Sequencing Across the Genome-Phenome Divide

The phenotype of a unicellular organism, or cells in a tissue of a eukaryotic multicellular organism is the consequence of both the biological processes that are activated and the way they are regulated. Biological processes involve the concerted activity and regulation of many genes. Hence, genes and gene products are not independent units, rather they are deeply interconnected, influencing each other in their activity and regulation. Indeed, individual not statistically significant observations can be substantially more informative when combined together. Gaining insight into plant cellular networks will require the integration of data from multiple genomic approaches. New DNA sequencing technologies produce vast amounts of sequence information, enable massively parallel surveying of complex nucleic acid populations, and have triggered a paradigm shift in biology. An immense range of cellular processes and properties can now be studied at the single-base resolution. We are sequencing the genomes of many Arabidopsis accessions as part of 1,001 genomes project. In parallel, we have developed and applied RNA-Seq and MethylC-Seq methods to create base-resolution maps of transcriptomes and cytosine DNA methylomes, respectively. When combined with a de novo assembled genome, these data sets provide an in depth view of the relationship between genetic and epigenetic variation and how variation can have effects on gene expression. In addition, we have also applied now-generation DNA sequencing approaches to capture sites of insertion of Agrobacterium T-DNA in large populations of arrayed plant genomes, enabling the identification of mutations for nearly all genes in the Arabidopsis genome. Finally, a major deficiency in the repertoire of plant genomic resources is the paucity of large-scale protein-protein interactome data. In collaboration with the Center for Cancer Systems Biology at Dana Farber Cancer Institute- Harvard, we have created a first generation plant interactome map. Properties of this interactome map and integrating of all these genomic scale data to create a ‘plant growth network’ will be described.