We have focussed on developing datasets for gene expression using RNA-Seq, which allows us to apply a standard set of methods to a variety of model systems. Using this approach we have contributed to a number of different studies. One of the most interesting areas is in the application to the human brain, where we have a large series of brains with information on both genetic variability and gene expression. Our data has been used in many studies to determine whether a nominated genetic variant associated with a given disease or other phenotype, has a proximal biological effect on gene expression. In the current period, we have greatly expanded the number of RNA-Seq datasets that we have generated within the laboratory. We now have completed 300 postmortem samples with a matrix of high density genomic measurements. We have shown that there are extensive age-associated changes in gene expression at both the transcript and alternate splicing.
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