Control of vein network topology by auxin transport
Bibliographic record
Abstract
BACKGROUND: Tissue networks such as the vascular networks of plant and animal organs transport signals and nutrients in most multicellular organisms. The transport function of tissue networks depends on topological features such as the number of networks' components and the components' connectedness; yet what controls tissue network topology is largely unknown, partly because of the difficulties in quantifying the effects of genes on tissue network topology. We address this problem for the vein networks of plant leaves by introducing biologically motivated descriptors of vein network topology; we combine these descriptors with cellular imaging and molecular genetic analysis; and we apply this combination of approaches to leaves of Arabidopsis thaliana that lack function of, overexpress or misexpress combinations of four PIN-FORMED (PIN) genes--PIN1, PIN5, PIN6, and PIN8--which encode transporters of the plant signal auxin and are known to control vein network geometry. RESULTS: We find that PIN1 inhibits vein formation and connection, and that PIN6 acts redundantly to PIN1 in these processes; however, the functions of PIN6 in vein formation are nonhomologous to those of PIN1, while the functions of PIN6 in vein connection are homologous to those of PIN1. We further find that PIN8 provides functions redundant and homologous to those of PIN6 in PIN1-dependent inhibition of vein formation, but that PIN8 has no functions in PIN1/PIN6-dependent inhibition of vein connection. Finally, we find that PIN5 promotes vein formation; that all the vein-formation-promoting functions of PIN5 are redundantly inhibited by PIN6 and PIN8; and that these functions of PIN5, PIN6, and PIN8 are independent of PIN1. CONCLUSIONS: Our results suggest that PIN-mediated auxin transport controls the formation of veins and their connection into networks.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".