis, several stress-related genes and a monocot-specific unknown gene, BoMSP41, play important roles in the elongation of bamboo internodes. Multiple signaling pathways might form a complex interconnected network that controls the rapid growth of this giant grass.

The etiology of systemic lupus erythematosus (SLE) involves a complex interaction of genetic and environmental factors. Investigations have shown that environmentally driven epigenetic changes contribute to the etiology of SLE. Here, we hypothesize that aberrant DNA methylation may contribute to the activation of the immune machinery and trigger lupus disease activity. A whole genome methylation array was applied to investigate the DNA methylation changes between 12 pairs of active SLE patients and healthy controls. The results were further confirmed in 66 SLE patients, 102 healthy controls. The methylation statuses of the IL10 and IL1R2 genes were significantly reduced in the SLE patient samples relative to the healthy controls (age-adjusted odds ratios, 64.2 and 16.9, respectively, P

DBCAT (database of CpG islands and analytical tools, http://dbcat.cgm.ntu.edu.tw/ ), developed to characterize comprehensive DNA methylation profiles in human cancers, is a web-based application and methylation database containing several convenient tools for investigating epigenetic regulation in human diseases. To our knowledge, DBCAT is the first online methylation analytical tool, and is composed of three parts: a CpG island finder, a genome query browser, and a tool for analyzing methylation microarray data. The analytical tools can quickly identify genes with methylated regions from microarray data, compare the methylation status changes between different arrays, and provide functional analysis in addition to colocalizing transcription factor binding sites.

Seasonal infertility is a well-known problem in the modern swine (Sus scrofa) industry. The molecular mechanisms responsible for thermal effects on spermatogenesis are, however, just beginning to be elucidated. The existence of specific messenger RNA (mRNA) remnants contained within freshly ejaculated sperm has been identified in several species. Investigators have obtained differential RNA profiles of infertile men compared with fertile individuals; however, there are limited to the probes, which are mostly derived from nucleic acids of testicular tissues of either human or mice. The objective of this study was to investigate mRNA remnants from ejaculated sperm of the domestic swine and uncover important clues regarding the molecular regulation of spermatogenesis under environmental thermo-impacts. We utilized the remnant mRNA collected from swine ejaculated sperm as the target source to detect the global gene expression in summer and in winter by swine sperm-specific oligonucleotide microarray. Sixty-seven transcripts were differentially expressed with statistical differences between seasons of sperm samples collected, including forty-nine in winter (49/67) and eighteen in summer (18/67). There were only 33 of these transcripts that could be annotated to gene ontology hierarchy with the database of Homo sapiens and their functions mostly were involved in variety of metabolic processes. Moreover, these studies also confirmed that significant differences of gene expression profiles were found in swine sperm when comparisons were made between ejaculates collected during the winter and the summer season under the subtropical area such as Taiwan. Even though most of the genes found in our experiments are still poorly understood in terms of their true functions in spermatogenesis, bioinformatics analysis suggested that they are involved in a broad spectrum of biochemical processes including gamete generation. These concordant profiles should permit the development of a non-invasive testing protocol to assess the functional capacity of sperm as well as a new molecular selection scheme for fine breeding swine.

Motivation: Genomic instability is one of the fundamental factors in tumorigenesis and tumor progression. Many studies have shown that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array comparative genomic hybridization (aCGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copies at a high resolution. However, due to the nature of aCGH, many standard expression data processing tools, such as data normalization, often fail to yield satisfactory results. Results: We demonstrated a novel aCGH normalization algorithm, which provides an accurate aCGH data normalization by utilizing the dependency of neighboring probe measurements in aCGH experiments. To facilitate the study, we have developed a hidden Markov model (HMM) to simulate a series of aCGH experiments with random DNA copy number alterations that are used to validate the performance of our normalization. In addition, we applied the proposed normalization algorithm to an aCGH study of lung cancer cell lines. By using the proposed algorithm, data quality and the reliability of experimental results are significantly improved, and the distinct patterns of DNA copy number alternations are observed among those lung cancer cell lines. Contact: chuangey@ntu.edu.tw Supplementary information: Source codes and.gures may be found at http://ntumaps.cgm.ntu.edu.tw/aCGH_supplementary

