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1.  Beyond Field Effect: Analysis of Shrunken Centroids in Normal Esophageal Epithelia Detects Concomitant Esophageal Adenocarcinoma 
Background and Aims:
Because of the extremely low neoplastic progression rate in Barrett’s esophagus, it is difficult to diagnose patients with concomitant adenocarcinoma early in their disease course. If biomarkers existed in normal squamous esophageal epithelium to identify patients with concomitant esophageal adenocarcinoma, potential applications would be far-reaching. The aim of the current study was to identify global gene expression patterns in normal esophageal epithelium capable of revealing simultaneous esophageal adenocarcinoma, even located remotely in the esophagus.
Methods:
Tissues comprised normal esophageal epithelia from 9 patients with esophageal adenocarcinoma, 8 patients lacking esophageal adenocarcinoma or Barrett’s, and 6 patients with Barrett’s esophagus alone. cDNA microarrays were performed, and pattern recognition in each of these subgroups was achieved using shrunken nearest centroid predictors.
Results:
Our method accurately discriminated normal esophageal epithelia of 8/8 patients without esophageal adenocarcinoma or Barrett’s esophagus and of 6/6 patients with Barrett’s esophagus alone from normal esophageal epithelia of 9/9 patients with Barrett’s esophagus and concomitant esophageal adenocarcinoma. Moreover, we identified genes differentially expressed between the above subgroups. Thus, based on their corresponding normal esophageal epithelia alone, our method accurately diagnosed patients who had concomitant esophageal adenocarcinoma.
Conclusions:
These global gene expression patterns, along with individual genes culled from them, represent potential biomarkers for the early diagnosis of esophageal adenocarcinoma from normal esophageal epithelia. Genes discovered in normal esophagus that are differentially expressed in patients with vs. without esophageal adenocarcinoma merit further pursuit in molecular genetic, functional, and therapeutic interventional studies.
PMCID: PMC2323355  PMID: 18425214
2.  Rarity of Somatic Mutation and Frequency of Normal Sequence Variation Detected in Sporadic Colon Adenocarcinoma Using High-Throughput cDNA Sequencing 
We performed high-throughput cDNA sequencing in colorectal adenocarcinoma and matching normal colorectal epithelium. All six hundred three genes in the UCSC database that were expressed in colon cancers and contained open reading frames of 1000 nucleotides or less were selected for study (total basepairs/bp, 366,686). 304,350 of these 366,686 bp (83.0%) were amplified and sequenced successfully. Seventy-eight sequence variants present in germline (i.e. normal) as well as matching somatic (i.e. tumor) DNA were discovered, yielding a frequency of 1 variant per 3,902 bp. Fifty-one of these sequence variants were homozygous (26 synonymous, 25 non-synonymous), while 27 were heterozygous (11 synonymous, 16 non-synonymous). Cancer tissue contained only one sequence-altered allele of the gene ATP50, which was present heterozygously alongside the wild-type allele in matching normal epithelium. Despite this relatively large number of bp and genes sequenced, no somatic mutations unique to tumor were found. High-throughput cDNA sequencing is a practical approach for detecting novel sequence variations and alterations in human tumors, such as those of the colon.
PMCID: PMC2287164  PMID: 18389087
3.  Beyond Field Effect: Analysis of Shrunken Centroids in Normal Esophageal Epithelia Detects Concomitant Esophageal Adenocarcinoma 
Background and Aims
Because of the extremely low neoplastic progression rate in Barrett’s esophagus, it is difficult to diagnose patients with concomitant adenocarcinoma early in their disease course. If biomarkers existed in normal squamous esophageal epithelium to identify patients with concomitant esophageal adenocarcinoma, potential applications would be far-reaching. The aim of the current study was to identify global gene expression patterns in normal esophageal epithelium capable of revealing simultaneous esophageal adenocarcinoma, even located remotely in the esophagus.
Methods
Tissues comprised normal esophageal epithelia from 9 patients with esophageal adenocarcinoma, 8 patients lacking esophageal adenocarcinoma or Barrett’s, and 6 patients with Barrett’s esophagus alone. cDNA microarrays were performed, and pattern recognition in each of these subgroups was achieved using shrunken nearest centroid predictors.
Results
Our method accurately discriminated normal esophageal epithelia of 8/8 patients without esophageal adenocarcinoma or Barrett’s esophagus and of 6/6 patients with Barrett’s esophagus alone from normal esophageal epithelia of 9/9 patients with Barrett’s esophagus and concomitant esophageal adenocarcinoma. Moreover, we identified genes differentially expressed between the above subgroups. Thus, based on their corresponding normal esophageal epithelia alone, our method accurately diagnosed patients who had concomitant esophageal adenocarcinoma.
