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Record W2737347245 · doi:10.1186/s12870-017-1079-2

Identification and characterization of suppressor mutants of stop1

2017· article· en· W2737347245 on OpenAlexaff
Fei Jiang, Tao Wang, Yuqi Wang, Leon V. Kochian, Fang Chen, Jiping Liu

Bibliographic record

VenueBMC Plant Biology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAluminum toxicity and tolerance in plants and animals
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersChina Scholarship CouncilU.S. Department of Agriculture
KeywordsBiologyIdentification (biology)Computational biologyMutantSuppressorGeneticsGeneBotany

Abstract

fetched live from OpenAlex

BACKGROUND: Proton stress and aluminum (Al) toxicity are major constraints limiting crop growth and yields on acid soils (pH < 5). In Arabidopsis, STOP1 is a master transcription factor that controls the expression of a set of well-characterized Al tolerance genes and unknown processes involved in low pH resistance. As a result, loss-of-function stop1 mutants are extremely sensitive to low pH and Al stresses. RESULTS: Here, we report on screens of an ethyl-methane sulphonate (EMS)-mutagenized stop1 population and isolation of nine strong stop1 suppressor mutants, i.e., the tolerant to proton stress (tps) mutants, with significantly enhanced root growth at low pH (4.3). Genetic analyses indicated these dominant and partial gain-of-function mutants are caused by mutations in single nuclear genes outside the STOP1 locus. Physiological characterization of the responses of these tps mutants to excess levels of Al and other metal ions further classified them into five groups. Three tps mutants also displayed enhanced resistance to Al stress, indicating that these tps mutations partially rescue the hypersensitive phenotypes of stop1 to both low pH stress and Al stress. The other six tps mutants showed enhanced resistance only to low pH stress but not to Al stress. We carried out further physiologic and mapping-by-sequencing analyses for two tps mutants with enhanced resistance to both low pH and Al stresses and identified the genomic regions and candidate loci in chromosomes 1 and 2 that harbor these two TPS genes. CONCLUSION: We have identified and characterized nine strong stop1 suppressor mutants. Candidate loci for two tps mutations that partially rescue the hypersensitive phenotypes of stop1 to low pH and Al stresses were identified by mapping-by-sequencing approaches. Further studies could provide insights into the structure and function of TPSs and the regulatory networks underlying the STOP1-mediated processes that lead to resistance to low pH and Al stresses in Arabidopsis.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.037
GPT teacher head0.247
Teacher spread0.210 · 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 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

Citations14
Published2017
Admission routes1
Has abstractyes

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