1,720,975 research outputs found
Generating beneficial predator genomes to provide comparative insights into insecticide resistance-related gene families.
Get PDFWith a rapidly growing population to feed, finding ways to increase crop yields has become
more important than ever. Insect pests contribute hugely to yield losses every year and finding
methods to effectively control pest levels is therefore crucial to reduce these losses. Insecticide
use alone is no longer a viable solution, due to ever increasing levels of resistance developing
amongst crop pests, as well as the environmental concerns associated with their overuse.
Biological control – the use of natural predators to keep pest populations under control – has
proven to be a highly effective method of pest control and generally has less severe
environmental impacts than pesticides (although introducing non-native species can result in
undesirable changes to local biodiversity). Biological control agents are therefore a key
component of Integrated Pest Management (IPM) strategies, which aim to manage pest
populations in a sustainable and economical manner. IPM programs prioritise selective
insecticides which target the pest species and are harmless to the beneficial predators.
However, the numbers of reported insecticide resistance cases are far lower in beneficial
predators as opposed to crop pests. As a result, insecticide application often harms beneficial
predator populations and reduces their biological control capabilities, which may allow
resistant pest populations to surge after application.
Genomic information is readily available for a multitude of crop pest species, however, when
this project began, there was minimal genomic data available for beneficial predators. By
increasing the availability of genomic data for beneficial predators, we can perform
comparative analyses between crop pests and their predators of insecticide target-sites and
genes encoding metabolic enzymes potentially responsible for insecticide resistance. These
analyses may help uncover whether there is any genomic basis for the reduced number of
insecticide resistance cases in beneficial predators compared to crop pests.
The aim of this project was to firstly sequence and assemble the genomes of key beneficial
predators for which no genomic information is currently available. This included Orius
laevigatus (minute pirate bug), Sphaerophoria rueppellii (European hoverfly) and Microctonus
brassicae (parasitoid wasp). Next, these genomes were annotated and manual curation of
resistance-associated detoxification genes was performed. The resultant detoxification gene
sets were then used to perform comparative analyses between beneficial predators and crop
pests.
The results from the comparative analysis suggest a greater degree of detoxification family
gene expansion within crop pests compared to beneficial predators. This difference was
particularly apparent in the families associated with detoxification of plant xenobiotics and
suggests that the plant-based diet of crop pests provided increased selection pressure for
resistance mechanisms prior to the introduction of insecticides. Once insecticides were
introduced, crop pests may therefore have had an advantage over beneficial predators in terms
of developing insecticide resistance. In addition, variation in the levels of resistance between
different beneficial predators correlated to some extent with gene expansion, with several
factors having likely had some influence on this, including diet, migration and length of
commercial use.
The knowledge gained from this project could contribute to our understanding of insecticide
resistance from a genomic perspective and aid in the development of successful IPM strategies.Hassani-Pak, Keywan (Associate)King, Robert (Associate)PhD in Environment and Agrifoo
Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes
No full textGenetics and “omics” studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future
Natural variation in acyl editing is a determinant of seed storage oil composition
Get PDFSeeds exhibit wide variation in the fatty acid composition of their storage oil. However, the genetic basis of this variation is only partially understood. Here we have used a multi-parent advanced generation inter-cross (MAGIC) population to study the genetic control of fatty acid chain length in Arabidopsis thaliana seed oil. We mapped four quantitative trait loci (QTL) for the quantity of the major very long chain fatty acid species 11-eicosenoic acid (20:1), using multiple QTL modelling. Surprisingly, the main-effect QTL does not coincide with FATTY ACID ELONGASE1 and a parallel genome wide association study suggested that LYSOPHOSPHATIDYLCHOLINE ACYLTRANSFERASE2 (LPCAT2) is a candidate for this QTL. Regression analysis also suggested that LPCAT2 expression and 20:1 content in seeds of the 19 MAGIC founder accessions are related. LPCAT is a key component of the Lands cycle; an acyl-editing pathway that enables acyl-exchange between the acyl-Coenzyme A and phosphatidylcholine precursor pools used for microsomal fatty acid elongation and desaturation, respectively. We Mendelianised the main-effect QTL using biparental chromosome segment substitution lines and carried out complementation tests to show that a single cis-acting polymorphism in the LPCAT2 promoter causes the variation in seed 20:1 content, by altering the LPCAT2 expression level and total LPCAT activity in developing siliques. Our work establishes that oilseed species exhibit natural variation in the enzymic capacity for acyl-editing and this contributes to the genetic control of storage oil composition