Conclusions
These global gene expression patterns, along with individual genes culled from them, represent potential biomarkers for the early diagnosis of esophageal adenocarcinoma from normal esophageal epithelia. Genes discovered in normal esophagus that are differentially expressed in patients with vs. without esophageal adenocarcinoma merit further pursuit in molecular genetic, functional, and therapeutic interventional studies.
PMCID: PMC2323355  PMID: 18425214
4.  The HapMap Resource is Providing New Insights into Ourselves and its Application to Pharmacogenomics 
The exploration of quantitative variation in complex traits such as gene expression and drug response in human populations has become one of the major priorities for medical genetics. The International HapMap Project provides a key resource of genotypic data on human lymphoblastoid cell lines derived from four major world populations of European, African, Chinese and Japanese ancestry for researchers to associate with various phenotypic data to find genes affecting health, disease and response to drugs. Recent progress in dissecting genetic contribution to natural variation in gene expression within and among human populations and variation in drug response are two examples in which researchers have utilized the HapMap resource. The HapMap Project provides new insights into the human genome and has applicability to pharmacogenomics studies leading to personalized medicine.
PMCID: PMC2288550  PMID: 18392109
HapMap; Lymphoblastoid cell lines; Genotype; Gene expression; Population genetics
5.  Rarity of Somatic Mutation and Frequency of Normal Sequence Variation Detected in Sporadic Colon Adenocarcinoma Using High-Throughput cDNA Sequencing 
We performed high-throughput cDNA sequencing in colorectal adenocarcinoma and matching normal colorectal epithelium. All six hundred three genes in the UCSC database that were expressed in colon cancers and contained open reading frames of 1000 nucleotides or less were selected for study (total basepairs/bp, 366,686). 304,350 of these 366,686 bp (83.0%) were amplified and sequenced successfully. Seventy-eight sequence variants present in germline (i.e. normal) as well as matching somatic (i.e. tumor) DNA were discovered, yielding a frequency of 1 variant per 3,902 bp. Fifty-one of these sequence variants were homozygous (26 synonymous, 25 non-synonymous), while 27 were heterozygous (11 synonymous, 16 non-synonymous). Cancer tissue contained only one sequence-altered allele of the gene ATP50, which was present heterozygously alongside the wild-type allele in matching normal epithelium. Despite this relatively large number of bp and genes sequenced, no somatic mutations unique to tumor were found. High-throughput cDNA sequencing is a practical approach for detecting novel sequence variations and alterations in human tumors, such as those of the colon.
PMCID: PMC2287164  PMID: 18389087
6.  The HapMap Resource is Providing New Insights into Ourselves and its Application to Pharmacogenomics 
The exploration of quantitative variation in complex traits such as gene expression and drug response in human populations has become one of the major priorities for medical genetics. The International HapMap Project provides a key resource of genotypic data on human lymphoblastoid cell lines derived from four major world populations of European, African, Chinese and Japanese ancestry for researchers to associate with various phenotypic data to find genes affecting health, disease and response to drugs. Recent progress in dissecting genetic contribution to natural variation in gene expression within and among human populations and variation in drug response are two examples in which researchers have utilized the HapMap resource. The HapMap Project provides new insights into the human genome and has applicability to pharmacogenomics studies leading to personalized medicine.
PMCID: PMC2288550  PMID: 18392109
HapMap; lymphoblastoid cell lines; genotype; gene expression; population genetics
7.  High-Throughput Sequencing of miRNAs Reveals a Tissue Signature in Gastric Cancer and Suggests Novel Potential Biomarkers 
Bioinformatics and Biology Insights  2015;9(Suppl 1):1-8.