Background Although much research effort has been devoted to elucidating lung cancer, the molecular mechanism of tumorigenesis still remains unclear. A major challenge to improve the understanding of lung cancer is the difficulty of identifying reproducible differentially expressed genes across independent studies, due to their low consistency. To enhance the reproducibility of the findings, an integrated analysis was performed to identify regulatory SNPs. Thirty-two pairs of tumor and adjacent normal lung tissue specimens were analyzed using Affymetrix U133plus2.0, Affymetrix SNP 6.0, and Illumina Infinium Methylation microarrays. Copy number variations (CNVs) and methylation alterations were analyzed and paired t-tests were used to identify differentially expressed genes. Results A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis. Subsequently, three statistical approaches were performed to explore regulatory SNPs, which revealed that the genotypes of 551 and 66 SNPs were associated with CNV and changes in methylation, respectively. Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations. Conclusions In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma. Electronic supplementary material The online version of this article (doi:10.1186/s13104-015-1053-8) contains supplementary material, which is available to authorized users.

Background Regional specificity allows different skin regions to exhibit different characteristics, enabling complementary functions to make effective use of the integumentary surface. Chickens exhibit a high degree of regional specificity in the skin and can serve as a good model for when and how these regional differences begin to emerge. Results We used developing feather and scale regions in embryonic chickens as a model to gauge the differences in their molecular pathways. We employed cosine similarity analysis to identify the differentially regulated and co-regulated genes. We applied low cell techniques for expression validation and chromatin immunoprecipitation (ChIP)-based enhancer identification to overcome limited cell availabilities from embryonic chicken skin. We identified a specific set of genes demonstrating a high correlation as being differentially expressed during feather and scale development and maturation. Some members of the WNT, TGF-beta/BMP, and Notch family known to be involved in feathering skin differentiation were found to be differentially regulated. Interestingly, we also found genes along calcium channel pathways that are differentially regulated. From the analysis of differentially regulated pathways, we used calcium signaling pathways as an example for further verification. Some voltage-gated calcium channel subunits, particularly CACNA1D, are expressed spatio-temporally in the skin epithelium. These calcium signaling pathway members may be involved in developmental decisions, morphogenesis, or epithelial maturation. We further characterized enhancers associated with histone modifications, including H3K4me1, H3K27ac, and H3K27me3, near calcium channel-related genes and identified signature intensive hotspots that may be correlated with certain voltage-gated calcium channel genes. Conclusion We demonstrated the applicability of cosine similarity analysis for identifying novel regulatory pathways that are differentially regulated during development. Our study concerning the effects of signaling pathways and histone signatures on enhancers suggests that voltage-gated calcium signaling may be involved in early skin development. This work lays the foundation for studying the roles of these gene pathways and their genomic regulation during the establishment of skin regional specificity. Electronic supplementary material The online version of this article (doi:10.1186/s12864-014-1202-9) contains supplementary material, which is available to authorized users.

