Evidence map›Paper›PMID 28314999›Full record

ArticlePlanta2017

Genetic diversity and metabolic profile of Salvia officinalis populations: implications for advanced breeding strategies.

Eirini Sarrou, Ioannis Ganopoulos, Aliki Xanthopoulou, Domenico Masuero, Stefan Martens, Panagiotis Madesis, Athanasios Mavromatis, Paschalina Chatzopoulou

Abstract read
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In one paragraph

Article in Planta, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
  2. Evaluation ofPlants (Basel, Switzerland) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Mitochondrial Genome Sequence ofInternational journal of molecular sciences · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Lignans of Sesame (Molecules (Basel, Switzerland) · 2021
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Eirini SarrouDepartment of Medicinal and Aromatic Plants, Hellenic Agricultural Organization DEMETER, Plant Breeding and Genetic Resources Institute, PB&GRI, Thermi, Thessaloniki, 57001, Greece. esarrou@agro.auth.com.ORCID http://orcid.org/0000-0002-3818-8382
Ioannis GanopoulosInstitute of Applied Biosciences, CERTH, 6th km Charilaou-Thermis Road, Thermi, 57001, Thessaloniki, Greece.
Aliki XanthopoulouInstitute of Applied Biosciences, CERTH, 6th km Charilaou-Thermis Road, Thermi, 57001, Thessaloniki, Greece.
Domenico MasueroDepartment of Food Quality and Nutrition Department, IASMA Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via E. Mach 1, 38010, San Michele all'Adige (TN), Italy.
Stefan MartensDepartment of Food Quality and Nutrition Department, IASMA Research and Innovation Centre, Fondazione Edmund Mach (FEM), Via E. Mach 1, 38010, San Michele all'Adige (TN), Italy.
Panagiotis MadesisInstitute of Applied Biosciences, CERTH, 6th km Charilaou-Thermis Road, Thermi, 57001, Thessaloniki, Greece.
Athanasios MavromatisLaboratory of Genetics and Plant Breeding, Department of Agriculture, Faculty of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Paschalina ChatzopoulouDepartment of Medicinal and Aromatic Plants, Hellenic Agricultural Organization DEMETER, Plant Breeding and Genetic Resources Institute, PB&GRI, Thermi, Thessaloniki, 57001, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MAIN

conclusionAs a result of this work, we were able to characterize seven indigenous to Greece Salvia officinalis populations using genetic and metabolomic tools. These tools can be used to select the most promising genotypes, capable to design future breeding programs for high valuable varieties. An initial investigation was carried out to compare the genetic and metabolic diversity in S. officinalis grown in Greece and to discern the relationship between the two sets of data. Analysis of inter-simple sequence repeats (ISSR) revealed significant genetic differences among seven sage populations, which were grouped into three main clusters according to an UPGMA ISSR data-based dendrogram and Principle Coordinate Analysis. 80 loci were scored of which up to 90% were polymorphic at species level. According to the composition of their essential oil, the populations were classified into two chemotypes: 1.8 cineole/α-thujone and α-thujone/1.8 cineole. Additionally, a targeted ultra performance liquid chromatography (UPLC-MS/MS) method was used to qualify and quantify phenolic compounds in methanolic extracts of the seven sage genotypes according to which they were districted in six clusters among the sage populations. The main compounds characterizing the seven genotypes were rosmarinic acid and carnosol, followed by apigenin-7-O-glucoside (Ap7glc), and luteolin-7-O-glucoside (Lu7glc). The correlation between matrices obtained from ISSR data and metabolic profiles was non-significant. However, based on the differences in metabolic fingerprint, we aimed to define populations using as main selection criteria the high polyphenol content and desired essential oil composition, using state to the art analytical tools for the identification of parent lines for breeding programs.

Indexed as

Genetic VariationMetabolomeBicyclic MonoterpenesBreedingCyclohexanolsEucalyptolFlavonesGenetics, PopulationGenotypeGlucosidesLuteolinMonoterpenesOils, VolatilePhylogenyPlant LeavesPolyphenolsbeta-thujoneBicyclic MonoterpenesCyclohexanolsEucalyptolFlavonesGlucosidesLuteolinluteolin-7-glucosideMonoterpenesOils, VolatilePolyphenolsChemotaxonomyEssential oilsGenetic diversityInter-simple sequence repeats (ISSRs)PhenolicsSage

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.