Transcendent thinking counteracts longitudinal effects of mid-adolescent exposure to community violence in the anterior cingulate cortex.

Adolescence involves extensive brain maturation, characterized by social sensitivity and emotional lability, that co-occurs with increased independence. Mid-adolescence is also a hallmark developmental stage when youths become motivated to reflect on the broader personal, ethical, and systems-level implications of happenings, a process we term transcendent thinking. Here, we examine the confluence of these developmental processes to ask, from a transdisciplinary perspective, how might community violence exposure (CVE) impact brain development during mid-adolescence, and how might youths' dispositions for transcendent thinking be protective? Fifty-five low-SES urban youth with no history of delinquency (32 female; 27 Latinx, 28 East Asian) reported their CVE and underwent structural MRI first at age 14-18, and again 2 years later. At the study's start, participants also discussed their feelings about 40 minidocumentaries featuring other teens' compelling situations in a 2-h private interview that was transcribed and coded for transcendent thinking. Controlling for CVE and brain structure at the start: (1) New CVE during the 2-year inter-scan interval was associated with greater gray matter volume (GMV) reduction over that interval in the anterior cingulate cortex (ACC), a central network hub whose reduced volume has been associated with posttraumatic stress disorder, and across multiple additional cortical and subcortical regions; (2) participants' transcendent thinking in the interview independently predicted greater GMV increase during the 2-year inter-scan interval in the ACC. Findings highlight the continued vulnerability of mid-adolescents to community violence and the importance of supporting teens' dispositions to reflect on the complex personal and systems-level implications and affordances of their civic landscape.

Integrating Single-Cell Transcriptome and Network Analysis to Characterize the Therapeutic Response of Chronic Myeloid Leukemia.

Chronic myeloid leukemia (CML) is a myeloproliferative disease characterized by a unique BCR-ABL fusion gene. Tyrosine kinase inhibitors (TKIs) were developed to target the BCR-ABL oncoprotein, inhibiting its abnormal kinase activity. TKI treatments have significantly improved CML patient outcomes. However, the patients can develop drug resistance and relapse after therapy discontinues largely due to intratumor heterogeneity. It is critical to understand the differences in therapeutic responses among subpopulations of cells. Single-cell RNA sequencing measures the transcriptome of individual cells, allowing us to differentiate and analyze individual cell populations. Here, we integrated a single-cell RNA sequencing profile of CML stem cells and network analysis to decipher the mechanisms of distinct TKI responses. Compared to normal hematopoietic stem cells, a set of genes that were concordantly differentially expressed in various types of stem cells of CML patients was revealed. Further transcription regulatory network analysis found that most of these genes were directly controlled by one or more transcript factors and the genes have more regulators in the cells of the patients who responded to the treatment. The molecular markers including a known drug-resistance gene and novel gene signatures for treatment response were also identified. Moreover, we combined protein-protein interaction network construction with a cancer drug database and uncovered the drugs that target the marker genes directly or indirectly via the protein interactions. The gene signatures and their interacted proteins identified by this work can be used for treatment response prediction and lead to new strategies for drug resistance monitoring and prevention. Our single-cell-based findings offered novel insights into the mechanisms underlying the therapeutic response of CML.

Technological properties of chickpea (Cicer arietinum): Production of snacks and health benefits related to type-2 diabetes.

Chickpea (Cicer arietinum) is one of the most consumed pulses worldwide (over 2.3 million tons enter the world market annually). Some chickpea components have shown, in preclinical and clinical studies, several health benefits, including antioxidant capacity, and antifungal, antibacterial, analgesic, anticancer, antiinflammatory, and hypocholesterolemic properties, as well as angiotensin I-converting enzyme inhibition. In the United States, chickpea is consumed mostly in the form of hummus. However, the development of new products with value-added bioactivity is creating new opportunities for research and food applications. Information about bioactive compounds and functional properties of chickpea ingredients in the development of new products is needed. The objective of this review was to summarize available scientific information, from the last 15 years, on chickpea production, consumption trends, applications in the food industry in the elaboration of plant-based snacks, and on its bioactive compounds related to type 2 diabetes (T2D). Areas of opportunity for future research and new applications of specific bioactive compounds as novel food ingredients are highlighted. Research is key to overcome the main processing obstacles and sensory challenges for the application of chickpea as ingredient in snack preparations. The use of chickpea bioactive compounds as ingredient in food products is also a promising area for accessibility of their health benefits, such as the management of T2D.

