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Related Concept Videos

The Eukaryotic Promoter Region02:40

The Eukaryotic Promoter Region

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The eukaryotic promoter region is a segment of DNA located upstream of a gene. It contains an RNA polymerase binding site, a transcription start site, and several cis-regulatory sequences.  The proximal promoter region is located in the vicinity of the gene and has cis-regulatory sequences and the core promoter. The core promoter is the binding site for RNA polymerase and is usually located between -35 and +35 nucleotides from the transcription start site. The distal promoter regions are...
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Initiation is the first step of transcription in eukaryotes. Prokaryotic RNA Polymerase (RNAP) can bind to the template DNA and start transcribing. On the other hand, transcription in eukaryotes requires additional proteins, called transcription factors, to first bind to the promoter region in the DNA template. This binding helps recruit the specific RNAP that can assemble on the DNA and start transcription.
The promoters and enhancers and their accessory proteins allow tight regulation of...
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Reporter Genes02:11

Reporter Genes

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Reporter genes are a type of protein-coding gene that are often tagged to a gene of interest. Once inside a target cell, reporter genes usually produce visually identifiable characteristics like fluorescence and luminescence when expressed along with the gene of interest. Thus, reporter genes “report” the presence or absence of genes of interest in an organism, determine the gene expression pattern, or track the physical location of a DNA segment or protein in the cell.
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Ribosome Profiling02:24

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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LTR retrotransposons are class I transposable elements with long terminal repeats flanking an internal coding region. These elements are less abundant in mammals compared to other class I transposable elements. About 8 percent of human genomic DNA comprises LTR retrotransposons. Some of the common examples of LTR retrotransposons are Ty elements in yeast and Copia elements in Drosophila.
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Related Experiment Video

Updated: Aug 26, 2025

RNA Next-Generation Sequencing and a Bioinformatics Pipeline to Identify Expressed LINE-1s at the Locus-Specific Level
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iPromoter-Seqvec: identifying promoters using bidirectional long short-term memory and sequence-embedded features.

Thanh-Hoang Nguyen-Vo1, Quang H Trinh2, Loc Nguyen1

  • 1School of Mathematics and Statistics, Victoria University of Wellington, Gate 7, Kelburn Parade, 6140, Wellington, New Zealand.

BMC Genomics
|October 3, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces iPromoter-Seqvec, an advanced computational model for accurately predicting TATA and non-TATA promoters in human and mouse genomes. The model demonstrates superior performance, aiding in gene discovery and molecular genetics research.

Keywords:
Bidirectional long short-term memoryDNAPromoterTATA-boxTranscription start site

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Promoters are crucial non-coding DNA sequences regulating gene transcription.
  • Accurate identification of promoters is vital for understanding gene structure and function.
  • Computational methods offer efficient alternatives to experimental techniques for promoter prediction.

Purpose of the Study:

  • To develop an efficient computational model, iPromoter-Seqvec, for predicting TATA and non-TATA promoters.
  • To utilize deep learning with sequence-embedded features for enhanced promoter prediction accuracy.
  • To provide a robust tool for researchers in human and mouse genomics.

Main Methods:

  • Employed bidirectional long short-term memory (BiLSTM) neural networks.
  • Integrated sequence-embedded features extracted from DNA sequences.
  • Constructed artificial non-promoter sequences to improve model specificity.
  • Utilized benchmark datasets from the Eukaryotic Promoter database.

Main Results:

  • iPromoter-Seqvec achieved high performance, with AUCROC values from 0.85 to 0.99 and AUCPR values from 0.86 to 0.99 on independent test sets.
  • The model demonstrated superior performance compared to existing state-of-the-art methods.
  • Predictive accuracy for TATA promoters was slightly higher than for non-TATA promoters in both species.

Conclusions:

  • iPromoter-Seqvec is a stable and robust tool for predicting TATA and non-TATA promoters in human and mouse genomes.
  • The developed model has been deployed as a user-friendly online web server.
  • Source code and web server access are provided to support the research community.