Evidence map›Paper›PMID 35371156›Full record

ArticleFrontiers in plant science2022

Quantitative Trait Loci Mapping and Identification of Candidate Genes Linked to Fruit Acidity in Apricot (

Luca Dondini, Cecilia Domenichini, Yonghui Dong, Fabio Gennari, Daniele Bassi, Stefano Foschi, Martina Lama, Marco Adami, Paolo De Franceschi, Claudia Cervellati and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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

13 authors at 4 institutions in 1 country.

Luca DondiniDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Cecilia DomenichiniDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Yonghui DongDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Fabio GennariDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Daniele BassiDepartment of Agricultural and Environmental Sciences (DISAA), University of Milan, Milan, Italy.
Stefano FoschiRinova, Cesena, Italy.
Martina LamaAstra Innovazione e Sviluppo, Imola, Italy.
Marco AdamiDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Paolo De FranceschiDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Claudia CervellatiDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Lorenzo BergonzoniDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Sara AlessandriDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
Stefano TartariniDepartment of Agricultural and Food Sciences, Alma Mater Studiorum - University of Bologna, Bologna, Italy.
University of Bologna · ITAzienda-Unita' Sanitaria Locale Di Cesena · ITInnova (Italy) · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Apricot breeding programs could be strongly improved by the availability of molecular markers linked to the main fruit quality traits. Fruit acidity is one of the key factors in consumer acceptance, but despite its importance, the molecular bases of this trait are still poorly understood. In order to increase the genetic knowledge on the fruit acidity, an F1 apricot population ('Lito' × 'BO81604311') has been phenotyped for titratable acidity and juice pH for the three following years. In addition, the contents of the main organic acids of the juice (malate, citrate, and quinate) were also evaluated. A Gaussian distribution was observed for most of the traits in this progeny, confirming their quantitative inheritance. An available simple sequence repeat (SSR)-based molecular map, implemented with new markers in specific genomic regions, was used to perform a quantitative trait loci (QTL) analysis. The molecular map was also anchored to the recently published apricot genome sequence of 'Stella.' Several major QTLs linked to fruit acidity-related traits have been identified both in the 'Lito' (no. 21) and 'BO81604311' (no. 13), distributed in five linkage groups (LG 4, 5, 6, 7, and 8). Some of these QTLs show good stability between years and their linked markers were used to identify candidate genes in specific QTLs genomic regions.

Indexed as

citratefruit pHfruit qualitymalatequinate

Identifiers

PMID35371156
PMCPMC8972129
OpenAlexW4220692441

What OpenQuestion holds

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LicenceCC BY
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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.