Biography

COMPARATIVE RNA BIOLOGY  Transcriptome analysis is fundamental to understanding the biochemical, cellular, physiological and environmental systems involved in the complex phenotypes that affect development, growth, reproduction and well-being in human and animals. In mammals, up to 75% of genes use alternative promoters, isoforms or polyadenylation sites, contributing greatly to transcriptome flexibility, diversity and dynamics. The long-term goal of our Comparative RNA Biology program is to create state-of-the-art tools for profiling the full transcriptome that will advance the field of functional genomics and increase its applicability to solve unmet problems in human health and animal productivity. We believe that accurate profiling of transcript variants will promote the discovery of genetic mutations that underlie complex phenotypes, aid in the selection of regulatory switch units for functional characterization, and discover alternative variants that can be used for disease diagnosis and drug discovery in humans and for biomarker selection in animals.

Specific Research Areas:

• Development of next-generation sequencing tools for profiling of alternative transcripts.
• Development of alternative transcript resources in animals and model organisms.
• Development of animal models to understand alternative transcripts and multi-functions of genes.

Most Recent Publications:

1. Zhou X, Li R, Michal JJ, Wu XL, Liu Z, Zhao H, Xia Y, Du W, Wildung MR, Pouchnik DJ, Harland RM, Jiang Z. 2016. Accurate profiling of gene expression and alternative polyadenylation with whole transcriptome termini site sequencing (WTTS-Seq). 203(2): 683-697 (Issue Highlights).
2. El-Halawany N, Zhou X, Al-Tohamy A, El-Sayed Y, Shawky A, Michal JJ, Jiang Z. 2016. Genome-wide screening of candidate genes for improving fertility in Egyptian native Rahmani sheep. Anim Genet.47(4):513.
3. Wei S, Du M, Jiang Z, Hausman GJ, Zhang L, Dodson MV. 2016. Long noncoding RNAs in regulating adipogenesis: new RNAs shed lights on obesity. Cell Mol Life Sci. 73(10):2079-2087.
4. Jiang Z, Wang H, Michal JJ, Zhou X, Solberg Woods LC, Fuchs RA. 2016. Genome wide sampling sequencing for SNP genotyping: methods, challenges and future development. Int J Biol Sci. 12(1): 100-108.
5. Sun W, Dodson MV, Jiang Z, Yu S, Chu W, Chen J. 2016. Myostatin inhibits porcine intramuscular preadipocyte differentiation in vitro. Domest Anim Endocrinol. 55:25-31.
6. Wang H, Wang C, Yang K, Liu J, Zhang Y, Xu X, Michal JJ, Jiang Z, Liu B. 2015. Genome wide distributions and functional characterization of copy number variations between Chinese and Western pigs. PLoS One 10(7):e0131522.
7. Jiang Z. 2015. Editorial – Mining the next generation sequencing data: how to avoid “treasure in, error out.” J Data Mining Genomics Proteomics 6: e170.
8. Jiang Z, Zhou X, Li R, Michal JJ, Zhang S, Zhang Z, Harland RM. 2015. Whole transcriptome analysis with sequencing: methods, challenges and potential solutions. Cell Mol Life Sci. 72:3425-3439.