Genomic Organization of Merkel cell polyomavirus (MCPyV)

Based on the provided image of the MCPyV (Merkel cell polyomavirus) genome, it appears that ALTO is positioned between the LT (Large T antigen) and sT (small T antigen) regions. However, it’s not entirely clear from the diagram alone if ALTO is a distinct domain within sT, or if it’s a separate gene entirely.

In the literature, the ALTO protein (A novel T antigen Open Reading Frame) of MCPyV has been described as a unique feature of the virus. While its specific function and relationship to the other T antigens (LT and sT) are still a topic of research, it is indeed distinct from the canonical LT and sT proteins.

In short, based on the diagram and typical annotations for MCPyV, ALTO does not appear to be a part of sT; rather, it’s a distinct open reading frame (ORF) or protein. However, more detailed genomic annotations and experimental studies would be needed to definitively determine its relationship with other proteins encoded by the virus.

MCPyV_genome_structure1

https://www.frontiersin.org/articles/10.3389/fmicb.2021.739695/full

MCPyV_genome_structure2

https://www.researchgate.net/publication/328072551_The_biology_and_treatment_of_Merkel_cell_carcinoma_current_understanding_and_research_priorities

JN707599.gtf

JN707599    Genbank gene    465 1190    .   +   .   gene_id "VP2"; gene_type "protein_coding"
JN707599    Genbank transcript  465 1190    .   +   .   gene_id "VP2"; transcript_id "tx-AEX86628.1"; gene_type "protein_coding"
JN707599    Genbank exon    465 1190    .   +   0   gene_id "VP2"; transcript_id "tx-AEX86628.1"; gene_type "protein_coding"
JN707599    Genbank CDS 465 1190    .   +   0   gene_id "VP2"; transcript_id "tx-AEX86628.1"; gene_type "protein_coding"
JN707599    Genbank gene    600 1190    .   +   .   gene_id "VP3"; gene_type "protein_coding"
JN707599    Genbank transcript  600 1190    .   +   .   gene_id "VP3"; transcript_id "tx-AEX86629.1"; gene_type "protein_coding"
JN707599    Genbank exon    600 1190    .   +   0   gene_id "VP3"; transcript_id "tx-AEX86629.1"; gene_type "protein_coding"
JN707599    Genbank CDS 600 1190    .   +   0   gene_id "VP3"; transcript_id "tx-AEX86629.1"; gene_type "protein_coding"
JN707599    Genbank gene    1156    2427    .   +   .   gene_id "VP1"; gene_type "protein_coding"
JN707599    Genbank transcript  1156    2427    .   +   .   gene_id "VP1"; transcript_id "tx-AEX86630.1"; gene_type "protein_coding"
JN707599    Genbank exon    1156    2427    .   +   0   gene_id "VP1"; transcript_id "tx-AEX86630.1"; gene_type "protein_coding"
JN707599    Genbank CDS 1156    2427    .   +   0   gene_id "VP1"; transcript_id "tx-AEX86630.1"; gene_type "protein_coding"
JN707599    Genbank gene    2503    5387    .   -   .   gene_id "LT"; gene_type "protein_coding"
JN707599    Genbank transcript  5154    5387    .   -   .   gene_id "LT"; transcript_id "tx1-AEX86632.1"; gene_type "protein_coding"
JN707599    Genbank exon    5154    5387    .   -   0   gene_id "LT"; transcript_id "tx1-AEX86632.1"; gene_type "protein_coding"
JN707599    Genbank CDS 5154    5387    .   -   0   gene_id "LT"; transcript_id "tx1-AEX86632.1"; gene_type "protein_coding"
JN707599    Genbank transcript  2503    4722    .   -   .   gene_id "LT"; transcript_id "tx2-AEX86632.1"; gene_type "protein_coding"
JN707599    Genbank exon    2503    4722    .   -   0   gene_id "LT"; transcript_id "tx2-AEX86632.1"; gene_type "protein_coding"
JN707599    Genbank CDS 2503    4722    .   -   0   gene_id "LT"; transcript_id "tx2-AEX86632.1"; gene_type "protein_coding"
JN707599    Genbank gene    4827    5387    .   -   .   gene_id "sT"; gene_type "protein_coding"
JN707599    Genbank transcript  4827    5387    .   -   .   gene_id "sT"; transcript_id "tx-AEX86631.1"; gene_type "protein_coding"
JN707599    Genbank exon    4827    5387    .   -   0   gene_id "sT"; transcript_id "tx-AEX86631.1"; gene_type "protein_coding"
JN707599    Genbank CDS 4827    5387    .   -   0   gene_id "sT"; transcript_id "tx-AEX86631.1"; gene_type "protein_coding"

JN707599.fasta

JN707599 CTTGTCTATATGCAGAAGGAGTTTGCAGAAAGAGCAGAGGAGCAAATGAGCTACCTCACTAAGGAGTGGT TTTTATACTGCAGTTTCCCGCCCTTGGGATCTGCCCTTAGATACTGCCTTTTTTGCTAATTAAGCCTCTT AAGCCTCAGAGGCCTCTCTCTTTTTTTTCCAGAGGCCTCGGAGGCTAGGAGCCCCAAGCCTCTGCCAACT TGAAAAAAAAAAGTCACCTAGGCAGCCAAGTTGTGGTTACATGATTGAACTTTTATTGCTGCAGGGTTTC TGGCATTGACTCATTTCCTGGAGAGGCGGAGTTTGACTGATAAACAAAACTTTTTTTCTTTCTGTTTGGG AGGGAGACGGAAGACTCTTAACTTTTTTTCAACAAGGGAGGCCCGGAGGCTTTTTTTTCTCTTACAAAGG GAGGAGGACATTAAAAGAGTAAGTATCCTTATTTATTTTTCAGGATGGGGGGCATCATCACACTGCTGGC CAATATTGGTGAAATTGCTACTGAACTAAGTGCCACCACAGGAGTAACTTTGGAAGCTATTCTTACAGGA GAAGCTTTAGCAGCTTTGGAAGCAGAGATCTCCAGTTTAATGACAATTGAGGGTATTTCTGGCATTGAGG CTTTAGCTCAACTTGGGTTCACAGCTGAACAGTTTTCAAATTTCTCATTAGTGGCTTCTTTGGTTAACCA AGGTTTAACTTATGGCTTCATTCTCCAAACTGTTAGTGGTATAGGCTCTCTAATAACTGTGGGGGTGAGG TTGTCACGCGAGCAAGTGTCACTTGTAAAGAGGGATGTTTCGTGGGTAGGTAGTAATGAGGTTTTGAGGC ATGCACTTATGGCCTTTAGCCTAGATCCTCTGCAGTGGGAAAATAGCTTGCTGCATTCTGTGGGGCAAGA TATTTTTAATTCTTTATCTCCTACCTCTAGGCTGCAGATACAATCAAACCTAGTGAATCTGATACTAAAT AGCCGGTGGGTCTTTCAGACAACTGCTTCTCAGAATCAGGGCCTTTTATCAGGAGAGGCTATATTAATTC CTGAACATATAGGAGGAACTCTGCAGCAGCAAACTCCAGATTGGCTTCTTCCTCTGGTACTAGGCCTTAG TGGATATATTTCTCCTGAATTACAAGTAATTGAAGATGGCACCAAAAAGAAAAGCATCATCCACCTGTAA AACACCCAAAAGGCAATGTATACCTAAGCCGGGATGCTGCCCTAATGTTGCCTCAGTTCCAAAACTGCTT GTTAAAGGAGGAGTGGAAGTATTATCTGTGGTTACTGGAGAAGATAGCATTACCCAAATTGAGTTGTATT TGAATCCAAGAATGGGAGTTAATTCCCCTGATCTTCCTACTACTTCAAACTGGTATACTTATACTTATGA CCTGCAGCCAAAGGGATCATCTCCAGATCAGCCCATCAAGGAAAATTTGCCAGCTTACAGTGTGGCAAGA GTGTCTCTGCCAATGCTAAATGAGGATATTACCTGTGACACATTGCAGATGTGGGAGGCAATATCTGTTA AAACAGAAGTAGTTGGAATAAGTTCTTTAATTAATGTTCATTATTGGGACATGAAAAGAGTTCATGATTA TGGTGCTGGTATTCCTGTGTCAGGGGTAAATTACCATATGTTTGCCATTGGGGGAGAACCTCTGGATTTG CAAGGCCTAGTTTTAGATTACCAGACTGAGTATCCAAAAACTACAAATGGTGGGCCTATTACAATTGAAA CTGTATTGGGAAGAAAAATGACACCTAAAAATCAGGGCCTAGATCCACAAGCTAAAGCAAAATTAGATAA AGATGGAAATTATCCTATAGAAGTATGGTGTCCTGATCCTTCTAAAAATGAAAACAGTAGATACTATGGG TCTATTCAGACAGGCTCTCAGACTCCTACAGTTCTTCAATTTAGTAATACTCTAACTACTGTCCTTTTAG ATGAGAATGGAGTGGGCCCTCTATGCAAAGGAGATGGCCTATTTATTAGCTGTGCAGACATAGTGGGGTT TCTGTTTAAAACCAGTGGAAAAATGGCTCTTCATGGGTTGCCTAGATATTTTAATGTTACTTTGAGAAAA AGATGGGTGAAAAACCCCTACCCAGTAGTTAATTTAATAAACTCACTCTTCAGCAACTTAATGCCAAAAG TGTCAGGCCAACCTATGGAAGGAAAAGATAATCAGGTAGAAGAGGTTAGAATATATGAGGGGTCAGAACA ATTACCTGGTGATCCTGATATTGTCAGATTTTTAGATAAATTTGGGCAGGAGAAAACTGTTTACCCAAAG CCCTCTGTTGCCCCAGCAGCAGTAACATTCCAAAGTAATCAGCAGGATAAGGGCAAGGCGCCACTGAAAG GACCTCAAAAGGCCTCTCAAAAAGAAAGCCAAACACAAGAATTATGAGAATTATTTCATGCATTCCTATT CAGTTAAGTAGGCCCCAGAAAAACAAACACAGGAAATATGAAGCAGATGCCTTTATTGAGAAAAAGTACC AGAATCTTGGGTTTCTTCAGTTTCCTCAGGGCCCTCTTCCTCAATAAGAATATTGAGCAGAGGGTCCTGA CCAGCTTCTACATTTTCTATCATTTGACAAAATTTACCATATGATATTTCACTCTGTAAAATTTGCTTCC AGTTTTTAATTTCTTCTTGTAAGCAAGGCTTAAAGGTTGTATCAGGCAAGCACCAAATAAGACAAAGCAA TAAAGTGGTTCCACTTTGAAGAATTCTTCTTTTTCTTATTTCCATGTTCTGATCCAGGGAATCTCTTAGA TTTGCCTTTGGGGAAAAGTGTAAAGTATAACTAAATCTTGCTATTAATGTTTTGGGAATAAAATAATCAT TAGCAGTAACAATACAAGGAGGAAAAATCTGATGCTTTTTATTCACATGCTTCTTCTCTAAGCTTACAGC TACAGCACCATCTAGATGATCTCTTAAGTTATCAAGGTTATTTATTCCTTGCCCTGGTTGCAGATCTTTA TTTAGGCTATTTTGCCCTTTCACATCCTCAAAAACAACCATAAATTTATCCAAAGCACATCCTAGTTCAA AAGGCAGTTTATCAGATGGACAGTTTATATTCAAGGCCTTCCCTTCTAGCAAATCTATTAAGGCTGCAGC AAAGCTTGTTTTTCCACTGTTAATAGGCCCTTTAAACCAAATGTTTCTATACTTAGGTATATTCTCTGTT AATAATTGAATAATTTTCTGCAGCTTCTTTTCAAACTCTTCAAATAAGCAGCAGTACCAGGCCACACCAC CCATATAATACAGTAGATCTATTGTATCTAAATCTCTTAATCTCTCTAGGTGCTTCTTAAACTTCTTACA TAGCATTTCTGTCCTGGTCATTTCCAGCATCTCTAACCTCCTTTTGGCTAGAACAGTGTCTGCGGCTTGT TGGCAAATGGTTTTCTGAGATTTAGATTCATAAAATAGCTTAGCATTAGAATGATGAGCCTCATGAGCCT TGTGAGGTTTGAGGCGAGATCTGTTTTCACACTTTTGGCAAGGAAATGGTTTTGCAAAGTCTAGATAATG