Quantitative Inference in Functional Genomics of Loblolly Pine (Pinus taeda L.) Using ESTs and Microarrays

Abstract

Recent advances in high throughput DNA sequencing technology have made possible the identification of large numbers of genes, and the development of cDNA microarrays have made it possible to learn about the timing and level of expression of large numbers of genes. These advances have been particularly important for biological systems that are typically recalcitrant to genetic analysis due to long generations times. Among the most difficult systems are many species of forest trees. Forest trees are important both as dominant species in forest ecosystems and for the commercial value of wood products. Here we report on the assignment of functional categories to six libraries of ESTs from loblolly pine, predominantly from xylem forming tissues. From these libraries, sequences were assigned putative cellular functions based on homologs identified in GenBank or the Arabidopsis genome (The Arabidopsis Genome Initiative 2000). We have used the EST data to estimate relative abundance of specific RNA populations within and between libraries. In addition, microarray technology has improved sufficiently so that differences in average signals of 50% or less, can be detected as statistically significant with at least 95% confidence, using improved experimental design and analysis.