P0802
Coffee Transcriptome Analysis using RNA Sequencing: Comparison of Coffees Grown at Different Altitudes

Date: Monday, January 14, 2013
Room: Grand Exhibit Hall
Juan F. Medrano , University of California-Davis, Davis, CA
Ricardo Koyner , Kotowa Farms, Boquete, Panama
Alma Islas-Trejo , University of California-Davis, Davis, CA
Gonzalo Rincon , University of California-Davis, Davis, CA
The objective of this study was to develop a transcriptome analytical framework of coffee beans to use as a reference to annotate and examine gene expression differences between coffee varieties and coffees grown at different altitudes. Coffee berries at different stages of maturity (unripe, half-ripe, cherry) were sampled from four plants (C. Arabica-Geisha) at two altitudes (1300m and 1650m) at Kotowa Farms, Boquete, Panama. It is known that the coffees grown at higher altitudes acquire unique flavor characteristics, whose molecular differences would be economically important to identify. Fresh bean slices were stored in RNAlater and ground in liquid nitrogen to extract RNA using Plant-RNA Reagent (Invitrogen). Bar-coded RNAseq libraries were sequenced using Illumina HiSeq. From 8 samples, 217 million 100bp single reads were used to perform a de-novo assembly using CLC Genomics software. A total of 119,678 contigs were generated (average contig size 527bp, N50 881bp and max-size 15,090bp). These contigs were used as reference to perform RNAseq analysis. Using Blast2Go software 21,000 contigs (17.5%) were annotated with known protein information. A t-test identified significant differentially expressed values (RPKM P<0.01) and fold changes greater than 2 in 206 contigs between cherry beans at 1300m and 1650m. The main GO terms for the 206 contigs corresponded to: ATP binding, nitrogen compound metabolic process, negative regulation of programmed cell death, anatomical structure development. This work contributes to the annotation of the coffee genome for the examination of differences between varieties and to study the effects of environmental variables on economically important phenotypes.