KAS-Analyzer: an integrated toolkit for exploring KAS-seq data
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA834084 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19034700.fastq.gz | Fastqsanger.gz | |||
| SRR19034701.fastq.gz | Fastqsanger.gz | |||
| SRR19034702.fastq.gz | Fastqsanger.gz | |||
| SRR19034703.fastq.gz | Fastqsanger.gz | |||
| SRR19034704.fastq.gz | Fastqsanger.gz |
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Project description:Kethoxal-assisted ssDNA sequencing (KAS-seq) is gaining popularity as a robust and effective approach to study the dynamics of transcriptionally engaged RNA polymerases through profiling of genome-wide single-stranded DNA (ssDNA). Its latest variant, spKAS-seq, a strand-specific version of KAS-seq, has been developed to map genome-wide R-loop structures by detecting imbalances of ssDNA on two strands. However, user-friendly, open-source, and specific bioinformatic analyzer for KAS-seq data are still lacking. Here we present KAS-Analyzer as a flexible and integrated toolkit to facilitate the analysis and interpretation of KAS-seq data. KAS-Analyzer can perform standard analyses such as quality control, read alignment, and differential RNA polymerase activity analysis. In addition, KAS-Analyzer introduces many novel features, including, but not limited to: calculation of transcriptional indexes, identification of single-stranded transcribing enhancers, and high-resolution mapping of R-loops. We use benchmark datasets to demonstrate that KAS-Analyzer provides a powerful framework to study transient transcriptional regulatory programs. KAS-Analyzer is available at https://github.com/Ruitulyu/KAS-Analyzer.
2022-07-27 | GSE202044 | GEO
Project description:MotivationKethoxal-assisted ssDNA sequencing (KAS-seq) is rapidly gaining popularity as a robust and effective approach to study the nascent dynamics of transcriptionally engaged RNA polymerases through profiling of genome-wide single-stranded DNA (ssDNA). Its latest variant, spKAS-seq, a strand-specific version of KAS-seq, has been developed to map genome-wide R-loop structures by detecting imbalances of ssDNA on two strands. However, user-friendly, open-source computational tools tailored for KAS-seq data are still lacking.ResultsHere, we introduce KAS-Analyzer, the first comprehensive computational framework aimed at streamlining and enhancing the analysis and interpretation of KAS-seq and spKAS-seq data. In addition to standard analyses, KAS-Analyzer offers many novel tools specifically designed for KAS-seq data, including, but not limited to: calculation of transcription-related metrics, identification of single-stranded transcribing (SST) enhancers, high-resolution mapping of R-loops, and differential RNA polymerase activity analysis. We provided a detailed overview of KAS-seq data and its diverse applications through the implementation of KAS-Analyzer. Using the example time-course KAS-seq datasets, we further showcase the robust capabilities of KAS-Analyzer for investigating dynamic transcriptional regulatory programs in response to UVB radiation.Availability and implementationKAS-Analyzer is available at https://github.com/Ruitulyu/KAS-Analyzer.
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Project description:Cis-regulatory elements (CREs) are pivotal in orchestrating gene expression throughout diverse biological systems. Accurate identification and in-depth characterization of functional CREs are crucial for decoding gene regulation network and dynamics during cellular processes. In this study, we developed a new KAS-seq (Opti-KAS-seq) procedure, with enhanced efficiency of capturing single-stranded DNA (ssDNA), broader genomic coverage, and adaptability to various sample types. By integrating the highly sensitive Opti-KAS-seq with ATAC-seq, we further introduce KAS-ATAC-seq, a new method that provides quantitative insights into transcriptional activity of CREs. A main advantage of KAS-ATAC-seq lies in its precise measurement of ssDNA levels within both proximal and distal ATAC-seq peaks. This feature is particularly adept at identifying ssDNA promoter and Single-Stranded Transcribing Enhancers (SSTEs). SSTEs are highly enriched with nascent RNA transcripts and specific transcription factors (TFs) binding sites that determine cellular identity. Moreover, KAS-ATAC-seq provides a detailed characterization and functional implications of various SSTE subtypes; KAS-ATAC-seq signals exhibit more robust correlation with enhancer activities when compared with ATAC-seq data and active histone mark profiles. Our analysis of promoters and SSTEs during mouse neural differentiation demonstrates that KAS-ATAC-seq can effectively identify immediate-early activated CREs in response to RA treatment. We further discovered that ETS TFs and YY1 are critical in initiating early neural differentiation from mESCs to NPCs. Our findings indicate that KAS-ATAC-seq provides more precise annotation of functional CREs in transcription. Future applications of KAS-ATAC-seq would help elucidate the intricate dynamics of gene regulation in diverse biological processes and biomedical applications.
