Research Areas

The lab is primarily committed to statistical genetics, multi-omics research (such as genomics, transcriptomics, and epigenomics), and big data analysis of human complex traits and diseases (such as depression, Alzheimer's disease, and schizophrenia). By integrating statistical genetic methods and omics data, Dr. Qi has accumulated extensive research experience in identifying disease susceptibility genes and deciphering the genetic regulatory mechanisms of complex traits and diseases. Currently, the main research directions of the lab include but are not limited to the following:

1) Understanding the genetic basis of molecular phenotypes (such as gene expression, DNA methylation) at the single-cell level, and exploring their associations with complex diseases;

2) Integrating multi-omics data to identify therapeutic targets and biomarkers for complex diseases;

3) Developing statistical genetic analysis methods and software.

Brief Biography

Principal Investigator (2024.09 - present)
Shanghai Institute of Nutrition and Health, CAS, Shanghai, China 

Research Associate Professor (2020.07 – 2024.08)   
School of Life Sciences, Westlake University, Hangzhou, China 

Postdoctoral Research Fellow (2016.09 – 2020.06)     Supervisor: Jian Yang 
Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia 

PhD in Statistical Genetics (2011.09 - 2016.06)    Supervisor: Jun Zhu 
Institute of Bioinformatics, Zhejiang University, Hangzhou, China 

BSc in Agronomy (2007.09 - 2011.06)  
College of Agriculture, Yangzhou University, Yangzhou, China

Selected Publications (*Co-corresponding author; #Co-first author;)

· Qi T. ^#,^* et al. From genetic associations to genes: methods, applications, and challenges. Trends in Genetics (2024)

· Zhang R. ^#, Fang J. ^#, Qi T. ^# et al. Maternal aging drives offspring adult trait formation via aged mitochondria. Cell Research 33, 821-834 (2023) (#Co-first author; Cover story)

· Qi T., Wu Y., Fang H., Zhang F., Liu S., Zeng J., Yang J. Genetic control of RNA splicing and its distinct role in complex trait variation. Nature Genetics 54, 1355-1363 (2022)

· Wu Y.^#, Qi T.^#, Wang H., Zhang F., Zheng Z., Phillips-Cremins J.E., Deary I.J., McRae A.F., Wray N.R., Zeng J., Yang J. Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data. Nature Communications 11, 2061 (2020) (#Co-first author)

· Qi T., Wu Y., Zeng J., Zhang F., Xue A., Jiang L., Zhu Z., Kemper K., Yengo L., Zheng Z., eQTLGen Consortium, Marioni R.E., Montgomery G.W., Deary I.J., Wray N.R., Visscher P.M., McRae A.F., Yang J. Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nature Communications 9, 2282 (2018)

· Qi T., Cao Y., Cao L., Gao Y., Zhu S., Lou X., Xu H. Dissecting genetic architecture underlying seed trait in multiple environment. Genetics 199, 61-71 (2015)

· Qi T., Jiang B., Zhu Z., Wei C., Gao Y., Zhu S., Xu H., Lou X. Mixed linear model approach for mapping quantitative trait loci underlying crop seed traits. Heredity 113, 224 (2014)

· Trubetskoy V., Pardinas A., Qi T. et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 604, 502-508 (2022)

· Sun X., Xue A., Qi T., Chen D., Shi D., Wu Y., Zheng Z., Zeng J., Yang J. Tumor mutational burden is polygenic and genetically associated with complex traits and diseases. Cancer Research 85, 1230-1239 (2021)

· Jiang L., Zheng Z., Qi T., Kemper K., Wray N.R., Visscher P.M., Yang J. A resource-efficient tool for mixed model association analysis of large-scale data. Nature Genetics 51, 1749-1755 (2019)