The SEQanswers wiki: a wiki database of tools for high-throughput sequencing analysis

Recent advances in sequencing technology have created unprecedented opportunities for biological research. However, the increasing throughput of these technologies has created many challenges for data management and analysis. As the demand for sophisticated analyses increases, the development time of software and algorithms is outpacing the speed of traditional publication. As technologies continue to be developed, methods change rapidly, making publications less relevant for users. The SEQanswers wiki (SEQwiki) is a wiki database that is actively edited and updated by the members of the SEQanswers community (http://SEQanswers.com/). The wiki provides an extensive catalogue of tools, technologies and tutorials for high-throughput sequencing (HTS), including information about HTS service providers. It has been implemented in MediaWiki with the Semantic MediaWiki and Semantic Forms extensions to collect structured data, providing powerful navigation and reporting features. Within 2 years, the community has created pages for over 500 tools, with approximately 400 literature references and 600 web links. This collaborative effort has made SEQwiki the most comprehensive database of HTS tools anywhere on the web. The wiki includes task-focused mini-reviews of commonly used tools, and a growing collection of more than 100 HTS service providers. SEQwiki is available at: http://wiki.SEQanswers.com/

Gramene 2016: comparative plant genomics and pathway resources

Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to approximately 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials

Gramene 2013: comparative plant genomics resources

Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces

Profiling microRNAs in individuals at risk of progression to rheumatoid arthritis

Background: Individuals at risk of rheumatoid arthritis (RA) demonstrate systemic autoimmunity in the form of anti-citrullinated peptide antibodies (ACPA). MicroRNAs (miRNAs) are implicated in established RA. This study aimed to (1) compare miRNA expression between healthy individuals and those at risk of and those that develop RA, (2) evaluate the change in expression of miRNA from "at-risk" to early RA and (3) explore whether these miRNAs could inform a signature predictive of progression from "at-risk" to RA. Methods: We performed global profiling of 754 miRNAs per patient on a matched serum sample cohort of 12 anti-cyclic citrullinated peptide (CCP) + "at-risk" individuals that progressed to RA. Each individual had a serum sample from baseline and at time of detection of synovitis, forming the matched element. Healthy controls were also studied. miRNAs with a fold difference/fold change of four in expression level met our primary criterion for selection as candidate miRNAs. Validation of the miRNAs of interest was conducted using custom miRNA array cards on matched samples (baseline and follow up) in 24 CCP+ individuals; 12 RA progressors and 12 RA non-progressors. Results: We report on the first study to use matched serum samples and a comprehensive miRNA array approach to identify in particular, three miRNAs (miR-22, miR-486-3p, and miR-382) associated with progression from systemic autoimmunity to RA inflammation. MiR-22 demonstrated significant fold difference between progressors and non-progressors indicating a potential biomarker role for at-risk individuals. Conclusions: This first study using a cohort with matched serum samples provides important mechanistic insights in the transition from systemic autoimmunity to inflammatory disease for future investigation, and with further evaluation, might also serve as a predictive biomarker

Ensembl Genomes 2013: scaling up access to genome-wide data

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species. The project exploits and extends technologies for genome annotation, analysis and dissemination, developed in the context of the vertebrate-focused Ensembl project, and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. This article provides an update to the previous publications about the resource, with a focus on recent developments. These include the addition of important new genomes (and related data sets) including crop plants, vectors of human disease and eukaryotic pathogens. In addition, the resource has scaled up its representation of bacterial genomes, and now includes the genomes of over 9000 bacteria. Specific extensions to the web and programmatic interfaces have been developed to support users in navigating these large data sets. Looking forward, analytic tools to allow targeted selection of data for visualization and download are likely to become increasingly important in future as the number of available genomes increases within all domains of life, and some of the challenges faced in representing bacterial data are likely to become commonplace for eukaryotes in future

The Geography of Fear: A Latitudinal Gradient in Anti-Predator Escape Distances of Birds across Europe

