RPL8 Human

What is RPL8 and what is its primary function in human cells?

RPL8, also known as uL2, is a critical component of the 60S large ribosomal subunit in human cells. Its primary role involves supporting ribosome assembly and participating in protein synthesis machinery . The protein is encoded by the RPL8 gene and has been evolutionarily conserved across species, highlighting its fundamental importance to cellular function.

While its canonical role centers on translation, recent research has revealed that RPL8, like other ribosomal proteins, possesses important extraribosomal functions including involvement in cell apoptosis and other biological processes . These non-canonical functions expand our understanding of RPL8 beyond simple structural roles in ribosomes.

For researchers investigating RPL8's basic functions, methods typically include:

• Ribosome profiling to understand translation dynamics

• Polysome analysis to assess ribosome assembly

• Structural approaches (cryo-EM, X-ray crystallography) to determine positioning and interactions within ribosomes

• Functional studies using knockout/knockdown approaches to assess essential roles

What techniques are commonly used to detect and quantify RPL8 in human samples?

Multiple established methodologies exist for RPL8 detection and quantification in research contexts:

Protein-level detection methods:

• Western blotting: Standard approach used to validate RPL8 overexpression in experimental systems, requiring careful antibody selection and optimization

• Immunohistochemistry/Immunofluorescence: For visualizing RPL8 distribution in tissues or cells

• ELISA: Commercial kits specific for human RPL8 enable precise quantification in various sample types

Transcript-level detection methods:

• RT-qPCR: Used to measure RPL8 mRNA expression with high sensitivity. In published studies, this method successfully confirmed significant RPL8 overexpression (p < 0.001) with GAPDH serving as a reference housekeeping gene

• RNA-seq: Enables genome-wide analysis of RPL8 expression alongside thousands of other transcripts

Genetic analysis methods:

• DNA sequencing: For identifying RPL8 variants or mutations, as demonstrated in studies of Diamond-Blackfan anemia patients

When designing experiments targeting RPL8, researchers should consider sample type, expected expression levels, and the specific research question when selecting appropriate detection methods.

What is the role of RPL8 in Diamond-Blackfan anemia pathogenesis?

Diamond-Blackfan anemia (DBA) is a rare genetic disease characterized by erythroblastopenia and developmental abnormalities. Recent research has established RPL8 as an important gene in DBA pathogenesis:

Functional studies have identified missense variants in RPL8 associated with both Diamond-Blackfan anemia and DBA-like phenotypes . While RPL8 had previously been proposed as a candidate DBA gene based on computational predictions, recent experimental evidence provides stronger support for its causative role.

Using both lymphoblastoid cell models and yeast systems, researchers demonstrated that RPL8 variants detected in DBA patients encode functionally deficient proteins that significantly impair ribosome production . This aligns with the broader understanding of DBA as a ribosomopathy, where defects in ribosomal proteins lead to specific clinical manifestations.

The methodological approaches for investigating RPL8's role in DBA include:

• Genetic screening of DBA patients to identify RPL8 variants

• Functional characterization in patient-derived lymphoblastoid cells

• Complementary studies in yeast models expressing human RPL8 variants

• Ribosome assembly and production assays to quantify variant impact

Based on accumulated evidence, researchers have proposed including RPL8 in the list of DBA-associated genes , emphasizing the importance of comprehensive functional validation when assessing the pathogenicity of variants in ribosomal protein genes.

How does RPL8 regulate alternative splicing events in human cells?

Research has revealed an unexpected role for RPL8 in regulating alternative splicing events (ASEs) in human cells, representing a significant extraribosomal function with implications for various cellular processes:

When RPL8 was overexpressed in HeLa cells, transcriptome analysis identified 20,663 annotated alternative splicing events regulated by RPL8, accounting for approximately 25.42% of the total genome . This finding suggests RPL8 has broad effects on RNA processing beyond its canonical ribosomal roles.

The methodology for identifying and validating RPL8-regulated alternative splicing events (RASEs) involves:

• RNA-seq analysis of control versus RPL8-overexpressing cells

• Alignment of uniquely mapped reads to annotated exons

• Classification of splice sites using specialized software (e.g., TopHat2)

• Detection of alternative splicing events using tools like ABLas

• Validation of selected events by RT-qPCR with isoform-specific primers

Multiple types of alternative splicing events were found to be regulated by RPL8, including:

• Cassette exon events (e.g., in TBX3 and MBNL3)

• Exon skipping events (e.g., in CASP3)

• Alternative 5' splice site usage (e.g., in SEPT2)

Notably, many genes subject to RPL8-regulated alternative splicing are involved in cancer-related pathways, including apoptosis-related genes CASP3, VHL, MYD88, RAF1, CAMK1D, and UBA52 . The validation experiments showed high consistency between RT-qPCR results and RNA-seq findings, confirming RPL8's ability to regulate alternative splicing patterns .

What is the significance of RPL8 in cancer biology and what mechanisms underlie its effects?

