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Abstract Detail

Pollination Biology

Prior, Natalie [1], Little, Stefan [2], Boyes, Ian [2], Smith, Derek [3], Hardie, Darryl [3], Griffith, M. Patrick [4], Stevenson, Dennis [5], Von Aderkas, Patrick [6].

Understanding gymnosperm pollination drop proteins with RNA-Seq transcriptome data.

Pollination drops are part of the reproductive biology of most extant gymnosperms. In particular, drops can be involved in pollen capture, pollen transport into ovule interiors, and in pollen germination. Drops are rich mixtures of mineral and organic components, including proteins. Some drop components are known to have specific functions, but much of the protein diversity in gymnosperm drops is currently unknown. Advances in proteomics such as highly sensitive mass-spectrometry provide abundant high-quality spectra, but the identification of proteins from these spectra is limited by the available public databases, which are primarily based on model organisms and angiosperms. One method to improve our understanding of pollination drop proteins involves searching peptide mass spectral data against protein databases derived from high throughput RNA-Seq transcriptome data. We will show how these datasets modify our understanding of pollination drop proteins.

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1 - Centre For Forest Biology, University of Victoria, Department of Biology, PO Box 3020, Station CSC, Victoria, BC, V8W 3N5, Canada
2 - University of Victoria, Biology, Cunningham Bldg. 202, Victoria, BC, V8P 5C2, Canada
3 - Uvic - Genome BC Proteomics Centre, Vancouver Island Technology Park, #3101-4464 Markham St, Victoria, BC, V8Z 7X8, Canada
4 - Montgomery Botanical Center, 11901 Old Cutler Road, Miami, FL, 33156-4242, USA
5 - The New York Botanical Garden, 2900 Southern Blvd., Bronx, NY, 10458, USA
6 - University of Victoria, Department of Biology, Dept Of Biology, Victoria, N/A, V8W 3N2, Canada

pollination drop

Presentation Type: Poster:Posters for Topics
Session: P
Location: Grand Salon A - D/Riverside Hilton
Date: Monday, July 29th, 2013
Time: 5:30 PM
Number: PPL011
Abstract ID:814
Candidate for Awards:None

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