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| Status |
Public on Dec 10, 2012 |
| Title |
Ovary transcriptome profiling via application of artificial intelligence predicts egg quality in striped bass |
| Organism |
Morone saxatilis |
| Experiment type |
Expression profiling by array
|
| Summary |
We modeled profiles of ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in striped bass (Morone saxatilis) using artificial neural networks and supervised machine learning. Collective changes in expression of a limited suite of genes (233) representing only 2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in expression (≤0.2-fold), with most gene transcripts making minor contribution (<1%) to the overall prediction of egg quality. Correlation analyses of this suite of candidate genes indicated that collective dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence in striped bass. Our results show that the transcriptomic signature evidencing this dysfunction is of, and therefore likely to influence, egg quality, a biologically complex trait that is crucial to reproductive fitness.
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| Overall design |
Female striped bass were sorted into groups (N=8 each) producing ‘high quality’ or ‘low quality’ eggs (spawns) based upon the percentage of eggs bearing viable 4 h embryos. Spawns with >50% of eggs producing 4 h embryos were considered to be of high quality and spawns with <30% of eggs producing 4 h embryos were considered to be of low quality.
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| |
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| Contributor(s) |
Reading BJ, Chapman RW, Williams VN, Ring BD, Hopper M, McGinty AS, Neely MG, Sullivan CV |
| Citation(s) |
24820964 |
| Submission date |
Dec 07, 2012 |
| Last update date |
Jul 29, 2019 |
| Contact name |
Marion Neely |
| E-mail(s) |
marion.neely@gmail.com
|
| Organization name |
National Ocean Services
|
| Department |
NCCOS
|
| Lab |
Marine Genomics Core Facility
|
| Street address |
331 Ft. Johnson Rd
|
| City |
Charleston |
| State/province |
SC |
| ZIP/Postal code |
29412 |
| Country |
USA |
| |
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| Platforms (1) |
| GPL16363 |
Agilent-029034 Morone saxatilis ST2010B [Probe Name version] |
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| Samples (16)
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| Relations |
| BioProject |
PRJNA183347 |
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