Similar Datasets
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.
2024-06-21 | GSE256230 | GEO
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.
2024-06-21 | GSE256231 | GEO
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.
2024-06-21 | GSE256229 | GEO
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.
2024-06-21 | GSE256228 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2020-01-08 | GSE136565 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2015-11-09 | GSE66955 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2024-04-17 | GSE239481 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-03-04 | GSE75161 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-10-29 | E-GEOD-68198 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2019-09-19 | GSE117205 | GEO