Zebrafish Mutation Project: Functional Genomics of Disease. E. M. Busch-Nentwich, J. E. Collins, I. Sealy, N. Wali, R. J. White, C. M. Dooley, C. Scahill, S. Carruthers, Z. Pusztai, C. Herd, A. Hall, R. N. W. Kettleborough, J. Morris, J. Barrett, D. L. Stemple Wellcome Trust Sanger Institute, Hinxton, United Kingdom.

   The advent of high-throughput sequencing has greatly accelerated the identification of inherited and de novo disease causing mutations. Following discovery the analysis of the developmental and cellular pathways of the affected genes is a crucial step on the path towards therapy with model organisms as the central tool. Traditionally, vertebrate model organisms such as mouse and zebrafish have been used on a gene-by-gene basis, however, in order to keep pace with the increasing speed of discovery, new approaches are needed. Owing to a high quality genome reference sequence and its genetic and embryological tractability the zebrafish is a vertebrate model especially suited for large scale studies. Previously having established methods to generate and identify disruptive zebrafish point mutations on a genome wide scale the Zebrafish Mutation Project is now assigning biological function to every protein-coding gene in the zebrafish genome. We submit alleles to a high-throughput assessment of morphological phenotypes which is followed by the quantitative analysis of genome wide transcriptional changes in response to the loss of function. For this transcriptome analysis we have developed a new sequence based method, the differential expression transcript counting technique (DETCT). Using this, we find a wealth of genes displaying alterations in transcript levels reflecting the observed morphological changes. Ontology term enrichment analysis on gene ontology (GO) annotations combined with the zebrafish anatomical and development (ZFA) ontology has led to surprisingly detailed insights into phenotypes. Thus far two general trends are emerging. Firstly, transcript profiles for previously uncharacterised mutants confirm predicted cellular function and show tissue-specific effects on transcript abundance, thus providing mechanistic evidence. Secondly, we are beginning to build pathway-specific gene networks. Transcriptome analysis of mutants has revealed novel candidate genes which, when mutated, lead to a phenotype affecting the same developmental pathway. Our approach and the results will be discussed especially in the context of gene families implicated in human disease.

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