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Ribosome profiling (Ribo-seq) Analysis

Ribosome profiling (Ribo-seq) Analysis Online Inquiry

CD Genomics is a bioinformatics data analysis provider. Our team is experienced Ribo-seq Data Analysis and our high-quality data analysis platform will be used to generate high-quality analysis results in a fast analysis cycle.

Introduction

Ribosome profiling sequencing (Ribo-seq) is a technology based on high-throughput sequencing to detect genome-wide RNA translation (Ingolia, Ghaemmaghami, Newman, & Weissman, 2009). Ribo-seq is also the current mainstream method for the study of translation of RNA to protein. The specific method is to treat ribosomal-nascent peptide complexes with low concentration of RNase, degrade the RNA fragments without ribosomal coverage, and then remove the ribosome. Finally, a small fragment of about ~30 bp of translating RNA protected by ribosomes was detected by next-generation sequencing technology. These protected RNA fragments accurately indicate the "footprints" of the ribosome in translation. Therefore, these protected RNA fragments are also called ribosome footprints (RFs).

Ribosome profiling sequencing (Ribo-seq) workflowFig. 1 Ribosome profiling sequencing (Ribo-seq) workflow

Application Field

Medicine: disease mechanism research, disease marker discovery, drug target screening

Plants: stress resistance mechanism, growth and development mechanism, breeding protection research, etc.

Animal husbandry: quality research, animal nutrition, breed breeding, etc.

Food environment: storage and processing conditions optimization, quality identification, food nutrition

CD Genomics Data Analysis Pipeline

CD Genomics Data Analysis Pipeline

Bioinformatics Analysis Content

  • Ribo-seq data analysis
    Reads filtering
    Reference genome alignment
    Three nucleotide periodicity analysis
    Alignment with Codon distribution analysis
    Pause sites analysis
    Quantification of gene abundance
  • Sample relationship analysis
    Correlation Analysis of Replicas
    Principal Component Analysis
  • Differentially translated genes (DTGs) analysis
  • GO Enrichment Analysis
  • ORF identification
  • Translation quantification for ORF
  • Differentially translated (DT) ORFs analysis
  • Evaluation of Coding potential of non-canonical ORFs
  • Sequence features analysis
  • The influence of the uORFs upon the mORFs
  • sORF annotation

How It Works

How It Works

Table 1 Partial software and database list

Software or database Uses
fastp Low quality Reads filtering
STAR Reference genome alignment
riboWaltz R package Three nucleotide periodicity analysis
PausePred Pause sites analysis
RSEM Quantification of gene abundance

1. What is ORF?

The key to Ribo-seq is to find ORF (Open Reading Frame), just like RNA-seq to identify mRNA/IncRNA & circRNA. An ORF is a continuous stretch of codons that begins with a start codon (usually AUG) and ends at a stop codon (usually UAA, UAG or UGA).

2. What are the difficulties of ribosomal sequencing?

  • The experimental rRNA residue is high
  • The short Ribosome footprints makes it difficult to identify the real ORF

3. Scientific questions to which Ribo-seq addresses.

  • First, it can be applied to the mechanism of translation inquiry. Attention should be paid to which of the genes being translated are being translated efficiently, and which elements regulate the efficiency of translation.
  • Second, transcriptome analysis can be deepened. Focus on which of the differentially expressed genes are being translated and how efficiently they are translated. Narrow down the range of differentially expressed genes and focus only on genes that are being translated.
  • Third, it can be used to explain the inconsistency between transcriptome and proteome results. When gene transcription is not translated, or translated inefficiently, it may occur that the transcriptome shows a difference or significant difference, while the proteome shows no difference or insignificant difference.

Reference

  1. Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S., & Weissman, J. S. (2009). Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling. Science, 324(5924), 218-223. doi:10.1126/science.1168978
* For Research Use Only. Not for use in diagnostic procedures.
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