It is now widely believed that low-frequency variants may play an important role in cancers. In addition, low-frequency variants are usually closely related to populations. To identify the disease-associated variants, several projects are now underway to build a reference of genetic variations from different populations. Furthermore, massive tools and databases are available to compare the dynamic gene expression among different organs and predict functional effects of genetic variants. These resources aid to identify genetic roots of cancers in populations easier. Despite the existence of population allele frequency information, gene expression databases and functional effects of protein mutations, a comprehensive platform providing an integrated annotation database in human genetic variants, is still lacking. In the study, we proposed a web-based database to determine potential variations in cancers with collected variant information from current common databases and integrated those data to provide comprehensive analyses. The web-site offers a function to upload a variant call format (VCF) files for variants annotation. Importantly, we integrated population allele frequency information from NHBI GO Exome Sequencing Project (ESP), 1000 Genomes Project and Tohoku Medical Megabank Project to help users figure out the correlation between disease and population. Additionally, we also collected gene expression profiles from The Human Protein Atlas, Expression Atlas and NCBI SRA in different organs of human, mouse, and zebrafish respectively to reflect the relationship between gene expression and genetic variations in a specific organ. Overall, the database aids to predict protein functions in mutations, analyze population allele frequency and gene expression information from provided variants of diseases. In the result, we use three EGFR mutations to display the proposed system. A recent study has reported that Asian patients with non-small cell lung cancer (NSCLC) carrying a higher rate of EGFR mutations than non-Asian patients. These mutations, such as chr7:55241708G>C (G719A), chr7:55249005G>T (S768I) and chr7:55259515T>G (L858R), are found approximately in 30% of Asian (Japanese) patients. In functional prediction results, these sites are exonic and nonsynonymous mutations. The REVEL scores of three EGFR mutations are 0.824, 0.765 and 0.961, and gerp++ scores are 5.5, 5.85 and 5.71, respectively. Both REVEL and gerp++ show high scores for severe damage of protein structure in the mutations. According to the results, researchers can infer that the three mutations are pathogenic variants implying the nucleotide positions with a higher constraint. Citation Format: Li Mei Chiang, Chien Yueh Lee, Liang Chuan Lai, Mong Hsun Tsai, Tzu Pin Lu, Eric Y. Chuang. VariED: an integrated database of variants and gene expression profiles for genetic diseases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3573. doi:10.1158/1538-7445.AM2017-3573

DNA methylation plays an important role in regulating cell growth and disease development. Methylation profiles are examined by bisulfite conversion; however, the lack of markers for bisulfite conversion efficiency and appropriate internal control genes remains a major challenge. To address these issues, we utilized two bioinformatics approaches, coefficients of variances and resampling tests, to identify probes showing stable methylation levels from several independent microarray datasets. Mass spectrometry validated the consistently high methylation levels of the five probes (N4BP2, EGFL8, CTRB1, TSPAN3, and ZNF690) in 13 human tissue types from 24 cell lines. Linear associations between detected methylation levels and methyl concentrations of DNA samples were further demonstrated in three genes (N4BP2, EGFL8, and CTRB1). To summarize, we identified five genes which may serve as internal controls for methylation studies by analyzing large-scale microarray data, and three of them can be used as markers for evaluating the efficiency of bisulfite conversion.

Acute radiation exposure of humans was observed to induce various forms of cytogenetic damage, including increased frequencies of micronuclei and chromosomal aberrations. However, the cytogenetic effects of chronic low dose radiation exposure in vivo needs further characterization. Sixteen subjects with chronic low dose rates of gamma-radiation exposure from 60Co-contaminated steel in radioactive buildings were compared with seven non-exposed reference subjects for micronucleus frequencies after they relocated. By in situ hybridization using a digoxigenin-labeled anti-alpha all human centromere probe, the exposed subjects were shown to have a significant increase in cytochalasin B-modulated micronucleus (CBMN) frequencies, as well as a significant increase in centromere-positive (C+) CBMN, centromere-negative (C-) CBMN, total C+signals, single C+ MN signals and multiple C+ signals/1000 binucleated cells (BN). However, decreases in the ratios C+MN/C- MN and C+MN/total CBMN (%) were also noted in the exposed subjects. By mixed effects analysis, considering individuals from the same families, the C- MN and single C+ MN/1000 BN were both positively and moderately associated with previous cumulative exposure. When the time period of relocation post-exposure (relocation time or RT) was considered, total C+MN and multiple C+MN/1000 BN were negatively and significantly associated with RT. Moreover, the C+MN, C- MN, C+MN/C- MN ratio and single C+MN/1000 BN were all negatively and moderately associated with RT, but not with exposure dose. This suggested that acentromeric and single or multiple centromeric CBMN cytogenetic damage seems to disappear differentially in human subjects post chronic low dose radiation exposure.

