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Wang, Yurong

Publications and source records attributed to Wang, Yurong.

Combinatorial transcription factor binding encodes cis -regulatory wiring of mouse forebrain GABAergic neurogenesis

Transcription factors (TFs) bind combinatorially to cis-regulatory elements, orchestrating transcriptional programs. Although studies of chromatin state and chromosomal interactions have demonstrated dynamic neurodevelopmental cis-regulatory landscapes, parallel understanding of TF interactions lags. To elucidate combinatorial TF binding driving mouse basal ganglia development, we integrated chromatin immunoprecipitation sequencing (ChIP-seq) for twelve TFs, H3K4me3-associated enhancer-promoter interactions, chromatin and gene expression data, and functional enhancer assays. We identified sets of putative regulatory elements with shared TF binding (TF-pRE modules) that orchestrate distinct processes of GABAergic neurogenesis and suppress other cell fates. The majority of pREs were bound by one or two TFs; however, a small proportion were extensively bound. These sequences had exceptional evolutionary conservation and motif density, complex chromosomal interactions, and activity as in vivo enhancers. Our results provide insights into the combinatorial TF-pRE interactions that activate and repress expression programs during telencephalon neurogenesis and demonstrate the value of TF binding toward modeling developmental transcriptional wiring.

59 BASIC BIOLOGICAL SCIENCES↗

Two interacting ethylene response factors regulate heat stress response

Abstract The ethylene response factor (ERF) transcription factors are integral components of environmental stress signaling cascades, regulating a wide variety of downstream genes related to stress responses and plant development. However, the mechanisms by which ERF genes regulate the heat stress response are not well understood. Here, we uncover the positive role of ethylene signaling, ERF95 and ERF97 in basal thermotolerance of Arabidopsis thaliana. We demonstrate that ethylene signaling-defective mutants exhibit compromised basal thermotolerance, whereas plants with constitutively activated ethylene response show enhanced basal thermotolerance. EIN3 physically binds to the promoters of ERF95 and ERF97. Ectopic constitutive expression of ERF95 or ERF97 increases the basal thermotolerance of plants. In contrast, erf95 erf96 erf97 erf98 quadruple mutants exhibit decreased basal thermotolerance. ERF95 and ERF97 genetically function downstream of EIN3. ERF95 can physically interact with ERF97, and this interaction is heat inducible. ERF95 and ERF97 regulate a common set of target genes, including known heat-responsive genes and directly bind to the promoter of HSFA2. Thus, our study reveals that the EIN3-ERF95/ERF97-HSFA2 transcriptional cascade may play an important role in the heat stress response, thereby establishing a connection between ethylene and its downstream regulation in basal thermotolerance of plants.

Biochemistry & Molecular Biology↗

Development Context Driven Change Awareness and Analysis Framework

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, DeCAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

Sarma, Anita↗