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Fine mapping of qGW1, a major QTL for grain weight in sorghum

Overview of attention for article published in Theoretical and Applied Genetics, June 2015
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Title
Fine mapping of qGW1, a major QTL for grain weight in sorghum
Published in
Theoretical and Applied Genetics, June 2015
DOI 10.1007/s00122-015-2549-2
Pubmed ID
Authors

Lijie Han, Jun Chen, Emma S. Mace, Yishan Liu, Mengjiao Zhu, Nana Yuyama, David R. Jordan, Hongwei Cai

Abstract

We detected seven QTLs for 100-grain weight in sorghum using an F 2 population, and delimited qGW1 to a 101-kb region on the short arm of chromosome 1, which contained 13 putative genes. Sorghum is one of the most important cereal crops. Breeding high-yielding sorghum varieties will have a profound impact on global food security. Grain weight is an important component of grain yield. It is a quantitative trait controlled by multiple quantitative trait loci (QTLs); however, the genetic basis of grain weight in sorghum is not well understood. In the present study, using an F2 population derived from a cross between the grain sorghum variety SA2313 (Sorghum bicolor) and the Sudan-grass variety Hiro-1 (S. bicolor), we detected seven QTLs for 100-grain weight. One of them, qGW1, was detected consistently over 2 years and contributed between 20 and 40 % of the phenotypic variation across multiple genetic backgrounds. Using extreme recombinants from a fine-mapping F3 population, we delimited qGW1 to a 101-kb region on the short arm of chromosome 1, containing 13 predicted gene models, one of which was found to be under purifying selection during domestication. However, none of the grain size candidate genes shared sequence similarity with previously cloned grain weight-related genes from rice. This study will facilitate isolation of the gene underlying qGW1 and advance our understanding of the regulatory mechanisms of grain weight. SSR markers linked to the qGW1 locus can be used for improving sorghum grain yield through marker-assisted selection.

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Mendeley readers

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Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 60 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 26%
Researcher 10 16%
Student > Master 8 13%
Student > Doctoral Student 5 8%
Other 2 3%
Other 4 7%
Unknown 16 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 64%
Biochemistry, Genetics and Molecular Biology 3 5%
Veterinary Science and Veterinary Medicine 1 2%
Economics, Econometrics and Finance 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 16 26%
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 14 June 2015.
All research outputs
#19,201,293
of 23,794,258 outputs
Outputs from Theoretical and Applied Genetics
#3,124
of 3,565 outputs
Outputs of similar age
#192,665
of 266,025 outputs
Outputs of similar age from Theoretical and Applied Genetics
#22
of 44 outputs
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