scholarly journals Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells

2019 ◽  
Vol 29 (3) ◽  
pp. 449-463 ◽  
Author(s):  
Emily R. Miraldi ◽  
Maria Pokrovskii ◽  
Aaron Watters ◽  
Dayanne M. Castro ◽  
Nicholas De Veaux ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Network Inference ◽  
Transcriptional Regulatory Network ◽  
Chromatin Accessibility ◽  
T Helper ◽  
T Helper 17 ◽  
T Helper 17 Cells ◽  
Transcriptional Regulatory

scholarly journals Leveraging chromatin accessibility for transcriptional regulatory network inference in T Helper 17 Cells

2018 ◽  
Author(s):  
Emily R. Miraldi ◽  
Maria Pokrovskii ◽  
Aaron Watters ◽  
Dayanne M. Castro ◽  
Nicholas De Veaux ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Network Inference ◽  
Transcriptional Regulatory Network ◽  
Indirect Evidence ◽  
T Helper ◽  
Motif Analysis ◽  
T Helper 17 ◽  
Transcriptional Regulatory

AbstractTranscriptional regulatory networks (TRNs) provide insight into cellular behavior by describing interactions between transcription factors (TFs) and their gene targets. The Assay for Transposase Accessible Chromatin (ATAC)-seq, coupled with transcription-factor motif analysis, provides indirect evidence of chromatin binding for hundreds of TFs genome-wide. Here, we propose methods for TRN inference in a mammalian setting, using ATAC-seq data to influence gene expression modeling. We rigorously test our methods in the context of T Helper Cell Type 17 (Th17) differentiation, generating new ATAC-seq data to complement existing Th17 genomic resources (plentiful gene expression data, TF knock-outs and ChIP-seq experiments). In this resource-rich mammalian setting, our extensive benchmarking provides quantitative, genome-scale evaluation of TRN inference combining ATAC-seq and RNA-seq data. We refine and extend our previous Th17 TRN, using our new TRN inference methods to integrate all Th17 data (gene expression, ATAC-seq, TF KO, ChIP-seq). We highlight newly discovered roles for individual TFs and groups of TFs (“TF-TF modules”) in Th17 gene regulation. Given the popularity of ATAC-seq, which provides high-resolution with low sample input requirements, we anticipate that application of our methods will improve TRN inference in new mammalian systems, especially in vivo, for cells directly from humans and animal models.

scholarly journals An Overview of NCA-Based Algorithms for Transcriptional Regulatory Network Inference

Microarrays ◽  
2015 ◽  
Vol 4 (4) ◽  
pp. 596-617 ◽  
Author(s):  
Xu Wang ◽  
Mustafa Alshawaqfeh ◽  
Xuan Dang ◽  
Bilal Wajid ◽  
Amina Noor ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Network Inference ◽  
Transcriptional Regulatory Network ◽  
Transcriptional Regulatory

scholarly journals Chromatin accessibility and translational landscapes of tea plants under chilling stress

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Pengjie Wang ◽  
Shan Jin ◽  
Xuejin Chen ◽  
Liangyu Wu ◽  
Yucheng Zheng ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Transcriptional Regulatory Network ◽  
Chilling Stress ◽  
Chromatin Accessibility ◽  
Open Reading Frames ◽  
Translation Efficiency ◽  
Limited Information ◽  
Transcriptional Regulatory ◽  
Tea Plants

AbstractPlants have evolved regulatory mechanisms at multiple levels to regulate gene expression in order to improve their cold adaptability. However, limited information is available regarding the stress response at the chromatin and translational levels. Here, we characterize the chromatin accessibility, transcriptional, and translational landscapes of tea plants in vivo under chilling stress for the first time. Chilling stress significantly affected both the transcription and translation levels as well as the translation efficiency of tea plants. A total of 3010 genes that underwent rapid and independent translation under chilling stress were observed, and they were significantly enriched in the photosynthesis-antenna protein and phenylpropanoid biosynthesis pathways. A set of genes that were significantly responsive to cold at the transcription and translation levels, including four (+)-neomenthol dehydrogenases (MNDs) and two (E)-nerolidol synthases (NESs) arranged in tandem on the chromosomes, were also found. We detected potential upstream open reading frames (uORFs) on 3082 genes and found that tea plants may inhibit the overall expression of genes by enhancing the translation of uORFs under chilling stress. In addition, we identified distal transposase hypersensitive sites (THSs) and proximal THSs and constructed a transcriptional regulatory network for tea plants under chilling stress. We also identified 13 high-confidence transcription factors (TFs) that may play a crucial role in cold regulation. These results provide valuable information regarding the potential transcriptional regulatory network in plants and help to clarify how plants exhibit flexible responses to chilling stress.

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