The expression of genes involves a sequence of enzymatic events, such as transcription, mRNA processing, mRNA decay, and translation, that are subject to gene regulatory networks (GRNs) of protein-nucleic acid interactions. It is well appreciated that the control of transcription via regulatory networks that regulate enhancer and promoter activities are not the sole determinant of what gene products result, but that exon skipping is pervasive and post-transcriptional mechanisms such as mRNA splicing and decay determine the kinetics of mRNA induction and abundance. Indeed, in our preliminary studies of the macrophage response to pathogens, we find that a majority of induced gene expression events result in mRNAs that deviate substantially from those predicted by the genome-browser, and that mRNA decay is controlled by both protein- nucleic acid and miRNA regulatory networks. The proposed Center for the Ribonomics of Gene Regulation leverages and pioneers Next Gen Sequencing and computational modeling approaches to develop a predictive model for which mRNA isoforms are expressed and at what level given a given promoter activity and transcription initiation rate. We will develop generally applicable tools in conjunction with or in depth and quantitative experimental analysis of the macrophage response to pathogen-associated endotoxin, which results in the dramatic up regulation of more than 1000 genes. Strikingly, our preliminary data identified more than 900 exon skipping events in addition to numerous cases of alternative 5' or 3' splice site use, emphasizing the essential contribution of post-initiation events. Further, these splice patterns are dependent on the macrophage subtype-specific chromatin landscape and are altered by inducible splice factors in primed or tolerated states. Thus we will leverage the well-described macrophage biology and associated experimental model systems, to examine the role of gene structure and sequence (Aim 1), the role of chromatin modifications (Aim 2), and of trans-acting splicing factors (Aim 3) in determining the identity of mature mRNAs and their associated synthesis rates, before adding the stimulus-responsive regulatory networks that confer mRNA half-life control and thus determine the abundance of each mRNA isoform (Aim 4).
The proposed Center for the Ribonomics of Gene Regulation leverages and pioneers Next Gen Sequencing and computational modeling approaches to develop gene regulatory network (GRN) models that predict which of many alternative mRNA isoforms are actually expressed and at what level. We will leverage the dramatic innate immune transcriptomic response and well-described macrophage biology and associated experimental model systems, to examine the role of gene structure and sequence (Aim 1), the role of chromatin modifications (Aim 2), and of trans-acting splicing factors (Aim 3) in determining the identity of mature mRNAs and their associated synthesis rates, before adding the stimulus-responsive regulatory networks that determine mRNA abundance via mRNA half-life control (Aim 4).
|Hsiao, Yun-Hua Esther; Bahn, Jae Hoon; Lin, Xianzhi et al. (2016) Alternative splicing modulated by genetic variants demonstrates accelerated evolution regulated by highly conserved proteins. Genome Res 26:440-50|
|Ji, Xinjun; Park, Juw Won; Bahrami-Samani, Emad et al. (2016) Î±CP binding to a cytosine-rich subset of polypyrimidine tracts drives a novel pathway of cassette exon splicing in the mammalian transcriptome. Nucleic Acids Res 44:2283-97|
|Duong, Dat; Zou, Jennifer; Hormozdiari, Farhad et al. (2016) Using genomic annotations increases statistical power to detect eGenes. Bioinformatics 32:i156-i163|
|Ernst, Jason; Melnikov, Alexandre; Zhang, Xiaolan et al. (2016) Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions. Nat Biotechnol 34:1180-1190|
|Tong, Ann-Jay; Liu, Xin; Thomas, Brandon J et al. (2016) A Stringent Systems Approach Uncovers Gene-Specific Mechanisms Regulating Inflammation. Cell 165:165-79|
|Cunningham, Cameron R; Champhekar, Ameya; Tullius, Michael V et al. (2016) Type I and Type II Interferon Coordinately Regulate Suppressive Dendritic Cell Fate and Function during Viral Persistence. PLoS Pathog 12:e1005356|
|Cieply, Benjamin; Park, Juw Won; Nakauka-Ddamba, Angela et al. (2016) Multiphasic and Dynamic Changes in Alternative Splicing during Induction of Pluripotency Are Coordinated by Numerous RNA-Binding Proteins. Cell Rep 15:247-55|
|Ahn, Jaegyoon; Xiao, Xinshu (2015) RASER: reads aligner for SNPs and editing sites of RNA. Bioinformatics 31:3906-13|
|Davis-Turak, Jeremy C; Allison, Karmel; Shokhirev, Maxim N et al. (2015) Considering the kinetics of mRNA synthesis in the analysis of the genome and epigenome reveals determinants of co-transcriptional splicing. Nucleic Acids Res 43:699-707|
|Stein, Shayna; Lu, Zhi-Xiang; Bahrami-Samani, Emad et al. (2015) Discover hidden splicing variations by mapping personal transcriptomes to personal genomes. Nucleic Acids Res 43:10612-22|
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