fIdentification of B. napus small RNAs responsive to infection by a necrotrophic pathogen

BACKGROUND

Small RNAs are short non-coding RNAs that are key gene regulators controlling various biological processes in eukaryotes. Plants may regulate discrete sets of sRNAs in response to pathogen attack. Sclerotinia sclerotiorum is an economically important pathogen affecting hundreds of plant species, including the economically important oilseed B. napus. However, there are limited studies on how regulation of sRNAs occurs in the S. sclerotiorum and B. napus pathosystem.

RESULTS

We identified different classes of sRNAs from B. napus using high throughput sequencing of replicated mock and infected samples at 24 h post-inoculation (HPI). Overall, 3999 sRNA loci were highly expressed, of which 730 were significantly upregulated during infection. These 730 up-regulated sRNAs targeted 64 genes, including disease resistance proteins and transcriptional regulators. A total of 73 conserved miRNA families were identified in our dataset. Degradome sequencing identified 2124 cleaved mRNA products from these miRNAs from combined mock and infected samples. Among these, 50 genes were specific to infection. Altogether, 20 conserved miRNAs were differentially expressed and 8 transcripts were cleaved by the differentially expressed miRNAs miR159, miR5139, and miR390, suggesting they may have a role in the S. sclerotiorum response. A miR1885-triggered disease resistance gene-derived secondary sRNA locus was also identified and verified with degradome sequencing. We also found further evidence for silencing of a plant immunity related ethylene response factor gene by a novel sRNA using 5'-RACE and RT-qPCR.

CONCLUSIONS

The findings in this study expand the framework for understanding the molecular mechanisms of the S. sclerotiorum and B. napus pathosystem at the sRNA level.

A2A: a platform for research in biomedical literature search

BACKGROUND

Finding relevant literature is crucial for many biomedical research activities and in the practice of evidence-based medicine. Search engines such as PubMed provide a means to search and retrieve published literature, given a query. However, they are limited in how users can control the processing of queries and articles-or as we call them documents-by the search engine. To give this control to both biomedical researchers and computer scientists working in biomedical information retrieval, we introduce a public online tool for searching over biomedical literature. Our setup is guided by the NIST setup of the relevant TREC evaluation tasks in genomics, clinical decision support, and precision medicine.

RESULTS

To provide benchmark results for some of the most common biomedical information retrieval strategies, such as querying MeSH subject headings with a specific weight or querying over the title of the articles only, we present our evaluations on public datasets. Our experiments report well-known information retrieval metrics such as precision at a cutoff of ranked documents.

CONCLUSIONS

We introduce the A2A search and benchmarking tool which is publicly available for the researchers who want to explore different search strategies over published biomedical literature. We outline several query formulation strategies and present their evaluations with known human judgements for a large pool of topics, from genomics to precision medicine.

Multiple recombination events between two cytochrome P450 loci contribute to global pyrethroid resistance in Helicoverpa armigera

The cotton bollworm, Helicoverpa armigera (Hübner) is one of the most serious insect pest species to evolve resistance against many insecticides from different chemical classes. This species has evolved resistance to the pyrethroid insecticides across its native range and is becoming a truly global pest after establishing in South America and having been recently recorded in North America. A chimeric cytochrome P450 gene, CYP337B3, has been identified as a resistance mechanism for resistance to fenvalerate and cypermethrin. Here we show that this resistance mechanism is common around the world with at least eight different alleles. It is present in South America and has probably introgressed into its closely related native sibling species, Helicoverpa zea. The different alleles of CYP337B3 are likely to have arisen independently in different geographic locations from selection on existing diversity. The alleles found in Brazil are those most commonly found in Asia, suggesting a potential origin for the incursion of H. armigera into the Americas.

An efficient algorithm for estimating brain covariance networks

Often derived from partial correlations or many pairwise analyses, covariance networks represent the inter-relationships among regions and can reveal important topological structures in brain measures from healthy and pathological subjects. However both approaches are not consistent network estimators and are sensitive to the value of the tuning parameters. Here, we propose a consistent covariance network estimator by maximising the network likelihood (MNL) which is robust to the tuning parameter. We validate the consistency of our algorithm theoretically and via a simulation study, and contrast these results against two well-known approaches: the graphical LASSO (gLASSO) and Pearson pairwise correlations (PPC) over a range of tuning parameters. The MNL algorithm had a specificity equal to and greater than 0.94 for all sample sizes in the simulation study, and the sensitivity was shown to increase as the sample size increased. The gLASSO and PPC demonstrated a specificity-sensitivity trade-off over a range of values of tuning parameters highlighting the discrepancy in the results for misspecified values. Application of the MNL algorithm to the case study data showed a loss of connections between healthy and impaired groups, and improved ability to identify between lobe connectivity in contrast to gLASSO networks. In this work, we propose the MNL algorithm as an effective approach to find covariance brain networks, which can inform the organisational features in brain-wide analyses, particularly for large sample sizes.

Anticyclonic eddies are more productive than cyclonic eddies in subtropical gyres because of winter mixing

Mesoscale eddies are ubiquitous features of ocean circulation that modulate the supply of nutrients to the upper sunlit ocean, influencing the rates of carbon fixation and export. The popular eddy-pumping paradigm implies that nutrient fluxes are enhanced in cyclonic eddies because of upwelling inside the eddy, leading to higher phytoplankton production. We show that this view does not hold for a substantial portion of eddies within oceanic subtropical gyres, the largest ecosystems in the ocean. Using space-based measurements and a global biogeochemical model, we demonstrate that during winter when subtropical eddies are most productive, there is increased chlorophyll in anticyclones compared with cyclones in all subtropical gyres (by 3.6 to 16.7% for the five basins). The model suggests that this is a consequence of the modulation of winter mixing by eddies. These results establish a new paradigm for anticyclonic eddies in subtropical gyres and could have important implications for the biological carbon pump and the global carbon cycle.