Over last several years, genome-wide association studies have successfully identified hundreds of genetic polymorphisms reproducibly associated with diverse complex diseases and traits, including cancers [34].
This is important since it will allow us to understand the contribution of diverse genetic backgrounds to complex traits.
Bradbury, P. J. et al. TASSEL: software for association mapping of complex traits in diverse samples.
In recent years, systems biology approaches, specifically network analyses that integrate experimentally derived information with computational modeling, have emerged as powerful tools for studying complex traits in diverse species [ 5, 12– 15].
Here we present the whole-genome sequences of two inbred strains, LG/J and SM/J, which are frequently used to study variation in complex traits as diverse as aging, bone-growth, adiposity, maternal behavior, and methamphetamine sensitivity.
Complex traits typically involve diverse biological pathways and are shaped by numerous genetic and environmental factors.
This densely sampled chronogram will provide the basis for unravelling the tempo and mode of evolution of many of the much-studied and complex traits in this diverse and economically important family such as self-incompatibility, fruit type, cold and salt tolerance, disease resistance, chromosomal re-arrangements, genome size, and gene sub-functionalization.
The allelic heterogeneity emphasizes the importance of including diverse populations in future genetic association studies of complex traits such as lipids; furthermore, the overlap in lipid loci across populations of diverse ancestral origin argues that additional knowledge can be gleaned from multiple populations.
Collections of genetically diverse D. melanogaster lines have been compiled to exploit natural genetic diversity to find the determinants of complex traits.
Future research should test these methods for improved risk prediction in other complex traits and diseases and in diverse populations.