Gastric cancer has a high incidence and mortality rate worldwide; however, the use of biomarkers for its clinical diagnosis remains limited. The microRNAs (miRNAs) are biomarkers with the potential to identify the risk and prognosis as well as therapeutic targets. We performed the ultradeep miRnomes sequencing of gastric adenocarcinoma and gastric antrum without tumor samples. We observed that a small set of those samples were responsible for approximately 80% of the total miRNAs expression, which might represent a miRNA tissue signature. Additionally, we identified seven miRNAs exhibiting significant differences, and, of these, hsa-miR-135b and hsa-miR-29c were able to discriminate antrum without tumor from gastric cancer regardless of the histological type. These findings were validated by quantitative real-time polymerase chain reaction. The results revealed that hsa-miR-135b and hsa-miR-29c are potential gastric adenocarcinoma occurrence biomarkers with the ability to identify individuals at a higher risk of developing this cancer, and could even be used as therapeutic targets to allow individualized clinical management.
doi:10.4137/BBI.S23773
PMCID: PMC4485834  PMID: 26157332
gastric cancer; miRnome; biomarkers; NGS
8.  Computational and in vitro Investigation of miRNA-Gene Regulations in Retinoblastoma Pathogenesis: miRNA Mimics Strategy 
PURPOSE
Retinoblastoma (RB), a primary pediatric intraocular tumor, arises from primitive retinal layers. Several novel molecular strategies are being developed for the clinical management of RB. miRNAs are known to regulate cancer-relevant biological processes. Here, the role of selected miRNAs, namely, miR-532-5p and miR-486-3p, has been analyzed for potential therapeutic targeting in RB.
METHODS
A comprehensive bioinformatic analysis was performed to predict the posttranscriptional regulators (miRNAs) of the select panel of genes [Group 1: oncogenes (HMGA2, MYCN, SYK, FASN); Group 2: cancer stem cell markers (TACSTD, ABCG2, CD133, CD44, CD24) and Group 3: cell cycle regulatory proteins (p53, MDM2)] using Microcosm, DIANALAB, miRBase v 18, and REFSEQ database, and RNA hybrid. The expressions of five miRNAs, namely, miR-146b-5p, miR-532-5p, miR-142-5p, miR-328, and miR-486-3p, were analyzed by qRT–PCR on primary RB tumor samples (n = 30; including 17 invasive RB tumors and 13 noninvasive RB tumors). Detailed complementary alignment between 5’ seed sequence of differentially expressed miRNAs and the sequence of target genes was determined. Based on minimum energy level and piCTAR scores, the gene targets were selected. Functional roles of these miRNA clusters were studied by using mimics in cultured RB (Y79, Weri Rb-1) cells in vitro. The gene targets (SYK and FASN) of the studied miRNAs were confirmed by qRT-PCR and western blot analysis. Cell proliferation and apoptotic studies were performed.
RESULTS
Nearly 1948 miRNAs were identified in the in silico analysis, From this list, only 9 upregulated miRNAs (miR-146b-5p, miR-305, miR-663b, miR-299, miR-532-5p, miR-892b, miR-501, miR-142-5p, and miR-513b) and 10 downregulated miRNAs (miR-1254, miR-328, miR-133a, miR-1287, miR-1299, miR-375, miR-486-3p, miR-720, miR-98, and miR-122*) were found to be common with the RB serum miRNA profile. Downregulation of five miRNAs (miR-146b-5p, miR-532-5p, miR-142-5p, miR-328, and miR-486-3p) was confirmed experimentally. Predicted common oncogene targets (SYK and FASN) of miR-486-3p and miR-532-5p were evaluated for their mRNA and protein expression in these miRNA mimic-treated RB cells. Experimental overexpression of these miRNAs mediated apoptotic cell death without significantly altering the cell cycle in RB cells.
CONCLUSION
Key miRNAs in RB pathogenesis were identified by an in silico approach. Downregulation of miR-486-3p and miR-532-5p in primary retinoblastoma tissues implicates their role in tumorigenesis. Prognostic and therapeutic potential of these miRNA was established by the miRNA mimic strategy.
doi:10.4137/BBI.S21742
PMCID: PMC4429751  PMID: 25983556
bio-informatics analysis; miRNA-mRNA; mimics; retinoblastoma
9.  Metagenomics: Tools and Insights for Analyzing Next-Generation Sequencing Data Derived from Biodiversity Studies 
Advances in next-generation sequencing (NGS) have allowed significant breakthroughs in microbial ecology studies. This has led to the rapid expansion of research in the field and the establishment of “metagenomics”, often defined as the analysis of DNA from microbial communities in environmental samples without prior need for culturing. Many metagenomics statistical/computational tools and databases have been developed in order to allow the exploitation of the huge influx of data. In this review article, we provide an overview of the sequencing technologies and how they are uniquely suited to various types of metagenomic studies. We focus on the currently available bioinformatics techniques, tools, and methodologies for performing each individual step of a typical metagenomic dataset analysis. We also provide future trends in the field with respect to tools and technologies currently under development. Moreover, we discuss data management, distribution, and integration tools that are capable of performing comparative metagenomic analyses of multiple datasets using well-established databases, as well as commonly used annotation standards.