Correction to: Identification and characterization of conserved lncRNAs in human and rat brain.

After publication of the original article [1], it was noticed that the Acknowledgement statement was incorrect. The original statement reads.

Community violence exposure correlates with smaller gray matter volume and lower IQ in urban adolescents.

Adolescents' exposure to community violence is a significant public health issue in urban settings and has been associated with poorer cognitive performance and increased risk for psychiatric illnesses, including PTSD. However, no study to date has investigated the neural correlates of community violence exposure in adolescents. Sixty-five healthy adolescents (age = 14-18 years; 36 females, 29 males) from moderate- to high-crime neighborhoods in Los Angeles reported their violence exposure, parents' education level, and free/reduced school lunch status (socio-economic status, SES), and underwent structural neuroimaging and intelligence testing. Violence exposure negatively correlated with measures of SES, IQ, and gray matter volume. Above and beyond the effect of SES, violence exposure negatively correlated with IQ and with gray matter volume in the left inferior frontal gyrus and anterior cingulate cortex, regions involved in high-level cognitive functions and autonomic modulation, and previously shown to be reduced in PTSD and combat-exposed military populations. The current results provide first evidence that frontal brain regions involved in cognition and affect appear to be selectively affected by exposure to community violence, even in healthy nondelinquent adolescents who are not the direct victims or perpetrators of violence.

Processing Narratives Concerning Protected Values: A Cross-Cultural Investigation of Neural Correlates.

Narratives are an important component of culture and play a central role in transmitting social values. Little is known, however, about how the brain of a listener/reader processes narratives. A receiver's response to narration is influenced by the narrator's framing and appeal to values. Narratives that appeal to "protected values," including core personal, national, or religious values, may be particularly effective at influencing receivers. Protected values resist compromise and are tied with identity, affective value, moral decision-making, and other aspects of social cognition. Here, we investigated the neural mechanisms underlying reactions to protected values in narratives. During fMRI scanning, we presented 78 American, Chinese, and Iranian participants with real-life stories distilled from a corpus of over 20 million weblogs. Reading these stories engaged the posterior medial, medial prefrontal, and temporo-parietal cortices. When participants believed that the protagonist was appealing to a protected value, signal in these regions was increased compared with when no protected value was perceived, possibly reflecting the intensive and iterative search required to process this material. The effect strength also varied across groups, potentially reflecting cultural differences in the degree of concern for protected values.

Identification and characterization of conserved lncRNAs in human and rat brain.

BACKGROUND: Long noncoding RNAs (lncRNAs) are involved in diverse biological processes and play an essential role in various human diseases. The number of lncRNAs identified has increased rapidly in recent years owing to RNA sequencing (RNA-Seq) technology. However, presently, most lncRNAs are not well characterized, and their regulatory mechanisms remain elusive. Many lncRNAs show poor evolutionary conservation. Thus, the lncRNAs that are conserved across species can provide insight into their critical functional roles. RESULTS: Here, we performed an orthologous analysis of lncRNAs in human and rat brain tissues. Over two billion RNA-Seq reads generated from 80 human and 66 rat brain tissue samples were analyzed. Our analysis revealed a total of 351 conserved human lncRNAs corresponding to 646 rat lncRNAs. Among these human lncRNAs, 140 were newly identified by our study, and 246 were present in known lncRNA databases; however, the majority of the lncRNAs that have been identified are not yet functionally annotated. We constructed co-expression networks based on the expression profiles of conserved human lncRNAs and protein-coding genes, and produced 79 co-expression modules. Gene ontology (GO) analysis of the co-expression modules suggested that the conserved lncRNAs were involved in various functions such as brain development (P-value = 1.12E-2), nervous system development (P-value = 1.26E-3), and cerebral cortex development (P-value = 1.31E-2). We further predicted the interactions between lncRNAs and protein-coding genes to better understand the regulatory mechanisms of lncRNAs. Moreover, we investigated the expression patterns of the conserved lncRNAs at different time points during rat brain growth. We found that the expression levels of three out of four such lncRNA genes continuously increased from week 2 to week 104, which is consistent with our functional annotation. CONCLUSION: Our orthologous analysis of lncRNAs in human and rat brain tissues revealed a set of conserved lncRNAs. Further expression analysis provided the functional annotation of these lncRNAs in humans and rats. Our results offer new targets for developing better experimental designs to investigate regulatory molecular mechanisms of lncRNAs and the roles lncRNAs play in brain development. Additionally, our method could be generalized to study and characterize lncRNAs conserved in other species and tissue types.

