Evidence map›Paper›PMID 30705685›Full record

ArticleFrontiers in plant science2018

Association Mapping Analysis for Fruit Quality Traits in

Carolina Font I Forcada, Verónica Guajardo, Sebastian Reyes Chin-Wo, María Ángeles Moreno

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
9.3field-weighted citation impact, top 3% of its field
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

17 citing papers in PubMed, 48 citations in OpenAlex.

  1. Article
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  5. Review
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  10. Review
  11. Detection of Quantitative TraitFrontiers in plant science · 2021
    Article
  12. Genome-Wide Association Study of Brown Rot (Frontiers in plant science · 2021
    Article
  13. Article
  14. Functional Markers for Precision Plant Breeding.International journal of molecular sciences · 2020
    Review
  15. Functional Analysis Reveals the Regulatory Role ofInternational journal of molecular sciences · 2020
    Article
  16. Article
  17. 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

4 authors at 2 institutions in 2 countries.

Carolina Font I ForcadaDepartment of Pomology, Estación Experimental de Aula Dei-CSIC, Zaragoza, Spain.
Verónica GuajardoCentro de Estudios Avanzados en Fruticultura, Rengo, Chile.
Sebastian Reyes Chin-WoGenome Center, University of California, Davis, Davis, CA, United States.
María Ángeles MorenoDepartment of Pomology, Estación Experimental de Aula Dei-CSIC, Zaragoza, Spain.
Estación Experimental de Aula Dei · ESUniversity of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of genes involved in variation of peach fruit quality would assist breeders to create new cultivars with improved fruit quality. Peach is a genetic and genomic model within the Rosaceae. A large quantity of useful data suitable for fine mapping using Single Nucleotide Polymorphisms (SNPs) from the peach genome sequence was used in this study. A set of 94 individuals from a peach germplasm collection was phenotyped and genotyped, including local Spanish and modern cultivars maintained at the Experimental Station of Aula Dei, Spain. Phenotypic evaluation based on agronomical, pomological and fruit quality traits was performed at least 3 years. A set of 4,558 out of a total of 8,144 SNPs markers developed by the Illumina Infinium BeadArray (v1.0) technology platform, covering the peach genome, were analyzed for population structure analysis and genome-wide association studies (GWAS). Population structure analysis identified two subpopulations, with admixture within them. While one subpopulation contains only modern cultivars, the other one is formed by local Spanish and several modern cultivars from international breeding programs. To test the marker trait associations between markers and phenotypic traits, four models comprising both general linear model (GLM) and mixed linear model (MLM) were selected. The MLM approach using co-ancestry values from population structure and kinship estimates (K model) identified a maximum of 347 significant associations between markers and traits. The associations found appeared to map within the interval where many candidate genes involved in different pathways are predicted in the peach genome. These results represent a promising situation for GWAS in the identification of SNP variants associated to fruit quality traits, potentially applicable in peach breeding programs.

Indexed as

antioxidantscandidate genesfirmnessgermplasmpeachsingle nucleotide polymorphismsugar content

Identifiers

PMID30705685
PMCPMC6344403
OpenAlexW2909747065

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.