Evidence map›Paper›PMID 31615398›Full record

ArticleBMC genomics2019

Selection of candidate genes controlling veraison time in grapevine through integration of meta-QTL and transcriptomic data.

Pietro Delfino, Sara Zenoni, Zahra Imanifard, Giovanni Battista Tornielli, Diana Bellin

Abstract read
In one paragraph

Article in BMC genomics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Frontiers in plant science · 2026
    Article
  4. Article
  5. Allele-based modeling to predict phenological stages of grapevine hybrids under future climatic conditions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  6. Review
  7. Article
  8. Article
  9. Biography ofHorticulture research · 2024
    Article
  10. Article
  11. Article
  12. A high-density integrated map for grapevine based on three mapping populations genotyped by the Vitis18K SNP chip.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  13. Consensus genetic map and QTLs for morphological and agronomical traits in mungbean using DArT markers.Physiology and molecular biology of plants : an international journal of functional plant biology · 2022
    Article
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  17. Review
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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

5 authors.

Pietro DelfinoDepartment of Biotechnology, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.
Sara ZenoniDepartment of Biotechnology, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.
Zahra ImanifardDepartment of Biotechnology, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.
Giovanni Battista TornielliDepartment of Biotechnology, University of Verona, Strada le Grazie 15, 37134, Verona, Italy.
Diana BellinDepartment of Biotechnology, University of Verona, Strada le Grazie 15, 37134, Verona, Italy. diana.bellin@univr.it.ORCID http://orcid.org/0000-0002-0308-7733

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh temperature during grape berry ripening impairs the quality of fruits and wines. Veraison time, which marks ripening onset, is a key factor for determining climatic conditions during berry ripening. Understanding its genetic control is crucial to successfully breed varieties more adapted to a changing climate. Quantitative trait loci (QTL) studies attempting to elucidate the genetic determinism of developmental stages in grapevine have identified wide genomic regions. Broad scale transcriptomic studies, by identifying sets of genes modulated during berry development and ripening, also highlighted a huge number of putative candidates.

resultsWith the final aim of providing an overview about available information on the genetic control of grapevine veraison time, and prioritizing candidates, we applied a meta-QTL analysis for grapevine phenology-related traits and checked for co-localization of transcriptomic candidates. A consensus genetic map including 3130 markers anchored to the grapevine genome assembly was compiled starting from 39 genetic maps. Two thousand ninety-three QTLs from 47 QTL studies were projected onto the consensus map, providing a comprehensive overview about distribution of available QTLs and revealing extensive co-localization especially across phenology related traits. From 141 phenology related QTLs we generated 4 veraison meta-QTLs located on linkage group (LG) 1 and 2, and 13 additional meta-QTLs connected to the veraison time genetic control, among which the most relevant were located on LG 14, 16 and 18. Functional candidates in these intervals were inspected. Lastly, taking advantage of available transcriptomic datasets, expression data along berry development were integrated, in order to pinpoint among positional candidates, those differentially expressed across the veraison transition.

conclusionIntegration of meta-QTLs analysis on available phenology related QTLs and data from transcriptomic dataset allowed to strongly reduce the number of candidate genes for the genetic control of the veraison transition, prioritizing a list of 272 genes, among which 78 involved in regulation of gene expression, signal transduction or development.

Indexed as

Quantitative Trait LociChromosome MappingChromosomes, PlantGene Expression ProfilingGene Expression Regulation, DevelopmentalGene Expression Regulation, PlantPlant ProteinsVitisPlant ProteinsGrape berry developmentGrapevineMeta-QTLPhenologyQTLTranscriptomicsVeraison

Identifiers

PMID31615398
PMCPMC6794750

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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.