doi:10.4137/BBI.S12462
PMCID: PMC4426941  PMID: 25983555
metagenomics; next-generation sequencing; computational tools; data analysis
10.  Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists 
Omics technologies enable unbiased investigation of biological systems through massively parallel sequence acquisition or molecular measurements, bringing the life sciences into the era of Big Data. A central challenge posed by such omics datasets is how to transform these data into biological knowledge, for example, how to use these data to answer questions such as: Which functional pathways are involved in cell differentiation? Which genes should we target to stop cancer? Network analysis is a powerful and general approach to solve this problem consisting of two fundamental stages, network reconstruction, and network interrogation. Here we provide an overview of network analysis including a step-by-step guide on how to perform and use this approach to investigate a biological question. In this guide, we also include the software packages that we and others employ for each of the steps of a network analysis workflow.
doi:10.4137/BBI.S12467
PMCID: PMC4415676  PMID: 25983554
network reconstruction; network interrogation; systems biology; big data; data integration; inter-omics network; transkingdom network
11.  Cross-Disciplinary Detection and Analysis of Network Motifs 
The detection of network motifs has recently become an important part of network analysis across all disciplines. In this work, we detected and analyzed network motifs from undirected and directed networks of several different disciplines, including biological network, social network, ecological network, as well as other networks such as airlines, power grid, and co-purchase of political books networks. Our analysis revealed that undirected networks are similar at the basic three and four nodes, while the analysis of directed networks revealed the distinction between networks of different disciplines. The study showed that larger motifs contained the three-node motif as a subgraph. Topological analysis revealed that similar networks have similar small motifs, but as the motif size increases, differences arise. Pearson correlation coefficient showed strong positive relationship between some undirected networks but inverse relationship between some directed networks. The study suggests that the three-node motif is a building block of larger motifs. It also suggests that undirected networks share similar low-level structures. Moreover, similar networks share similar small motifs, but larger motifs define the unique structure of individuals. Pearson correlation coefficient suggests that protein structure networks, dolphin social network, and co-authorships in network science belong to a superfamily. In addition, yeast protein–protein interaction network, primary school contact network, Zachary’s karate club network, and co-purchase of political books network can be classified into a superfamily.
doi:10.4137/BBI.S23619
PMCID: PMC4403903  PMID: 25983553
network motifs; biological networks; social networks; directed network; undirected network; network motif detection
12.  An Interpretation of the Ancestral Codon from Miller’s Amino Acids and Nucleotide Correlations in Modern Coding Sequences 
Purine bias, which is usually referred to as an “ancestral codon”, is known to result in short-range correlations between nucleotides in coding sequences, and it is common in all species. We demonstrate that RWY is a more appropriate pattern than the classical RNY, and purine bias (Rrr) is the product of a network of nucleotide compensations induced by functional constraints on the physicochemical properties of proteins. Through deductions from universal correlation properties, we also demonstrate that amino acids from Miller’s spark discharge experiment are compatible with functional primeval proteins at the dawn of living cell radiation on earth. These amino acids match the hydropathy and secondary structures of modern proteins.
doi:10.4137/BBI.S24021
PMCID: PMC4401237  PMID: 25922573
genomics; ancestral codon; purine bias; short-range correlations; protein features
13.  A Systems Biology Approach Reveals the Dose- and Time-Dependent Effect of Primary Human Airway Epithelium Tissue Culture After Exposure to Cigarette Smoke In Vitro 
To establish a relevant in vitro model for systems toxicology-based mechanistic assessment of environmental stressors such as cigarette smoke (CS), we exposed human organotypic bronchial epithelial tissue cultures at the air liquid interface (ALI) to various CS doses. Previously, we compared in vitro gene expression changes with published human airway epithelia in vivo data to assess their similarities. Here, we present a follow-up evaluation of these in vitro transcriptomics data, using complementary computational approaches and an integrated mRNA–microRNA (miRNA) analysis. The main cellular pathways perturbed by CS exposure were related to stress responses (oxidative stress and xenobiotic metabolism), inflammation (inhibition of nuclear factor-κB and the interferon gamma-dependent pathway), and proliferation/differentiation. Within post-exposure periods up to 48 hours, a transient kinetic response was observed at lower CS doses, whereas higher doses resulted in more sustained responses. In conclusion, this systems toxicology approach has potential for product testing according to “21st Century Toxicology”.
