Department of Biology
338 Gardner Hall
Ph.D., Genetics, University of Wisconsin-Madison
M.A., Entomology, University of Kansas
B.S., Biology, University of Wisconsin-Stevens Point
B.A., English and Philosophy, University of Wisconsin-Milwaukee
SPRING 2016 schedule
Each semester, I teach Genetics (Biology 3330). With varying frequencies, I also teach several introductory courses for Biology majors, including Unity of Life (Biology 1650, lecture and laboratory), Diversity of Life (Biology 1750, laboratory), Fundamentals of Biological Investigation (Biology 2420), and BioQuest (Biology 1020).
Currently I am working with Dr. Elizabeth Frieders to develop a course in methods of evolutionary biology.
In each class I teach, my main goals are to:
1. provide students with the knowledge and skills required to think and work as biologists and, more generally, scientists
2. foster intellectual curiosity and wonder
I am also deeply committed to:
1. contextualizing the diverse topics we study by relating them to evolutionary theory
2. encouraging the use of computational and statistical learning methods, which have become important tools for the modern biologist
It is critical that students in the natural sciences perform meaningful research as undergraduates. This experience enriches their understanding of course content and prepares them for employment and postgraduate education.
Currently I am engaged in several research areas and encourage motivated students to contact me regarding research opportunities. Because the work in our group requires basic understanding of genetical concepts, I prefer that students have taken Genetics (Biology 3330).
RESEARCH TOPICS: a few of the projects that undergraduates and I are currently pursuing.
software, datasets, ...
Datasets for Haasl, Johnson, and Payseur (2014)
Full autosomal scan of 85 individuals of Northwestern European ancestry (population CEU) using the ksk2(20) and ksk2(1) statistics detailed in Haasl, Johnson, and Payseur (2014).
The following links will load custom tracks into the UCSC human genome browser. The initial view is centered on MAGI2 (chr. 7); however, all autosomal regions may be viewed.
This software simulates 1Mb chromosomal segments with a selected SNP or microsatellite at it center (500kb). New mutation, recombination, and reproduction are all accounted for. We wrote this software to produce the simulated datasets detailed in Haasl, Johnson, and Payseur (2014). It requires the use of Hudson's ms program, which is bundled with our source code. Please e-mail for source code.
To simulate the evolution of microsatellite loci themselves under a variety of demographic and mutational conditions, use MARKSIM (Haasl and Payseur 2011), which you can download here.
† denotes UWP undergraduate student
01. Haasl RJ and Payseur BA. (2016) Fifteen years of genome-wide scans for selection: trends, lessons, and unaddressed genetic sources of complication. Molecular Ecology, 25: 5-23. access PDF
02. Haasl RJ, Johnson RC†, and Payseur BA (2014) The effects of microsatellite selection on linked sequence diversity. Genome Biology and Evolution, 6: 1843-1861. access PDF
03. Haasl RJ and Payseur BA (2014) Remarkable selective constraints on exonic dinucleotide repeats. Evolution, 68: 2737-2744. access PDF
04. Gray MM, Wegmann D, Haasl RJ, White MA, Gabreil S, Searle JB, Cuthbert RJ, Ryan PG, Payseur BA (2014) Demographic history of a recent invasion of house mice on the isolated island of Gough. Molecular Ecology, 23: 1923-1939. access PDF
05. Haasl RJ and Paysuer BA (2013) Microsatellites as targets of natural selection. Molecular Biology and Evolution, 30: 285-298. access PDF
06. Haasl RJ, McCarty CA, and Payseur BA (2013) Genetic ancestry inference using support vector machines, and the active emergence of a unique American population. European Journal of Human Genetics, 21: 554-562. access PDF
07. Payseur BA, Jing P, Haasl RJ (2011) A genomic portrait of human microsatellite variation. Molecular Biology and Evolution, 28: 303-312. access PDF
08. Haasl RJ and Payseur BA (2011) Multi-locus inference of population structure: a comparison between single nucleotide polymorphisms and microsatellites. Heredity, 106: 158-171. access PDF
09. Haasl RJ and Payseur BA (2010) The number of alleles at a microsatellite defines the allele frequency spectrum and facilitates fast accurate estimation of θ. Molecular Biology and Evolution, 27: 2702-2715. access PDF
10. Simon DP, Meethal SV, Wilson AC, Gallego MJ, Weinecke SL, Bruce E, Lyons PF, Haasl RJ, Bowen RL, Atwood CS (2009) Activin receptor signaling regulates prostatic epithelial cell adhesion and viability. Neoplasia, 11: 365.
11. Chan HW, Liu T, Verdile G, Bishop G, Haasl RJ, Smith MA, Perry G, Martins RN, Atwood CS (2008) Copper induces apoptosis of neuroblastoma cells via post-translational regulation of the expression of Bcl-2-family proteins and the TxJ mouse is a better model of hepatic than brain Cu toxicity. Intl J. Clinical and Experimental Medicine, 1: 76.
12. Chen X, Han B, Fang J, Haasl RJ (2008) Large-scale Protein-Protein Interaction prediction using novel kernel methods. Intl J. of Data Mining and Bioinformatics, 2: 145-156.
13. Haasl RJ, Ahmadi MR, Meethal SV, Gleason CE, Johnson SC, Asthana S, Bowen RL, Atwood CS (2008) A luteinizing hormone receptor intronic variant is significantly associated with decreased risk of Alzheimer's disease in males carrying an apolipoprotein E ε4 allele. BMC Medical Genetics, 9: 37.
14. Wilson AC, Salamat MS, Haasl RJ, Roche KM, Karande A, Meethal SV, Terasawa E, Bowen RL, Atwood CS (2006) Human neurons express type I GnRH receptor and respond to GnRH I by increasing luteinizing hormone expression. Journal of Endocrinology, 191: 651-663.
15. Haasl RJ, Fang J (2006) Mining protein-protein interaction data. Current Bioinformatics, 1: 197-205.
16. Meethal SV, Gallego MJ, Haasl RJ, Petras SJ, Sgro JY, Atwood CS (2006) Identification of a gonadotropin-releasing hormone receptor orthologue in Caenorhabditis elegans. BMC Evolutionary Biology, 6: 103.
17. Fang J, Haasl RJ, Dong Y, Lushington GH (2005) Discover protein signatures from protein-protein interaction data. BMC Bioinformatics, 6: 277.