RPL8 demonstrates significant relevance to cancer biology through several mechanisms that extend beyond its canonical ribosomal function:

Cellular effects:

Research has shown that RPL8 overexpression in HeLa cells inhibits cell proliferation and promotes apoptosis , suggesting potential tumor-suppressive activity in certain contexts. Clinical observations indicate that patients with lower RPL8 expression may have different outcomes compared to those with higher expression levels .

Molecular mechanisms underlying RPL8's cancer-related functions:

• Transcriptional regulation: RPL8 modulates the expression of numerous oncogenic genes, as revealed by transcriptome analysis of RPL8-overexpressing cells

• Alternative splicing regulation: RPL8 regulates alternative splicing events in cancer-related genes , with many RPL8-regulated alternative splicing genes (RASGs) enriched in tumorigenesis pathways

• Pathway modulation: Functional enrichment analysis identified RPL8-regulated genes associated with multiple cancer-related processes including:

  • Angiogenesis

  • Inflammation

  • Cell proliferation regulation

  • Apoptosis regulation

• Transcription factor regulation: RPL8 may influence cancer-related gene expression by modulating the alternative splicing of transcription factors . Analysis using specialized tools identified transcription factors among RPL8-regulated genes, with enriched motifs in the promoter regions of differentially expressed genes.

Experimental approaches for investigating RPL8 in cancer contexts include:

• Cell proliferation assays (e.g., MTT assay)

• Flow cytometry for apoptosis detection

• Transcriptome sequencing and bioinformatic analysis

• RT-qPCR validation of gene expression and splicing changes

These findings suggest that RPL8 affects cancer cell phenotypes by altering transcriptome profiles at both expression and splicing levels , providing novel insights into its potential as a therapeutic target or biomarker.

What computational approaches can be used to analyze RPL8-related transcriptomic data?

Several sophisticated computational approaches have been employed to analyze RPL8-related transcriptomic data, providing a methodological framework for researchers in this field:

RNA-seq data processing and analysis:

• Quality control and alignment:

  • Filtering raw reads and aligning to the human genome (GRCH38)

  • Normalization for mRNA length and sequencing depth

  • Principal component analysis (PCA) to visualize sample clustering

• Differential expression analysis:

  • Identification of differentially expressed genes between RPL8-overexpressing and control samples

  • Statistical testing to determine significance of expression changes

Alternative splicing analysis:

• Identification of splice sites and events:

  • Extraction of uniquely mapped reads and matching to annotated exons

  • Classification of splice sites using TopHat2

  • Detection of alternative splicing events using ABLas

• Visualization and validation:

  • IGV-sashimi plots to visualize splicing patterns

  • Design of isoform-specific primers for RT-qPCR validation

Functional enrichment analysis:

• Pathway and Gene Ontology assessment:

  • KOBAS 2.0 server for identifying enriched biological process terms

  • Hypergeometric testing with Benjamini-Hochberg FDR control

  • Identification of cancer-related pathways enriched among RPL8-regulated genes

Motif analysis:

• Regulatory element identification:

  • HOMER software for motif detection in promoter regions of RPL8-regulated genes

  • TFBSTools to identify transcription factor motifs in alternatively spliced genes

  • JASPAR2020 database analysis for transcription factor binding site prediction

These approaches provide a comprehensive framework for analyzing how RPL8 affects the transcriptome. Integration of differential expression analysis with alternative splicing assessment offers powerful insights into RPL8's complex regulatory roles beyond its canonical function.

How can researchers effectively model RPL8 dysfunction in experimental systems?

Based on published research, several effective approaches can be employed to model RPL8 dysfunction:

Cell culture models:

• Overexpression systems:

  • Design of expression constructs (e.g., in pIRES-hrGFP-1a vector)

  • Transfection into appropriate cell lines (HeLa cells have been successfully used)

  • Confirmation of overexpression by RT-qPCR and Western blot

• Knockdown/knockout approaches:

  • siRNA or shRNA targeting RPL8

  • CRISPR-Cas9 mediated gene editing

  • Inducible expression systems for temporal control

Disease-specific models:

• Patient-derived cell models: Lymphoblastoid cells have been used to functionally characterize RPL8 variants identified in Diamond-Blackfan anemia patients

• Yeast models: Expression of human RPL8 variants in yeast provides a simplified system for studying functional consequences

Functional assays for phenotypic evaluation:

• Proliferation analysis: MTT assay to detect changes upon RPL8 manipulation

• Apoptosis assessment: Flow cytometry to measure cell death

• Transcriptome analysis: RNA-seq to identify expression and splicing changes

• Ribosome production assays: To evaluate impact on ribosome assembly

Validation approaches:

• RT-qPCR validation of gene expression and splicing changes

• Western blotting to confirm protein expression

• Statistical analysis: t-tests to assess differences between experimental groups

When designing RPL8 dysfunction models, researchers should consider:

• Cell type specificity (different cell types may respond differently)

• Degree of RPL8 modulation (complete knockout may be lethal)

• Appropriate controls to distinguish between translation effects versus specific extraribosomal functions

• Time-course experiments to capture both immediate and adaptive responses

How do mutations in RPL8 affect ribosome assembly and function?