Decoding the neural representation of story meanings across languages.

Drawing from a common lexicon of semantic units, humans fashion narratives whose meaning transcends that of their individual utterances. However, while brain regions that represent lower-level semantic units, such as words and sentences, have been identified, questions remain about the neural representation of narrative comprehension, which involves inferring cumulative meaning. To address these questions, we exposed English, Mandarin, and Farsi native speakers to native language translations of the same stories during fMRI scanning. Using a new technique in natural language processing, we calculated the distributed representations of these stories (capturing the meaning of the stories in high-dimensional semantic space), and demonstrate that using these representations we can identify the specific story a participant was reading from the neural data. Notably, this was possible even when the distributed representations were calculated using stories in a different language than the participant was reading. Our results reveal that identification relied on a collection of brain regions most prominently located in the default mode network. These results demonstrate that neuro-semantic encoding of narratives happens at levels higher than individual semantic units and that this encoding is systematic across both individuals and languages. Hum Brain Mapp 38:6096-6106, 2017. © 2017 Wiley Periodicals, Inc.

The up-regulation of Myb may help mediate EGCG inhibition effect on mouse lung adenocarcinoma.

BACKGROUND: Green tea polyphenol epigallocatechin-3-gallate (EGCG) has been demonstrated to inhibit cancer in experimental studies through its antioxidant activity and modulations on cellular functions by binding specific proteins. By means of computational analysis and functional genomic approaches, we previously identified a set of protein coding genes and microRNAs whose expressions were significantly modulated in response to the EGCG treatment in tobacco carcinogen-induced lung adenocarcinoma in A/J mice. However, to what degree these genes are involved in the cancer inhibition of EGCG remains unclear. RESULTS: In this study, we further employed statistical methods and literature research to analyze these data in combination with The Cancer Genome Atlas (TCGA) lung adenocarcinoma datasets for additional data mining. Under the assumption that, if a gene mediates EGCG's cancer inhibition, its expression level change caused by EGCG should be opposite to what occurred in the carcinogenesis, we identified Myb and Peg3 as the primary putative genes involved in the cancer inhibitory activity. Further analysis suggested that the regulation of Myb could be mediated through an EGCG-upregulated microRNA, miR-449c-5p. CONCLUSIONS: Although the actions of EGCG involve multiple targets/pathways, further analysis by mining the existing genomic datasets revealed that the upregulations of Myb and Peg3 are likely the key anti-cancer events of EGCG in vivo.

Association of six CpG-SNPs in the inflammation-related genes with coronary heart disease.

BACKGROUND: Chronic inflammation has been widely considered to be the major risk factor of coronary heart disease (CHD). The goal of our study was to explore the possible association with CHD for inflammation-related single nucleotide polymorphisms (SNPs) involved in cytosine-phosphate-guanine (CpG) dinucleotides. A total of 784 CHD patients and 739 non-CHD controls were recruited from Zhejiang Province, China. Using the Sequenom MassARRAY platform, we measured the genotypes of six inflammation-related CpG-SNPs, including IL1B rs16944, IL1R2 rs2071008, PLA2G7 rs9395208, FAM5C rs12732361, CD40 rs1800686, and CD36 rs2065666). Allele and genotype frequencies were compared between CHD and non-CHD individuals using the CLUMP22 software with 10,000 Monte Carlo simulations. RESULTS: Allelic tests showed that PLA2G7 rs9395208 and CD40 rs1800686 were significantly associated with CHD. Moreover, IL1B rs16944, PLA2G7 rs9395208, and CD40 rs1800686 were shown to be associated with CHD under the dominant model. Further gender-based subgroup tests showed that one SNP (CD40 rs1800686) and two SNPs (FAM5C rs12732361 and CD36 rs2065666) were associated with CHD in females and males, respectively. And the age-based subgroup tests indicated that PLA2G7 rs9395208, IL1B rs16944, and CD40 rs1800686 were associated with CHD among individuals younger than 55, younger than 65, and over 65, respectively. CONCLUSIONS: In conclusion, all the six inflammation-related CpG-SNPs (rs16944, rs2071008, rs12732361, rs2065666, rs9395208, and rs1800686) were associated with CHD in the combined or subgroup tests, suggesting an important role of inflammation in the risk of CHD.

