Dr Emma Hine
Postdoctoral Research Fellow
School of Biological Sciences
+61 7 336 52194
Journal Articles
Dugand, Robert J., Aguirre, J. David, Hine, Emma, Blows, Mark W. and McGuigan, Katrina (2021). The contribution of mutation and selection to multivariate quantitative genetic variance in an outbred population of Drosophila serrata. Proceedings of the National Academy of Sciences, 118 (31) e2026217118, 1-10. doi: 10.1073/pnas.2026217118
Hine, Emma, Runcie, Daniel E., McGuigan, Katrina and Blows, Mark W. (2018). Uneven distribution of mutational variance across the transcriptome of Drosophila serrata revealed by high-dimensional analysis of gene expression. Genetics, 209 (4), 1319-1328. doi: 10.1534/genetics.118.300757
Hugo, Leon E., Jeffery, Jason A. L., Trewin, Brendan J., Wockner, Leesa F., Nguyen Thi Yen, Nguyen Hoang Le, Le Trung Nghia, Hine, Emma, Ryan, Peter A. and Kay, Brian H. (2014). Adult Survivorship of the Dengue Mosquito Aedes aegypti Varies Seasonally in Central Vietnam. PLoS Neglected Tropical Diseases, 8 (2) e2669, e2669.1-e2669.12. doi: 10.1371/journal.pntd.0002669
Aguirre, J. D., Hine, E., McGuigan, K. and Blows, M. W. (2014). Comparing G: multivariate analysis of genetic variation in multiple populations. Heredity, 112 (1), 21-29. doi: 10.1038/hdy.2013.12
Hine, Emma, McGuigan, Katrina and Blows, Mark W. (2014). Evolutionary constraints in high-dimensional trait sets. American Naturalist, 184 (1), 119-131. doi: 10.1086/676504
McGraw, Elizabeth A., Ye, Yixin H., Foley, Brad, Chenoweth, Stephen F., Higgie, Megan, Hine, Emma and Blows, Mark W. (2011). High-dimensional variance partitioning reveals the modular genetic basis of adaptive divergence in gene expressionduring reproductive character displacement. Evolution, 65 (11), 3126-3137. doi: 10.1111/j.1558-5646.2011.01371.x
Hine, Emma, McGuigan, Katrina and Blows, Mark W (2011). Natural selection stops the evolution of male attractiveness. Proceedings of the National Academy of Sciences of the United States of America, 108 (9), 3659-3664. doi: 10.1073/pnas.1011876108
Hine, E, Chenoweth, SF, Rundle, HD and Blows, MW (2009). Characterizing the evolution of genetic variance using genetic covariance tensors. Philosphical Transactions of the Royal Society B-Biological Sciences, 364 (1523), 1567-1578. doi: 10.1098/rstb.2008.0313
Luciano, M, Hine, E., Wright, M. J., Duffy, D. L., MacMillan, J. and Martins, N. G. (2007). Effects of SCA1, MJD, and DPRLA triplet repeat polymorphisms on cognitive phenotypes in a normal population of adolescent twins. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics, 144B (1), 95-100. doi: 10.1002/ajmg.b.30413
Hine, E. and Blows, M. W. (2006). Determining the effective dimensionality of the genetic variance-covariance matrix. Genetics, 173 (2), 1135-1144. doi: 10.1534/genetics.105.054627
Blows, Mark W., Chenoweth, Stephen F. and Hine, Emma (2004). Orientation of the genetic variance-covariance matrix and the fitness surface for multiple male sexually selected traits. American Naturalist, 163 (3), 329-340. doi: 10.1086/381941
Hine, E. J., Chenoweth, S. F. and Blows, M. W. (2004). Multivariate quantitative genetics and the Lek Paradox: genetic variance in male sexually selected traits of Drosophila serrata under field control. Evolution, 58 (12), 2754-2762. doi: 10.1554/04-558
Hine, Emma, Lachish, Shelly, Higgie, Megan and Blows, Mark W. (2002). Positive genetic correlation between female preference and offspring fitness. Proceedings of The Royal Society of London Series B, 269 (1506), 2215-2219. doi: 10.1098/rspb.2002.2149
Thesis
Emma Hine (2009). Mutation-Selection Balance and the evolution of genetic variance in multiple male sexually-selected pheromones of the vinegar fly Drosophila serrata. PhD Thesis, School of Biological Sciences, The University of Queensland.
Data Collections
Emma Hine, Daniel E. Runcie, Scott L. Allen, Yiguan Wang, Stephen F. Chenoweth, Mark W. Blows and Katrina McGuigan (2021). R code and input files required to generate figures and tables for BSFG analysis of standing variance in two Drosophila datasets. This dataset is the current version and supercedes any earlier versions.. The University of Queensland. (Dataset) doi: 10.48610/a3c5652
Hine, Emma, Runcie, Daniel E., Allen, Scott L., Wang, Yiguan, Chenoweth, Stephen F., Blows, Mark W. and McGuigan, Katrina (2021). Enrichment analysis results for heritable common factors of Drosophila gene expression. The University of Queensland. (Dataset) doi: 10.48610/90441fc
Emma Hine, Daniel E. Runcie, Scott L. Allen, Yiguan Wang, Stephen F. Chenoweth, Mark W. Blows and Katrina McGuigan (2021). R code used to implement Bayesian sparse factor genetic analysis of Drosophila gene expression.. The University of Queensland. (Dataset) doi: 10.48610/ec9b92c
Emma Hine, Daniel E. Runcie, Scott L. Allen, Yiguan Wang, Stephen F. Chenoweth, Mark W. Blows and Katrina McGuigan (2021). Two Drosophila datasets used in the Bayesian sparse factor analysis of standing genetic variance in 3385 gene expression traits. The University of Queensland. (Dataset) doi: 10.48610/f3eede4
Alejandro Oliveros Sandino, Katrina McGuigan and Emma Hine (2020). R code used to simulate directional selection on a moderately heritable polygenic phenotype. The University of Queensland. (Dataset) doi: 10.14264/701bad9
Emma Hine (2018). R code used to process Matlab output for Bayesian sparse factor analysis of mutation accumulation lines. The University of Queensland. (Dataset) doi: 10.14264/uql.2018.101
Dataset Collections
Emma Hine (2018). Univariate REML analyses of 3385 gene expression traits. The University of Queensland. (Dataset) doi: 10.14264/uql.2018.113
Emma Hine (2018). Matlab code for Bayesian sparse factor analysis of mutation accumulation lines. The University of Queensland. (Dataset) doi: 10.14264/uql.2018.121
Emma Hine (2018). Matlab output from Bayesian Sparse Factor analysis of mutational accumulation lines. The University of Queensland. (Dataset) doi: 10.14264/uql.2018.111
Emma Hine (2017). 3385 gene expression traits for 41 MA lines of Drosophila serrata BSF input format. The University of Queensland. (Dataset) doi: 10.14264/uql.2017.783