Marshall W. Nirenberg Collegiate Professor of Ecology and Evolutionary Biology
About
Academic Background
B. S., Fudan University, Shanghai, China, 1992
Ph. D., Pennsylvania State University, University Park, PA, 1998
Fogarty Postdoctoral Fellow, National Institute of Allergy and Infectious Diseases, Bethesda, MD, 1999-2001
Assistant Professor, Department of Ecology and Evolutionary Biology, University of Michigan, 2001-2005
Associate Professor, Department of Ecology and Evolutionary Biology, University of Michigan, 2005-2009
Professor, Department of Ecology and Evolutionary Biology, University of Michigan, 2009-2013
Marshall W. Nirenberg Collegiate Professor, Department of Ecology and Evolutionary Biology, University of Michigan, 2013-present.
Research Interests
I am most interested in the relative roles of chance and necessity in evolution. There are two major research areas in my lab.
I. Yeast as an experimental system for studying evolution
We are using the budding yeast Saccharomyces cerevisiae and its relatives as model organisms to understand a variety of evolutionary processes, including for example questions about (i) the rate, molecular spectrum, and fitness effect of mutation, (ii) epistasis and fitness landscapes, (iii) pleiotropy and evolutionary impacts, (iv) gene expression evolution, (v) genomic basis of adaptation, and (vi) experimental speciation. Commonly used approaches include experimental evolution, mutation accumulation, genome and transcriptome sequencing, and genome editing.
II. Computational evolutionary genomics
Using evolutionary, genomic, and/or systemic approaches, we analyze publicly available data to characterize and understand plasticity, pleiotropy, epistasis, gene expression and expression noise, posttranscriptional modification, convergent evolution, natural and sexual selection, human phenotypic variation and evolution, and other important genetic and evolutionary phenomena. We are not limited in the study organism in this line of research, but most often analyze functional genomic data from humans and yeasts. Projects may also involve theory development, mathematical modeling, and computer simulation.
I also encourage students and postdoctoral fellows to develop their own projects in the general area of evolutionary genetics and genomics.
Selected Recent Publications
Song, S., P. Chen, X. Shen, and J. Zhang (2025) Adaptive tracking with antagonistic pleiotropy results in seemingly neutral molecular evolution. Nat. Ecol. Evol. 9:2358-2373.
Zhang, J., and W. Qian (2025) Functional synonymous mutations and their evolutionary consequences. Nat. Rev. Genet. 26:789-804.
Zhang, J. (2023) Patterns and evolutionary consequences of pleiotropy. Annu. Rev. Ecol. Evol. Syst. 54:1-19.
Long, E., and J. Zhang (2023) Evidence for the role of selection for reproductively advantageous alleles in human aging. Sci. Adv. 9:eadh4990.
Shen, X., S. Song, C. Li, and J. Zhang (2022) Synonymous mutations in representative yeast genes are mostly strongly non-neutral. Nature 606:725-731.
Liu, H., and J. Zhang (2021) The rate and molecular spectrum of mutation are selectively maintained in yeast. Nat. Commun. 12:4044.
Lyons, D.M., Z. Zou, H. Xu., and J. Zhang (2020) Idiosyncratic epistasis creates universals in mutational effects and evolutionary trajectories. Nat. Ecol. Evol. 4:1685-1693.
Chen, P., and J. Zhang (2020) Antagonistic pleiotropy conceals molecular adaptations in changing environments. Nat. Ecol. Evol. 4:461-469.
Zou, Z., H. Zhang, Y. Guan, and J. Zhang (2020) Deep residual neural networks resolve quartet molecular phylogenies. Mol. Biol. Evol. 37:1495-1507.
Xu, H., J.-J. Liu, Z. Liu, Y. Li, Y.-S Jin, and J. Zhang (2019) Synchronization of stochastic expressions drives the clustering of functionally related genes. Sci. Adv. 5: eaax6525.
Wei, X., and J. Zhang. (2018) The optimal mating distance resulting from heterosis and genetic incompatibility. Sci. Adv. 4:eaau5518.
Ho, W.-C., and J. Zhang (2018) Evolutionary adaptations to new environments generally reverse plastic phenotypic changes. Nat. Commun. 9:350.
Li, C., and J. Zhang (2018) Multi-environment fitness landscapes of a tRNA gene. Nat. Ecol. Evol. 2:1025-1032.
Li, C., Qian, W., Maclean, C. J., and J. Zhang (2016) The fitness landscape of a tRNA gene. Science 352:837-840.
Zhang, J., and J.-R. Yang (2015) Determinants of the rate of protein sequence evolution. Nat. Rev. Genet. 16:409-420.
Teaching
EEB 410: EEB Capstone Seminars
EEB 512: Molecular and Genomic Evolution
Research Areas
- Molecular and genome evolution
Affiliation(s)
- Center for Statistical Genetics, School of Public Health
- Bioinformatics Program, U-M Medical School
Field(s) of Study
- Evolutionary genetics and genomics
Graduate Students
Postdoctoral Fellows
