MétaCan
Menu
Back to cohort
Record W3183440941 · doi:10.5376/rgg.2021.12.0003

Tibet Identification of the Fragrance Allele and Development of the Functional Markers for Fragrance in Taiguoxiaoxiangzhan

2021· article· en· W3183440941 on OpenAlexvenueno aff
Yuehui Zeng, Xinyu Wei, Jianhong Huang, Ruiyan Zhang, Wei Shang, Xinpo Hou, Xuming Xu

Bibliographic record

VenueRice Genomics and Genetics · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGABA and Rice Research
Canadian institutionsnot available
Fundersnot available
KeywordsIndelAromatic riceGermplasmBiologyAlleleMarker-assisted selectionGeneGenotypeSingle-nucleotide polymorphismHorticultureOryza sativaGenetics

Abstract

fetched live from OpenAlex

The fragrant rice breeding has become an important direction for hybrid rice breeding program. The selection and utilization of parent materials with ideal plant type, fine grain quality, strong resistance and other excellent agronomic characteristics with strong fragrance, especially the utilization and cultivation of the fragrant rice restorer lines, is of great significance to further promote the fragrant hybrid rice breeding. Taiguoxiaoxiangzhan is a restorer line with excellent grain quality, strong resistance and fragrance, which has been widely used in fragrant rice breeding in China. In order to trace the fragrance in Taiguoxiaoxiangzhan, we identified the type of the fragrance gene in Taiguoxiaoxiangzhan was badh2-E7 which has an 8 bp deletion and three single nucleotide polymorphisms (SNPs) in exon 7, and this gene is a non-functional badh2 allele and that the functional Badh2 allele encoding betaine aldehyde dehydrogenase (BADH2) could render rice non-fragrant. Furthermore, we found that the Taiguoxiaoxiangzhan increased 2-acetyl-1-pyrroline (2-AP) content (0.108 mg/kg) compared with the non-fragrant rice varieties of Nipponbare and 9311 (<0.01 mg/kg) by the GC-MS method. We also proved that FMbadh2-E7 and InDel-E7, two molecular markers reported earlier, can be applied in different genotypes, including Badh2/Badh2 (non-fragrance homozygote), Badh2/bahd2 (non-fragrance heterozygote) and badh2/badh2 (fragrance homozygote). In addition, based on sequence divergence amongst the functional Badh2 and null badh2-E7 allele, we developed two functional markers, FMbadh2-E7A and FMbadh2-E7B, which can be easily used to distinguish non-fragrant from fragrant rice. Genetic analysis shows that the segregation of Badh2/Badh2 , Badh2/badh2 and badh2/badh2 in the F 2 population derived from crosses between Taiguoxiaoxiangzhan and different restorer lines fitted a theoretical ratio of 1:2:1, indicating that the fragrance of Taiguoxiaoxiangzhan is controlled by a single nuclear recessive gene ( bahd2 ). In this study, the identification and genetic analysis of the fragrance gene in Taiguoxiaoxiangzhan and the development of functional markers for fragrance have been studied, which provides a theoretical foundation for the further breeding of fragrant hybrid rice with excellent quality, high yield and strong resistance by molecular marker-assisted selection technology.

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 score0.005
Threshold uncertainty score0.010

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)0.0020.000

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 head0.022
GPT teacher head0.220
Teacher spread0.198 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRice Genomics and GeneticsSame topicGABA and Rice ResearchFrench-language works237,207