The clinical significance of snail protein expression in gastric cancer: a meta-analysis.

BACKGROUND: Snail is a typical transcription factor that could induce epithelial-mesenchymal transition (EMT) and cancer progression. There are some related reports about the clinical significance of snail protein expression in gastric cancer. However, the published results were not completely consistent. This study was aimed to investigate snail expression and clinical significance in gastric cancer. RESULTS: A systematic review of PubMed, CNKI, Weipu, and Wanfang database before March 2015 was conducted. We established an inclusion criterion according to subjects, method of detection, and results evaluation of snail protein. Meta-analysis was conducted using RevMan4.2 software. And merged odds ratio (OR) and 95 % CI (95 % confidence interval) were calculated. Also, forest plots and funnel plot were used to assess the potential of publication bias. A total of 10 studies were recruited. The meta-analysis was conducted to evaluate the positive rate of snail protein expression. OR and 95 % CI for different groups were listed below: (1) gastric cancer and para-carcinoma tissue [OR = 6.15, 95 % CI (4.70, 8.05)]; (2) gastric cancer and normal gastric tissue [OR = 17.00, 95 % CI (10.08, 28.67)]; (3) non-lymph node metastasis and lymph node metastasis [OR = 0.40, 95 % CI (0.18, 0.93)]; (4) poor differentiated cancer, highly differentiated cancer, and moderate cancer [OR = 3.34, 95 % CI (2.22, 5.03)]; (5) clinical stage TI + TII and stage TIII + TIV [OR = 0.38, 95 % CI (0.23, 0.60)]; (6) superficial muscularis and deep muscularis [OR = 0.18, 95 % CI (0.11, 0.31)]. CONCLUSIONS: Our results indicated that the increase of snail protein expression may play an important role in the carcinogenesis, progression, and metastasis of gastric cancer. And this result might provide instruction for the diagnosis, therapy, and prognosis of gastric cancer.

Neural mediators of the intergenerational transmission of family aggression.

Youth exposed to family aggression may become more aggressive themselves, but the mechanisms of intergenerational transmission are understudied. In a longitudinal study, we found that adolescents' reduced neural activation when rating their parents' emotions, assessed via magnetic resonance imaging, mediated the association between parents' past aggression and adolescents' subsequent aggressive behavior toward parents. A subsample of 21 youth, drawn from the larger study, underwent magnetic resonance imaging scanning proximate to the second of two assessments of the family environment. At Time 1 (when youth were on average 15.51 years old) we measured parents' aggressive marital and parent-child conflict behaviors, and at Time 2 (≈2 years later), we measured youth aggression directed toward parents. Youth from more aggressive families showed relatively less activation to parent stimuli in brain areas associated with salience and socioemotional processing, including the insula and limbic structures. Activation patterns in these same areas were also associated with youths' subsequent parent-directed aggression. The association between parents' aggression and youths' subsequent parent-directed aggression was statistically mediated by signal change coefficients in the insula, right amygdala, thalamus, and putamen. These signal change coefficients were also positively associated with scores on a mentalizing measure. Hypoarousal of the emotional brain to family stimuli may support the intergenerational transmission of family aggression.

Mapping the subcellular distribution of α-synuclein in neurons using genetically encoded probes for correlated light and electron microscopy: implications for Parkinson's disease pathogenesis.

