Evidence map›Paper›PMID 24518809›Full record

ArticleMolecules (Basel, Switzerland)2014

Use of EST-SSR markers for evaluating genetic diversity and fingerprinting celery (Apium graveolens L.) cultivars.

Nan Fu, Ping-Yong Wang, Xiao-Dan Liu, Huo-Lin Shen

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  3. Review
  4. Article
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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

4 authors.

Nan FuCollege of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China. funan@cau.edu.cn.
Ping-Yong WangCollege of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China. wpy0320fn@cau.edu.cn.
Xiao-Dan LiuCollege of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China. liuxiaodan4875527@126.com.
Huo-Lin ShenCollege of Agronomy and Biotechnology, China Agricultural University, No.2 Yuanmingyuan Xi Lu, Haidian District, Beijing 100193, China. SHL1606@cau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Celery (Apium graveolens L.) is one of the most economically important vegetables worldwide, but genetic and genomic resources supporting celery molecular breeding are quite limited, thus few studies on celery have been conducted so far. In this study we made use of simple sequence repeat (SSR) markers generated from previous celery transcriptome sequencing and attempted to detect the genetic diversity and relationships of commonly used celery accessions and explore the efficiency of the primers used for cultivars identification. Analysis of molecular variance (AMOVA) of Apium graveolens L. var. dulce showed that approximately 43% of genetic diversity was within accessions, 45% among accessions, and 22% among horticultural types. The neighbor-joining tree generated by unweighted pair group method with arithmetic mean (UPGMA), and population structure analysis, as well as principal components analysis (PCA), separated the cultivars into clusters corresponding to the geographical areas where they originated. Genetic distance analysis suggested that genetic variation within Apium graveolens was quite limited. Genotypic diversity showed any combinations of 55 genic SSRs were able to distinguish the genotypes of all 30 accessions.

Indexed as

Expressed Sequence TagsApiumDNA FingerprintingGenetic VariationGenotypeMicrosatellite RepeatsPolymorphism, Genetic

Identifiers

PMID24518809
PMCPMC6270925

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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.