PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity

<p>Abstract</p> <p>Background</p> <p>Phages (viruses that infect bacteria) have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or "signature genes") present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples; however, there is currently no existing computational tool that biologists can use for this purpose.</p> <p>Results</p> <p>Here we present PhiSiGns, a web-based and standalone application that performs a pairwise comparison of each gene present in user-selected phage genomes, identifies signature genes, generates alignments of these genes, and designs potential PCR primer pairs. PhiSiGns is available at (<url>http://www.phantome.org/phisigns/</url>; <url>http://phisigns.sourceforge.net/</url>) with a link to the source code. Here we describe the specifications of PhiSiGns and demonstrate its application with a case study.</p> <p>Conclusions</p> <p>PhiSiGns provides phage biologists with a user-friendly tool to identify signature genes and design PCR primers to amplify related genes from uncultured phages in environmental samples. This bioinformatics tool will facilitate the development of novel signature genes for use as molecular markers in studies of phage diversity, phylogeny, and evolution.</p

Development of a RAD-Seq Based DNA Polymorphism Identification Software, AgroMarker Finder, and Its Application in Rice Marker-Assisted Breeding

Abstract Rapid and accurate genome-wide marker detection is essential to the marker-assisted breeding and functional genomics studies. In this work, we developed an integrated software, AgroMarker Finder (AMF: http://erp.novelbio.com/AMF), for providing graphical user interface (GUI) to facilitate the recently developed restriction-site associated DNA (RAD) sequencing data analysis in rice. By application of AMF, a total of 90,743 high-quality markers (82,878 SNPs and 7,865 InDels) were detected between rice varieties JP69 and Jiaoyuan5A. The density of the identified markers is 0.2 per Kb for SNP markers, and 0.02 per Kb for InDel markers. Sequencing validation revealed that the accuracy of genome-wide marker detection by AMF is 93%. In addition, a validated subset of 82 SNPs and 31 InDels were found to be closely linked to 117 important agronomic trait genes, providing a basis for subsequent marker-assisted selection (MAS) and variety identification. Furthermore, we selected 12 markers from 31 validated InDel markers to identify seed authenticity of variety Jiaoyuanyou69, and we also identified 10 markers closely linked to the fragrant gene BADH2 to minimize linkage drag for Wuxiang075 (BADH2 donor)/Jiachang1 recombinants selection. Therefore, this software provides an efficient approach for marker identification from RAD-seq data, and it would be a valuable tool for plant MAS and variety protection

Intelligent Monitoring and Controlling of Public Policies Using Social Media and Cloud Computing

Part 3: Government and InfrastructureInternational audienceLack of public participation in various policy making decision has always been a major cause of concern for government all around the world while formulating as well as evaluating such policies. With availability of latest IT infrastructure and the migration of government think-tank towards realizing more efficient cloud based e-government, this problem has been partially answered, but this predicament still persists. However, the exponential rise in usage of social media platforms by general public has given the government a wider insight to overcome this long pending dilemma. This paper presents a pragmatic approach that combines the capabilities of cloud computing and social media analytics towards efficient monitoring and controlling of public policies. The proposed arrangement has provided us some encouraging results, when tested for the policy of the century i.e. GST implementation by Indian government and established that proposed system can be successfully implemented for efficient policy making and implementation

General Minimal Flavor Violation

A model independent study of the minimal flavor violation (MFV) framework is presented, where the only sources of flavor breaking at low energy are the up and down Yukawa matrices. Two limits are identified for the Yukawa coupling expansion: linear MFV, where it is truncated at the leading terms, and nonlinear MFV, where such a truncation is not possible due to large third generation Yukawa couplings. These are then resummed to all orders using non-linear sigma-model techniques familiar from models of collective breaking. Generically, flavor diagonal CP violating (CPV) sources in the UV can induce O(1) CPV in processes involving third generation quarks. Due to a residual U(2) symmetry, the extra CPV in B_d-\bar B_d mixing is bounded by CPV in B_s-\bar B_s mixing. If operators with right-handed light quarks are subdominant, the extra CPV is equal in the two systems, and is negligible in processes involving only the first two generations. We find large enhancements in the up type sector, both in CPV in D-\bar D mixing and in top flavor violation.Comment: 5 pages and no figure

Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism

Neuroticism is a relatively stable personality trait characterized by negative emotionality (for example, worry and guilt)1; heritability estimated from twin studies ranges from 30 to 50%2, and SNP-based heritability ranges from 6 to 15%3,4,5,6. Increased neuroticism is associated with poorer mental and physical health7,8, translating to high economic burden9. Genome-wide association studies (GWAS) of neuroticism have identified up to 11 associated genetic loci3,4. Here we report 116 significant independent loci from a GWAS of neuroticism in 329,821 UK Biobank participants; 15 of these loci replicated at P &lt; 0.00045 in an unrelated cohort (N = 122,867). Genetic signals were enriched in neuronal genesis and differentiation pathways, and substantial genetic correlations were found between neuroticism and depressive symptoms (rg = 0.82, standard error (s.e.) = 0.03), major depressive disorder (MDD; rg = 0.69, s.e. = 0.07) and subjective well-being (rg = –0.68, s.e. = 0.03) alongside other mental health traits. These discoveries significantly advance understanding of neuroticism and its association with MDD

Genomic-based-breeding tools for tropical maize improvement

Maize has traditionally been the main staple diet in the Southern Asia and Sub-Saharan Africa and widely grown by millions of resource poor small scale farmers. Approximately, 35.4 million hectares are sown to tropical maize, constituting around 59% of the developing worlds. Tropical maize encounters tremendous challenges besides poor agro-climatic situations with average yields recorded <3 tones/hectare that is far less than the average of developed countries. On the contrary to poor yields, the demand for maize as food, feed, and fuel is continuously increasing in these regions. Heterosis breeding introduced in early 90 s improved maize yields significantly, but genetic gains is still a mirage, particularly for crop growing under marginal environments. Application of molecular markers has accelerated the pace of maize breeding to some extent. The availability of array of sequencing and genotyping technologies offers unrivalled service to improve precision in maize-breeding programs through modern approaches such as genomic selection, genome-wide association studies, bulk segregant analysis-based sequencing approaches, etc. Superior alleles underlying complex traits can easily be identified and introgressed efficiently using these sequence-based approaches. Integration of genomic tools and techniques with advanced genetic resources such as nested association mapping and backcross nested association mapping could certainly address the genetic issues in maize improvement programs in developing countries. Huge diversity in tropical maize and its inherent capacity for doubled haploid technology offers advantage to apply the next generation genomic tools for accelerating production in marginal environments of tropical and subtropical world. Precision in phenotyping is the key for success of any molecular-breeding approach. This article reviews genomic technologies and their application to improve agronomic traits in tropical maize breeding has been reviewed in detail