Analyzes of genome-wide association follow-up study for calving traits in dairy cattle

Background

Genomic islands play an important role in medical, methylation and biological studies. To explore the region, we propose a CpG islands prediction analysis platform for genome sequence exploration (CpGPAP).

Results

CpGPAP is a web-based application that provides a user-friendly interface for predicting CpG islands in genome sequences or in user input sequences. The prediction algorithms supported in CpGPAP include complementary particle swarm optimization (CPSO), a complementary genetic algorithm (CGA) and other methods (CpGPlot, CpGProD and CpGIS) found in the literature. The CpGPAP platform is easy to use and has three main features (1) selection of the prediction algorithm; (2) graphic visualization of results; and (3) application of related tools and dataset downloads. These features allow the user to easily view CpG island results and download the relevant island data. CpGPAP is freely available at http://bio.kuas.edu.tw/CpGPAP/.

Conclusions

The platform's supported algorithms (CPSO and CGA) provide a higher sensitivity and a higher correlation coefficient when compared to CpGPlot, CpGProD, CpGIS, and CpGcluster over an entire chromosome.     

webFOG: A web tool to map genomic features onto genes

A large number of new genomic features are being discovered using high throughput techniques. The next challenge is to automatically map them to the reference genome for further analysis and functional annotation. We have developed a tool that can be used to map important genomic features to the latest version of the human genome and also to annotate new features. These genomic features could be of many different source types, including miRNAs, microarray primers or probes, Chip-on-Chip data, CpG islands and SNPs to name a few. A standalone version and web interface for the tool can be accessed through: http://populationhealth.qimr.edu.au/cgi-bin/webFOG/index.cgi. The project details and source code is also available at http://www.bioinformatics.org/webfog.     

CRISPcut: A novel tool for designing optimal sgRNAs for CRISPR/Cas9 based experiments in human cells

The ability to direct the CRISPR/Cas9 nuclease to a unique target site within a genome would have broad use in targeted genome engineering. However, CRISPR RNA is reported to bind to other genomic locations that differ from the intended target site by a few nucleotides, demonstrating significant off-target activity. We have developed the CRISPcut tool that screens the off-targets using various parameters and predicts the ideal genomic target for –guide RNAs in human cell lines. sgRNAs for four different types of Cas9 nucleases can be designed with an option for the user to work with different PAM sequences. Direct experimental measurement of genome-wide DNA accessibility is incorporated that effectively restricts the prediction of CRISPR targets to open chromatin. An option to predict target sites for paired CRISPR nickases is also provided. The tool has been validated using a dataset of experimentally used sgRNA and their identified off-targets.URL: http://web.iitd.ac.in/crispcut     

PHProteomicDB： A Module for Two-dimensional Gel Electrophoresis Database Creation on Personal Web Sites

PHProteomicDB is a PHP-written module to help researchers in proteomics to share two-dimenslonal gel electrophoresis data using personal web sites. No technical or PHP knowledge is necessary except a few basics about web site management. PHProteomicDB has a user-friendly administration interface to enter and update data. It creates web pages on the fly displaying gel characteristics, gel pictures, and numbered gel spots with their related identifications pointing to their reference pages in protein databanks. The module is freely available at http：//www.huvec.com/index.php3？rub=Download.     

A species-generalized probabilistic model-based definition of CpG islands

The DNA of most vertebrates is depleted in CpG dinucleotides, the target for DNA methylation. The remaining CpGs tend to cluster in regions referred to as CpG islands (CGI). CGI have been useful as marking functionally relevant epigenetic loci for genome studies. For example, CGI are enriched in the promoters of vertebrate genes and thought to play an important role in regulation. Currently, CGI are defined algorithmically as an observed-to-expected ratio (O/E) of CpG greater than 0.6, G+C content greater than 0.5, and usually but not necessarily greater than a certain length. Here we find that the current definition leaves out important CpG clusters associated with epigenetic marks, relevant to development and disease, and does not apply at all to nonvertabrate genomes. We propose an alternative Hidden Markov model-based approach that solves these problems. We fit our model to genomes from 30 species, and the results support a new epigenomic view toward the development of DNA methylation in species diversity and evolution. The O/E of CpG in islands and nonislands segregated closely phylogenetically and showed substantial loss in both groups in animals of greater complexity, while maintaining a nearly constant difference in CpG O/E between islands and nonisland compartments. Lists of CGI for some species are available at http://www.rafalab.org.     

