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An experimental study of the fundamental period of vibration of geologic strata above multiple impedance contrasts is presented for the Canterbury Plains, a deep, complex sedimentary basin on the South Island of New Zealand. Microtremor Horizontal-to-Vertical Spectral Ratio (mHVSR) analysis was used at 152 locations to investigate the fundamental period of the strata above three significant impedance contrasts in the region: the Riccarton Gravel, the Banks Peninsula volcanic (BPV) rock, and the deep graywacke basement bedrock. Up to three mHVSR peaks were observed in many of the mHVSR curves, with the long-period (2–7 s) peaks controlled by the BPV and/or the underlying bedrock. As the thickness of the BPV increases, the response of the geologic strata above the basement bedrock was masked by the shallower BPV, effectively changing the definition of what constitutes the reference condition (i.e. engineering bedrock) for site response analyses. The mHVSR peaks matched the long-period amplification peaks observed in the response spectra calculated from ground motions recorded during the Canterbury Earthquake Sequence events, underscoring the importance of the identification and consideration of deep impedance contrasts in site classification.

 

Olfactory receptors (ORs), encoded by the largest vertebrate multigene family, enable the detection of thousands of unique odorants in the environment and consequently play a critical role in species survival. Here, we advance our knowledge of OR gene evolution in procellariiform seabirds, an avian group which relies on the sense of olfaction for critical ecological functions. We built a cosmid library of Cory’s Shearwater (Calonectris borealis) genomic DNA, a model species for the study of olfaction-based navigation, and sequence OR gene-positive cosmid clones with a combination of sequencing technologies. We identified 220 OR open reading frames, 20 of which are full length, intact OR genes, and found a large ratio of partial and pseudogenes to intact OR genes (2:1), suggestive of a dynamic mode of evolution. Phylogenetic analyses revealed that while a few genes cluster with those of other sauropsid species in aγ(gamma) clade that predates the divergence of different avian lineages, most genes belong to an avian-specificγ-c clade, within which sequences cluster by species, suggesting frequent duplication and/or gene conversion events. We identified evidence of positive selection on full lengthγ-c clade genes. These patterns are consistent with a key role of adaptation in the functional diversification of olfactory receptor genes in a bird lineage that relies extensively on olfaction.

 

Saline migrants into freshwater habitats constitute among the most destructive invaders in aquatic ecosystems throughout the globe. However, the evolutionary and physiological mechanisms underlying such habitat transitions remain poorly understood. To explore the mechanisms of freshwater adaptation and distinguish between adaptive (evolutionary) and acclimatory (plastic) responses to salinity change, we examined genome‐wide patterns of gene expression between ancestral saline and derived freshwater populations of theEurytemora affinisspecies complex, reared under two different common‐garden conditions (0 versus 15 PSU). We found that evolutionary shifts in gene expression (between saline and freshwater inbred lines) showed far greater changes and were more widespread than acclimatory responses to salinity (0 versus 15 PSU). Most notably, 30–40 genes showing evolutionary shifts in gene expression across the salinity boundary were associated with ion transport function, withinorganic cation transmembrane transportforming the largest Gene Ontology category. Of particular interest was the sodium transporter, the Na⁺/H⁺antiporter (NHA) gene family, which was discovered in animals relatively recently. Thirty key ion regulatory genes, such as NHA paralogue #7, demonstrated concordant evolutionary and plastic shifts in gene expression, suggesting the evolution of ion transporter function and plasticity during rapid invasions into novel salinities. Moreover, freshwater invasions were associated with the evolution of reduced plasticity in the freshwater population, again for the same key ion transporters, consistent with the predicted evolution of canalization following adaptation to stressful conditions. Our results have important implications for understanding evolutionary and physiological mechanisms of range expansions by some of the most widespread invaders in aquatic habitats.

 

The Evidence & Conclusion Ontology (ECO) is a community standard for summarizing evidence in scientific research in a controlled, structured way. Annotations at the world's most frequented biological databases (e.g. model organisms, UniProt, Gene Ontology) are supported using ECO terms. ECO describes evidence derived from experimental and computational methods, author statements curated from the literature, inferences drawn by curators, and other types of evidence. Here, we describe recent ECO developments and collaborations, most notably: (i) a new ECO website containing user documentation, up-to-date news, and visualization tools; (ii) improvements to the ontology structure; (iii) implementing logic via an ongoing collaboration with the Ontology for Biomedical Investigations (OBI); (iv) addition of numerous experimental evidence types; and (v) addition of new evidence classes describing computationally derived evidence. Due to its utility, popularity, and simplicity, ECO is now expanding into realms beyond the protein annotation community, for example the biodiversity and phenotype communities. As ECO continues to grow as a resource, we are seeking new users and new use cases, with the hope that ECO will continue to be a broadly used and easy-to-implement community standard for representing evidence in diverse biological applications. Feel free to visit two ECO-sponsored workshops at ICBO 2016 to learn more: 1. “An introduction to the Evidence and Conclusion Ontology and representing evidence in scientific research” and 2. “OBI-ECO Interactions & Evidence”. 

The Evidence and Conclusion Ontology (ECO) is a community resource that provides an ontology of terms used to capture the type of evidence that supports biomedical annotations and assertions. Consistent capture of evidence information with ECO allows tracking of annotation provenance, establishment of quality control measures, and evidence-based data mining. ECO is in use by dozens of data repositories and resources with both specific and general areas of focus. ECO is continually being expanded and enhanced in response to user requests as well as our aim to adhere to community best-practices for ontology development. The ECO support team engages in multiple collaborations with other ontologies and annotating groups. Here we report on recent updates to the ECO ontology itself as well as associated resources that are available through this project. ECO project products are freely available for download from the project website (https://evidenceontology.org/) and GitHub (https://github.com/evidenceontology/evidenceontology). ECO is released into the public domain under a CC0 1.0 Universal license.

 

Abstract The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.