Alyssa Gulledge and Ann Loraine
Thanks to advances in genomic analysis technologies, notably microarrays and high throughput sequencing, biologists can routinely generate massive amounts of data per experiment. The sheer volume of these new data sets requires flexible, easy-to-use software tools biologists can use to process, analyze, and understand their data. A crucial component in this process involves converting columns and rows of numbers associated with genes and other genomic features into visual representations that allow biologists to fully explore their data. The Integrated Genome Browser (IGB), developed in our group, organizes the data by location along the genomic sequence axis and presents it in terms of understandable gene models and sequences. IGB has the capacity to take data from tiling arrays and next-gen sequencing experiments and display it against known gene models for an organism. By seeing the data alongside familiar genomic features (the genomic landscape), a biologist can assess the quality of individual samples, the quality of the alignments themselves, and the technical quality of the overall experiment. More importantly, visualizing the results allows the biologist to ask new questions and create new hypotheses. We’ll present an example from our lab in which we used IGB to investigate an Arabidopsis gene, atSR45a, and observe multiple alternative splicing events including retention of introns in mature mRNA, a common use case for high-throughput sequencing data. Finally, we’ll discuss possible future directions for genomic visualization, which must change to accommodate advances (and lowering costs) in genomic techniques.