<i>Biological Bulletin</i> Virtual Symposium: Genomics of Large Marine Metazoans
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Abstract
Previous articleNext article FreeGenomics of Large Marine MetazoansBiological Bulletin Virtual Symposium: Genomics of Large Marine MetazoansR. Andrew Cameron and Jonathan P. RastR. Andrew Cameron1. Beckman Institute, California Institute of Technology, 1200 E. California Blvd., Pasadena, California 91125 Search for more articles by this author and Jonathan P. Rast2. Department of Medical Biophysics, University of Toronto, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada Search for more articles by this author Received 8 April 2008; accepted 14 April 2008.PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreThe phrase “genomics of large marine metazoans” is an ungainly mouthful. So are the animals themselves, in most cases. The species addressed in this virtual symposium circumscribe a great catalog of morphological, ecological, and phylogenetic diversity that has fascinated marine scientists for many years. Genome sequences and expressed sequence tag projects provide a means to understand this diversity from a different and in some ways more comprehensive viewpoint. Collectively the animals that are the subject of these papers differ significantly from the standard genetic models that dominate our current understanding of the breadth of animal molecular biology. These differences are reflected in their life history and larger genomes (though by no means unusually large). Their longer life spans may correlate with their often greater genetic complexity. Finally, the marine environment compasses extreme ranges of physical conditions, and understanding the unique genetic features of extremophiles will be helped tremendously by genomic approaches (see Nyholm et al., this issue).In the end, all of the adaptations that make each marine animal unique can be traced in some manner or other to variations in its genomes. For the developmental biologist, changes in developmental programs are the mechanism by which morphology becomes altered. The gene regulatory networks that compose these programs are hard-wired in the genome (see papers by Magie and Martindale; Materna and Cameron; Sauka-Spengler and Bronner-Fraser; Fahey et al.; this issue). For the physiologist and other scientists interested in the relationship of the organism with its surroundings, the questions may be refocused on genetic programs that regulate the flow of information from the environment through molecular sensors and to biochemical responses (see Reitzel et al., this issue). Much of biology can be viewed as a question of how function is encoded in biological programs and how the programs are maintained in the genome sequence. While this is anything but a trivial problem, genome sequences have the immediate advantage of putting very different animals on relatively equal footing for comparative analysis.It is certainly true that many of the secrets of an animal remain undecipherable even with a genome sequence in hand, but the often heard lament that genome sequences per se are merely a steppingstone could not be further from the truth. Especially as the knowledge-base of protein structure and function expands, genome sequence data can almost immediately be transformed into often unexpected knowledge about virtually every aspect of the organism. Put another way: all genomics is functional genomics.The obvious values of genome sequences fall into a few categories: ) The genome provides a complete gene catalog for an organism. From such a catalog emerge differences in gene number or diversity of gene families that can directly inform the biological mechanisms that operate in that organism (see Freeman et al., this issue). Indeed the sensitivity allowed by sequence information is far beyond that which can be achieved by standard molecular approaches and is critical to studying quickly evolving genetic systems such as immunity (see Rast and Messier-Solek, this issue). For many classes of genes, a comprehensive parts list immediately emerges, and the nature of this list may set boundaries on the biology of the organisms.) Genome sequences also provide a solid framework on which to base exploration of complex genetic phenomena. This will be especially critical to understanding subjects like immunity and sensory systems in which genes are often divergent, polymorphic, and expanded as multigene families. Subtle anomalies in the processing of these genes might go unnoticed in the absence of a genomic reference. And thus undiscovered immune diversification mechanisms or other noncanonical molecular mechanisms may be overlooked.) Whole-genome sequences lend huge amounts of data to the study of phylogeny. Although more data per se may not solve some of the more pressing systematic problems, genome sequences increase the chances of identifying useful discrete characters that are less susceptible to homoplasy.) Genomes have revolutionized our view of the relationship between phylogenetic position and genetic complexity—especially notable in the genome of the sea anemone Nematostella, but also emerging in lophotrochozoan genomes. Many genes that were thought to be restricted to vertebrates or deuterostomes were likely present early in eumetazoan phylogeny.A welcome revolution in speed and cost of nucleic acid sequencing technology has begun in the last few years. News stories of $1000 human genome sequences abound. While this dazzling goal is still some distance in the future, sequencing projects that were very recently possible only in large government-run facilities will soon be routine at the core facility level and eventually even within the individual laboratory. Of course, this momentum stems from human biomedical goals. Nevertheless, the cost of entire bilaterian genome sequences will move into the realm of individual research grant budgets, and a new genome sequence will be seen as experimental data. The most important outcome of this futurism is the contribution, mentioned above, that genomes make to providing a scientific understanding how an animal works.It is particularly appropriate that this virtual symposium and its introduction of blatant propaganda in support of genome sequencing be published in The Biological Bulletin, for the home institution of the journal, the Marine Biological Laboratory, has been one of the places where mechanistic biology of marine animals first flourished and where it continues today.Literature CitedFahey, B., C. Larroux, B. Woodcroft, and B. M. Degnan. 2008. Does the high gene density in the sponge NK homeobox gene cluster reflect limited regulatory capacity? Biol. Bull. 214: 205–217.First citation in articleLinkGoogle ScholarFreeman, R. M., Jr., M. Wu, M-M. Cordonnier-Pratt, L. H. Pratt, C. E. Gruber, M. Smith, E. S. Lander, N. Stange-Thomann, C. J. Lowe, J. Gerhart, and M. Kirschner. 2008. cDNA sequences for transcription factors and signaling proteins of the hemichordate Saccoglossus kowalevskii: efficacy of the expressed sequence tag (EST) approach for evolutionary and developmental studies of a new organism. Biol. Bull. 214: 284–302.First citation in articleLinkGoogle ScholarMagie, C. R., and M. Q. Martindale. 2008. Cell-cell adhesion in the Cnidaria: insights into the evolution of tissue morphogenesis. Biol. Bull. 214: 218–232.First citation in articleLinkGoogle ScholarMaterna, S. C., and R. A. Cameron. 2008. The sea urchin genome as a window on function. Biol. Bull. 214: 266–273.First citation in articleLinkGoogle ScholarNyholm, S. V., J. Robidart, and P. R. Girguis. 2008. Coupling metabolite flux to transcriptomics: insights into the molecular mechanisms underlying primary productivity by the hydrothermal vent tubeworm Ridgeia piscesae. Biol. Bull. 214: 255–265.First citation in articleLinkGoogle ScholarRast, J. P., and C. Messier-Solek. 2008. Marine invertebrate genome sequences and our evolving understanding of animal immunity. Biol. Bull. 214: 274–283.First citation in articleLinkGoogle ScholarReitzel, A. M., J. C. Sullivan, N. Traylor-Knowles, and J. R. Finnerty. 2008. Genomic survey of candidate stress-response genes in the estuarine anemone Nematostella vectensis. Biol. Bull. 214: 233–254.First citation in articleLinkGoogle ScholarSauka-Spengler, T., and M. Bronner-Fraser. 2008. Insights from a sea lamprey into the evolution of neural crest gene regulatory network. Biol. Bull. 214: 303–314.First citation in articleLinkGoogle Scholar Previous articleNext article DetailsFiguresReferencesCited by The Biological Bulletin Volume 214, Number 3June 2008 Published in association with the Marine Biological Laboratory Article DOIhttps://doi.org/10.1086/BBLv214n3p203 Views: 225Total views on this site PDF download Crossref reports no articles citing this article.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.011 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it