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Prunus transcription factors: breeding perspectives

Overview of attention for article published in Frontiers in Plant Science, June 2015
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Title
Prunus transcription factors: breeding perspectives
Published in
Frontiers in Plant Science, June 2015
DOI 10.3389/fpls.2015.00443
Pubmed ID
Authors

Valmor J. Bianchi, Manuel Rubio, Livio Trainotti, Ignazio Verde, Claudio Bonghi, Pedro Martínez-Gómez

Abstract

Many plant processes depend on differential gene expression, which is generally controlled by complex proteins called transcription factors (TFs). In peach, 1533 TFs have been identified, accounting for about 5.5% of the 27,852 protein-coding genes. These TFs are the reference for the rest of the Prunus species. TF studies in Prunus have been performed on the gene expression analysis of different agronomic traits, including control of the flowering process, fruit quality, and biotic and abiotic stress resistance. These studies, using quantitative RT-PCR, have mainly been performed in peach, and to a lesser extent in other species, including almond, apricot, black cherry, Fuji cherry, Japanese apricot, plum, and sour and sweet cherry. Other tools have also been used in TF studies, including cDNA-AFLP, LC-ESI-MS, RNA, and DNA blotting or mapping. More recently, new tools assayed include microarray and high-throughput DNA sequencing (DNA-Seq) and RNA sequencing (RNA-Seq). New functional genomics opportunities include genome resequencing and the well-known synteny among Prunus genomes and transcriptomes. These new functional studies should be applied in breeding programs in the development of molecular markers. With the genome sequences available, some strategies that have been used in model systems (such as SNP genotyping assays and genotyping-by-sequencing) may be applicable in the functional analysis of Prunus TFs as well. In addition, the knowledge of the gene functions and position in the peach reference genome of the TFs represents an additional advantage. These facts could greatly facilitate the isolation of genes via QTL (quantitative trait loci) map-based cloning in the different Prunus species, following the association of these TFs with the identified QTLs using the peach reference genome.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 1%
Mexico 1 1%
Czechia 1 1%
France 1 1%
Unknown 89 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 23%
Researcher 21 23%
Professor > Associate Professor 7 8%
Student > Master 7 8%
Student > Doctoral Student 5 5%
Other 15 16%
Unknown 17 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 61%
Biochemistry, Genetics and Molecular Biology 9 10%
Environmental Science 3 3%
Business, Management and Accounting 2 2%
Nursing and Health Professions 1 1%
Other 3 3%
Unknown 18 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 July 2015.
All research outputs
#13,944,553
of 22,807,037 outputs
Outputs from Frontiers in Plant Science
#7,268
of 20,087 outputs
Outputs of similar age
#131,960
of 264,956 outputs
Outputs of similar age from Frontiers in Plant Science
#81
of 268 outputs
Altmetric has tracked 22,807,037 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,087 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,956 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 268 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.