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Record W4401548680 · doi:10.1038/s41588-024-01876-7

Chloroplast and whole-genome sequencing shed light on the evolutionary history and phenotypic diversification of peanuts

2024· article· en· W4401548680 on OpenAlexaff
Zheng Zheng, Ziqi Sun, Feiyan Qi, Yuanjin Fang, Ke Lin, Stefano Pavan, Bingyan Huang, Wenzhao Dong, Pei Du, Mengdi Tian, Lei Shi, Jing Xu, Suoyi Han, Huan Liu, Qin Li, Zhongxin Zhang, Xiaodong Dai, Lijuan Miao, Ruifang Zhao, Juan Wang, Yan-Lin Liao, Alun Li, Jue Ruan, Chiara Delvento, Riccardo Aiese Cigliano, Chris Maliepaard, Yuling Bai, Richard G. F. Visser, Xinyou Zhang

Bibliographic record

VenueNature Genetics · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPeanut Plant Research Studies
Canadian institutionsMinistry of Agriculture
FundersNational Key Research and Development Program of ChinaChinese Academy of Agricultural SciencesEuropean Commission
KeywordsBiologyArachis hypogaeaDomesticationGermplasmGenomeArachisEvolutionary biologyGeneticsBotanyGene

Abstract

fetched live from OpenAlex

Cultivated peanut (Arachis hypogaea L.) is a widely grown oilseed crop worldwide; however, the events leading to its origin and diversification are not fully understood. Here by combining chloroplast and whole-genome sequence data from a large germplasm collection, we show that the two subspecies of A. hypogaea (hypogaea and fastigiata) likely arose from distinct allopolyploidization and domestication events. Peanut genetic clusters were then differentiated in relation to dissemination routes and breeding efforts. A combination of linkage mapping and genome-wide association studies allowed us to characterize genes and genomic regions related to main peanut morpho-agronomic traits, namely flowering pattern, inner tegument color, growth habit, pod/seed weight and oil content. Together, our findings shed light on the evolutionary history and phenotypic diversification of peanuts and might be of broad interest to plant breeders.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.217
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2024
Admission routes1
Has abstractyes

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