Crop improvement is accelerating with the advances of sequencing technology and the utilization of RNA Sequencing.  The basics of data analysis of these large data sets and the application of these analyses to soybean will be discussed.  Specifically, RNA-Seq was applied to investigate differential expression between fourteen soybean tissues.  These analyses led to the creation of an RNA-Seq atlas for Glycine max.  Furthermore, RNA-Seq was applied to identify candidate genes responsible for iron deficiency chlorosis between two near isogenic lines.  This was accomplished by defining the boundaries of the quantitative trait locus using SNP data and differential gene expression analysis to narrow the list of candidate genes.  The talk will conclude with methods for improving the efficiency of analysis and the dissemination of information.