doi:10.4137/BBI.S19908
PMCID: PMC4357630  PMID: 25788831
air liquid interface; cigarette smoke; mechanistic investigations; organotypic culture; systems biology
14.  Identification and Expression Analysis of Ribosome Biogenesis Factor Co-orthologs in Solanum lycopersicum 
Ribosome biogenesis involves a large inventory of proteinaceous and RNA cofactors. More than 250 ribosome biogenesis factors (RBFs) have been described in yeast. These factors are involved in multiple aspects like rRNA processing, folding, and modification as well as in ribosomal protein (RP) assembly. Considering the importance of RBFs for particular developmental processes, we examined the complexity of RBF and RP (co-)orthologs by bioinformatic assignment in 14 different plant species and expression profiling in the model crop Solanum lycopersicum. Assigning (co-)orthologs to each RBF revealed that at least 25% of all predicted RBFs are encoded by more than one gene. At first we realized that the occurrence of multiple RBF co-orthologs is not globally correlated to the existence of multiple RP co-orthologs. The transcript abundance of genes coding for predicted RBFs and RPs in leaves and anthers of S. lycopersicum was determined by next generation sequencing (NGS). In combination with existing expression profiles, we can conclude that co-orthologs of RBFs by large account for a preferential function in different tissue or at distinct developmental stages. This notion is supported by the differential expression of selected RBFs during male gametophyte development. In addition, co-regulated clusters of RBF and RP coding genes have been observed. The relevance of these results is discussed.
doi:10.4137/BBI.S20751
PMCID: PMC4325683  PMID: 25698879
next generation sequencing; orthologous prediction; ribosome biogenesis; MACE; qRT-PCR; tomato
15.  POEAS: Automated Plant Phenomic Analysis Using Plant Ontology 
Biological enrichment analysis using gene ontology (GO) provides a global overview of the functional role of genes or proteins identified from large-scale genomic or proteomic experiments. Phenomic enrichment analysis of gene lists can provide an important layer of information as well as cellular components, molecular functions, and biological processes associated with gene lists. Plant phenomic enrichment analysis will be useful for performing new experiments to better understand plant systems and for the interpretation of gene or proteins identified from high-throughput experiments. Plant ontology (PO) is a compendium of terms to define the diverse phenotypic characteristics of plant species, including plant anatomy, morphology, and development stages. Adoption of this highly useful ontology is limited, when compared to GO, because of the lack of user-friendly tools that enable the use of PO for statistical enrichment analysis. To address this challenge, we introduce Plant Ontology Enrichment Analysis Server (POEAS) in the public domain. POEAS uses a simple list of genes as input data and performs enrichment analysis using Ontologizer 2.0 to provide results in two levels, enrichment results and visualization utilities, to generate ontological graphs that are of publication quality. POEAS also offers interactive options to identify user-defined background population sets, various multiple-testing correction methods, different enrichment calculation methods, and resampling tests to improve statistical significance. The availability of such a tool to perform phenomic enrichment analyses using plant genes as a complementary resource will permit the adoption of PO-based phenomic analysis as part of analytical workflows. POEAS can be accessed using the URL http://caps.ncbs.res.in/poeas.
doi:10.4137/BBI.S19057
PMCID: PMC4274039  PMID: 25574136
phenomics; plant ontology; phenotype enrichment; plant genomics; Arabidopsis thaliana
16.  Computational Methods for CLIP-seq Data Processing 
RNA-binding proteins (RBPs) are at the core of post-transcriptional regulation and thus of gene expression control at the RNA level. One of the principal challenges in the field of gene expression regulation is to understand RBPs mechanism of action. As a result of recent evolution of experimental techniques, it is now possible to obtain the RNA regions recognized by RBPs on a transcriptome-wide scale. In fact, CLIP-seq protocols use the joint action of CLIP, crosslinking immunoprecipitation, and high-throughput sequencing to recover the transcriptome-wide set of interaction regions for a particular protein. Nevertheless, computational methods are necessary to process CLIP-seq experimental data and are a key to advancement in the understanding of gene regulatory mechanisms. Considering the importance of computational methods in this area, we present a review of the current status of computational approaches used and proposed for CLIP-seq data.
