International Association for Plant Taxonomy 2021 Stebbins Medal
Bibliographic record
Abstract
Luke T. Dunning, Jill K. Olofsson, Christian Parisod, Rimjhim R. Choudhury, Jose J. Moreno-Villena, Yang Yang, Jacqueline Dionora, W. Paul Quick, Minkyu Park, Jeffrey L. Bennetzen, Guillaume Besnard, Patrik Nosil, Colin P. Osborne & Pascal-Antoine Christin. 2019. Lateral transfers of large DNA fragments spread functional genes among grasses. Proc. Natl. Acad. Sci. U.S.A. 116(10): 4416–4425. https://www.pnas.org/content/116/10/4416.short The Stebbins Medal was first awarded in 2003 in honour of the American botanist and geneticist George Ledyard Stebbins (1906–2000), one of the world's leading plant evolutionary biologists of the 20th century. The medal is awarded biennially by IAPT for an outstanding paper in phylogenetic systematics and evolution of plants. The 2021 award considered papers published in 2018 and 2019. In their paper, Dunning & al. presented the most thorough and far-reaching study to date that convincingly demonstrates extensive lateral gene transfer (LGT) in plants. By comparing genomes of many grasses, they showed that large blocks of DNA containing functional genes are laterally passed among species that are distantly related across the grass phylogeny. Through stringent phylogenomic analyses, they discovered 59 LGTs clustered on 23 laterally acquired genomic fragments that are up to 170 kb long in the genome of the grass Alloteropsis semialata (R.Br.) Hitchc., involving at least nine different donor species. They also showed that some of these laterally transferred genes have added functions to the recipient species genomes. This suggests that LGT represents a potent evolutionary force capable of spreading functional genes among distantly related lineages of grasses. Luke Dunning (Fig. 1), the first author of the 2021 Stebbins Medal paper, studied for his Bachelor's Degree at Cardiff University, Wales, United Kingdom and his Ph.D. at the University of Auckland in New Zealand. Since October 2020, he holds a Natural Environment Research Council (NERC) Independent Research Fellowship in the Department of Animal and Plant Sciences at the University of Sheffield, U.K. Previously, he worked as a postdoctoral researcher with Pascal-Antoine Christin, the senior author of the winning paper, also at the University of Sheffield. Luke's work focuses on the genomics of rapid adaptation in grasses and combines cutting-edge genomic techniques, comparative analyses and experimental approaches to understand how organisms adapt to their environment (https://dunning-lab.group.shef.ac.uk). Many congratulations to Luke Dunning and colleagues! The Stebbins Award committee comprises Paula Rudall (U.K.), Loren Rieseberg (Canada) and Colin Hughes, Chair (Switzerland). The IAPT Council is grateful to the committee for their hard work in making this outstanding selection.
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.
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 | 0.000 | 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".