SESAME (SEquence Sorter & AMplicon Explorer): genotyping based on high-throughput multiplex amplicon sequencing

SUMMARY: Characterizing genetic diversity through genotyping short amplicons is central to evolutionary biology. Next-generation sequencing (NGS) technologies changed the scale at which these type of data are acquired. SESAME is a web application package that assists genotyping of multiplexed individuals for several markers based on NGS amplicon sequencing. It automatically assigns reads to loci and individuals, corrects reads if standard samples are available and provides an intuitive graphical user interface (GUI) for allele validation based on the sequences and associated decision-making tools. The aim of SESAME is to help allele identification among a large number of sequences. AVAILABILITY: SESAME and its documentation are freely available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported Licence for Windows and Linux from http://www1.montpellier.inra.fr/CBGP/NGS/ or http://tinyurl.com/ngs-sesame.     

GIV: A Tool for Genomic Islands Visualization

A Genomic Islands (GI) is a chunk of DNA sequence in a genome whose origin can be traced back to other organisms or viruses. The detection of GIs plays an indispensable role in biomedical research, due to the fact that GIs are highly related to special functionalities such as disease-causing GIs - pathogenicity islands. It is also very important to visualize genomic islands, as well as the supporting features corresponding to the genomic islands in the genome. We have developed a program, Genomic Island Visualization (GIV), which displays the locations of genomic islands in a genome, as well as the corresponding supportive feature information for GIs. GIV was implemented in C++, and was compiled and executed on Linux/Unix operating systems.

Availability

GIV is freely available for non-commercial use at http://www5.esu.edu/cpsc/bioinfo/software/GIV     

miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs

miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs. The fundamental design of miRDeepFinder is based on miRNA biogenesis, miRNA-mediated gene regulation and target recognition, such as perfect or near perfect hairpin structures, different read abundances of miRNA and miRNA*, and targeting patterns of plant miRNAs. To test the accuracy and robustness of miRDeepFinder, we analyzed a small RNA deep sequencing dataset of Arabidopsis thaliana published in the GEO database of NCBI. Our test retrieved 128 of 131 (97.7%) known miRNAs that have a more than 3 read count in Arabidopsis. Because many known miRNAs are not associated with miRNA*s in small RNA datasets, miRDeepFinder was also designed to recover miRNA candidates without the presence of miRNA*. To mine as many miRNAs as possible, miRDeepFinder allows users to compare mature miRNAs and their miRNA*s with other small RNA datasets from the same species. Cleaveland software package was also incorporated into miRDeepFinder for miRNA target identification using degradome sequencing analysis. Using this new computational tool, we identified 13 novel miRNA candidates with miRNA*s from Arabidopsis and validated 12 of them experimentally. Interestingly, of the 12 verified novel miRNAs, a miRNA named AC1 spans the exons of two genes (UTG71C4 and UGT71C3). Both the mature AC1 miRNA and its miRNA* were also found in four other small RNA datasets. We also developed a tool, ??miRNA primer designer?? to design primers for any type of miRNAs. miRDeepFinder provides a powerful tool for analyzing small RNA datasets from all species, with or without the availability of genome information. miRDeepFinder and miRNA primer designer are freely available at http://www.leonxie.com/DeepFinder.php and at http://www.leonxie.com/miRNAprimerDesigner.php, respectively. A program (called RefFinder: http://www.leonxie.com/referencegene.php) was also developed for assessing the reliable reference genes for gene expression analysis, including miRNAs.     

29 Accelerating nucleic acid design using pre-selected sequences

Nanoscale nucleic acids could potentially be designed to be catalysts, pharmaceuticals, or probes for detecting pathogens. We hypothesize that designing nucleic acid molecules from pre-selected sequences, rather than from random sequences, would increase the speed of designing large molecules and also increase the accuracy of design. Helices should be formed in the optimal folding free energy change range, have maximal structure probability, and minimal ensemble defect. Loops should be composed of sequences with the lowest ensemble free energy change. All sequences should have low tendency to cross- and self-hybridize. These features are observed in RNA sequences with known structure.We demonstrate that preselected sequences and accelerate the design of structures that are mimics of biologically relevant structures. This is implemented as a new structure design component of RNAstructure (http://rna.urmc.rochester.edu/RNAstructure.html). This work is a collaboration with Celadon Laboratories, Inc. (http://www.celadonlabs.com/).     

A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions

This article is a response to Wang and Luo. See correspondence article http://www.biomedcentral.com/1741-7007/10/30/ [WEBCITE] and the original research article http://www.biomedcentral.com/1741-7007/9/24 [WEBCITE].     