Modifications to the gene encoding human α-synuclein have been linked to the development of Parkinson's disease. The highly conserved structure of α-synuclein suggests a functional interaction with membranes, and several lines of evidence point to a role in vesicle-related processes within nerve terminals. Using recombinant fusions of human α-synuclein, including new genetic tags developed for correlated light microscopy and electron microscopy (the tetracysteine-biarsenical labeling system or the new fluorescent protein for electron microscopy, MiniSOG), we determined the distribution of α-synuclein when overexpressed in primary neurons at supramolecular and cellular scales in three dimensions (3D). We observed specific association of α-synuclein with a large and otherwise poorly characterized membranous organelle system of the presynaptic terminal, as well as with smaller vesicular structures within these boutons. Furthermore, α-synuclein was localized to multiple elements of the protein degradation pathway, including multivesicular bodies in the axons and lysosomes within neuronal cell bodies. Examination of synapses in brains of transgenic mice overexpressing human α-synuclein revealed alterations of the presynaptic endomembrane systems similar to our findings in cell culture. Three-dimensional electron tomographic analysis of enlarged presynaptic terminals in several brain areas revealed that these terminals were filled with membrane-bounded organelles, including tubulovesicular structures similar to what we observed in vitro. We propose that α-synuclein overexpression is associated with hypertrophy of membrane systems of the presynaptic terminal previously shown to have a role in vesicle recycling. Our data support the conclusion that α-synuclein is involved in processes associated with the sorting, channeling, packaging, and transport of synaptic material destined for degradation.

Orthology-driven mapping of bidirectional promoters in human and mouse genomes.

BACKGROUND: The presence of bidirectional promoters in all vertebrate species suggests that the promoters may be maintained in orthologous positions. Therefore the identification of the comprehensive orthologous mapping of this type promoter across species can facilitate elucidation of regulatory mechanisms controlling bidirectional gene expression. However, the lack of annotation for many transcribed regions in the genome can impact the orthology designation of these promoters. Human and mouse are among genomes that have been relatively well annotated. Thus we used them as models to study the orthologous patterns of bidirectional promoters. RESULTS: We developed a method to annotate these regulatory regions by confirming the orthology of the genes found on each side of the promoters. In this manuscript we report the cross-species comparisons between human and mouse genomes, where the bidirectional promoter sets regulating UCSC Known Genes and spliced EST annotations were mapped from human to mouse and vice versa. We validate hundreds of orthologous bidirectional promoters through the presence of orthologous flanking gene annotations in the second species. We also show that regulatory activity of these orthologous promoters confers similar gene expression profiles in 21 tissues of human and mouse. In particular, more than one third of human bidirectional promoters annotated from spliced EST annotations regulate ncRNA, of which over 90% are lncRNAs. CONCLUSIONS: Although evolutionary conservation shows a weaker signature in promoters than coding regions, our technique of mapping of orthologous genes shows that most bidirectional promoter arrangements are conserved across human and mouse genomes, suggesting a critical function. In addition, the similar expression patterns of the orthologous gene sets indicate that the regulatory mechanisms remain largely conserved as well.

A new statistical approach to combining p-values using gamma distribution and its application to genome-wide association study.

BACKGROUND: Combining information from different studies is an important and useful practice in bioinformatics, including genome-wide association study, rare variant data analysis and other set-based analyses. Many statistical methods have been proposed to combine p-values from independent studies. However, it is known that there is no uniformly most powerful test under all conditions; therefore, finding a powerful test in specific situation is important and desirable. RESULTS: In this paper, we propose a new statistical approach to combining p-values based on gamma distribution, which uses the inverse of the p-value as the shape parameter in the gamma distribution. CONCLUSIONS: Simulation study and real data application demonstrate that the proposed method has good performance under some situations.

Developing discriminate model and comparative analysis of differentially expressed genes and pathways for bloodstream samples of diabetes mellitus type 2.

