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Title: Construction of a blueberry (Vaccinium corymbosum) draft genomic sequence using multiple platforms

Author
item BROWN, ALLAN - North Carolina State University
item COLMAN, STEVE - David H Murdock Research Institute
item LOMMEL, STEVE - North Carolina State University
item Rowland, Lisa
item DIENER, STEVE - Orion Genomics
item BURKE, MARK - North Carolina State University

Submitted to: Annual International Plant & Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: 12/10/2009
Publication Date: 1/30/2010
Citation: Brown, A., Colman, S., Lommel, S., Rowland, L.J., Diener, S., Burke, M. 2010. Construction of a blueberry (Vaccinium corymbosum) draft genomic sequence using multiple platforms. Meeting Abstract.

Interpretive Summary:

Technical Abstract: Blueberry (Vaccinium spp. section Cyanococcus) production and value has steadily increased over the past decade as both researchers and the general public have come to recognize the health benefits associated with its consumption. Genetic improvement of blueberry, however, has been hampered by a limited amount of information on its genome structure and organization. DNA from a diploid V. corymbosum (‘W8520’) with a genome size of approximately 500 mb was used to construct 454 shotgun and multiple paired end libraries of 3 and 20kb. In addition, Illumina shotgun and paired libraries were also constructed. The method we are utilizing to sequence the Vaccinium genome optimizes available resources by generating long read structural scaffolds using paired end 454 libraries of different insert sizes and filling in the gaps with a high density of low cost-per-base Illumina reads. To date, we have generated 5,112,343 sequences (or 1,885,460,964 base pairs) of raw data in 8 plates on the Roche 454 and 27,064,088,290 base pairs in two flow cells on the GA2x. While the cost of sequencing is steadily decreasing, the overall value of the data is proportional to the effectiveness of the analysis strategy. The problems encountered in data analysis and management are directly related to the volume of data currently available, the continued influx of that data, and the computational requirements necessary to effectively perform analysis.