Lung cancer is the leading cause of cancer death worldwide, and brain metastasis is a major cause of morbidity and mortality in lung cancer. CDH2 (N-cadherin, a mesenchymal marker of the epithelial-mesenchymal transition) and ADAM9 (a type I transmembrane protein) are related to lung cancer brain metastasis; however, it is unclear how they interact to mediate this metastasis. Because microRNAs regulate many biological functions and disease processes (e.g., cancer) by down-regulating their target genes, microRNA microarrays were used to identify ADAM9-regulated miRNAs that target CDH2 in aggressive lung cancer cells. Luciferase assays and western blot analysis showed that CDH2 is a target gene of miR-218. MiR-218 was generated from pri-mir-218-1, which is located in SLIT2, in non-invasive lung adenocarcinoma cells, whereas its expression was inhibited in aggressive lung adenocarcinoma. The down-regulation of ADAM9 up-regulated SLIT2 and miR-218, thus down-regulating CDH2 expression. This study revealed that ADAM9 activates CDH2 through the release of miR-218 inhibition on CDH2 in lung adenocarcinoma.

Macrophages play a pivotal role in the immune system through recognition and elimination of microbial pathogens. Toll-like receptors (TLRs) on macrophages interact with microbial substances and initiate signal transduction through intracellular adapters. TLR4, which recognizes the lipopolysaccharides (LPS) on Gram-positive and Gram-negative bacteria, triggers downstream signaling mediators and eventually activates IκB kinase (IKK) complex and mitogen-activated protein kinases (MAPKs) such as p38. Previous reports revealed that, in addition to NF-κB, a core transcription factor of the innate immune response, the induction of some LPS-induced genes in macrophages required another transcription factor whose activity depends on p38. However, these additional transcription factors remain to be identified. In order to identify p38-activated transcription factors that cooperate with NF-κB in response to LPS stimulation, microarrays were used to identify genes regulated by both NF-κB and p38 using wild-type, IKK-depleted, and p38 inhibitor-treated mouse bone marrow-derived macrophages (BMDMs). In silico analysis of transcription factor binding sites was used to predict the potential synergistic transcription factors from the co-expressed genes. Among these genes, NF-κB and C/EBPβ, a p38 downstream transcription factor, were predicted to co-regulate genes in LPS-stimulated BMDMs. Based on the subsequent results of a chromatin immunoprecipitation assay and TNFAIP3 expression in C/EBPβ-ablated macrophages, we demonstrated that Tnfaip3 is regulated by both NF-κB and p38-dependent C/EBPβ. These results identify a novel regulatory mechanism in TLR4-mediated innate immunity.

Lung cancer is the leading cause of cancer-related mortality worldwide. Radiotherapy is often applied for treating lung cancer, but it often fails because of the relative non-susceptibility of lung cancer cells to radiation. MicroRNAs (miRNAs) have been reported to modulate the radiosensitivity of lung cancer cells and have the potential to improve the efficacy of radiotherapy. The purpose of this study was to identify a miRNA that can adjust radiosensitivity in lung adenocarcinoma cells. Two lung adenocarcinoma cell lines (CL1-0 and CL1-5) with different metastatic ability and radiosensitivity were used. In order to understand the regulatory mechanisms of differential radiosensitivity in these isogenic tumor cells, both CL1-0 and CL1-5 were treated with 10 Gy radiation, and were harvested respectively at 0, 1, 4, and 24 h after radiation exposure. The changes in expression of miRNA upon irradiation were examined using Illumina Human microRNA BeadChips. Twenty-six miRNAs were identified as having differential expression post-irradiation in CL1-0 or CL1-5 cells. Among these miRNAs, miR-449a, which was down-regulated in CL1-0 cells at 24 h after irradiation, was chosen for further investigation. Overexpression of miR-449a in CL1-0 cells effectively increased irradiation-induced DNA damage and apoptosis, altered the cell cycle distribution and eventually led to sensitization of CL1-0 to irradiation.

