Abstract The transcription initiation landscape of eukaryotic genes is complex and highly dynamic. In eukaryotes, genes can generate multiple transcript variants that differ in 5′ boundaries due to usages of alternative transcription start sites (TSSs), and the abundance of transcript isoforms are highly variable. Due to a large number and complexity of the TSSs, it is not feasible to depict details of transcript initiation landscape of all genes using text-format genome annotation files. Therefore, it is necessary to provide data visualization of TSSs to represent quantitative TSS maps and the core promoters (CPs). In addition, the selection and activity of TSSs are influenced by various factors, such as transcription factors, chromatin remodeling and histone modifications. Thus, integration and visualization of functional genomic data related to these features could provide a better understanding of the gene promoter architecture and regulatory mechanism of transcription initiation. Yeast species play important roles for the research and human society, yet no database provides visualization and integration of functional genomic data in yeast. Here, we generated quantitative TSS maps for 12 important yeast species, inferred their CPs and built a public database, YeasTSS (www.yeastss.org). YeasTSS was designed as a central portal for visualization and integration of the TSS maps, CPs and functional genomic data related to transcription initiation in yeast. YeasTSS is expected to benefit the research community and public education for improving genome annotation, studies of promoter structure, regulated control of transcription initiation and inferring gene regulatory network.
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TSSr: an R package for comprehensive analyses of TSS sequencing data
Transcription initiation is regulated in a highly organized fashion to ensure proper cellular functions. Accurate identification of transcription start sites (TSSs) and quantitative characterization of transcription initiation activities are fundamental steps for studies of regulated transcriptions and core promoter structures. Several high-throughput techniques have been developed to sequence the very 5′end of RNA transcripts (TSS sequencing) on the genome scale. Bioinformatics tools are essential for processing, analysis, and visualization of TSS sequencing data. Here, we present TSSr, an R package that provides rich functions for mapping TSS and characterizations of structures and activities of core promoters based on all types of TSS sequencing data. Specifically, TSSr implements several newly developed algorithms for accurately identifying TSSs from mapped sequencing reads and inference of core promoters, which are a prerequisite for subsequent functional analyses of TSS data. Furthermore, TSSr also enables users to export various types of TSS data that can be visualized by genome browser for inspection of promoter activities in association with other genomic features, and to generate publication-ready TSS graphs. These user-friendly features could greatly facilitate studies of transcription initiation based on TSS sequencing data. The source code and detailed documentations of TSSr can be freely accessed at https://github.com/Linlab-slu/TSSr.
more » « less- Award ID(s):
- 1951332
- NSF-PAR ID:
- 10307831
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- NAR Genomics and Bioinformatics
- Volume:
- 3
- Issue:
- 4
- ISSN:
- 2631-9268
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Promoters and the noncoding sequences that drive their function are fundamental aspects of genes that are critical to their regulation. The transcription preinitiation complex binds and assembles on promoters where it facilitates transcription. The transcription start site (TSS) is located downstream of the promoter sequence and is defined as the location in the genome where polymerase begins transcribing DNA into RNA. Knowing the location of TSSs is useful for annotation of genes, identification of non‐coding sequences important to gene regulation, detection of alternative TSSs, and understanding of 5′ UTR content. Several existing techniques make it possible to accurately identify TSSs, but are often difficult to perform experimentally, require large amounts of input RNA, or are unable to identify a large number of TSSs from a single sample. Many of these protocols take advantage of template switching reverse transcriptases (TSRTs), which reliably place an adaptor at the 5′ end of a first strand synthesis of cDNA. Here, we introduce a protocol that exploits TSRT activity combined with rolling circle amplification to identify TSSs with several unique advantages over existing methods. Sequence adaptors are placed on the 5′ and 3′ end of the full‐length cDNA copy of a transcript. A splint compatible with those adaptors is then used to circularize the full‐length cDNA. Linear DNA containing concatemers of the cDNA are generated using rolling circle amplification, and a sequencing library is formed by fragmenting the concatemers. This protocol is straightforward to execute, requiring limited bench time with relatively stable reagents. Using extremely low amounts of RNA input, this protocol produces large numbers of accurate, deduplicated TSSs genome wide. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.
Basic Protocol 1 : Splint generationBasic Protocol 2 : RNA extractionBasic Protocol 3 : cDNA synthesisBasic Protocol 4 : cDNA circularization and amplificationBasic Protocol 5 : Library generation -
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