doi:10.4137/BBI.S16803
PMCID: PMC4196881  PMID: 25336930
RNA-binding proteins; RBP; CLIP-based; CLIP-seq; HITS-CLIP; PAR-CLIP; RBPome; RNA–Protein; post transcriptional regulation
17.  Interactions Among Plant Transcription Factors Regulating Expression of Stress-responsive Genes 
Plants are simultaneously subjected to a variety of stress conditions in the field and are known to combat the hostile conditions by up/down-regulating number of genes. There exists a significant level of cross-talk between different stress responses in plants. In this study, we predict the interacting pairs of transcription factors that regulate the multiple abiotic stress-responsive genes in the plant Arabidopsis thaliana. We identified the interacting pair(s) of transcription factors (TFs) based on the spatial proximity of their binding sites. We also examined the interactions between the predicted pairs of TFs using molecular docking. Subsequent to docking, the best interaction pose was selected using our scoring scheme DockScore, which ranks the docked solutions based on several interface parameters and aims to find optimal interactions between proteins. We analyzed the selected docked pose for the interface residues and their conservation.
doi:10.4137/BBI.S16313
PMCID: PMC4167486  PMID: 25249757
transcription factors; protein–protein interactions; Arabidopsis thaliana; docking; stress conditions
18.  Integrated Analysis of Dysregulated miRNA-gene Expression in HMGA2-silenced Retinoblastoma Cells 
Retinoblastoma (RB) is a primary childhood eye cancer. HMGA2 shows promise as a molecule for targeted therapy. The involvement of miRNAs in genome-level molecular dys-regulation in HMGA2-silenced RB cells is poorly understood. Through miRNA expression microarray profiling, and an integrated array analysis of the HMGA2-silenced RB cells, the dysregulated miRNAs and the miRNA-target relationships were modelled. Loop network analysis revealed a regulatory association between the transcription factor (SOX5) and the deregulated miRNAs (miR-29a, miR-9*, miR-9-3). Silencing of HMGA2 deregulated the vital oncomirs (miR-7, miR-331, miR-26a, miR-221, miR-17~92 and miR-106b∼25) in RB cells. From this list, the role of the miR-106b∼25 cluster was examined further for its expression in primary RB tumor tissues (n = 20). The regulatory targets of miR-106b∼25 cluster namely p21 (cyclin-dependent kinase inhibitor) and BIM (pro-apoptotic gene) were elevated, and apoptotic cell death was observed, in RB tumor cells treated with the specific antagomirs of the miR-106b∼25 cluster. Thus, suppression of miR-106b∼25 cluster controls RB tumor growth. Taken together, HMGA2 mediated anti-tumor effect present in RB is, in part, mediated through the miR-106b∼25 cluster.
doi:10.4137/BBI.S16958
PMCID: PMC4159370  PMID: 25232279
Retinoblastoma; High mobility group proteins (HMG)A2; miR-106b-25 cluster; Integrated mRNA-miRNA analysis; Antagomirs
19.  Computational Identification of Dengue Virus MicroRNA-Like Structures and their Cellular Targets 
MicroRNAs (miRNAs) are small, noncoding RNA molecules that regulate transcriptional and posttranscriptional gene regulation of the cell. Experimental evidence shows that miRNAs have a direct role in different cellular processes, such as immune function, apoptosis, and tumorigenesis. In a viral infection context, miRNAs have been connected with the interplay between host and pathogen, occupying a major role in pathogenesis. While numerous viral miRNAs from DNA viruses have been identified, characterization of functional RNA virus-encoded miRNAs and their potential targets is still ongoing. Here, we used an in silico approach to analyze dengue Virus genome sequences. Pre-miRNAs were extracted through VMir software, and the identification of putative pre-miRNAs and mature miRNAs was accessed using Support Vector Machine web tools. The targets were scanned using miRanda software and functionally annotated using ClueGo. Via computational tools, eight putative miRNAs were found to hybridize with numerous targets of morphogenesis, differentiation, migration, and growth pathways that may play a major role in the interaction of the virus and its host. Future approaches will focus on experimental validation of their presence and target messenger RNA genes to further elucidate their biological functions in human and mosquito cells.