Genetic variation has proved to contribute to tumor formation. One of the phenomenon caused by genetic variation, allelic imbalance, means different expression abundance between two alleles, recently has become a special landmark on cancer biology, with high prevalence in recent cancer studies. However, the present of allelic imbalance has not been fully understood yet. Taking the advantages of next generation sequencing, allelic imbalance can be identified and quantified through bioinformatics algorithms. Here, we developed a mathematical model to identify with allelic imbalance by concurrently analyzing RNA-Seq and DNA-Seq. First we called heterozygous SNP variants from both RNA-Seq and Exome-Seq data. The allele ratio is counted by the ratio of read depth between two alleles after integrating SNPs into gene level. Next, we identify allelic imbalance genes by differences of RNA and DNA allele ratios between tumor and normal samples. As results, a total of 91143 SNPs were identified in Exome-Seq, and about 3% (2586 out of 91143) SNPs were heterozygous in both tumor and normal tissues. We found that about 118 allelic imbalance genes in tumor tissue are significantly different from those in normal tissue. Furthermore, we investigate the enriched function of these allelic imbalance genes. These result showed that these genes are significantly enriched in DNA repair pathway. We speculated that allelic imbalance in tumor tissue may be involved in the dysregulation of DNA repair. Also other enriched functions were identified, such as z-finger protein pathway. Our goal is to investigate the landscape of allelic imbalance between tumor sample and normal sample. Our results demonstrate the role of allelic imbalance of dysregulation of tumor. Moreover, our method can be applied to uncover more basic mechanisms on allelic imbalance and tumorigenesis. Citation Format: Yao-Wei Jheng, Yu-Chiao Chiu, Tzu-Pin Lu, Liang-Chuan Lai, Mong-Hsun Tsai, Tzu-Hung Hsiao, Eric Y Chuang. Characterizing the differences of allelic imbalance between tumor and normal tissues by next-generation sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5284.

Hypoxia is a crucial factor that associated with solid tumor progression by driving multiple signaling pathway. Our lab previously reported that NDRG1 was oxygen-responsive genes and could affect cellular function in a breast cancer cell line MCF-7. Long-non coding RNAs (lncRNAs) have recently emerged as important regulators of tumor progression by participating in several process of gene expression. However, it is unclear whether lncRNAs are responsed to oxygen concentrations in breast cancer. Therefore, the aim of this study is to identify lncRNAs which are responsive upon changes in oxygen concentrations, and its regulatory mechanism in the breast cancer MCF-7 cells. We investigated the differentially expressed lncRNAs in different oxygen concentrations using next-generation sequencing (NGS) and validated these results through quantitative reverse transcription polymerase chain reaction (qRT-PCR). We found an lncRNA, NDRG1-OT1, that was up-regulated during hypoxia and down-regulated during reoxygenation. Next, we identified the differentially expressed genes regulated by NDRG1-OT1 using microarrays and confirmed these results through qRT-PCR and Western blotting. We found an oxygen responsive gene, NDRG1, was inhibited by NDRG1-OT1. Furthermore, Ingenuity Pathway Analysis(IPA) indicated that NDRG1-OT1 could involve in the Ubiquitin-proteasome pathway. We considered NDRG1-OT1 might regulate NDRG1 stability and ubiquitination, and we are proving these possibility by immunoblotting and immunoprecipitation. These findings may provide new insights into epigenetic regulation of breast cancer during hypoxia. Citation Format: Hsin-Chen Lin, Liang-Chuan Lai, Hsing-Guang Chen, Hung-Hsin Chen, Mei-Hung Chang, Mong-Hsun Tsai, Eric Y. Chung. Hypoxic long noncoding RNA NDRG1-OT1 inhibit NDRG1 in MCF-7 breast cancer cell line. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 975.

BackgroundTriple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.Methodology/principal findingsClinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04-5.06, Cox P=0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.Conclusions/significanceGene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.

BackgroundMany prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.ResultsFirst, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.ConclusionsMiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.

Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p

Lung cancer has been one of the major causes of cancer-related death worldwide. To predict survival outcomes of lung cancer patients, many prognosis gene sets were identified by using gene expression microarrays. However, these gene sets were often inconsistent across independent cohorts. To identify genes with more consistency, we combined gene expression and copy number variations (CNVs). Affymetrix SNP 6.0 and u133plus2.0 microarrays were performed on 42 pairs of lung adenocarcinoma patients. The copy number varied regions (CNVR) existed in more than 30% samples were identified and 475 differentially expressed genes with concordant changes were selected for pathway analysis. Thirteen pathways were significantly enriched among the 475 CNV-associated genes, and survival analyses showed these pathways had generally consistent and significant prediction probabilities across three independent microarray studies. Therefore, integration between gene expression and copy number may help to lower false discovery rate and identify genes used to predict survival outcomes.

Genomic instability is one of fundamental factors in tumorigenesis and tumor progression. Many studies have demonstrated that copy-number abnormalities at the DNA level are important in the pathogenesis of cancer. Array Comparative Genomic Hybridization (aCGH), developed based on expression microarray technology, can reveal the chromosomal aberrations in segmental copy at a high-resolution. However, due to the nature of aCGH, many standard expression data processing tools, such as data normalization, often failed to yield satisfactory results. The proposed study demonstrated a novel aCGH normalization procedure, which provides an accurate aCGH data normalization by utilizing the dependency of neighboring probe measurements in aCGH experiments. To facilitate the study, we have developed a Hidden Markov Model (HMM) to simulate a series of aCGH experiment with random DNA copy number alteration. Furthermore, based on this new development, we will establish a user-friendly web system in order to provide convenient aCGH analysis.

The p53 protein has been implicated in multiple cellular responses related to DNA damage. Alterations in any of these cellular responses could be related to increased genomic instability. Our previous study has shown that mutations in p53 lead to hypermutability to ionizing radiation. To investigate further how p53 is involved in regulating mutational processes, we used 8K cDNA microarrays to compare the patterns of gene expression among three closely related human cell lines with different p53 status including TK6 (wild-type p53), NH32 (p53-null), and WTK1 (mutant p53). Total RNA samples were collected at 1, 3, 6, 9, and 24 h after 10 Gy gamma-irradiation. Template-based clustering analysis of the gene expression over the time course showed that 464 genes are either up or downregulated by at least twofold following radiation treatment. In addition, cluster analyses of gene expression profiles among these three cell lines revealed distinct patterns. In TK6, 165 genes were upregulated, while 36 genes were downregulated. In contrast, in WTK1 75 genes were upregulated and 12 genes were downregulated. In NH32, only 54 genes were upregulated. Furthermore, we found several genes associated with DNA repair namely p53R2, DDB2, XPC, PCNA, BTG2, and MSH2 that were highly induced in TK6 compared to WTK1 and NH32. p53R2, which is regulated by the tumor suppressor p53, is a small subunit of ribonucleotide reductase. To determine whether it is involved in radiation-induced mutagenesis, p53R2 protein was inhibited by siRNA in TK6 cells and followed by 2 Gy radiation. The background mutation frequencies at the TK locus of siRNA-transfected TK6 cells were about three times higher than those seen in TK6 cells. The mutation frequencies of siRNA-transfected TK6 cells after 2 Gy radiation were significantly higher than the irradiated TK6 cells without p53R2 knock down. These results indicate that p53R2 was induced by p53 protein and is involved in protecting against radiation-induced mutagenesis.

Rickettsia prowazekii , the causative agent of epidemic typhus, has been responsible for millions of human deaths. Madrid E is an attenuated strain of R. prowazekii , while Breinl is a virulent strain. The genomic DNA sequence of Madrid E has recently been published. To study the genomic variations between Madrid E (reference) and Breinl (test) DNAs, cohybridization experiments were performed on a DNA microarray containing all 834 protein-coding genes of Madrid E. Of the 834 genes assessed, 24 genes showed 1.5- to 2.0-fold increases in hybridization signals in Breinl DNA compared to Madrid E DNA, indicating the presence of genomic variations in ∼3% of the total genes. Eighteen of these 24 genes are predicted to be involved in different functions. Southern blot analysis of five genes, virB4 , ftsK , rfbE , lpxA , and rpoH , suggested the presence of an additional paralog(s) in Breinl, which might be related to the observed increase in hybridization signals. Studies by real-time reverse transcription-PCR revealed an increase in expression of the above-mentioned five genes and five other genes. In addition to the elevated hybridization signals of 24 genes observed in the Breinl strain, one gene ( rp084 ) showed only 1/10 the hybridization signal of Madrid E. Further analysis of this gene by PCR and sequencing revealed a large deletion flanking the whole rp084 gene and part of the rp083 gene in the virulent Breinl strain. The results of this first rickettsial DNA microarray may provide some important information for the elucidation of pathogenic mechanisms of R. prowazekii .

