Genome sequencing projects are discovering millions of genetic variants in humans, and interpreting their functional effects is essential for understanding the genetic basis of variation in human traits. One approach to address this challenge is to combine genomic data from human populations to a functional readout of the cell, such as the transcriptome. In the Geuvadis project, we produced the first high-quality mRNA- and miRNA-seq data set from multiple human populations with high-quality genome sequences from 1000 Genomes (Lappalainen et al. Nature, in press). We discovered extremely widespread genetic variation affecting both gene expression and splicing, and created the largest existing catalog of putative causal functional variants, including dozens of disease-associated loci. With population genetic analysis we have shown that regulatory variants can also affect penetrance of deleterious coding variants, with contributions to rare and common disease (Lappalainen et al. AJHG, 2011). Anther important dimension for understanding functional variation is tissue- specificity, which is the focus of the GTEx Consortium that is creating the largest RNA-seq and genotype data set of multiple human tissues. Using allele-specific expression analysis, we have quantified how genetic cis-regulatory effects are shared between tissues, and how loss-of-function variants affect transcripts. Finally, translating these population-scale association signals to the level of an individual, we have shown that a regulatory variant rarely shows uniform effects in all the individuals with the same genotype. This indicates widespread modifier effects even at the cellular level, highlighting the importance of personalized transcriptomics approaches to interpret individual genomes. Altogether, integration of genome and transcriptome data provides important insight into functional genetic variation and biological mechanisms behind phenotypic diversity in human populations and individuals.