BACKGROUND: Diabetes mellitus of type 2 (T2D), also known as noninsulin-dependent diabetes mellitus (NIDDM) or adult-onset diabetes, is a common disease. It is estimated that more than 300 million people worldwide suffer from T2D. In this study, we investigated the T2D, pre-diabetic and healthy human (no diabetes) bloodstream samples using genomic, genealogical, and phonemic information. We identified differentially expressed genes and pathways. The study has provided deeper insights into the development of T2D, and provided useful information for further effective prevention and treatment of the disease. RESULTS: A total of 142 bloodstream samples were collected, including 47 healthy humans, 22 pre-diabetic and 73 T2D patients. Whole genome scale gene expression profiles were obtained using the Agilent Oligo chips that contain over 20,000 human genes. We identified 79 significantly differentially expressed genes that have fold change ≥ 2. We mapped those genes and pinpointed locations of those genes on human chromosomes. Amongst them, 3 genes were not mapped well on the human genome, but the rest of 76 differentially expressed genes were well mapped on the human genome. We found that most abundant differentially expressed genes are on chromosome one, which contains 9 of those genes, followed by chromosome two that contains 7 of the 76 differentially expressed genes. We performed gene ontology (GO) functional analysis of those 79 differentially expressed genes and found that genes involve in the regulation of cell proliferation were among most common pathways related to T2D. The expression of the 79 genes was combined with clinical information that includes age, sex, and race to construct an optimal discriminant model. The overall performance of the model reached 95.1% accuracy, with 91.5% accuracy on identifying healthy humans, 100% accuracy on pre-diabetic patients and 95.9% accuract on T2D patients. The higher performance on identifying pre-diabetic patients was resulted from more significant changes of gene expressions among this particular group of humans, which implicated that patients were having profound genetic changes towards disease development. CONCLUSION: Differentially expressed genes were distributed across chromosomes, and are more abundant on chromosomes 1 and 2 than the rest of the human genome. We found that regulation of cell proliferation actually plays an important role in the T2D disease development. The predictive model developed in this study has utilized the 79 significant genes in combination with age, sex, and racial information to distinguish pre-diabetic, T2D, and healthy humans. The study not only has provided deeper understanding of the disease molecular mechanisms but also useful information for pathway analysis and effective drug target identification.

Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms.

Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular functions and biological behaviours relies on the development of effective approaches at higher systems level. In particular, advances in RNA-Seq technology has helped the studies of transcriptome, RNA expressed from the genome, while systems biology on the other hand provides more comprehensive pictures, from which genes and proteins actively interact to lead to cellular behaviours and physiological phenotypes. As biological interactions mediate many biological processes that are essential for cellular function or disease development, it is important to systematically identify genomic information including genetic mutations from GWAS (genome-wide association study), differentially expressed genes, bidirectional promoters, intrinsic disordered proteins (IDP) and protein interactions to gain deep insights into the underlying mechanisms of gene regulations and networks. Furthermore, bidirectional promoters can co-regulate many biological pathways, where the roles of bidirectional promoters can be studied systematically for identifying co-regulating genes at interactive network level. Combining information from different but related studies can ultimately help revealing the landscape of molecular mechanisms underlying complex diseases such as cancer.

Identification of genes and pathways involved in kidney renal clear cell carcinoma.

