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Record W3185678042 · doi:10.1111/pbi.13660

Engineering chloroplast development in rice through cell‐specific control of endogenous genetic circuits

2021· article· en· W3185678042 on OpenAlexaff
Dong‐Yeon Lee, Lei Hua, Roxana Khoshravesh, R. Giuliani, Indrajit Kumar, Asaph B. Cousins, Tammy L. Sage, Julian M. Hibberd, Thomas P. Brutnell

Bibliographic record

VenuePlant Biotechnology Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversity of Toronto
FundersUniversity of OxfordBill and Melinda Gates FoundationNational Science Foundation
KeywordsBiologyChloroplastEndogenyComputational biologyCell biologyBiotechnologyGeneticsGeneBiochemistry

Abstract

fetched live from OpenAlex

Summary The engineering of C 4 photosynthetic activity into the C 3 plant rice has the potential to nearly double rice yields. To engineer a two‐cell photosynthetic system in rice, the rice bundle sheath (BS) must be rewired to enhance photosynthetic capacity. Here, we show that BS chloroplast biogenesis is enhanced when the transcriptional activator, Oryza sativa Cytokinin GATA transcription factor 1 ( OsCGA1) , is driven by a vascular specific promoter. Ectopic expression of OsCGA1 resulted in increased BS chloroplast planar area and increased expression of photosynthesis‐associated nuclear genes (PhANG), required for the biogenesis of photosynthetically active chloroplasts in BS cells of rice. A further refinement using a DNAse dead Cas9 (dCas9) activation module driven by the same cell‐type specific promoter, directed enhanced chloroplast development of the BS cells when gRNA sequences were delivered by the dCas9 module to the promoter of the endogenous OsCGA1 gene. Single gRNA expression was sufficient to mediate the transactivation of both the endogenous gene and a transgenic GUS reporter fused with OsCGA1 promoter. Our results illustrate the potential for tissue‐specific dCas9‐activation and the co‐regulation of genes needed for multistep engineering of C 4 rice.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

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

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 head0.011
GPT teacher head0.181
Teacher spread0.171 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations33
Published2021
Admission routes1
Has abstractyes

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