AgAnimalGenomes: browsers for viewing and manually annotating farm animal genomes.

Current genome sequencing technologies have made it possible to generate highly contiguous genome assemblies for non-model animal species. Despite advances in genome assembly methods, there is still room for improvement in the delineation of specific gene features in the genomes. Here we present genome visualization and annotation tools to support seven livestock species (bovine, chicken, goat, horse, pig, sheep, and water buffalo), available in a new resource called AgAnimalGenomes. In addition to supporting the manual refinement of gene models, these browsers provide visualization tracks for hundreds of RNAseq experiments, as well as data generated by the Functional Annotation of Animal Genomes (FAANG) Consortium. For species with predicted gene sets from both Ensembl and RefSeq, the browsers provide special tracks showing the thousands of protein-coding genes that disagree across the two gene sources, serving as a valuable resource to alert researchers to gene model issues that may affect data interpretation. We describe the data and search methods available in the new genome browsers and how to use the provided tools to edit and create new gene models.

Hymenoptera Genome Database: new genomes and annotation datasets for improved go enrichment and orthologue analyses.

We report an update of the Hymenoptera Genome Database (HGD; http://HymenopteraGenome.org), a genomic database of hymenopteran insect species. The number of species represented in HGD has nearly tripled, with fifty-eight hymenopteran species, including twenty bees, twenty-three ants, eleven wasps and four sawflies. With a reorganized website, HGD continues to provide the HymenopteraMine genomic data mining warehouse and JBrowse/Apollo genome browsers integrated with BLAST. We have computed Gene Ontology (GO) annotations for all species, greatly enhancing the GO annotation data gathered from UniProt with more than a ten-fold increase in the number of GO-annotated genes. We have also generated orthology datasets that encompass all HGD species and provide orthologue clusters for fourteen taxonomic groups. The new GO annotation and orthology data are available for searching in HymenopteraMine, and as bulk file downloads.

Monetary and non-monetary rewards reduce attentional capture by emotional distractors.

Irrelevant emotional stimuli often capture attention, disrupting ongoing cognitive processes. In two experiments, we examined whether availability of rewards (monetary and non-monetary) can prevent this attentional capture. Participants completed a central letter identification task while attempting to ignore negative, positive, and neutral distractor images that appeared above or below the targets on 25% of trials. Distraction was indexed by slowing on distractor-present trials. Half the participants completed the task with no performance-contingent reward, while the other half earned points for fast and accurate performance. In Experiment 1, points translated into monetary reward, but in Experiment 2, points had no monetary value. In both experiments, reward reduced capture by emotional distractors, showing that even non-monetary reward can aid attentional control. These findings suggest that motivation encourages use of effective cognitive control mechanisms that effectively prevent attentional capture, even when distractors are emotional.

MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database.

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.

Bovine Genome Database: new annotation tools for a new reference genome.

The Bovine Genome Database (BGD) (http://bovinegenome.org) has been the key community bovine genomics database for more than a decade. To accommodate the increasing amount and complexity of bovine genomics data, BGD continues to advance its practices in data acquisition, curation, integration and efficient data retrieval. BGD provides tools for genome browsing (JBrowse), genome annotation (Apollo), data mining (BovineMine) and sequence database searching (BLAST). To augment the BGD genome annotation capabilities, we have developed a new Apollo plug-in, called the Locus-Specific Alternate Assembly (LSAA) tool, which enables users to identify and report potential genome assembly errors and structural variants. BGD now hosts both the newest bovine reference genome assembly, ARS-UCD1.2, as well as the previous reference genome, UMD3.1.1, with cross-genome navigation and queries supported in JBrowse and BovineMine, respectively. Other notable enhancements to BovineMine include the incorporation of genomes and gene annotation datasets for non-bovine ruminant species (goat and sheep), support for multiple assemblies per organism in the Regions Search tool, integration of additional ontologies and development of many new template queries. To better serve the research community, we continue to focus on improving existing tools, developing new tools, adding new datasets and encouraging researchers to use these resources.

Reward elicits cognitive control over emotional distraction: Evidence from pupillometry.

Attention is biased toward emotional stimuli, even when they are irrelevant to current goals. Motivation, elicited by performance-contingent reward, reduces behavioural emotional distraction. In emotionally neutral contexts, reward is thought to encourage use of a proactive cognitive control strategy, altering anticipatory attentional settings to more effectively suppress distractors. The current preregistered study investigates whether a similar proactive shift occurs even when distractors are highly arousing emotional images. We monitored pupil area, an online measure of both cognitive and emotional processing, to examine how reward influences the time course of control. Participants (n = 110) identified a target letter flanking an irrelevant central image. Images were meaningless scrambles on 75% of trials; on the remaining 25%, they were intact positive (erotic), negative (mutilation), or neutral images. Half the participants received financial rewards for fast and accurate performance, while the other half received no performance-contingent reward. Emotional distraction was greater than neutral distraction, and both were attenuated by reward. Consistent with behavioural findings, pupil dilation was greater following emotional than neutral distractors, and dilation to intact distractors (regardless of valence) was decreased by reward. Although reward did not enhance tonic pupil dilation (an index of sustained proactive control), exploratory analyses showed that reward altered the time course of control-eliciting a sharp, rapid, increase in dilation immediately preceding stimulus onset (reflecting dynamic use of anticipatory control), that extended until well after stimulus offset. These findings suggest that reward alters the time course of control by encouraging proactive preparation to rapidly disengage from emotional distractors.

Motivation enhances control of positive and negative emotional distractions.

Using cognitive control to ignore distractions is essential for successfully achieving our goals. In emotionally-neutral contexts, motivation can reduce interference from irrelevant stimuli by enhancing cognitive control. However, attention is commonly biased towards emotional stimuli, making them potent distractors. Can motivation aid control of emotional distractions, and does it do so similarly for positive and negative stimuli? Here, we examined how task motivation influences control of distraction from positive, negative, and neutral scenes. Participants completed a simple perceptual task while attempting to ignore task-irrelevant images. One group received monetary reward for fast and accurate task performance; another (control) group did not. Overall, both negative (mutilation) and positive (erotic) images caused greater slowing of responses than neutral images of people, but emotional distraction was reduced with reward. Crucially, despite the different motivational directions associated with negative and positive stimuli, reward reduced negative and positive distraction equally. Our findings suggest that motivation may encourage the use of a sustained proactive control strategy that can effectively reduce the impact of emotional distraction.