Type Package Title integrated Bayesian Modeling of eQTL data Version 1.0.1 Date 2011-10-28

R topics documented: iBMQ-package....................................... 2 calculateThreshold..................................... 2 eqtlClassifier........................................ 3 eqtlFinder.......................................... 4 eqtlMcmc.......................................... 4 gene............................................. 5 genepos........................................... 6 genotype.liver........................................ 7 hotspotFinder........................................ 7 map.liver.......................................... 8 phenotype.liver....................................... 8 1 2 calculateThreshold PPA.liver.......................................... 9 probe.liver.......................................... 9 snp.............................................. 10 snppos............................................ 1

Predictable transcriptome evolution in the convergent and complex bioluminescent organs of squid

Despite contingency in life's history, the similarity of evolutionarily convergent traits may represent predictable solutions to common conditions. However, the extent to which overall gene expression levels (transcriptomes) underlying convergent traits are themselves convergent remains largely unexplored. Here, we show strong statistical support for convergent evolutionary origins and massively parallel evolution of the entire transcriptomes in symbiotic bioluminescent organs (bacterial photophores) from two divergent squid species. The gene expression similarities are so strong that regression models of one species' photophore can predict organ identity of a distantly related photophore from gene expression levels alone. Our results point to widespread parallel changes in gene expression evolution associated with convergent origins of complex organs. Therefore, predictable solutions may drive not only the evolution of novel, complex organs but also the evolution of overall gene expression levels that underlie them