Tinyi Chu

Transcriptional response to stress is pre-wired by promoter and enhancer architecture

Programs of gene expression are executed by a battery of transcription factors that coordinate divergent transcription from a pair of tightly linked core initiation regions of promoters and enhancers. Here, to investigate how divergent transcription is reprogrammed upon stress, we measured nascent RNA synthesis at nucleotide-resolution, and profiled histone H4 acetylation in human cells. Our results globally show that the release of promoter-proximal paused RNA polymerase into elongation functions as a critical switch at which a gene’s response to stress is determined. Highly transcribed and highly inducible genes display strong transcriptional directionality and selective assembly of general transcription factors on the core sense promoter. Heat-induced transcription at enhancers, instead, correlates with prior binding of cell-type, sequence-specific transcription factors. Activated Heat Shock Factor 1 (HSF1) binds to transcription-primed promoters and enhancers, and CTCF-occupied, non-transcribed chromatin. These results reveal chromatin architectural features that orient transcription at divergent regulatory elements and prime transcriptional responses genome-wide.Heat Shock Factor 1 (HSF1) is a regulator of stress-induced transcription. Here, the authors investigate changes to transcription and chromatin organization upon stress and find that activated HSF1 binds to transcription-primed promoters and enhancers, and to CTCF occupied, untranscribed chromatin.

Dynamic evolution of regulatory element ensembles in primate CD4(+) T cells

How evolutionary changes at enhancers affect the transcription of target genes remains an important open question. Previous comparative studies of gene expression have largely measured the abundance of messenger RNA, which is affected by post-transcriptional regulatory processes, hence limiting inferences about the mechanisms underlying expression differences. Here, we directly measured nascent transcription in primate species, allowing us to separate transcription from post-transcriptional regulation. We used precision run-on and sequencing to map RNA polymerases in resting and activated CD4+ T cells in multiple human, chimpanzee and rhesus macaque individuals, with rodents as outgroups. We observed general conservation in coding and non-coding transcription, punctuated by numerous differences between species, particularly at distal enhancers and non-coding RNAs. Genes regulated by larger numbers of enhancers are more frequently transcribed at evolutionarily stable levels, despite reduced conservation at individual enhancers. Adaptive nucleotide substitutions are associated with lineage-specific transcription and at one locus, SGPP2, we predict and experimentally validate that multiple substitutions contribute to human-specific transcription. Collectively, our findings suggest a pervasive role for evolutionary compensation across ensembles of enhancers that jointly regulate target genes.It is unclear how evolutionary changes at enhancers affect the transcription of target genes. Measuring nascent transcription in CD4+ T cells in primates, the authors show that the effects of evolutionary changes in enhancers are buffered at the transcriptional level.

Identification of regulatory elements from nascent transcription using dREG

Our genomes encode a wealth of transcription initiation regions (TIRs) that can be identified by their distinctive patterns of transcription initiation. We previously introduced dREG to identify TIRs using PROseq data. Here we introduce an efficient new implementation of dREG that uses PRO-seq data to identify both uni- and bidirectionally transcribed TIRs with 70% improvements in accuracy, 3–4-fold higher resolution, and >100-fold increases in computational efficiency. Using a novel strategy to identify TIRs based on their statistical confidence reveals extensive overlap with orthogonal assays, yet also reveals thousands of additional weakly-transcribed TIRs that were not identified by H3K27ac ChIP-seq or DNase-I-hypersensitivity. Novel TIRs discovered by dREG were often associated with RNA polymerase III initiation or bound by transcription factors that recognize DNA concurrently with a nucleosome. We provide a web interface to dREG that can be used by the scientific community (http://dREG.DNASequence.org).

