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Biography:
Jeff Jensen is a population geneticist and Professor in the ASU School of Life Sciences, the Center for Evolution and Medicine, and the Center for Mechanisms of Evolution.
The Jensen Lab develops theory and statistical methodology for describing and quantifying evolutionary processes, and analyzes natural population data to describe the relative roles of these processes during the colonization of novel environments. The lab also analyzes experimental evolution data in order to gain insights into the underlying distribution of selective effects and fitness landscapes.
Education:
- Postdoctoral. NSF Biological Informatics Fellow at UCSD and UC Berkeley, co-advised by Doris Bachtrog, Peter Andolfatto, and Rasmus Nielsen. 2007-2009
- Ph.D. Molecular Biology & Genetics, Cornell University, co-advised by Charles Aquadro and Carlos Bustamante. 2002-2006
- BS/BA Ecology & Evolutionary Biology and Biological Anthropology, University of Arizona, co-advised by Michael Nachman and Brian Charlesworth. 1998-2002
Research Website URL:
Google Scholar URL:
Research Interests:
We are a dry lab, using a variety of approaches from population genetics in order to study fundamental evolutionary processes. This work can be summarized in to two primary research areas:
(i) Population Genetic Theory, Methodology, & Analysis: This line of research involves developing theory, as well as likelihood and approximate Bayesian based statistical approaches, for quantifying and untangling the evolutionary pressures driving populations. Our empirical applications of these developments are generally focused upon the forces at play during the colonization of novel environments.
(ii) Experimental & Virus Evolution: We also work in systems where we can control aspects of demography experimentally, and artificially generate mutations, in order to study the shape of the distribution of fitness effects and the underlying fitness landscapes. Within this context, we have a major interest in the evolution of drug resistance in influenza virus, and in the demographic and selective processes underlying human cytomegalovirus (HCMV) infection.
Research Group:
Publications:
Ten Recent, Representative Publications
- Johri P, B Charlesworth, and JD Jensen, 2020. Towards an evolutionarily appropriate null model: jointly inferring demography and purifying selection. Genetics 215: 173-92.
- Sackman A, RB Harris, and JD Jensen, 2019. Inferring demography and selection in organisms characterized by skewed offspring distributions. Genetics 211: 1019-28.
- Jensen JD, BA Payseur, W Stephan, CF Aquadro, M Lynch, D Charlesworth, and B Charlesworth, 2019. The importance of the Neutral Theory in 1968 and 50 years on. Evolution 73: 111-4.
- Harris RB, A Sackman, and JD Jensen, 2018. On the unfounded enthusiasm for soft selective sweeps II: examining recent evidence from humans, flies, and viruses. PLOS Genetics 14(12): e1007859.
- Matuszewski S, M Hildebrandt, G Achaz, and JD Jensen, 2018. Coalescent processes with skewed offspring distributions and non-equilibrium demography. Genetics 208: 323-38.
- Renzette N, SP Pfeifer, S Matuszewski, TF Kowalik, and JD Jensen, 2017. On the analysis of intra-host and inter-host viral populations: human cytomegalovirus as a case study of pitfalls and expectations. Journal of Virology 91: e01976-16.
- Bank C, S Matuszewski, R Hietpas, and JD Jensen, 2016. On the (un)predictability of a large intragenic fitness landscape. PNAS 113: 14085-90.
- Ewing G, and JD Jensen, 2016. The consequences of not accounting for background selection in demographic inference. Molecular Ecology 25: 135-141.
- Bank C, R Hietpas, A Wong, D Bolon, and JD Jensen, 2014. A Bayesian MCMC approach to assess the complete distribution of fitness effects of new mutations: uncovering the potential for adaptive walks in challenging environments. Genetics 196: 841-52.
- Foll M, YP Poh, N Renzette, A Ferrer-Admetlla, H Shim, AS Malaspinas, G Ewing, C Bank, P Liu, D Wegmann, D Caffrey, K Zeldovich, D Bolon, J Wang, T Kowalik, C Schiffer, R Finberg, and JD Jensen, 2014. Influenza drug resistance: a time-sampled population genetics perspective. PLOS Genetics 10: e1004185.
| Spring 2021 | |
|---|---|
| Course Number | Course Title |
| BIO 492 | Honors Directed Study |
| BIO 498 | Pro-Seminar |
| BIO 591 | Seminar |
| Fall 2020 | |
|---|---|
| Course Number | Course Title |
| BIO 493 | Honors Thesis |
| BIO 498 | Pro-Seminar |
| EVO 498 | Pro-Seminar |
| BIO 591 | Seminar |
| EVO 598 | Special Topics |
| Spring 2020 | |
|---|---|
| Course Number | Course Title |
| BIO 492 | Honors Directed Study |
| Fall 2019 | |
|---|---|
| Course Number | Course Title |
| BIO 493 | Honors Thesis |
| BIO 498 | Pro-Seminar |
| EVO 498 | Pro-Seminar |
| BIO 591 | Seminar |
| EVO 598 | Special Topics |
| Spring 2019 | |
|---|---|
| Course Number | Course Title |
| BIO 492 | Honors Directed Study |
| Fall 2018 | |
|---|---|
| Course Number | Course Title |
| BIO 498 | Pro-Seminar |
| BIO 591 | Seminar |
| Spring 2018 | |
|---|---|
| Course Number | Course Title |
| BIO 345 | Evolution |
| Fall 2017 | |
|---|---|
| Course Number | Course Title |
| BIO 498 | Pro-Seminar |
| BIO 591 | Seminar |
Expertise Areas: