Research in the Macdonald lab focuses on understanding the genetic basis of complex trait variation, principally using Drosophila as a model system. The lab employs a range of genetic, genomic, bioinformatic and functional tools to identify genes and sequence variants controlling trait variation. In addition, the Macdonald lab leads the development of a large, powerful set of resources for the dissection of trait variation in flies, the Drosophila Synthetic Population Resource (DSPR).
Stuart Macdonald earned a B.A. in biological sciences (1997) and a D.Phil in zoology (2000) from the University of Oxford, was a postdoctoral researcher in the lab of Dr. Tony Long at the University of California - Irvine, and in 2006 started his faculty position in the Department of Molecular Biosciences at the University of Kansas. Dr. Macdonald is also an affiliate member of the Center for Computational Biology, the Director of the K-INBRE Bioinformatics Core at KU, and the Director of Graduate Studies for the Department of Molecular Biosciences.
D.Phil, Zoology, University of Oxford
B.A., Biological Sciences, St. John’s College, University of Oxford
- Genetics and genomics
- Cell and molecular biology
Complex phenotypes are influenced by a number of genetic loci and environmental factors. Examples of complex traits include susceptibility to a variety of human diseases, such as heart disease and many forms of mental illness, as well as numerous ecologically- and evolutionarily-relevant traits. Even though complex traits are tremendously important with regard to human health and organismal diversity, they have proven difficult to molecularly characterize. Indeed, we have only limited information on a broad range of key questions:
What types of loci contribute to variation in complex traits? Are they generally structural (protein-coding) or regulatory in nature?
How many loci contribute to genetic variation in complex traits? What are the effects of these causative sites?
Do causative loci interact epistatically with each other?
Do variants show different phenotypic effects in different environments (genotype-by-environment interaction)?
Only by identifying the precise DNA variants that contribute to variation in complex traits can we begin to answer these questions. Such understanding is vital both for human health (Can we assess whether a patient carries alleles at certain genes that may predispose them to develop disease? Is it possible to predict which individuals may have adverse reactions to drug regimes?) and evolutionary biology (How is genetic variation in complex traits maintained in the face of selection which should erode this variation?).
In our lab we use the elite model genetic organism Drosophila melanogaster to answer fundamental questions about the molecular genetics of complex traits. Drosophila is an excellent model system because, (1) complete genome sequences are available for D. melanogaster and several closely-related species, (2) sophisticated genetic tools are available for Drosophila, and (3) flies can be easily/rapidly cultured in the laboratory, allowing us to carry out powerful experiments on a massive scale. We also implement empirical high-throughput technologies to allow us to collect vast genetic polymorphism (SNP - Single Nucleotide Polymorphism) datasets, and use computationally intensive analytical approaches to examine the relationship between phenotype and genotype.
Current projects in the lab include association mapping of Drosophila bristle number (a model quantitative trait), developing novel methodologies for genetic mapping, and QTL (Quantitative Trait Locus) mapping of morphological traits distinguishing Drosophila species.
- Genetics of complex traits
- Drosophila biology
- Quantitative and population genetics
- Functional genetics and genome editing
Highfill, C. A., Tran, J. H., Nguyen, S. K., Moldenhauer, T. R., Wang, X. & Macdonald, S. J. (2017). Naturally Segregating Variation at Ugt86Dd Contributes to Nicotine Resistance in Drosophila melanogaster. Genetics, 207(1), 311-325. DOI:10.1534/genetics.117.300058
Najarro, M. A., Hackett, J. L., & Macdonald, S. J. (2017). Loci Contributing to Boric Acid Toxicity in Two Reference Populations of Drosophila melanogaster. G3, 7(6), 1631-1641. DOI:10.1534/g3.117.041418
Najarro, M. A., Hackett, J. L., Smith, B. R., Highfill, C. A., King, E. G., Long, A. D., & Macdonald, S. J. (2015). Identifying Loci Contributing to Natural Variation in Xenobiotic Resistance in Drosophila. PLoS genetics, 11(11), e1005663. DOI:10.1371/journal.pgen.1005663
Marriage, T. N., King, E. G., Long, A. D., & Macdonald, S. J. (2014). Fine-mapping nicotine resistance Loci in Drosophila using a multiparent advanced generation inter-cross population. Genetics, 198(1), 45-57. DOI:10.1534/genetics.114.162107
King, E. G., Sanderson, B. J., McNeil, C. L., Long, A. D., & Macdonald, S. J. (2014). Genetic dissection of the Drosophila melanogaster female head transcriptome reveals widespread allelic heterogeneity. PLoS genetics, 10(5), e1004322. DOI:10.1371/journal.pgen.1004322