447 research outputs found

    White Shark Genome Reveals Ancient Elasmobranch Adaptations Associated with Wound Healing and the Maintenance of Genome Stability

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    The white shark (Carcharodon carcharias; Chondrichthyes, Elasmobranchii) is one of the most publicly recognized marine animals. Here we report the genome sequence of the white shark and comparative evolutionary genomic analyses to the chondrichthyans, whale shark (Elasmobranchii) and elephant shark (Holocephali), as well as various vertebrates. The 4.63-Gbp white shark genome contains 24,520 predicted genes, and has a repeat content of 58.5%. We provide evidence for a history of positive selection and gene-content enrichments regarding important genome stability-related genes and functional categories, particularly so for the two elasmobranchs. We hypothesize that the molecular adaptive emphasis on genome stability in white and whale sharks may reflect the combined selective pressure of large genome sizes, high repeat content, high long-interspersed element retrotransposon representation, large body size, and long lifespans, represented across these two species. Molecular adaptation for wound healing was also evident, with positive selection in key genes involved in the wound-healing process, as well as Gene Ontology enrichments in fundamental wound-healing pathways. Sharks, particularly apex predators such as the white shark, are believed to have an acute sense of smell. However, we found very few olfactory receptor genes, very few trace amine-associated receptors, and extremely low numbers of G protein-coupled receptors. We did however, identify 13 copies of vomeronasal type 2 (V2R) genes in white shark and 10 in whale shark; this, combined with the over 30 V2Rs reported previously for elephant shark, suggests this gene family may underlie the keen odorant reception of chondrichthyans

    The Development of a Content Analysis Model for Assessing Students’ Cognitive Learning in Asynchronous Online Discussions

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    The purpose of this study was to develop and validate a content analysis model for assessing students\u27 cognitive learning in asynchronous online discussions. It adopted a fully mixed methods design, in which qualitative and quantitative methods were employed sequentially for data analysis and interpretation. Specifically, the design was a sequential exploratory (QUAL→ quan) design with priority given to qualitative data and methods. Qualitative data were 800 online postings collected in two online courses. Quantitative data were 803 online postings from the same two courses but from different discussion topics and different weeks. During the qualitative process, a grounded theory approach was adopted to construct a content analysis model based on qualitative data. During the quantitative process, chi-square tests and confirmative factor analysis (CFA) which used online postings as cases or observations and was the first of its kind were performed to test if the new model fit the quantitative data
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