Title |
De novo sequencing and analysis of the lily pollen transcriptome: an open access data source for an orphan plant species
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Published in |
Plant Molecular Biology, October 2014
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DOI | 10.1007/s11103-014-0261-2 |
Pubmed ID | |
Authors |
Veronika Lang, Björn Usadel, Gerhard Obermeyer |
Abstract |
Pollen grains of Lilium longiflorum are a long-established model system for pollen germination and tube tip growth. Due to their size, protein content and almost synchronous germination in synthetic media, they provide a simple system for physiological measurements as well as sufficient material for biochemical studies like protein purifications, enzyme assays, organelle isolation or determination of metabolites during germination and pollen tube elongation. Despite recent progresses in molecular biology techniques, sequence information of expressed proteins or transcripts in lily pollen is still scarce. Using a next generation sequencing strategy (RNAseq), the lily pollen transcriptome was investigated resulting in more than 50 million high quality reads with a length of 90 base pairs. Sequenced transcripts were assembled and annotated, and finally visualized with MAPMAN software tools and compared with other RNAseq or genome data including Arabidopsis pollen, Lilium vegetative tissues and the Amborella trichopoda genome. All lily pollen sequence data are provided as open access files with suitable tools to search sequences of interest. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 20% |
Unknown | 4 | 80% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 80% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Czechia | 1 | 2% |
Slovakia | 1 | 2% |
Unknown | 62 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 15 | 23% |
Student > Ph. D. Student | 10 | 16% |
Student > Master | 10 | 16% |
Student > Bachelor | 6 | 9% |
Student > Doctoral Student | 5 | 8% |
Other | 12 | 19% |
Unknown | 6 | 9% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 34 | 53% |
Biochemistry, Genetics and Molecular Biology | 11 | 17% |
Social Sciences | 2 | 3% |
Chemistry | 2 | 3% |
Medicine and Dentistry | 2 | 3% |
Other | 4 | 6% |
Unknown | 9 | 14% |