Evidence map›Paper›PMID 38683231›Full record

ArticleMolecular biology reports2024

Applicability of SCoT markers in unraveling genetic variation and population structure among sugar beet (Beta vulgaris L.) germplasm.

Nazlı Aybar Yalinkiliç, Sema Başbağ, Muhammad Tanveer Altaf, Amjad Ali, Muhammad Azhar Nadeem, Faheem Shehzad Baloch

Abstract read
PubMed Publisher
In one paragraph

Article in Molecular biology reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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

6 authors.

Nazlı Aybar YalinkiliçFaculty of Applied Sciences, Department of Plant Production and Technologies, Mus Alparslan University, Muş, Türkiye, Turkey.
Sema BaşbağDepartment of field crops, Faculty of agriculture, Dicle University, Diyarbakir, Türkiye, Turkey.
Muhammad Tanveer AltafDepartment of Plant Production and Technologies, Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, 58140, Sivas, Türkiye, Turkey.
Amjad AliDepartment of Plant Protection, Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, 58140, Sivas, Türkiye, Turkey.
Muhammad Azhar NadeemDepartment of Plant Production and Technologies, Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, 58140, Sivas, Türkiye, Turkey.
Faheem Shehzad BalochDepartment of Biotechnology, Faculty of Science, Mersin University, Yenişehir, Mersin, Türkiye, 33343, Turkey. balochfaheem13@gmail.com.

Funding

Dicle Üniversitesi ZİRAAT.22.014
6 · The paper itself

Abstract

backgroundSugar beet (Beta vulgaris L.) holds significant importance as a crop globally cultivated for sugar production. The genetic diversity present in sugar beet accessions plays a crucial role in crop improvement programs. METHODS AND

resultsDuring the present study, we collected 96 sugar beet accessions from different regions and extracted DNA from their leaves. Genomic DNA was amplified using SCoT primers, and the resulting fragments were separated by gel electrophoresis. The data were analyzed using various genetic diversity indices, and constructed a population STRUCTURE, applied the unweighted pair-group method with arithmetic mean (UPGMA), and conducted Principle Coordinate Analysis (PCoA). The results revealed a high level of genetic diversity among the sugar beet accessions, with 265 bands produced by the 10 SCoT primers used. The percentage of polymorphic bands was 97.60%, indicating substantial genetic variation. The study uncovered significant genetic variation, leading to higher values for overall gene diversity (0.21), genetic distance (0.517), number of effective alleles (1.36), Shannon's information index (0.33), and polymorphism information contents (0.239). The analysis of molecular variance suggested a considerable amount of genetic variation, with 89% existing within the population. Using STRUCTURE and UPGMA analysis, the sugar beet germplasm was divided into two major populations. Structure analysis partitioned the germplasm based on the origin and domestication history of sugar beet, resulting in neighboring countries clustering together.

conclusionThe utilization of SCoT markers unveiled a noteworthy degree of genetic variation within the sugar beet germplasm in this study. These findings can be used in future breeding programs with the objective of enhancing both sugar beet yield and quality.

Indexed as

Beta vulgarisGenetic VariationAllelesDNA, PlantGenetic MarkersGenetics, PopulationPhylogenyPlant BreedingPolymorphism, GeneticDNA, PlantGenetic MarkersBeta vulgarisGenetic diversityL. SCoT markersPopulation structurePrinciple coordinate analysis

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.