Chromatin run-on reveals nascent RNAs that differentiate normal and malignant brain tissue

Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties.The human genome encodes a variety of poorly understood RNA species that remain challenging to identify using existing genomic tools. We developed chromatin run-on and sequencing (ChRO-seq) to map the location of RNA polymerase using virtually any input sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in primary human glioblastoma (GBM) brain tumors. Whereas enhancers discovered in primary GBMs resemble open chromatin in the normal human brain, rare enhancers activated in malignant tissue drive regulatory programs similar to the developing nervous system. We identified enhancers that regulate genes characteristic of each known GBM subtype, identified transcription factors that drive them, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.

Building a Science Gateway For Processing and Modeling Sequencing Data Via Apache Airavata

The amount of DNA sequencing data has been exponentially growing during the past decade due to advances in sequencing technology. Processing and modeling large amounts of sequencing data can be computationally intractable for desktop computing platforms. High performance computing (HPC) resources offer advantages in terms of computing power, and can be a general solution to these problems. Using HPCs directly for computational needs requires skilled users who know their way around HPCs and acquiring such skills take time. Science gateways acts as the middle layer between users and HPCs, providing users with the resources to accomplish compute-intensive tasks without requiring specialized expertise. We developed a web-based computing platform for genome biologists by customizing the PHP Gateway for Airavata (PGA) framework that accesses publicly accessible HPC resources via Apache Airavata. This web computing platform takes advantage of the Extreme Science and Engineering Discovery Environment (XSEDE) which provides the resources for gateway development, including access to CPU, GPU, and storage resources. We used this platform to develop a gateway for the dREG algorithm, an online computing tool for finding functional regions in mammalian genomes using nascent RNA sequencing data. The dREG gateway provides its users a free, powerful and user-friendly GPU computing resource based on XSEDE, circumventing the need of specialized knowledge about installation, configuration, and execution on an HPC for biologists. The dREG gateway is available at: https://dREG.dnasequence.org/.

A bi-stable feedback loop between GDNF, EGR1, and ERα contribute to endocrine resistant breast cancer

Discovering regulatory interactions between genes that specify the behavioral properties of cells remains an important challenge. We used the dynamics of transcriptional changes resolved by PRO-seq to identify a regulatory network responsible for endocrine resistance in breast cancer. We show that GDNF leads to endocrine resistance by switching the active state in a bi-stable feedback loop between GDNF, EGR1, and the master transcription factor ERα. GDNF stimulates MAP kinase, activating the transcription factors SRF and AP-1. SRF initiates an immediate transcriptional response, activating EGR1 and suppressing ERα. Newly translated EGR1 protein activates endogenous GDNF, leading to constitutive GDNF and EGR1 up-regulation, and the sustained down-regulation of ERα. Endocrine resistant MCF-7 cells are constitutively in the GDNF-high/ ERα-low state, suggesting that the state in the bi-stable feedback loop may provide a ‘memory’ of endocrine resistance. Thus, we identified a regulatory network switch that contributes to drug resistance in breast cancer.

Chromatin run-on and sequencing maps the transcriptional regulatory landscape of glioblastoma multiforme

The human genome encodes a variety of poorly understood RNA species that remain challenging to identify using existing genomic tools. We developed chromatin run-on and sequencing (ChRO-seq) to map the location of RNA polymerase for almost any input sample, including samples with degraded RNA that are intractable to RNA sequencing. We used ChRO-seq to map nascent transcription in primary human glioblastoma (GBM) brain tumors. Enhancers identified in primary GBMs resemble open chromatin in the normal human brain. Rare enhancers that are activated in malignant tissue drive regulatory programs similar to the developing nervous system. We identified enhancers that regulate groups of genes that are characteristic of each known GBM subtype and transcription factors that drive them. Finally we discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study characterizes the transcriptional landscape of GBM and introduces ChRO-seq as a method to map regulatory programs that contribute to complex diseases.Chromatin run-on and sequencing (ChRO-seq) is a new method that maps the location of RNA polymerase using virtually any input sample. Here, ChRO-seq is used to study nascent transcription in human glioblastoma, and to identify regulators of tumor subtype.

