Comparison of techniques for correlating survival and gene expression data from wild salmon

In laboratory and field studies of survival, one of two alternative analytical techniques is often used to estimate survival rates and identify covariates, namely parametric survival analysis or CormackJollySeber models. These techniques differ in algorithms and assumptions of the data. They also tend to be used under different circumstances depending on whether the intention is to demonstrate group-specific differences or to predict survival variables. Here, we apply and compare both analytical techniques in a study that couples functional genomics with biotelemetry to ascertain the role of physiological condition on survival of adult sockeye salmon (Oncorhynchus nerka) migrating in the Fraser River, British Columbia, which builds on the growing concern over the decline in numbers of spawning fish. Herein, we show a high level of quantitative and qualitative agreement between the two analytical methods, with both showing a strong relationship exists between the genomic signature that accounts for the largest source of variance in gene expression among individuals and survival in one of the three populations assessed. This high level of agreement suggests the data and the approaches are generating reliable results. The novel approach used in our study to identify physiological processes associated with reduced fitness in wild populations should be of broad interest to conservation biologists and resource managers as it may help reduce the uncertainty associated with predicting population sizes.