The Zou Lab is mainly interested in the evolution modes of molecular sequences and the corresponding methodology. We study key questions on the frontiers of molecular evolution, primarily using computational approaches such as comparative analysis, statistical test, model simulation, and machine learning.

1. Evolution patterns and modes of molecular sequences.

Molecular evolution models describe the evolution process of DNA or protein sequences are among the core tools in bioinformatic analyses. In recent years, accumulation of sequence data allows us to recognize more complex patterns and modes in sequence evolution. For example, prevalent heterogeneity of features such as evolutionary rate among species or between genomic loci, and the non-independence between biochemically interacting loci in the sequence, i.e. epistasis or coevolution. Based on available comparative genomics data, we are interested in finding the biological mechanisms and driving factors of such patterns, and how to combine these factors into molecular evolution analyses, so that we can better model the patterns and processes of sequence evolution, i.e. phylogeny and adaptation, etc.

2. Application of deep learning in evolution analyses (AI for Evolution).

Deep learning is a fast-advancing field of computational tools, suitable for complex pattern extraction and prediction from big data. Regarding the living system, the genotype-phenotype mapping from molecular sequences to organismal morphology and function is complex and of high orders, thus difficult to capture. We hope to harness deep learning techniques to extract complex high-order features of genomes, proteins, or phenotypes, and explore the application of such features in identifying or predicting evolution patterns such as phylogeny and adaptation. Meanwhile, we want to map phenotypes and functions back to molecular mechanisms, using interpretable AI approaches.

3. Other directions.

We are broadly interested in the topics of molecular or morphological phenotype evolution, case study of genome adaptation in particular taxonomic groups, etc.

2013/8 – 2017/8 Ph.D. in Bioinformatics, Department of Computational Medicine and Bioinformatics, University of Michigan

2009/9 – 2013/7 B.S. in Biological Science, Peking University

   

2020/9 – present Principal Investigator, Institute of Zoology, Chinese Academy of Sciences

2017/9 – 2020/8 Research Fellow, Department of Ecology and Evolutionary Biology, University of Michigan

   

Hao Y^*, Zhou X^*, Zhao Q^*, She H, Fang Y, Ma L, Zou Z, Zhai W, Ericson PGP, Lei F^#, Meng F^#, Zhang S^#, Qu Y^#. Avian lung single-cell atlas elucidates evolutionary divergence in endothermic respiration. Mol. Biol. Evol., 2026, 43: 1-16. doi: 10.1093/molbev/msag072.

Ma Q, Ma Y, Tan C, Chen J, Lin Y, Xiao M, Dai H, Wei G, Mallon JC, Wang J, Yao H, Zou Z, Xing H. First report of a hollow cranial crest in an early-diverging duck-billed dinosaur, with implications for convergent evolution of acoustic signaling. Biology, 2026, 15: 615; doi: 10.3390/biology15080615.

Chen S, Zou Z. Detecting convergence of amino acid physicochemical properties underlying the organismal adaptive convergent evolution. Mol. Ecol. Resour., 2025, 25: e70052. doi: 10.1111/1755-0998.70052

Cao Z, Zhang H, Zou Z. Language model reveals complex sequence basis for adaptive convergent evolution of protein functions. Proc. Natl. Acad. Sci. U. S. A., 2025, 122: e2418254122. doi: 10.1073/pnas.2418254122

Qin T, Zhang H, Zou Z. Unveiling cell-type-specific mode of evolution in comparative single-cell expression data. J. Genet. Genomics, 2025, 53:28-42. doi: 10.1016/j.jgg.2025.04.022

Masubuchi T, Chen L, Marcel N, Wen GA, Caron C, Zhang J, Zhao Y, Morris GP, Chen X, Hedrick SM, Lu LF, Wu C, Zou Z^#, Bui JD^#, Hui E^#. Functional differences between rodent and human PD-1 linked to evolutionary divergence. Sci. Immunol., 2025, 10: eads6295. doi: 10.1126/sciimmunol.ads6295

Tan X^#*, Chai Y^#*, Li R^*, Zhang B^*, Li H^*, Zhang J, Zhu T, Wu W, An L, Hu S, Yang B, Wang L, Cao Z, Zhang H, Wang P, Yu L, Yin S, Li X, Shao F, Huang J, Li J, Yang F, Zhao C, Guo J, Zeng L, Liang D, Zou Z, Zheng H, Fan X^#, Xie L^#, Cao Y^#, Yang H^#. Tip optofluidic immunoassay: Evaluating COVID-19 antibody protection with 1 μL fingertip blood. hLife, 2025, 3: 338-356. doi: 10.1016/j.hlife.2025.04.005

Wang T^*, Yang M^*, Shi X^*, Tian S, Li Y, Xie W, Zou Z, Leng D, Zhang M, Zheng C, Feng C, Zeng B, Fan X, Qiu H, Li J, Zhao G, Yuan Z, Li D^#, Jie H^#. Multiomics analysis provides insights into musk secretion in muskrat and musk deer. GigaScience, 2025, 14: 1-19. doi: 10.1093/gigascience/giaf006

