Whole Genome Sequencing Reveals Genetic Differences Between Symbiodiniaceae Populations Among Reproductively and Geographically Isolated <i>Acropora</i> Colonies in Western Australia
Bibliographic record
Abstract
ABSTRACT Significant genetic differentiation between Symbiodiniaceae populations in coral hosts can be induced by a range of factors including geography, latitude, depth, temperature and light utilisation. The conventional method of measuring Symbiodiniaceae diversity involving the ITS2 region of rDNA has several limitations, stemming from insufficient genetic resolution and the multi‐copy nature of the marker. This could be improved by using higher throughput whole genome sequencing to identify fine‐scale population genetic differences and provide new insight into factors influencing coral‐Symbiodiniaceae associations. The aim of this study was to investigate the genetic diversity of Symbiodiniaceae populations using low‐coverage whole genome sequencing in sympatric populations of Acropora cf. secale and allopatric populations of Acropora millepora that reproduce in different seasons in Western Australia. Genetic diversity of Symbiodiniaceae populations in these two species was examined using principal coordinates analysis and permutational analysis of variance. This analysis revealed that while all colonies were dominated by Cladocopium, there was a significant genetic difference between Symbiodiniaceae populations in both species. In A. millepora, this variation could be due to the latitudinal variation between populations or differences in reproductive seasonality, but in sympatric populations of A. cf. secale, genetic differences between Symbiodiniaceae populations were clearly aligned with the reproductive seasonality of the coral host. The use of whole genome sequencing improved the sensitivity to detect Symbiodiniaceae genetic population structure between coral populations, which increases our ability to identify genetic and potentially functional differences associated with variation in Symbiodiniaceae populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".