Tomato late blight caused by the oomycete pathogen Phytophthora infestans (Mont.) de Bary is a major threat to tomato production in cool and wet environments. Intensified outbreaks of late blight have been observed globally from the 1980s, and are associated with migration of new and more aggressive populations of P. infestans in the field. The objective of this study was to reassess late blight resistance in the wild tomato accession L3708 (Solanum pimpinellifolium L.) against pathogens of different aggressiveness. An F2:3 genetic mapping population was developed using L3708 as the paternal parent. Two isolates of P. infestans, Pi39A and Pi733, were used for inoculation. Pi733 is a highly aggressive genotype that defeats three known late blight resistance genes, Ph-1, Ph-2, and Ph-5t in tomato. In contrast, Pi39A is a less aggressive genotype that defeats only Ph-1. Restriction site Associated DNA Sequencing (RAD-Seq) technology was used to massively sequence 90 bp nucleotides adjacent to both sides of PstI restriction enzyme cutting sites in the genome for all individuals in the genetic mapping population. The RAD-seq data were used to construct a genetic linkage map containing 440 single nucleotide polymorphism markers. Quantitative trait locus (QTL) analysis identified a new disease-resistant QTL specific to Pi733 on chromosome 2. The Ph-3 gene located on chromosome 9 could be detected whichever isolates were used. This study demonstrated the feasibility and efficiency of RAD-Seq technology for conducting a QTL mapping experiment using an F2:3 mapping population, which allowed the identification of a new late blight resistant QTL in tomato.

To assess DNA damage remaining in peripheral lymphocytes, 48 individuals were evaluated twice for lymphocyte micronucleus frequencies by the cytokinesis-blocking cytochalasin B (CBMN) analysis post relocation from radio-contaminated apartments after various periods of time. The frequencies of CBMN at the first evaluation were significantly higher than those at the second examination (Chang et al., 1999c). These individuals were categorized into three groups: those with cumulative exposure of >300 mSv (defined as high exposure, HDose), those with 100-300 mSv (MDose) and those with

A growing body of evidence has indicated that microRNAs play important roles in many cellular processes and dysregulation of microRNAs results in several diseases including cancers. With advances in massive parallel sequencing technology, Next-Generation Sequencing (NGS), detection of low-quantity sequences improves and hence achieves better ability to find microRNAs expressed in low numbers. We construct a small RNA pipeline to identify novel microRNAs by miRDeep2 and other tools, which can be fully performed on Galaxy with friendly graphical user interface. After the construction of pipeline and tools, several proper small RNA-seq datasets of breast cancer containing enough samples statistically are derived for novel microRNA identification. MiRDeep2 is an integrated tool which uses a probabilistic model of microRNA biogenesis to score pattern and frequency of sequenced RNA with the secondary structure of the microRNA precursor in order to discover novel microRNAs. The method of finding microRNA using miRDeep2 has been widely used and has been validated with remarkable accuracy. Due to the long time and large space-consuming computing and multiple tools involved when processing NGS data, a bio-info framework made by USCS, Galaxy, is introduced into the pipeline, which serves as a great data integration and analysis platform. As the results, few hundreds of candidates are scored over 0 by miRDeep2. However, judging from the number and the probability of the true positives of being a novel microRNA, we set a score lower bound of 5 and use the 50 predicted candidates that pass the threshold in further analysis, which means we have 39±3 true positives out of 50 with probability of 78±7%. Then, candidates will be discarded when mapped to other functional RNAs by BLAST. Finally, 30 candidates of novel microRNAs are found out. A further investigation shows that 25 of 30 candidates are successfully mapped to another RNA-seq dataset including over a hundred samples of breast cancer and covering all tumor, tumor-adjacent, and normal type of tissue samples. Profiles of these candidates generated by miRDeep2 potentially show the trend of correlation with the tissue type of sample. More RNA-seq datasets can be performed following the pipeline set up in this study for microRNA characterization and in vitro experiments can be designed for further verification and profiling in the future. Citation Format: Chien-Yueh Lee, Liang-Bo Wang, Mong-Hsun Tsai, Liang-Chuan Lai, Eric Y. Chuang. Identification of novel miRNAs in breast data of the next generation sequencing using miRDeep2 and Galaxy. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2903. doi:10.1158/1538-7445.AM2013-2903 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend.