Zhang X, Chen Y, Liang J, Yang Y, Chen H, Chen Z, Li M, Chen S, Chen T, He H, Liu Y, Liu Z, Han L, Wu D, Zou Z, Qu Y, Li M, Stoneking M, Fu Q, Xu S, Zeng YX, Ma L^#, Liu J^#, Xu M^#, Zhai W^#. Out-of-Africa migration and clonal expansion of a recombinant Epstein-Barr virus drives frequent nasopharyngeal carcinoma in southern China. Natl. Sci. Rev., 2024, 12: nwae438. doi: 10.1093/nsr/nwae438

Xu S, Jiang L, Zou Z, Zou M, Qiao G^#, Chen J^#. Two chromosome-level genome assemblies of galling aphids Slavum lentiscoides and Chaetogeoica ovagalla. Sci. Data, 2024, 11:803. doi: 10.1038/s41597-024-03653-x

Lu Y, Ballerio A, Wang S, Zou Z, Gorb SN, Wang T, Li L, Ji S, Zhao Z, Li S, Tong Y, Chen Y, Zhuo D, Luo C, Zhang W, Liu N, Gu Q^#, Bai M^#. The evolution of conglobation in Ceratocanthinae. Commun. Biol., 2022, 5:777. doi: 10.1038/s42003-022-03685-2

Si S, Xu X^#, Zhuang Y, Gao X, Zhang H, Zou Z^#, Luo SJ^#. The genetics and evolution of eye color in domestic pigeons (Columba livia). PLoS Genet., 2021, 17:e1009770. doi: 10.1371/journal.pgen.1009770

Zou Z, Zhang J. Are nonsynonymous transversions generally more deleterious than nonsynonymous transitions? Mol. Biol. Evol., 2021, 38:181-191. doi: 10.1093/molbev/msaa200

Lyons DM^*, Zou Z^*, Xu H, Zhang J. Idiosyncratic epistasis creates universals in mutational effects and evolutionary trajectories. Nat. Ecol. Evol., 2020, 4:1685-1693. doi: 10.1038/s41559-020-01286-y

Zou Z, Zhang J. The nature and phylogenomic impact of sequence convergence. Phylogenetics in the Genomic Era (C. Scornavacca, et al., eds). No commercial publisher | Authors open access book, pp.4.6:1-4.6:17, 2020. ffhal-02536347

Zou Z^*, Zhang H^*, Guan Y, Zhang J. Deep residual neural networks resolve quartet molecular phylogenies. Mol. Biol. Evol., 2020, 37:1495-1507. doi: 10.1093/molbev/msz307

Zou Z, Zhang J. Amino acid exchangeabilities vary across the tree of life. Sci. Adv., 2019, 5: eaax3124. doi: 10.1126/sciadv.aax3124

Ding X, Zou Z, Brooks III CL. 2019. Deciphering protein evolution and fitness landscapes with latent space models. Nat. Commun., 10: 5644. doi: 10.1038/s41467-019-13633-0

Zhang W, Xu X, Yue B, Hou R, Xie J, Zou Z-T, Han Y, Shen F, Zhang L, Xie Z, Yuan Y, Yin Y, Fu W, Chen D, Huang W, Liu Z, Tang Y, Zhao B, Zhang Q, Chen W, Zhang R, Chen J, Luo S-J, Zhang Z. 2019. Sorting out the genetic background of the last surviving South China tigers. J. Hered., pii: esz034. 10.1093/jhered/esz034

Zou Z, Zhang J. Gene tree discordance does not explain away the temporal decline of convergence in mammalian protein sequence evolution. Mol. Biol. Evol., 2017, 34: 1682-1688. doi: 10.1093/molbev/msx109

Zou Z, Zhang J. Morphological and molecular convergences in mammalian phylogenetics. Nat. Commun., 2016, 7: 12758. doi: 10.1038/ncomms12758

Oetjens MT, Shen F, Emery SB, Zou Z, Kidd JM. 2016. Y-Chromosome structural diversity in the bonobo and chimpanzee lineages. Genome Biol. Evol., 8: 2231-2240. doi: 10.1093/gbe/evw150

Zou Z, Zhang J. Are convergent and parallel amino acid substitutions in protein evolution more prevalent than neutral expectations? Mol. Biol. Evol., 2015, 32: 2085-2096. doi: 10.1093/molbev/msv091

Zou Z, Zhang J. No genome-wide convergence for echolocation. Mol. Biol. Evol., 2015, 32: 1237-1241. doi: 10.1093/molbev/msv014

Zou Z-T, Uphyrkina O, Fomenko P, Luo S-J. The development and application of a multiplex short tandem repeat (STR) system for identifying subspecies, individuals and sex in tigers. Integr. Zool., 2015, 10: 376-388. doi: 10.1111/1749-4877.12136

Xu X, Dong G-X, Hu X-S, Miao L, Zhang X-L, Zhang D-L, Yang H-D, Zhang T-Y, Zou Z-T, Zhang T-T, Zhuang Y, Bhak J, Cho YS, Dai W-T, Jiang T-J, Xie C, Li R-Q, Luo S-J. 2013. The genetic basis of white tigers. Curr. Biol., 23: 1031-1035. doi: 10.1016/j.cub.2013.04.054

Molecular evolution and phylogenetics, evolutionary development biology, deep learning application