doi:10.4137/BBI.S13649
PMCID: PMC4149395  PMID: 25210446
flavivirus; dengue virus; in silico screening; microRNA precursor; target prediction; functional annotation
20.  In Silico Studies of Medicinal Compounds Against Hepatitis C Capsid Protein from North India 
Hepatitis viral infection is a leading cause of chronic hepatitis, cirrhosis, and hepatocellular carcinoma (HCC). Over one million people are estimated to be persistently infected with hepatitis C virus (HCV) worldwide. As capsid core protein is the key element in spreading HCV; hence, it is considered to be the superlative target of antiviral compounds. Novel drug inhibitors of HCV are in need to complement or replace the current treatments such as pegylated interferon’s and ribavirin as they are partially booming and beset with various side effects. Our study was conducted to predict 3D structure of capsid core protein of HCV from northern part of India. Core, the capsid protein of HCV, handles the assembly and packaging of HCV RNA genome and is the least variable of all the ten HCV proteins among the six HCV genotypes. Therefore, we screened four phytochemicals inhibitors that are known to disrupt the interactions of core and other HCV proteins such as (a) epigallocatechin gallate (EGCG), (b) ladanein, (c) naringenin, and (d) silybin extracted from medicinal plants; targeted against active site of residues of HCV-genotype 3 (G3) (Q68867) and its subtypes 3b (Q68861) and 3g (Q68865) from north India. To study the inhibitory activity of the recruited flavonoids, we conducted a quantitative structure–activity relationship (QSAR). Furthermore, docking interaction suggests that EGCG showed a maximum number of hydrogen bond (H-bond) interactions with all the three modeled capsid proteins with high interaction energy followed by naringenin and silybin. Thus, our results strongly correlate the inhibitory activity of the selected bioflavonoid. Finally, the dynamic predicted capsid protein molecule of HCV virion provides a general avenue to target structure-based antiviral compounds that support the hypothesis that the screened inhibitors for viral capsid might constitute new class of potent agents but further confirmation is necessary using in vitro and in vivo studies.
doi:10.4137/BBI.S15211
PMCID: PMC4076477  PMID: 25002815
hepatitis C virus; hepatocellular carcinoma; capsid protein; docking; inhibitors
21.  DOR – a Database of Olfactory Receptors – Integrated Repository for Sequence and Secondary Structural Information of Olfactory Receptors in Selected Eukaryotic Genomes 
Olfaction is the response to odors and is mediated by a class of membrane-bound proteins called olfactory receptors (ORs). An understanding of these receptors serves as a good model for basic signal transduction mechanisms and also provides important clues for the strategies adopted by organisms for their ultimate survival using chemosensory perception in search of food or defense against predators. Prior research on cross-genome phylogenetic analyses from our group motivated the addressal of conserved evolutionary trends, clustering, and ortholog prediction of ORs. The database of olfactory receptors (DOR) is a repository that provides sequence and structural information on ORs of selected organisms (such as Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, and Homo sapiens). Users can download OR sequences, study predicted membrane topology, and obtain cross-genome sequence alignments and phylogeny, including three-dimensional (3D) structural models of 100 selected ORs and their predicted dimer interfaces. The database can be accessed from http://caps.ncbs.res.in/DOR. Such a database should be helpful in designing experiments on point mutations to probe into the possible dimerization modes of ORs and to even understand the evolutionary changes between different receptors.
doi:10.4137/BBI.S14858
PMCID: PMC4069036  PMID: 25002814
olfaction; insect olfactory system; membrane proteins; odor perception
22.  Identification of Chicken Pulmonary miRNAs Targeting PB1, PB1-F2, and N40 Genes of Highly Pathogenic Avian Influenza Virus H5N1 In Silico 
Highly pathogenic Avian influenza (HPAI) is a notifiable viral disease caused by avian influenza type A viruses of the Orthomyxoviridae family. Type A influenza genome consists of eight segments of negative-sense RNA. RNA segment 2 encodes three proteins, PB1, PB1-F2, and N40, which are translated from the same mRNA by ribosomal leaky scanning and reinitiation. Since these proteins are critical for viral replication and pathogenesis, targeting their expression can be one of the approaches to control and resist HPAI. MicroRNAs are short noncoding RNAs that regulate a variety of biological processes such as cell growth, tissue differentiation, apoptosis, and viral infection. In this study, a set of 300 miRNAs expressed in chicken lungs were screened against the HPAI virus (H5N1) segment 2 with different screening parameter like thermodynamic stability of heteroduplex, seed sequence complementarity, conserved target sequence, and target-site accessibility for identifying miRNAs that can potentially target the transcript of segment 2 of H5N1. Chicken miRNAs gga-mir-133c, gga-mir-1710, and gga-mir-146c* are predicted to target the expression of PB1, PB1-F2, and N40 proteins. This indicates that chicken has genetic potential to resist/tolerate H5N1 infection and these can be suitably exploited in designing strategies for control of avian influenza in chicken.
