I spent the week at NIMBioS in Knoxville, TN, with a great group of colleagues. It was an interesting and exhausting week of talking about landscape genomics and generating a plan for the next two years of the working group.
As we move forward in the genomic age, we can rapidly sequence complete genomes and transcriptomes, as well as assay genomic structural features (e.g., gene copy number variants, transposable elements), of virtually any species. Advances in genomics provide new avenues for understanding the genetic basis of functionally adaptive trait variation. For example, we have made great strides in understanding adaptation to extreme environments and the genetic basis for many diseases in human populations, as well as in non-model organisms. However, scientists are awash with data, and methods to unlock the power of genome projects are still under development.
Rapid advances in our ability to obtain genomic data have also caused a paradigm shift in the way we view “genes.” Once thought to be directly related to phenotype, genes operate in complex genomic landscapes, rather than in isolation. A gene’s location and copy number within a genome may regulate its expression, as well as its interaction with other genes and noncoding RNA. The complexity of the genomic landscape is compounded by the environment in which an individual persists. Genes are expressed differently in different environments, and selection varies spatially across the ecological landscape. A major challenge, then, is to analyze data sets that integrate both the genomic landscape and the ecological landscape to understand the spatial distribution of adaptive genetic variation. This working group will address this challenge by advancing analytical and computational methods with an interdisciplinary collaboration of experts in genomics, statistics, mathematics, bioinformatics and population genetics.