MicroRNAs (miRNAs) are short non-coding RNAs about 22 nucleotides in length that play important regulatory roles in animals for translational repression by targeting mRNAs. Recent studies reported that miRNAs may function as tumor suppressors or oncogenes, and the alterations in miRNA expression may be critical in tumor genesis and cancer progression. Using computational methodologies can rapidly identify miRNA targets in massive data, and provide rich gene-related information for human cancer studies. However, it is challenging to predict targets in animals due to imperfect complementarity between miRNAs and mRNA targets. In order to further improve the prediction performance, we proposed a novel miRNA target-gene prediction algorithm that combines several conventional prediction models including the sequence complementary searching for calculating alignment scores and thermodynamic stability approaches for assigning folding free energy to each miRNA-target interaction. A Hidden Markov Model (HMM), a well known machine learning approach, was implemented in the algorithm to help the prediction decision. However, an HMM cannot consider all global information of the sequences due to its innate limitation. Therefore, forward and backward HMMs were simultaneously utilized in the proposed algorithm to overcome this limitation. As a result, any element information of miRNA-target interactions was able to pass to any other element by bi-directions. The proposed algorithm can predict the cancer-related miRNA target genes through a suitable combination of the proposed models. The results show that the highest sensitivity, specificity, and overall accuracy were 84.25%, 96.78%, and 96.67%, respectively. Based on our analysis, 52.42% prediction result of the proposed algorithm was consistent with other existing prediction algorithms. Furthermore, the predicted target genes obtained by the proposed algorithm could be likely found from the potential cancer-related genes discovered by microarray data. A total of 70.37% predicted target genes were significantly overlapped with the cancer-related genes from microarray data, suggesting these genes were substantially regulated by miRNAs in cancer. In conclusion, our proposed novel algorithm is able to predict miRNA target genes, commonly found among microarray-identified dysregulated genes in previous cancer studies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 55. doi:10.1158/1538-7445.AM2011-55

Background Salamanders are unique among vertebrates in their ability to completely regenerate amputated limbs through the mediation of blastema cells located at the stump ends. This regeneration is nerve-dependent because blastema formation and regeneration does not occur after limb denervation. To obtain the genomic information of blastema tissues, de novo transcriptomes from both blastema tissues and denervated stump ends of Ambystoma mexicanum (axolotls) 14 days post-amputation were sequenced and compared using Solexa DNA sequencing. Results The sequencing done for this study produced 40,688,892 reads that were assembled into 307,345 transcribed sequences. The N50 of transcribed sequence length was 562 bases. A similarity search with known proteins identified 39,200 different genes to be expressed during limb regeneration with a cut-off E-value exceeding 10-5. We annotated assembled sequences by using gene descriptions, gene ontology, and clusters of orthologous group terms. Targeted searches using these annotations showed that the majority of the genes were in the categories of essential metabolic pathways, transcription factors and conserved signaling pathways, and novel candidate genes for regenerative processes. We discovered and confirmed numerous sequences of the candidate genes by using quantitative polymerase chain reaction and in situ hybridization. Conclusion The results of this study demonstrate that de novo transcriptome sequencing allows gene expression analysis in a species lacking genome information and provides the most comprehensive mRNA sequence resources for axolotls. The characterization of the axolotl transcriptome can help elucidate the molecular mechanisms underlying blastema formation during limb regeneration.