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Record W4385727910 · doi:10.1093/hr/uhad161

Chromosome-scale genome sequence of <i>Suaeda glauca</i> sheds light on salt stress tolerance in halophytes

2023· article· en· W4385727910 on OpenAlexaff
Yan Cheng, Jin Sun, Mengwei Jiang, Ziqiang Luo, Yu Wang, Yanhui Liu, Weiming Li, Bing Hu, Chunxing Dong, Kangzhuo Ye, Zixian Li, Fang Deng, Lulu Wang, Ling Cao, Shijiang Cao, Chenglang Pan, Ping Zheng, Sheng Wang, Mohammad Aslam, Hong Wang, Yuan Qin

Bibliographic record

VenueHorticulture Research · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversity of Saskatchewan
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsBiologyGeneticsGenomeGeneHalophyteGene familySyntenySalinity

Abstract

fetched live from OpenAlex

Abstract Soil salinity is a growing concern for global crop production and the sustainable development of humanity. Therefore, it is crucial to comprehend salt tolerance mechanisms and identify salt-tolerance genes to enhance crop tolerance to salt stress. Suaeda glauca, a halophyte species well adapted to the seawater environment, possesses a unique ability to absorb and retain high salt concentrations within its cells, particularly in its leaves, suggesting the presence of a distinct mechanism for salt tolerance. In this study, we performed de novo sequencing of the S. glauca genome. The genome has a size of 1.02 Gb (consisting of two sets of haplotypes) and contains 54 761 annotated genes, including alleles and repeats. Comparative genomic analysis revealed a strong synteny between the genomes of S. glauca and Beta vulgaris. Of the S. glauca genome, 70.56% comprises repeat sequences, with retroelements being the most abundant. Leveraging the allele-aware assembly of the S. glauca genome, we investigated genome-wide allele-specific expression in the analyzed samples. The results indicated that the diversity in promoter sequences might contribute to consistent allele-specific expression. Moreover, a systematic analysis of the ABCE gene families shed light on the formation of S. glauca’s flower morphology, suggesting that dysfunction of A-class genes is responsible for the absence of petals in S. glauca. Gene family expansion analysis demonstrated significant enrichment of Gene Ontology (GO) terms associated with DNA repair, chromosome stability, DNA demethylation, cation binding, and red/far-red light signaling pathways in the co-expanded gene families of S. glauca and S. aralocaspica, in comparison with glycophytic species within the chenopodium family. Time-course transcriptome analysis under salt treatments revealed detailed responses of S. glauca to salt tolerance, and the enrichment of the transition-upregulated genes in the leaves associated with DNA repair and chromosome stability, lipid biosynthetic process, and isoprenoid metabolic process. Additionally, genome-wide analysis of transcription factors indicated a significant expansion of FAR1 gene family. However, further investigation is needed to determine the exact role of the FAR1 gene family in salt tolerance in S. glauca.

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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.001

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 head0.028
GPT teacher head0.328
Teacher spread0.300 · 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

Citations27
Published2023
Admission routes1
Has abstractyes

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