All animals flee from potential predators, and the distance at which this happens is optimized so the benefits from staying are balanced against the costs of flight. Because predator diversity and abundance decreases with increasing latitude, and differs between rural and urban areas, we should expect escape distance when a predator approached the individual to decrease with latitude and depend on urbanization. We measured the distance at which individual birds fled (flight initiation distance, FID, which represents a reliable and previously validated surrogate measure of response to predation risk) following a standardized protocol in nine pairs of rural and urban sites along a ca. 3000 km gradient from Southern Spain to Northern Finland during the breeding seasons 2009–2010. Raptor abundance was estimated by means of standard point counts at the same sites where FID information was recorded. Data on body mass and phylogenetic relationships among bird species sampled were extracted from the literature. An analysis of 12,495 flight distances of 714 populations of 159 species showed that mean FID decreased with increasing latitude after accounting for body size and phylogenetic effects. This decrease was paralleled by a similar cline in an index of the abundance of raptors. Urban populations had consistently shorter FIDs, supporting previous findings. The difference between rural and urban habitats decreased with increasing latitude, also paralleling raptor abundance trends. Overall, the latitudinal gradient in bird fear was explained by raptor abundance gradients, with additional small effects of latitude and intermediate effects of habitat. This study provides the first empirical documentation of a latitudinal trend in anti-predator behavior, which correlated positively with a similar trend in the abundance of predators.TG was supported by the Human Frontier Science Program (RGY69/07) and MSM6198959212. JJ was supported by the EU Regional Development Foundation for the project (A31026). MD was funded by the project RISKDISP (CGL2009-08430) of the Spanish Ministerio de Ciencia e Innovación. GM was supported by TÁMOP-4.2.1./B-09/1-KMR-2010-0005 and TÁMOP-4.2.2./B-10/1-2010-0023 grants

Construction of reference chromosome-scale pseudomolecules for potato: integrating the potato genome with genetic and physical maps

The genome of potato, a major global food crop, was recently sequenced. The work presented here details the integration of the potato reference genome (DM) with a new STS marker based linkage map and other physical and genetic maps of potato and the closely related species tomato. Primary anchoring of the DM genome assembly was accomplished using a diploid segregating population, which was genotyped with several types of molecular genetic markers to construct a new ~936 cM linkage map comprising 2,469 marker loci. In silico anchoring approaches employed genetic and physical maps from the diploid potato genotype RH and tomato. This combined approach has allowed 951 superscaffolds to be ordered into pseudomolecules corresponding to the 12 potato chromosomes. These pseudomolecules represent 674 Mb (~93%) of the 723 Mb genome assembly and 37,482 (~96%) of the 39,031 predicted genes. The superscaffold order and orientation within the pseudomolecules is closely collinear with independently constructed high density linkage maps. Comparisons between marker distribution and physical location reveal regions of greater and lesser recombination, as well as regions exhibiting significant segregation distortion. The work presented here has led to a greatly improved ordering of the potato reference genome superscaffolds into chromosomal 'pseudomolecules'.Fil: Carboni, Martín Federico. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires. Estación Experimental Agropecuaria Balcarce; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: D'ambrosio, Juan Martín. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional San Cristobal de Huamanga. Laboratorio de Genética y Biotecnología Vegetal; PerúFil: Sharma, Sanjeev Kumar. The James Hutton Institute; Reino UnidoFil: Bolser, Daniel. University of Dundee; Reino UnidoFil: de Boer, Jan. Wageningen University & Researc; Países BajosFil: Sønderkær, Mads . Aalborg University; DinamarcaFil: Amoros, Walter. International Potato Center; PerúFil: de la Cruz, Germán. Universidad Nacional San Cristobal de Huamanga; PerúFil: Di Genova, Alex. Universidad de Chile; ChileFil: Douches, David S.. Michigan State University; Estados UnidosFil: Eguiluz, Maria. Universidad Peruana Cayetano Heredia; PerúFil: Guo, Xiao. Shandong Academy of Agricultural Sciences; ChinaFil: Guzman, Frank. Universidad Peruana Cayetano Heredia; PerúFil: Hackett, Christine A.. Biomathematics and Statistics Scotland; Reino UnidoFil: Hamilton, John P.. Crops Environment and Land Use Programme; IrlandaFil: Li, Guangcun. Shandong Academy of Agricultural Sciences; ChinaFil: Li, Ying. The New Zealand Institute for Plant & Food Research; Nueva ZelandaFil: Lozano, Roberto. Universidad Peruana Cayetano Heredia; PerúFil: Maass, Alejandro. Universidad de Chile; ChileFil: Marshall, David. The James Hutton Institute; Reino UnidoFil: Martinez, Diana. Universidad Peruana Cayetano Heredia; PerúFil: McLean, Karen. The James Hutton Institute; Reino UnidoFil: Mejía, Nilo. Instituto de Investigaciones Agropecuarias. Centro Regional de Investigación La Platina; ChileFil: Milne, Linda. The James Hutton Institute; Reino UnidoFil: Munive, Susan. International Potato Center; PerúFil: Nagy, Istvan. Crops Environment and Land Use Programme; IrlandaFil: Ponce, Olga. Universidad Peruana Cayetano Heredia; PerúFil: Ramirez, Manuel. Universidad Peruana Cayetano Heredia; PerúFil: Simon, Reinhard. International Potato Center; PerúFil: Thomson, Susan J.. Chinese Academy of Agricultural Sciences; Chin