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Project description:Cis-regulatory elements (CREs) are pivotal in orchestrating gene expression throughout diverse biological systems. Accurate identification and in-depth characterization of functional CREs are crucial for decoding gene regulation network and dynamics during cellular processes. In this study, we developed a new KAS-seq (Opti-KAS-seq) procedure, with enhanced efficiency of capturing single-stranded DNA (ssDNA), broader genomic coverage, and adaptability to various sample types. By integrating the highly sensitive Opti-KAS-seq with ATAC-seq, we further introduce KAS-ATAC-seq, a new method that provides quantitative insights into transcriptional activity of CREs. A main advantage of KAS-ATAC-seq lies in its precise measurement of ssDNA levels within both proximal and distal ATAC-seq peaks. This feature is particularly adept at identifying ssDNA promoter and Single-Stranded Transcribing Enhancers (SSTEs). SSTEs are highly enriched with nascent RNA transcripts and specific transcription factors (TFs) binding sites that determine cellular identity. Moreover, KAS-ATAC-seq provides a detailed characterization and functional implications of various SSTE subtypes; KAS-ATAC-seq signals exhibit more robust correlation with enhancer activities when compared with ATAC-seq data and active histone mark profiles. Our analysis of promoters and SSTEs during mouse neural differentiation demonstrates that KAS-ATAC-seq can effectively identify immediate-early activated CREs in response to RA treatment. We further discovered that ETS TFs and YY1 are critical in initiating early neural differentiation from mESCs to NPCs. Our findings indicate that KAS-ATAC-seq provides more precise annotation of functional CREs in transcription. Future applications of KAS-ATAC-seq would help elucidate the intricate dynamics of gene regulation in diverse biological processes and biomedical applications.
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Project description:Cis-regulatory elements (CREs) are pivotal in orchestrating gene expression throughout diverse biological systems. Accurate identification and in-depth characterization of functional CREs are crucial for decoding gene regulation network and dynamics during cellular processes. In this study, we developed a new KAS-seq (Opti-KAS-seq) procedure, with enhanced efficiency of capturing single-stranded DNA (ssDNA), broader genomic coverage, and adaptability to various sample types. By integrating the highly sensitive Opti-KAS-seq with ATAC-seq, we further introduce KAS-ATAC-seq, a new method that provides quantitative insights into transcriptional activity of CREs. A main advantage of KAS-ATAC-seq lies in its precise measurement of ssDNA levels within both proximal and distal ATAC-seq peaks. This feature is particularly adept at identifying ssDNA promoter and Single-Stranded Transcribing Enhancers (SSTEs). SSTEs are highly enriched with nascent RNA transcripts and specific transcription factors (TFs) binding sites that determine cellular identity. Moreover, KAS-ATAC-seq provides a detailed characterization and functional implications of various SSTE subtypes; KAS-ATAC-seq signals exhibit more robust correlation with enhancer activities when compared with ATAC-seq data and active histone mark profiles. Our analysis of promoters and SSTEs during mouse neural differentiation demonstrates that KAS-ATAC-seq can effectively identify immediate-early activated CREs in response to RA treatment. We further discovered that ETS TFs and YY1 are critical in initiating early neural differentiation from mESCs to NPCs. Our findings indicate that KAS-ATAC-seq provides more precise annotation of functional CREs in transcription. Future applications of KAS-ATAC-seq would help elucidate the intricate dynamics of gene regulation in diverse biological processes and biomedical applications.
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Project description:Cis-regulatory elements (CREs) are pivotal in orchestrating gene expression throughout diverse biological systems. Accurate identification and in-depth characterization of functional CREs are crucial for decoding gene regulation network and dynamics during cellular processes. In this study, we developed a new KAS-seq (Opti-KAS-seq) procedure, with enhanced efficiency of capturing single-stranded DNA (ssDNA), broader genomic coverage, and adaptability to various sample types. By integrating the highly sensitive Opti-KAS-seq with ATAC-seq, we further introduce KAS-ATAC-seq, a new method that provides quantitative insights into transcriptional activity of CREs. A main advantage of KAS-ATAC-seq lies in its precise measurement of ssDNA levels within both proximal and distal ATAC-seq peaks. This feature is particularly adept at identifying ssDNA promoter and Single-Stranded Transcribing Enhancers (SSTEs). SSTEs are highly enriched with nascent RNA transcripts and specific transcription factors (TFs) binding sites that determine cellular identity. Moreover, KAS-ATAC-seq provides a detailed characterization and functional implications of various SSTE subtypes; KAS-ATAC-seq signals exhibit more robust correlation with enhancer activities when compared with ATAC-seq data and active histone mark profiles. Our analysis of promoters and SSTEs during mouse neural differentiation demonstrates that KAS-ATAC-seq can effectively identify immediate-early activated CREs in response to RA treatment. We further discovered that ETS TFs and YY1 are critical in initiating early neural differentiation from mESCs to NPCs. Our findings indicate that KAS-ATAC-seq provides more precise annotation of functional CREs in transcription. Future applications of KAS-ATAC-seq would help elucidate the intricate dynamics of gene regulation in diverse biological processes and biomedical applications.
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