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Whole-exome sequencing of selected bread wheat recombinant inbred lines as a useful resource for allele mining and bulked segregant analysis

Overview of attention for article published in Frontiers in Genetics, November 2022
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Title
Whole-exome sequencing of selected bread wheat recombinant inbred lines as a useful resource for allele mining and bulked segregant analysis
Published in
Frontiers in Genetics, November 2022
DOI 10.3389/fgene.2022.1058471
Pubmed ID
Authors

Salvatore Esposito, Nunzio D’Agostino, Francesca Taranto, Gabriella Sonnante, Francesco Sestili, Domenico Lafiandra, Pasquale De Vita

Abstract

Although wheat (Triticum aestivum L.) is the main staple crop in the world and a major source of carbohydrates and proteins, functional genomics and allele mining are still big challenges. Given the advances in next-generation sequencing (NGS) technologies, the identification of causal variants associated with a target phenotype has become feasible. For these reasons, here, by combining sequence capture and target-enrichment methods with high-throughput NGS re-sequencing, we were able to scan at exome-wide level 46 randomly selected bread wheat individuals from a recombinant inbred line population and to identify and classify a large number of single nucleotide polymorphisms (SNPs). For technical validation of results, eight randomly selected SNPs were converted into Kompetitive Allele-Specific PCR (KASP) markers. This resource was established as an accessible and reusable molecular toolkit for allele data mining. The dataset we are making available could be exploited for novel studies on bread wheat genetics and as a foundation for starting breeding programs aimed at improving different key agronomic traits.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Other 1 20%
Researcher 1 20%
Student > Master 1 20%
Unknown 2 40%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 20%
Computer Science 1 20%
Agricultural and Biological Sciences 1 20%
Unknown 2 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 February 2023.
All research outputs
#13,665,124
of 23,755,107 outputs
Outputs from Frontiers in Genetics
#3,042
of 12,670 outputs
Outputs of similar age
#171,516
of 459,860 outputs
Outputs of similar age from Frontiers in Genetics
#85
of 762 outputs
Altmetric has tracked 23,755,107 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,670 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 75% 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 459,860 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.
We're also able to compare this research output to 762 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.