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1. YeasTSS: an integrative web database of yeast transcription start sites

   https://doi.org/10.1093/database/baz048  

   McMillan, Jonathan; Lu, Zhaolian; Rodriguez, Judith S; Ahn, Tae-Hyuk; Lin, Zhenguo (January 2019, Database)

   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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2. Noncanonical transcription initiation is primarily tissue specific and epigenetically tuned in paleopolyploid plants

   https://doi.org/10.1093/plcell/koae288  

   Wang, Xutong; Duan, Jingbo; Clark, Chancelor B; Feng, Wanjie; Ma, Jianxin (November 2024, The Plant Cell)

   Abstract Alternative transcription initiation (ATI) appears to be a ubiquitous regulatory mechanism of gene expression in eukaryotes. However, the extent to which it affects the products of gene expression and how it evolves and is regulated remain unknown. Here, we report genome-wide identification and analysis of transcription start sites (TSSs) in various soybean (Glycine max) tissues using a survey of transcription initiation at promoter elements with high-throughput sequencing (STRIPE-seq). We defined 193,579 TSS clusters/regions (TSRs) in 37,911 annotated genes, with 56.5% located in canonical regulatory regions and 43.5% from start codons to 3′ untranslated regions, which were responsible for changes in open reading frames of 24,131 genes. Strikingly, 6,845 genes underwent ATI within coding sequences (CDSs). These CDS-TSRs were tissue-specific, did not have TATA-boxes typical of canonical promoters, and were embedded in nucleosome-free regions flanked by nucleosomes with enhanced levels of histone marks potentially associated with intragenic transcriptional initiation, suggesting that ATI within CDSs was epigenetically tuned and associated with tissue-specific functions. Overall, duplicated genes possessed more TSRs, exhibited lower degrees of tissue specificity, and underwent stronger purifying selection than singletons. This study highlights the significance of ATI and the genomic and epigenomic factors shaping the distribution of ATI in CDSs in a paleopolyploid eukaryote. 

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3. Computational annotation of miRNA transcription start sites

   https://doi.org/10.1093/bib/bbz178  

   Wang, Saidi; Talukder, Amlan; Cha, Mingyu; Li, Xiaoman; Hu, Haiyan (January 2020, Briefings in Bioinformatics)

   Abstract Motivation MicroRNAs (miRNAs) are small noncoding RNAs that play important roles in gene regulation and phenotype development. The identification of miRNA transcription start sites (TSSs) is critical to understand the functional roles of miRNA genes and their transcriptional regulation. Unlike protein-coding genes, miRNA TSSs are not directly detectable from conventional RNA-Seq experiments due to miRNA-specific process of biogenesis. In the past decade, large-scale genome-wide TSS-Seq and transcription activation marker profiling data have become available, based on which, many computational methods have been developed. These methods have greatly advanced genome-wide miRNA TSS annotation. Results In this study, we summarized recent computational methods and their results on miRNA TSS annotation. We collected and performed a comparative analysis of miRNA TSS annotations from 14 representative studies. We further compiled a robust set of miRNA TSSs (RSmirT) that are supported by multiple studies. Integrative genomic and epigenomic data analysis on RSmirT revealed the genomic and epigenomic features of miRNA TSSs as well as their relations to protein-coding and long non-coding genes. Contact xiaoman@mail.ucf.edu, haihu@cs.ucf.edu 

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4. A two-stream convolutional neural network for microRNA transcription start site feature integration and identification

   https://doi.org/10.1038/s41598-021-85173-x  

   Cha, Mingyu; Zheng, Hansi; Talukder, Amlan; Barham, Clayton; Li, Xiaoman; Hu, Haiyan (December 2021, Scientific Reports)

   null (Ed.)

   Abstract MicroRNAs (miRNAs) play important roles in post-transcriptional gene regulation and phenotype development. Understanding the regulation of miRNA genes is critical to understand gene regulation. One of the challenges to study miRNA gene regulation is the lack of condition-specific annotation of miRNA transcription start sites (TSSs). Unlike protein-coding genes, miRNA TSSs can be tens of thousands of nucleotides away from the precursor miRNAs and they are hard to be detected by conventional RNA-Seq experiments. A number of studies have been attempted to computationally predict miRNA TSSs. However, high-resolution condition-specific miRNA TSS prediction remains a challenging problem. Recently, deep learning models have been successfully applied to various bioinformatics problems but have not been effectively created for condition-specific miRNA TSS prediction. Here we created a two-stream deep learning model called D-miRT for computational prediction of condition-specific miRNA TSSs ( http://hulab.ucf.edu/research/projects/DmiRT/ ). D-miRT is a natural fit for the integration of low-resolution epigenetic features (DNase-Seq and histone modification data) and high-resolution sequence features. Compared with alternative computational models on different sets of training data, D-miRT outperformed all baseline models and demonstrated high accuracy for condition-specific miRNA TSS prediction tasks. Comparing with the most recent approaches on cell-specific miRNA TSS identification using cell lines that were unseen to the model training processes, D-miRT also showed superior performance. 

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5. Smar2C2: A Simple and Efficient Protocol for the Identification of Transcription Start Sites

   https://doi.org/10.1002/cpz1.705  

   Murray, Andrew; Vollmers, Christopher; Schmitz, Robert J. (March 2023, Current Protocols)

   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 generation Basic Protocol 2: RNA extraction Basic Protocol 3: cDNA synthesis Basic Protocol 4: cDNA circularization and amplification Basic Protocol 5: Library generation 

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