Discovery and assembly of repeat family pseudomolecules from sparse genomic sequence data using the Assisted Automated Assembler of Repeat Families (AAARF) algorithm

<p>Abstract</p> <p>Background</p> <p>Higher eukaryotic genomes are typically large, complex and filled with both genes and multiple classes of repetitive DNA. The repetitive DNAs, primarily transposable elements, are a rapidly evolving genome component that can provide the raw material for novel selected functions and also indicate the mechanisms and history of genome evolution in any ancestral lineage. Despite their abundance, universality and significance, studies of genomic repeat content have been largely limited to analyses of the repeats in fully sequenced genomes.</p> <p>Results</p> <p>In order to facilitate a broader range of repeat analyses, the Assisted Automated Assembler of Repeat Families algorithm has been developed. This program, written in PERL and with numerous adjustable parameters, identifies sequence overlaps in small shotgun sequence datasets and walks them out to create long pseudomolecules representing the most abundant repeats in any genome. Testing of this program in maize indicated that it found and assembled all of the major repeats in one or more pseudomolecules, including coverage of the major Long Terminal Repeat retrotransposon families. Both Sanger sequence and 454 datasets were appropriate.</p> <p>Conclusion</p> <p>These results now indicate that hundreds of higher eukaryotic genomes can be efficiently characterized for the nature, abundance and evolution of their major repetitive DNA components.</p

MaHPIC malaria systems biology data from Plasmodium cynomolgi sporozoite longitudinal infections in macaques

Plasmodium cynomolgi causes zoonotic malarial infections in Southeast Asia and this parasite species is important as a model for Plasmodium vivax and Plasmodium ovale. Each of these species produces hypnozoites in the liver, which can cause relapsing infections in the blood. Here we present methods and data generated from iterative longitudinal systems biology infection experiments designed and performed by the Malaria Host-Pathogen Interaction Center (MaHPIC) to delve deeper into the biology, pathogenesis, and immune responses of P. cynomolgi in the Macaca mulatta host. Infections were initiated by sporozoite inoculation. Blood and bone marrow samples were collected at defined timepoints for biological and computational experiments and integrative analyses revolving around primary illness, relapse illness, and subsequent disease and immune response patterns. Parasitological, clinical, haematological, immune response, and -omic datasets (transcriptomics, proteomics, metabolomics, and lipidomics) including metadata and computational results have been deposited in public repositories. The scope and depth of these datasets are unprecedented in studies of malaria, and they are projected to be a F.A.I.R., reliable data resource for decades

The Water-Energy-Food Nexus Beyond “Technical Quick Fix”: The Case of Hydro-Development in the Blue Nile Basin, Ethiopia

This paper builds upon empirical material from a case study of two dam sites in Ethiopia to revisit nexus narratives from a political ecology perspective. The two dams on tributaries of the Upper Blue Nile are examples of the success of hydro-development in increasing food and energy production, but at the same time they are evidence of the controversial effects these developments have on local populations. The paper argues that conventional nexus thinking has often been too water- and economy-centric, and too much focussed on a “technical quick fix” instead of a holistic approach. The paper calls for a broadening of nexus perspectives in order to better acknowledge the social complexity of hydro-development in local contexts, to understand the political construction of scarcity, and to combine different knowledges at the science-practice interface

A New Single-Step PCR Assay for the Detection of the Zoonotic Malaria Parasite Plasmodium knowlesi

