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Three subfamilies of grasses, the Erhardtoideae (rice), the Panicoideae (maize, sorghum, sugar cane and millet), and the Pooideae (wheat, barley and cool season forage grasses) provide the basis of human nutrition and are poised to become major sources of renewable energy. Here we describe the complete genome sequence of the wild grass Brachypodium distachyon (Brachypodium), the first member of the Pooideae subfamily to be completely sequenced. Comparison of the Brachypodium, rice and sorghum genomes reveals a precise sequence- based history of genome evolution across a broad diversity of the grass family and identifies nested insertions of whole chromosomes into centromeric regions as a predominant mechanism driving chromosome evolution in the grasses. The relatively compact genome of Brachypodium is maintained by a balance of retroelement replication and loss. The complete genome sequence of Brachypodium, coupled to its exceptional promise as a model system for grass research, will support the development of new energy and food crops

The aryl hydrocarbon receptor (AHR) is required for vertebrate development and is also activated by exogenous chemicals, including polycyclic aromatic hydrocarbons (PAHs) and 2,3,7,8-tetrachlorodibenzo- p -dioxin (TCDD). AHR activation is well-understood, but roles of downstream molecular signaling events are largely unknown. From previous transcriptomics in 48 h postfertilization (hpf) zebrafish exposed to several PAHs and TCDD, we found wfikkn1 was highly coexpressed with cyp1a (marker for AHR activation). Thus, we hypothesized wfikkn1 's role in AHR signaling, and showed that wfikkn1 expression was Ahr2 (zebrafish ortholog of human AHR)-dependent in developing zebrafish exposed to TCDD. To functionally characterize wfikkn1 , we made a CRISPR-Cas9 mutant line with a 16-bp deletion in wfikkn1 's exon, and exposed wildtype and mutants to dimethyl sulfoxide or TCDD. 48-hpf mRNA sequencing revealed over 700 genes that were differentially expressed (p  <  .05, log2FC > 1) between each pair of treatment combinations, suggesting an important role for wfikkn1 in altering both the 48-hpf transcriptome and TCDD-induced expression changes. Mass spectrometry-based proteomics of 48-hpf wildtype and mutants revealed 325 significant differentially expressed proteins. Functional enrichment demonstrated wfikkn1 was involved in skeletal muscle development and played a role in neurological pathways after TCDD exposure. Mutant zebrafish appeared morphologically normal but had significant behavior deficiencies at all life stages, and absence of Wfikkn1 did not significantly alter TCDD-induced behavior effects at all life stages. In conclusion, wfikkn1 did not appear to be significantly involved in TCDD's overt toxicity but is likely a necessary functional member of the AHR signaling cascade. [ABSTRACT FROM AUTHOR]

Abstract Background Large molecular sequence databases are fundamental resources for modern bioscientists. Whether for project-specific purposes or sharing data with colleagues, it is often advantageous to maintain smaller sequence databases. However, this is usually not an easy task for the average bench scientist. Results We present the Personal Sequence Database (PSD), a suite of tools to create and maintain small- to medium-sized web-accessible sequence databases. All interactions with PSD tools occur via the internet with a web browser. Users may define sequence groups within their database that can be maintained privately or published to the web for public use. A sequence group can be downloaded, browsed, searched by keyword or searched for sequence similarities using BLAST. Publishing a sequence group extends these capabilities to colleagues and collaborators. In addition to being able to manage their own sequence databases, users can enroll sequences in BLASTAgent, a BLAST hit tracking system, to monitor NCBI databases for new entries displaying a specified level of nucleotide or amino acid similarity. Conclusion The PSD offers a valuable set of resources unavailable elsewhere. In addition to managing sequence data and BLAST search results, it facilitates data sharing with colleagues, collaborators and public users. The PSD is hosted by the authors and is available at http://bioinfo.cgrb.oregonstate.edu/psd/.

Passive acoustic monitoring is an emerging approach to wildlife monitoring that leverages recent improvements in automated recording units and other technologies. A central challenge of this approach is the task of locating and identifying target species vocalizations in large volumes of audio data. To address this issue, we developed an efficient data processing pipeline using a deep convolutional neural network (CNN) to automate the detection of owl vocalizations in spectrograms generated from unprocessed field recordings. While the project was initially focused on spotted and barred owls, we also trained the network to recognize northern saw‐whet owl, great horned owl, northern pygmy‐owl, and western screech‐owl. Although classification performance varies across species, initial results are promising. Recall, or the proportion of calls in the dataset that are detected and correctly identified, ranged from 63.1% for barred owl to 91.5% for spotted owl based on raw network output. Precision, the rate of true positives among apparent detections, ranged from 0.4% for spotted owl to 77.1% for northern saw‐whet owl based on raw output. In limited tests, the CNN performed as well as or better than human technicians at detecting owl calls. Our model output is suitable for developing species encounter histories for occupancy models and other analyses. We believe our approach is sufficiently general to support long‐term, large‐scale monitoring of a broad range of species beyond our target species list, including birds, mammals, and others. [ABSTRACT FROM AUTHOR]