85
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Systems Genetics of Complex Traits in Drosophila melanogaster

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          SUMMARY

          Determining the genetic architecture of complex traits is challenging because phenotypic variation arises from interactions between multiple, environmentally sensitive alleles. We quantified genome-wide transcript abundance and phenotypes for six ecologically relevant traits in D. melanogaster wild-derived inbred lines. We observed 10,096 genetically variable transcripts and high heritabilities for all organismal phenotypes. The transcriptome is highly genetically inter-correlated, forming 241 transcriptional modules. Modules are enriched for transcripts in common pathways, gene ontology categories, tissue-specific expression, and transcription factor binding sites. The high transcriptional connectivity allows us to infer genetic networks and the function of predicted genes based on annotations of other genes in the network. Regressions of organismal phenotypes on transcript abundance implicate several hundred candidate genes that form modules of biologically meaningful correlated transcripts affecting each phenotype. Overlapping transcripts in modules associated with different traits provides insight into the molecular basis of pleiotropy between complex traits.

          Related collections

          Most cited references43

          • Record: found
          • Abstract: not found
          • Book: not found

          Introduction to Quantitative Genetics

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Evolution of genes and genomes on the Drosophila phylogeny.

            Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Using FlyAtlas to identify better Drosophila melanogaster models of human disease.

              FlyAtlas, a new online resource, provides the most comprehensive view yet of expression in multiple tissues of Drosophila melanogaster. Meta-analysis of the data shows that a significant fraction of the genome is expressed with great tissue specificity in the adult, demonstrating the need for the functional genomic community to embrace a wide range of functional phenotypes. Well-known developmental genes are often reused in surprising tissues in the adult, suggesting new functions. The homologs of many human genetic disease loci show selective expression in the Drosophila tissues analogous to the affected human tissues, providing a useful filter for potential candidate genes. Additionally, the contributions of each tissue to the whole-fly array signal can be calculated, demonstrating the limitations of whole-organism approaches to functional genomics and allowing modeling of a simple tissue fractionation procedure that should improve detection of weak or tissue-specific signals.
                Bookmark

                Author and article information

                Journal
                9216904
                2419
                Nat Genet
                Nature genetics
                1061-4036
                1546-1718
                27 January 2009
                22 February 2009
                March 2009
                25 September 2009
                : 41
                : 3
                : 299-307
                Affiliations
                [1 ]Department of Genetics, North Carolina State University, Raleigh, NC 27695, USA.
                [2 ]Department of Biology, North Carolina State University, Raleigh, NC 27695, USA.
                [3 ]Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA.
                [4 ]Department of W. M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC 27695, USA.
                Author notes
                [5]

                Present address: Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, West Mains Road, Edinburgh EH9 3JT, UK (M. M. M.); Department of Biological Sciences, University of Cincinnati, PO Box 210006, 614 Rieveschl Hall, Cincinnati, OH 45221-0006, USA (S. M. R.).

                [6]

                These authors contributed equally to this work.

                Author Contributions T. F. C. M., J. F. A., E. A. S. and R. R. H. A. wrote the paper. R. F. L. constructed the Drosophila lines. M. A. C. obtained the gene expression data. K. W. J., M. M. M., S. M. R., L. H. D. and F. L. obtained the organismal phenotype data. J. F. A., E. A. S. and K. W. J. performed the statistical analyses.

                Correspondence should be addressed to T. F. C. M. ( trudy_mackay@ 123456ncsu.edu )
                Article
                nihpa90535
                10.1038/ng.332
                2752214
                19234471
                1c780861-4328-4d9d-ae0c-c9cadf6d288d
                History
                Funding
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: R01 GM059469-12A1 ||GM
                Categories
                Article

                Genetics
                Genetics

                Comments

                Comment on this article