RET Ligands Mediate Endocrine Sensitivity via a Bi-stable Feedback Loop with ERα

The molecular mechanisms of endocrine resistance in breast cancer remain poorly understood. Here we used PRO-seq to map the location of hundreds of genes and thousands of distal enhancers whose transcriptional activities differ between endocrine sensitive and resistant MCF-7 cells. Our genome-wide screen discovered increased transcription of the glial-cell line derived neurotrophic factor (GDNF), a RET tyrosine kinase receptor ligand, which we validate as both necessary and sufficient for resistance in MCF-7 cells. GDNF caused endocrine resistance by switching the active state of a bi-stable feedback loop in the MCF-7 regulatory network from ERα signaling to GDNF-RET signaling. To cause this switch, GDNF downregulated ERα transcription and activated the transcription factor EGR1, which, in turn, induced GDNF. Remarkably, both MCF-7 cells and ER+ primary tumors appear poised for endocrine resistance via the RET signaling pathway, but lack robust RET ligand expression and only develop resistance upon expression of GDNF or other RET ligands. Highlights GDNF expression promotes endocrine resistance in MCF-7 cells. ER+ MCF-7 cells are poised for RET-mediated endocrine resistance, but lack expression of RET ligands. RET ligand expression predicts resistance to the aromatase inhibitor letrozole. GDNF regulatory network directly down-regulates ERα and indirectly up-regulates GDNF.The RET tyrosine kinase signaling pathway is involved in the development of endocrine resistant ER+ breast cancer. However, the expression of the RET receptor itself has not been directly linked to clinical cases of resistance, suggesting that additional factors are involved. We show that both ER+ endocrine resistant and sensitive breast cancers have functional RET tyrosine kinase signaling pathway, but that endocrine sensitive breast cancer cells lack RET ligands that are necessary to drive endocrine resistance. Transcription of one RET ligand, GDNF, is necessary and sufficient to confer resistance in the ER+ MCF-7 cell line. In patients, RET ligand expression predicts responsiveness to endocrine therapies and correlates with survival. Collectively, our findings show that ER+ tumor cells are poised for RET mediated endocrine resistance, expressing all components of the RET signaling pathway, but endocrine sensitive cells lack high expression of RET ligands that are necessary to initiate the resistance phenotype.

Funmap2: an R package for QTL mapping using longitudinal phenotypes

QTL mapping is a powerful tool to infer the complexity of the genetic architecture underlying phenotypic traits, and has been extended to include longitudinal traits measured at multiple temporal/spatial points. Here, we introduce the R package Funmap2 based on the functional mapping framework, which integrates biological prior knowledge into the statistical model. Specifically, the functional mapping framework is engineered to include longitudinal curves that describes the genetic effects, and the covariance matrix of the trait of interest. Funmap2 may automatically choose the type of longitudinal curve and covariance matrix by information criterion. Funmap2 is available for download at https://github.com/wzhy2000/Funmap2.

Natural Selection has Shaped Coding and Non-coding Transcription in Primate CD4+ T-cells

Transcriptional regulatory changes have been shown to contribute to phenotypic differences between species, but many questions remain about how gene expression evolves. Here we report the first comparative study of nascent transcription in primates. We used PRO-seq to map actively transcribing RNA polymerases in resting and activated CD4+ T-cells in multiple human, chimpanzee, and rhesus macaque individuals, with rodents as outgroups. This approach allowed us to directly measure active transcription separately from post-transcriptional processes. We observed general conservation in coding and non-coding transcription, punctuated by numerous differences between species, particularly at distal enhancers and non-coding RNAs. Transcription factor binding sites are a primary determinant of transcriptional differences between species. We found evidence for stabilizing selection on gene expression levels and adaptive substitutions associated with lineage-specific transcription. Finally, rates of evolutionary change are strongly correlated with long-range chromatin interactions. These observations clarify the role of primary transcription in regulatory evolution.