BACKGROUND: Kidney Renal Clear Cell Carcinoma (KIRC) is one of fatal genitourinary diseases and accounts for most malignant kidney tumours. KIRC has been shown resistance to radiotherapy and chemotherapy. Like many types of cancers, there is no curative treatment for metastatic KIRC. Using advanced sequencing technologies, The Cancer Genome Atlas (TCGA) project of NIH/NCI-NHGRI has produced large-scale sequencing data, which provide unprecedented opportunities to reveal new molecular mechanisms of cancer. We combined differentially expressed genes, pathways and network analyses to gain new insights into the underlying molecular mechanisms of the disease development. RESULTS: Followed by the experimental design for obtaining significant genes and pathways, comprehensive analysis of 537 KIRC patients' sequencing data provided by TCGA was performed. Differentially expressed genes were obtained from the RNA-Seq data. Pathway and network analyses were performed. We identified 186 differentially expressed genes with significant p-value and large fold changes (P < 0.01, |log(FC)| > 5). The study not only confirmed a number of identified differentially expressed genes in literature reports, but also provided new findings. We performed hierarchical clustering analysis utilizing the whole genome-wide gene expressions and differentially expressed genes that were identified in this study. We revealed distinct groups of differentially expressed genes that can aid to the identification of subtypes of the cancer. The hierarchical clustering analysis based on gene expression profile and differentially expressed genes suggested four subtypes of the cancer. We found enriched distinct Gene Ontology (GO) terms associated with these groups of genes. Based on these findings, we built a support vector machine based supervised-learning classifier to predict unknown samples, and the classifier achieved high accuracy and robust classification results. In addition, we identified a number of pathways (P < 0.04) that were significantly influenced by the disease. We found that some of the identified pathways have been implicated in cancers from literatures, while others have not been reported in the cancer before. The network analysis leads to the identification of significantly disrupted pathways and associated genes involved in the disease development. Furthermore, this study can provide a viable alternative in identifying effective drug targets. CONCLUSIONS: Our study identified a set of differentially expressed genes and pathways in kidney renal clear cell carcinoma, and represents a comprehensive computational approach to analysis large-scale next-generation sequencing data. The pathway and network analyses suggested that information from distinctly expressed genes can be utilized in the identification of aberrant upstream regulators. Identification of distinctly expressed genes and altered pathways are important in effective biomarker identification for early cancer diagnosis and treatment planning. Combining differentially expressed genes with pathway and network analyses using intelligent computational approaches provide an unprecedented opportunity to identify upstream disease causal genes and effective drug targets.

Gene regulation mediated by microRNAs in response to green tea polyphenol EGCG in mouse lung cancer.

BACKGROUND: Epigallocatechin-3-gallate (EGCG) has been demonstrated to inhibit cancer in experimental studies through its antioxidant activity and modulations on cellular functions by binding specific proteins. We demonstrated previously that EGCG upregulates the expression of microRNA (i.e. miR-210) by binding HIF-1α, resulting in reduced cell proliferation and anchorage-independent growth. However, the binding affinities of EGCG to HIF-1α and many other targets are higher than the EGCG plasma peak level in experimental animals administered with high dose of EGCG, raising a concern whether the microRNA regulation by HIF-1α is involved in the anti-cancer activity of EGCG in vivo. RESULTS: We employed functional genomic approaches to elucidate the role of microRNA in the EGCG inhibition of tobacco carcinogen-induced lung tumors in A/J mice. By analysing the microRNA profiles, we found modest changes in the expression levels of 21 microRNAs. By correlating these 21 microRNAs with the mRNA expression profiles using the computation methods, we identified 26 potential targeted genes of the 21 microRNAs. Further exploration using pathway analysis revealed that the most impacted pathways of EGCG treatment are the regulatory networks associated to AKT, NF-κB, MAP kinases, and cell cycle, and the identified miRNA targets are involved in the networks of AKT, MAP kinases and cell cycle regulation CONCLUSIONS: These results demonstrate that the miRNA-mediated regulation is actively involved in the major aspects of the anti-cancer activity of EGCG in vivo.

The emerging genomics and systems biology research lead to systems genomics studies.

Synergistically integrating multi-layer genomic data at systems level not only can lead to deeper insights into the molecular mechanisms related to disease initiation and progression, but also can guide pathway-based biomarker and drug target identification. With the advent of high-throughput next-generation sequencing technologies, sequencing both DNA and RNA has generated multi-layer genomic data that can provide DNA polymorphism, non-coding RNA, messenger RNA, gene expression, isoform and alternative splicing information. Systems biology on the other hand studies complex biological systems, particularly systematic study of complex molecular interactions within specific cells or organisms. Genomics and molecular systems biology can be merged into the study of genomic profiles and implicated biological functions at cellular or organism level. The prospectively emerging field can be referred to as systems genomics or genomic systems biology. The Mid-South Bioinformatics Centre (MBC) and Joint Bioinformatics Ph.D. Program of University of Arkansas at Little Rock and University of Arkansas for Medical Sciences are particularly interested in promoting education and research advancement in this prospectively emerging field. Based on past investigations and research outcomes, MBC is further utilizing differential gene and isoform/exon expression from RNA-seq and co-regulation from the ChiP-seq specific for different phenotypes in combination with protein-protein interactions, and protein-DNA interactions to construct high-level gene networks for an integrative genome-phoneme investigation at systems biology level.