Research Summary
I am a statistical geneticist. My previous research mainly focused on development of theory and statistical methods for quantitative genetic analysis in both diploid and autotetraploid species. Particularly, I have been working on
- Development of theoretical models and statistical methods
for multilocus linkage analysis in autotetraploids - Development of theoretical and experimental strategies for
map-based identification of major effect genes underlying
cell aggregation in budding yeast - Evaluation of the recombination frequency and other relevant parameters in natural populations of the same species with different polyploidy levels (e.g., diploid, allotetraploid and autotetraploid
Arabidopsis)
In addition, I have been involved in population based linkage disequilibrium analysis and genetic association studies with collaborators at Fudan and from other research institutions in China and overseas.
Since I joined UC Berkeley, my research interest has been in understanding novel mechanisms in regulation of gene expression in model eukaryotic organisms, e.g. Drosophila and Saccharomyces cerevisiae. Genome-wide natural antisense transcription has been reported in various animal and plant species. Natural antisense transcripts (NATs) have already been found to function at several levels of eukaryotic gene regulation including translational regulation, alternative splicing, RNA stability, genomic imprinting, etc. However, the mechanistic underpinning of NATs mediated transcription is still far from being well established. By taking advantage of the rapidly accumulated sequencing datasets, I will focus on the identification and analysis of cis-NATs in eukaryotic genomes, particularly in Drosophila, to enhance our understanding of the functional significance of cis-NATs in gene regulation in Drosophila and the evolution of sense/antisense pairs at both the structural and functional levels within and between Drosophila species.
Impact in China
Statistical genetics occupies a critical position in understanding the structure and function of genomes. In comparison to the huge community of molecular biologists, statistical geneticists, particularly those with a high standard qualification, are very rare in China. With a strong motivation to develop a highly recognized professional career in the subject, I am greatly honored to join the Eisen Lab at the University of California, Berkeley with sponsorship of the prestigious Tang Scholarship. My chosen research at UC Berkeley will focus on the evolutionary and functional implications of the structural organization of the genes in convergent, consistent or divergent orientations using the next generation sequencing data. This opens a new research field for me and will equip me with knowledge and skills highly relevant to biomedical sciences in China.
Publications
Li, J.R.*, Wang, L.*, Fang, O., Wang, L.W., Lu, C.Q., Hu, X.H. and Luo, Z.W. (2013) Polygenic molecular architecture underlying non-sexual cell aggregation in budding yeast. DNA Research 20,55-66 (*Co-first author).
Wang, M.H., Wang, L., Jiang, N., Jia, T. and Luo, Z.W. (2013) A robust and efficient statistical method for genetic association studies using case and control samples from multiple cohorts. BMC Genomics 14:88.
Wang, L., and Luo, Z.W. (2012) Polyploidization increases meiotic recombination frequency in Arabidopsis: a close look at statistical modelling and data analysis. BMC Biology 10:30.
Jiang, N., Wang, M., Jia, T., Wang, L., et al. (2011) A robust statistical method for association-based eQTL analysis. PLoS ONE 6(8): e23192.
Leach, L.J., Wang, L., Kearsey, M.J., and Luo, Z.W. (2010) Multilocus tetrasomic linkage analysis using hidden Markov chain model. Proceedings of the National Academy of Sciences 107: 4270-4274.
Wang, M.H., Jia, T.Y., J, N., Wang, L., et al. (2010) Inferring linkage disequilibrium from non-random samples. BMC Genomics 11: 328.
Wang, L., Hu, X.H., Feng, Z.Y., and Pan, Y.J. (2009) Development of AFLP markers and phylogenetic analysis in Hypsizygus marmoreus. Journal of General and Applied Microbiology 55: 9-17.