CpGProD: identifying CpG islands associated with transcription start sites in large genomic mammalian sequences

RESULTS: CpGProD is an application for identifying mammalian promoter regions associated with CpG islands in large genomic sequences. Although it is strictly dedicated to this particular promoter class corresponding to approximately 50% of the genes, CpGProD exhibits a higher sensitivity and specificity than other tools used for promoter prediction. Notably, CpGProD uses different parameters according to species (human, mouse) studied. Moreover, CpGProD predicts the promoter orientation on the DNA strand. AVAILABILITY: http://pbil.univ-lyon1.fr/software/cpgprod.html SUPPLEMENTARY INFORMATION: http://pbil.univ-lyon1.fr/software/cpgprod.html     

TeCK database: a comprehensive collection of telomeric and centromeric sequences with their associated proteins

Telomeres and centromere are two essential features of all eukaryotic chromosomes. They provide function that is necessary for the stability of chromosomes. We developed a comprehensive database named TeCK, which covers a gamut of sequence and other related information about telomeric patterns, telomere repeat sequences, centromere sequences and centromeric patterns present in chromosomes. It also contains information about telomerase ribo-nucleoprotein complexes, centromere binding protein and centromere DNA-binding protein complexes. The database also includes a collection of all kinetochore-associated proteins including inner, outer and central kinetochore proteins. The database can be searched using a user-friendly web interface. AVAILABILITY: http://www.bioinfosastra.com/services/teck/index.html.     

Protein kinase C-α negatively regulates EGF-induced PLC- activity through direct phosphorylation

Phospholipase C- is a PLC isozyme that contains a CDC25 homology domain and a pair of RA domains in addition to a conserved PLC catalytic domain. PLC- is activated by both growth factors and GPCR ligands in a distinct manner. Growth factors such as EGF stimulate PLC- in an RA2 domain-dependent manner through Ras and Rap. On the other hand, several GPCR ligands that are linked with Ga₁₂ or Ga₁₃ can activate PLC- by associating with GTP-RhoA. GTP-RhoA binds with the region in the PLC- Y domain. Gs-linked ligands such as PGE1 and adrenaline stimulate PLC- by cAMP-dependent activation of Epac and Rap2B. PLC- is important for cardiac development and function. In addition, several lines of evidence indicate that PLC- promotes cell growth in an activity-dependent or -independent manner. In particular, PLC--dependent suppression of EGF receptor downregulation contributes to its growth promoting activity. Proper regulation of PLC- activity is essential for preventing tumor formation. Our previous report indicated that EGF-dependent ubiquitination of PLC- is required for the control of PLC--dependent cell growth. Recently, we found that PLC- is phosphorylated by growth factor stimulation, and this is another mechanism of the negative regulation. PLC- is phosphorylated by PKC-α upon stimulation with growth factors such as EGF and PDGF. The EGF-induced phosphorylation of PLC- was abolished by PKC inhibitors and by the expression of the dominant negative mutant of PKC-α. Furthermore, PKC-α was found to phosphorylate PLC- directly in vitro, suggesting that PLC- is a substrate of PKC-α in cells. In addition, PLC- was co-immunoprecipitated with PKC-α in an EGF-dependent manner. Immunocytochemical studies showed that PLC- co-localized with PKC-α in the plasma membrane after EGF stimulation. In addition, inhibition of PKC activity enhanced PLC--mediated PIP₂ hydrolysis, suggesting that PKC-α negatively regulates PLC- activity. Taken together, these results suggest for the first time that PLC- is regulated by PKC-α-dependent phosphorylation.     

BIOFFORC: Tool development for biological file format conversion

The use of bioinformatics tools require different sequence formats at various instances. Every tool uses specific set of formats for processing. Sequence in one format is often required in another format. Thus, there is a need for sequence format conversion. A number of such tools are available in the public domain. Here, we describe BIOFFORC as a file format converter. The tool is developed with a graphical user interface in PERL.

Availability

http://www.winningpath.com/biofforc/     

AMIGene: Annotation of MIcrobial Genes

AMIGene (Annotation of MIcrobial Genes) is an application for automatically identifying the most likely coding sequences (CDSs) in a large contig or a complete bacterial genome sequence. The first step in AMIGene is dedicated to the construction of Markov models that fit the input genomic data (i.e. the gene model), followed by the combination of well-known gene-finding methods and an heuristic approach for the selection of the most likely CDSs. The web interface allows the user to select one or several gene models applied to the analysis of the input sequence by the AMIGene program and to visualize the list of predicted CDSs graphically and in a downloadable text format. The AMIGene web site is accessible at the following address: http://www.genoscope.cns.fr/agc/tools/amigene/index.html (Contact: sbocs@genoscope.cns.fr).