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Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population

Overview of attention for article published in Frontiers in Plant Science, July 2016
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Title
Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population
Published in
Frontiers in Plant Science, July 2016
DOI 10.3389/fpls.2016.01032
Pubmed ID
Authors

Hui Jin, Weie Wen, Jindong Liu, Shengnan Zhai, Yan Zhang, Jun Yan, Zhiyong Liu, Xianchun Xia, Zhonghu He

Abstract

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 35%
Researcher 6 14%
Student > Master 4 9%
Student > Bachelor 3 7%
Student > Doctoral Student 2 5%
Other 5 12%
Unknown 8 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 67%
Biochemistry, Genetics and Molecular Biology 4 9%
Unspecified 1 2%
Economics, Econometrics and Finance 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 7 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 04 August 2016.
All research outputs
#18,465,988
of 22,880,691 outputs
Outputs from Frontiers in Plant Science
#13,816
of 20,270 outputs
Outputs of similar age
#279,142
of 363,105 outputs
Outputs of similar age from Frontiers in Plant Science
#340
of 528 outputs
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