With the tremendous progress in the development of high-throughput sequencing technologies during the past ten year, many life science studies are not limited by generating data, instead, how to manage and analyze those high-throughput data are the real challenges for the majority of biologists. Research in my lab focuses on the design of statistical and computational algorithms on high-throughput biological data to study the epigenetic priming effects on stem cell differentiation and embryo development. The specific fields we study are described as follows.
Computational Algorithms on Epigenomics
One the most important contributions made by bioinformatics community is the cutting-edge computational algorithms for general or specific analysis questions. We have recently developed a series of computational algorithms to analyze high-throughput biological data. For general analysis purposes, we have built MACS, a widely used ChIP-seq peak caller (cited over 8,000 times), and GFOLD for ranking differentially expressed gene from RNA-seq. For specific epigenomics questions, we have contributed NPS and DiNuP for nucleosome positioning, GeSICA for genome segmentation from Hi-C data, and MethylPurify for tumor purity deconvolution from DNAmethylome. Recently, we developed a universal bioinformatics approach to systematically reveal the non-canonical functional mechanisms of chromatin regulators with high efficiency (Genome Biol 2020a), and we built a DNA methylation state transition model to reveal the programmed epigenetic heterogeneity in human pre-implantation embryos (Genome Biol 2020b). We are currently working on a variety of challenging epigenomic questions.
Embryogenesis / Stem Cell Epigenomics
During the early embryogenesis and stem cell differentiation, epigenetic status changed dramatically and usually asymmetry between cells. Therefore, to reveal when and how the specific epigenetic pattern is established is of vital importance to understand the mechanisms of embryogenesis and stem cell differentiation. Over the past few years, we made a number of observations on the features of epigenetic pattern during embryogenesis or in embryonic stem cells: (i) In zebrafish, the histone modification pattern associated with pluripotency is established during the maternal-zygotic transition (Nature 2010). (ii) In zebrafish, well-positioned nucleosome arrays appear on thousands of promoters during the activation of the zygotic genome. The formation of canonical promoter nucleosome organization correlates with the presence of H3K4me3 and affects future transcriptional activation (Genome Res 2014). (iii) In zebrafish, we demonstrate a model whereby inherited DNA methylation signatures from gametes prime the establishment of accessible chromatin during zygotic genome activation through two distinct mechanisms. (Genome Res 2018). (iv) In mouse pre-implantation embryos, the re-establishment of H3K4me3 occurs much more rapidly than that of H3K27me3 following fertilization. The co-occurrence of H3K4me3 and H3K27me3 in early embryos is relatively infrequent and unstable, and the breadth of the H3K4me3 domain is a highly dynamic feature (Nature 2016). (v) In mouse pre-implantation embryos, H3K9me3 exhibits distinct dynamic features in promoters and long terminal repeats. Lineage-specific H3K9me3 is established in post-implantation embryos. (Nat Cell Biol 2018). We are currently performing a number of projects designed to evaluate the mechanistic basis and effects of epigenetic dynamics during stem cell differentiation and embryo development. The broad goal of this research program is to determine the epigenetic priming effects in stem cells, which will benefit the clinical applications of stem cells.