Education:
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2002–2006 |
B.S. in Biological Sciences, Peking University, Beijing, China
Adviser: Wen Wang (Kunming Institute of Zoology, Chinese Academy of Sciences) |
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2006–2012 |
Ph.D. in Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
Adviser: Jianzhi “George” Zhang |
Research Interests:
Thousands of genomes have been sequenced, but our knowledge about them is still very limited. To demonstrate this point, I use an analogy from computer science. Let’s think about the binary numbers that are read by a computer for certain functions (e.g., to print “hello world” in Fig 1A): we know exactly how this process works. On the contrary, judged by the same standard, we are far away from understanding how cells decode DNA sequences to realize functions (Fig 1B). We don’t know the function of most nucleotides in the promoter region of a gene; we don’t know the function of most amino acids in a protein even if we have a rough idea about the function of the protein; we especially don’t know how all biological molecules work together to function as a cell, even though we have already understood some pathways in a cell. In other words, it is still mysterious how lives are encoded in genomes. .
Figure 1 A comparison between our understanding of binary code and DNA sequence. (A) We know exactly how binary numbers are decoded by computers. (B) Judged by the same standard, our knowledge about how cells decode genomes is very limited.
To infer the function of a nucleotide, one can certainly change the nucleotide and observe the functional effect of the change. However, so many nucleotides exist in a genome (3,000,000,000 base pairs for human). Therefore, it is extremely labor intensive to change every nucleotide in a genome. Thus, it is of central importance to predict the functional important nucleotides computationally or with a high-throughput approach.
Specifically, my lab focuses on
(1) Regulatory mechanisms of transcription and translation, aiming to understand the function of each nucleotide;
(2) Single-cell DNA methylome and transcriptome, aiming to understand how robust transcriptome is maintained among isogenic cells that are in the same environment;
(3) The rates of point mutation and homologous recombination, and their impacts on the rate of adaptation;
(4) Ploidy and aneuploidy variation, and their impacts on the growth rate of cells (including tumor cells).
We used a number of high-throughput strategies to address these questions.
(1) Omics approaches, including BS-seq, RNA-seq, Ribo-seq, and SILAC, etc.;
(2) High-throughput nucleotide replacement and reporter detection, including FACS-seq, Polysome-seq, etc.;
(3) Single-cell RNA-seq;
(4) Comparative and evolutionary genomics.
In the long run, we aim to understand basic rules in gene expression regulation and biological adaptation.
Publications:
13. B. Zhang*, S. Wu*, Y. Zhang, T. Xu, F. Guo, H. Tang, X. Li, P. Wang, W. Qian, and Y. Xue (2016) A high temperature-dependent mitochondrial lipase EXTRA GLUME1 promotes floral phenotypic robustness against temperature fluctuation in rice (Oryza sativa L.). PLoS Genetics 12 (7):e1006152. (*, equal contributions)
12. C. Li, W. Qian, C. J. Maclean and J. Zhang (2016) The fitness landscape of a tRNA gene. Science. 352(6287):837-40
11. W. Qian, and J. Zhang (2014) Genomic evidence for adaptation by gene duplication. Genome Research 24:1356-1362.
10. C. Park, W. Qian, and J. Zhang (2012) Genomic evidence for elevated mutation rates in highly expressed genes. EMBO Reports 13:1123-1129.
9. W. Qian, D. Ma, C. Xiao, Z. Wang, and J. Zhang (2012) The genomic landscape and evolutionary resolution of antagonistic pleiotropy in yeast. Cell Reports, 2:1399-1410.
8. W. Qian, J.-R. Yang, N. M. Pearson, C. Maclean, and J. Zhang (2012) Balanced codon usage optimizes eukaryotic translational efficiency. PLoS Genetics 8(3): e1002603.
7. W. Qian, X. He, E. Chan, H. Xu, and J. Zhang (2011) Measuring the evolutionary rate of protein-protein interaction. Proc. Natl. Acad. Sci. USA 108:8725-8730.
6. W. Qian*, B.-Y. Liao*, A. Y.-F. Chang, and J. Zhang (2010) Maintenance of duplicate genes and their functional redundancy by reduced expression. Trends in Genetics 26:425-430. (*, equal contributions)
5. X. He*, W. Qian*, Z. Wang*, Y. Li, and J. Zhang (2010) Prevalent positive epistasis in Escherichia coli and Saccharomyces cerevisiae metabolic networks. Nature Genetics 42:272-276. (*, equal contributions)
4. Z. Zhang, W. Qian, and J. Zhang (2009) Positive selection for elevated gene expression noise in yeast. Molecular Systems Biology 5:299 (12 pages).
3. W. Qian, and J. Zhang (2009) Protein subcellular relocalization in the evolution of yeast singleton and duplicate genes. Genome Biology and Evolution 1:198-204.
2. W. Qian, and J. Zhang (2008) Gene dosage and gene duplicability. Genetics 179:2319-2324.
1. W. Qian, and J. Zhang (2008) Evolutionary dynamics of nematode operons: easy come, slow go. Genome Research 18:412-421.
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