Recent studies in Southeast Asia have demonstrated substantial zoonotic transmission of Plasmodium knowlesi to humans. Microscopically, P. knowlesi exhibits several stage-dependent morphological similarities to P. malariae and P. falciparum. These similarities often lead to misdiagnosis of P. knowlesi as either P. malariae or P. falciparum and PCR-based molecular diagnostic tests are required to accurately detect P. knowlesi in humans. The most commonly used PCR test has been found to give false positive results, especially with a proportion of P. vivax isolates. To address the need for more sensitive and specific diagnostic tests for the accurate diagnosis of P. knowlesi, we report development of a new single-step PCR assay that uses novel genomic targets to accurately detect this infection.We have developed a bioinformatics approach to search the available malaria parasite genome database for the identification of suitable DNA sequences relevant for molecular diagnostic tests. Using this approach, we have identified multi-copy DNA sequences distributed in the P. knowlesi genome. We designed and tested several novel primers specific to new target sequences in a single-tube, non-nested PCR assay and identified one set of primers that accurately detects P. knowlesi. We show that this primer set has 100% specificity for the detection of P. knowlesi using three different strains (Nuri, H, and Hackeri), and one human case of malaria caused by P. knowlesi. This test did not show cross reactivity with any of the four human malaria parasite species including 11 different strains of P. vivax as well as 5 additional species of simian malaria parasites.The new PCR assay based on novel P. knowlesi genomic sequence targets was able to accurately detect P. knowlesi. Additional laboratory and field-based testing of this assay will be necessary to further validate its utility for clinical diagnosis of P. knowlesi

Transmedia, sofistas y el jogo bonito. Caso de estudio: Santander Fútbol Pasión

Artículo para la sección Tribuna de adComunica

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center in 2023.

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) is a Bioinformatics Resource Center funded by the National Institutes of Health with additional funding from the Wellcome Trust. VEuPathDB supports >600 organisms that comprise invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Since 2004, VEuPathDB has analyzed omics data from the public domain using contemporary bioinformatic workflows, including orthology predictions via OrthoMCL, and integrated the analysis results with analysis tools, visualizations, and advanced search capabilities. The unique data mining platform coupled with >3000 pre-analyzed data sets facilitates the exploration of pertinent omics data in support of hypothesis driven research. Comparisons are easily made across data sets, data types and organisms. A Galaxy workspace offers the opportunity for the analysis of private large-scale datasets and for porting to VEuPathDB for comparisons with integrated data. The MapVEu tool provides a platform for exploration of spatially resolved data such as vector surveillance and insecticide resistance monitoring. To address the growing body of omics data and advances in laboratory techniques, VEuPathDB has added several new data types, searches and features, improved the Galaxy workspace environment, redesigned the MapVEu interface and updated the infrastructure to accommodate these changes

VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center

The Eukaryotic Pathogen, Vector and Host Informatics Resource (VEuPathDB, https://veupathdb.org) represents the 2019 merger of VectorBase with the EuPathDB projects. As a Bioinformatics Resource Center funded by the National Institutes of Health, with additional support from the Welllcome Trust, VEuPathDB supports &gt;500 organisms comprising invertebrate vectors, eukaryotic pathogens (protists and fungi) and relevant free-living or non-pathogenic species or hosts. Designed to empower researchers with access to Omics data and bioinformatic analyses, VEuPathDB projects integrate &gt;1700 pre-analysed datasets (and associated metadata) with advanced search capabilities, visualizations, and analysis tools in a graphic interface. Diverse data types are analysed with standardized workflows including an in-house OrthoMCL algorithm for predicting orthology. Comparisons are easily made across datasets, data types and organisms in this unique data mining platform. A new site-wide search facilitates access for both experienced and novice users. Upgraded infrastructure and workflows support numerous updates to the web interface, tools, searches and strategies, and Galaxy workspace where users can privately analyse their own data. Forthcoming upgrades include cloud-ready application architecture, expanded support for the Galaxy workspace, tools for interrogating host-pathogen interactions, and improved interactions with affiliated databases (ClinEpiDB, MicrobiomeDB) and other scientific resources, and increased interoperability with the Bacterial &amp; Viral BRC

paraat: F1000Research/Paraat Dockerfile

paraat2.0 code and files for creation of dockerfile. Source code from http://bigd.big.ac.cn/tools/paraat. See above and https://code.google.com/archive/p/paraat/ for usage and documentation