Mutations in RPL8 can significantly impact ribosome assembly and function, with important implications for human disease:

Research has demonstrated that missense variants in RPL8 identified in Diamond-Blackfan anemia patients encode functionally deficient proteins that impair ribosome production . As RPL8 (uL2) is a component of the 60S large ribosomal subunit, mutations can disrupt structural integrity and assembly pathways.

While the specific molecular mechanisms aren't fully detailed in the current research, RPL8 mutations likely affect ribosome biology through:

• Disruption of protein-rRNA interactions

• Impaired incorporation into pre-ribosomal particles

• Defective ribosomal RNA processing or maturation

• Destabilization of 60S subunit structure

• Altered translation efficiency or fidelity

Methodological approaches for studying these effects include:

Ribosome profiling and analysis:

• Polysome profiling to assess assembly defects

• Sucrose gradient centrifugation to separate ribosomal subunits

• Northern blotting or RT-qPCR to analyze rRNA processing

Structural studies:

• Cryo-electron microscopy to visualize structural alterations

• Structural modeling to predict mutation impacts

Functional assays:

• In vitro translation assays to measure functional capacity

• Ribosome half-transit time measurements

• Peptidyl transferase activity assessment

Cellular response analysis:

• Evaluation of nucleolar stress responses

• Assessment of p53 activation pathways

• Cell cycle progression analysis

The established link between RPL8 variants and Diamond-Blackfan anemia demonstrates how ribosomal protein mutations can lead to specific disease phenotypes, highlighting the importance of proper ribosome assembly in cellular homeostasis and development.

How does RPL8 interact with transcription factors to regulate gene expression?

The interaction between RPL8 and transcription factors represents an important mechanism through which this ribosomal protein exerts extraribosomal regulatory functions:

Research has shown that RPL8 can influence the expression of differentially expressed genes (DEGs) by regulating the alternative splicing patterns of transcription factors (TFs) . This suggests RPL8 participates in complex regulatory networks affecting gene expression beyond its canonical role.

Experimental and computational analyses have revealed:

• Transcription factor splicing regulation: RPL8 overexpression alters alternative splicing of transcription factor genes

• Motif enrichment in regulated genes: Computational analysis using HOMER software identified enriched motifs in the promoter regions of RPL8-regulated genes, with 48 common motifs in upregulated DEGs and 70 common motifs in downregulated DEGs

• Pathway connections: Many of the transcription factors affected by RPL8-regulated alternative splicing are involved in cancer-related pathways

Methodological approaches for investigating these interactions include:

• TFBSTools analysis: Used to identify transcription factors among RPL8-regulated alternative splicing genes

• Motif analysis: Calculation of enriched motifs in promoter regions (1K, 2K, and 3K from transcription start sites)

• Integrative analysis: Connecting alternative splicing changes with differential expression patterns

The regulatory interaction between RPL8 and transcription factors may help explain how RPL8 influences multiple cancer-related pathways, including those involved in cell proliferation, apoptosis, and angiogenesis . This highlights the complex regulatory networks that extend beyond RPL8's structural role in ribosomes.

What experimental controls are essential when studying RPL8 function?

When investigating RPL8 function, implementing appropriate experimental controls is crucial for generating reliable and interpretable results:

Expression manipulation controls:

• Empty vector controls: Studies overexpressing RPL8 used appropriate vector-only controls to account for effects of transfection and vector expression

• Non-targeting controls: For knockdown experiments, non-targeting siRNA/shRNA controls should be included

• Expression validation: RPL8 expression changes were confirmed at both RNA level (RT-qPCR) and protein level (Western blot)

Experimental design considerations:

• Multiple replicates: Studies employed biological replicates (e.g., Ctrl-2, Ctrl-3, OE-2, and OE-3 samples for RNA-seq)

• Principal component analysis: Used to confirm sample clustering and separation between experimental groups

• Multiple time points: Where temporal effects may be important

Technique-specific controls:

• RNA-seq controls:

  • Normalization for mRNA length and sequencing depth

  • Reference housekeeping genes (GAPDH used in validated studies)

  • Analysis of read distribution and coverage metrics

• RT-qPCR validation:

  • Internal reference gene controls

  • Isoform-specific primers for splicing verification

  • Technical replicates

• Functional assay controls:

  • Positive controls for cell proliferation and apoptosis assays

  • Concentration gradients where appropriate

  • Time course analyses where temporal effects are expected

• Statistical validation:

  • Appropriate statistical tests (t-tests commonly used)

  • Multiple testing correction (e.g., Benjamini-Hochberg FDR)

  • Clear significance thresholds (typically p < 0.05)

For disease-related studies, additional controls may include:

• Wild-type RPL8 expression alongside mutant variants

• Patient samples matched with appropriate healthy controls

• Rescue experiments to confirm specificity of observed effects

These controls help distinguish RPL8-specific effects from experimental artifacts and ensure that findings related to RPL8 function are robust and reproducible across different experimental systems.