Genome wide analysis of fatty acid desaturation and its response to temperature
Get PDFPlants modify the polyunsaturated fatty acid content of their membrane and storage lipids in order to adapt to changes in temperature. In developing seeds, this response is largely controlled by the activities of the microsomal ω-6 and ω-3 fatty acid desaturases, FAD2 and FAD3. Although temperature regulation of desaturation has been studied at the molecular and biochemical levels, the genetic control of this trait is poorly understood. Here, we have characterized the response of Arabidopsis (Arabidopsis thaliana) seed lipids to variation in ambient temperature and found that heat inhibits both ω-6 and ω-3 desaturation in phosphatidylcholine, leading to a proportional change in triacylglycerol composition. Analysis of the 19 parental accessions of the multiparent advanced generation intercross (MAGIC) population showed that significant natural variation exists in the temperature responsiveness of ω-6 desaturation. A combination of quantitative trait locus (QTL) analysis and genome-wide association studies (GWAS) using the MAGIC population suggests that ω-6 desaturation is largely controlled by cis-acting sequence variants in the FAD2 5′ untranslated region intron that determine the expression level of the gene. However, the temperature responsiveness of ω-6 desaturation is controlled by a separate QTL on chromosome 2. The identity of this locus is unknown, but genome-wide association studies identified potentially causal sequence variants within ∼40 genes in an ∼450-kb region of the QTL
KnetMiner - An integrated data platform for gene mining and biological knowledge discovery
Get PDFDiscovery of novel genes that control important phenotypes and diseases is one of the key challenges in biological sciences. Now, in the post-genomics era, scientists have access to a vast range of genomes, genotypes, phenotypes and ‘omics data which - when used systematically - can help to gain new insights and make faster discoveries. However, the volume and diversity of such un-integrated data is often seen as a burden that only those with specialist bioinformatics skills, but often only minimal specialist biological knowledge, can penetrate. Therefore, new tools are required to allow researchers to connect, explore and compare large-scale datasets to identify the genes and pathways that control important phenotypes and diseases in plants, animals and humans.
KnetMiner, with a silent "K" and standing for Knowledge Network Miner, is a suite of open-source software tools for integrating and visualising large biological datasets. The software mines the myriad databases that describe an organism’s biology to present links between relevant pieces of information, such as genes, biological pathways, phenotypes and publications with the aim to provide leads for scientists who are investigating the molecular basis for a particular trait. The KnetMiner approach is based on 1) integration of heterogeneous, complex and interconnected biological information into a knowledge graph; 2) text-mining to enrich the knowledge graph with novel relations extracted from literature; 3) graph queries of varying depths to find paths between genes and evidence nodes; 4) evidence-based gene rank algorithm that combines graph and information theory; 5) fast search and interactive knowledge visualisation techniques. Overall, KnetMiner is a publicly available resource that helps scientists trawl diverse biological databases for clues to design better crop varieties and understand diseases. The key strength of KnetMiner is to include the end user into the “interactive” knowledge discovery process with the goal of supporting human intelligence with machine intelligence
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and Graph Database Approach
No full textThe speed and accuracy of new scientific discoveries – be it by humans or artificial intelligence – depends on the quality of the underlying data and on the technology to connect, search and share the data efficiently. In recent years, we have seen the rise of graph databases and semi-formal data models such as knowledge graphs to facilitate software approaches to scientific discovery. These approaches extend work based on formalised models, such as the Semantic Web. In this paper, we present our developments to connect, search and share data about genome-scale knowledge networks (GSKN). We have developed a simple application ontology based on OWL/RDF with mappings to standard schemas. We are employing the ontology to power data access services like resolvable URIs, SPARQL endpoints, JSON-LD web APIs and Neo4j-based knowledge graphs. We demonstrate how the proposed ontology and graph databases considerably improve search and access to interoperable and reusable biological knowledge (i.e. the FAIRness data principles)
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