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De novo transcriptomic analysis of cowpea (Vigna unguiculata L. Walp.) for genic SSR marker development

Overview of attention for article published in BMC Genomic Data, July 2017
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Title
De novo transcriptomic analysis of cowpea (Vigna unguiculata L. Walp.) for genic SSR marker development
Published in
BMC Genomic Data, July 2017
DOI 10.1186/s12863-017-0531-5
Pubmed ID
Authors

Honglin Chen, Lixia Wang, Xiaoyan Liu, Liangliang Hu, Suhua Wang, Xuzhen Cheng

Abstract

Cowpea [Vigna unguiculata (L.) Walp.] is one of the most important legumes in tropical and semi-arid regions. However, there is relatively little genomic information available for genetic research on and breeding of cowpea. The objectives of this study were to analyse the cowpea transcriptome and develop genic molecular markers for future genetic studies of this genus. Approximately 54 million high-quality cDNA sequence reads were obtained from cowpea based on Illumina paired-end sequencing technology and were de novo assembled to generate 47,899 unigenes with an N50 length of 1534 bp. Sequence similarity analysis revealed 36,289 unigenes (75.8%) with significant similarity to known proteins in the non-redundant (Nr) protein database, 23,471 unigenes (49.0%) with BLAST hits in the Swiss-Prot database, and 20,654 unigenes (43.1%) with high similarity in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Further analysis identified 5560 simple sequence repeats (SSRs) as potential genic molecular markers. Validating a random set of 500 SSR markers yielded 54 polymorphic markers among 32 cowpea accessions. This transcriptomic analysis of cowpea provided a valuable set of genomic data for characterizing genes with important agronomic traits in Vigna unguiculata and a new set of genic SSR markers for further genetic studies and breeding in cowpea and related Vigna species.

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 71 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 14%
Student > Ph. D. Student 9 13%
Student > Doctoral Student 7 10%
Student > Bachelor 5 7%
Researcher 4 6%
Other 8 11%
Unknown 28 39%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 30%
Biochemistry, Genetics and Molecular Biology 9 13%
Nursing and Health Professions 2 3%
Unspecified 2 3%
Chemistry 2 3%
Other 3 4%
Unknown 32 45%
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 12 July 2017.
All research outputs
#22,764,772
of 25,382,440 outputs
Outputs from BMC Genomic Data
#1,008
of 1,204 outputs
Outputs of similar age
#284,484
of 324,855 outputs
Outputs of similar age from BMC Genomic Data
#17
of 24 outputs
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