doi:10.4137/BBI.S14631
PMCID: PMC4069037  PMID: 25002813
chicken; miRNA; H5N1; PB1; PB1-F2; N40
23.  A Protocol for mtGenome Analysis on Large Sample Numbers 
The mitochondrial genome is widely studied in a variety of fields, such as population, forensic, and human and medical genetics. Most studies have been limited to a small portion of the sequence that, although highly diverse, does not describe the total variability. The arrival of modern high-throughput sequencing technologies has made it possible to investigate larger sequences in a shorter amount of time as well as in a more affordable fashion. This work aims to describe a protocol for sequencing and analyzing the complete mitochondrial genome with the Ion PGM™ platform. To evaluate the protocol, the mitochondrial genome was sequenced to approximately 210 Mbp, with high-quality sequences distributed between 12 samples that had an average coverage of 1023× per sample. Several variant callers were compared to improve the protocol outcome. The results suggest that it is possible to run up to 120 samples per run without any loss of any significant quality. Therefore, this protocol is an efficient and accurate tool for full mitochondrial genome analysis.
doi:10.4137/BBI.S14623
PMCID: PMC4069038  PMID: 25002812
next-generation sequencing; mitochondrial DNA; analysis protocol; polymorphism; population genetics
24.  High-throughput Methods Redefine the Rumen Microbiome and Its Relationship with Nutrition and Metabolism 
Diversity in the forestomach microbiome is one of the key features of ruminant animals. The diverse microbial community adapts to a wide array of dietary feedstuffs and management strategies. Understanding rumen microbiome composition, adaptation, and function has global implications ranging from climatology to applied animal production. Classical knowledge of rumen microbiology was based on anaerobic, culture-dependent methods. Next-generation sequencing and other molecular techniques have uncovered novel features of the rumen microbiome. For instance, pyrosequencing of the 16S ribosomal RNA gene has revealed the taxonomic identity of bacteria and archaea to the genus level, and when complemented with barcoding adds multiple samples to a single run. Whole genome shotgun sequencing generates true metagenomic sequences to predict the functional capability of a microbiome, and can also be used to construct genomes of isolated organisms. Integration of high-throughput data describing the rumen microbiome with classic fermentation and animal performance parameters has produced meaningful advances and opened additional areas for study. In this review, we highlight recent studies of the rumen microbiome in the context of cattle production focusing on nutrition, rumen development, animal efficiency, and microbial function.
doi:10.4137/BBI.S15389
PMCID: PMC4055558  PMID: 24940050
cattle; metabolism; microbiome; nutrition; rumen
25.  The Purine Bias of Coding Sequences is Determined by Physicochemical Constraints on Proteins 
For this report, we analyzed protein secondary structures in relation to the statistics of three nucleotide codon positions. The purpose of this investigation was to find which properties of the ribosome, tRNA or protein level, could explain the purine bias (Rrr) as it is observed in coding DNA. We found that the Rrr pattern is the consequence of a regularity (the codon structure) resulting from physicochemical constraints on proteins and thermodynamic constraints on ribosomal machinery. The physicochemical constraints on proteins mainly come from the hydropathy and molecular weight (MW) of secondary structures as well as the energy cost of amino acid synthesis. These constraints appear through a network of statistical correlations, such as (i) the cost of amino acid synthesis, which is in favor of a higher level of guanine in the first codon position, (ii) the constructive contribution of hydropathy alternation in proteins, (iii) the spatial organization of secondary structure in proteins according to solvent accessibility, (iv) the spatial organization of secondary structure according to amino acid hydropathy, (v) the statistical correlation of MW with protein secondary structures and their overall hydropathy, (vi) the statistical correlation of thymine in the second codon position with hydropathy and the energy cost of amino acid synthesis, and (vii) the statistical correlation of adenine in the second codon position with amino acid complexity and the MW of secondary protein structures. Amino acid physicochemical properties and functional constraints on proteins constitute a code that is translated into a purine bias within the coding DNA via tRNAs. In that sense, the Rrr pattern within coding DNA is the effect of information transfer on nucleotide composition from protein to DNA by selection according to the codon positions. Thus, coding DNA structure and ribosomal machinery co-evolved to minimize the energy cost of protein coding given the functional constraints on proteins.
doi:10.4137/BBI.S13161
PMCID: PMC4039185  PMID: 24899802
genomics; ancestral codon; RNY; purine bias; secondary structure; helix; sheet; turn coil; ribosome; translation; energy cost

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