GGCTAAGATAATAAAGTGGTCGTCTAGCTCATATTCACAAGCAAATTCAGCAACTAAATTCCAATTACAG CTGGCCTCTTTTTCTTTTTCTTGAAATTCATAATTGAGCAGTGGCTTATTCTCTTGCAGTAATTTGTAAG GGGGCTTGCATAAATTATTATACATTTCAGGCATCTTATTCACTCCTTTACAAATTAAAAAGCTTATAGT GCAGAAGGTAGAGCAAAAATTCTTAATAGCAGATACTCTATGCTTTGATAAAGTTATAAACAATAAAATA CATCCTAATTCACAGGCATGCCTGCTTTTAAAATCAACTTTAAATTTCTCAATCTTATCATATAACTCTA TAGCTTTATCAGAAGTAGTATAAATGGCAAAACAACTTACTGTTTTATTACTATATACAGCATGGCTAAG ATAATCAGAAAGATCAATAGGAAAATCAGTAGGAACAGGAGTTTCTCTGTTCTTTTTTGGCTTTGGTGGA GTGCTTGTAAAACTTGCTGAACTAGCAGAGCTTGCAGAGCTTCGGGACCCCCCAAATTTTCGCTTTCTTG AGAATGGAGGAGGGGTCTTCGGGGTGGTGAAGGAGGAGGATCTGTATTCCTCATCTGTAAACTGAGATGA CGAGGCCTCCTCGGCAGAGGAAGACGGGGGCTGCCGGGGCGAGCTTCTTGAGGAGGGGGGCTCCTCAGGC TCCTCAGAGGACGAGGGAGGCTCAGGGGAGGAAAGTGATTCATCGCAGAAGAGATCCTCCCAGGTGCCAT CCGTTCTGGAAGAATTTCTAGGTACACTGGTTCCATTGGGTGTGCTGGATTCTCTTCCTGAATTGGTGGT CTCCTCTCTGCTACTGGATCCAGAGGATGAGGTGGGTTCCTCATGGTGTTCGGGAGGTATATCGGGTCCT CTGGACTGGGAGTCTGAAGCCTGGGACGCTGAGAAGGACCCATACCCAGAGGAAGAGCTCTGGCTGTGGG GTGGTGAGCTTCCACTGGGGGCTCCCCTGGATGCATTGGAGGAAGGCTTTCTGGATCTTGAGTTGGTCCC GTGTGGATTGGGCCCATATTCGTATGCCTTCCCGAAGCTGAATCCTCCTGATCTCCACCATTCTTTGAAT TTAGTGGTCCCATATATAGGGGCCTCGTCAACCTAGATGGGAAAGTACAGAAAATCTGTCATAAATAACC TTTCTTTGATATTTTGCCTTATAGACTTTTCCATATCTAATACTTACAGAGGAAGGAAGTAGGAGTCTAG AAAAGGTGCAGATGCAGTAAGCAGTAGTCAGTTTCTTCTAAAGTTTTTTGCCACCAGTCAAAACTTTCCC AAGTAGGAGGAAATCCAAACCAAAGAATAAAGCACTGATAGCAAAAACACTCTCCCCACGTCAGACAGTT TTTTTGCTTTAAAGTTTTTAGACTACAATGCTGGCGAGACAACTTACAGCTAATACAAGCGCACTTAGAA TCTCTAAGTTGCTTAAGCATGCACCCAGGACCTCTGCAAAATCTAGCATTATATCCACTTTGCATATAAT CCTTTAAAGTTCCATATTCTTCCCAAGGAAATTTTGTACTGACCTCATCAAACATAGAGAAGTCACTTCT GAGCTTGTGGATATTTTGCTGGAATTTGCTCCAAAGGGTGTTCAATTCCATCATTATAACAGGATTTCCC CCTTTATCAGGGTGATGCTTTAAGCAGCTTCTTTTGAAAGCAGCTTTCATCAGAGGGATGTTGCCATAAC AATTAGGAGCAATCTCTAAAAGCTTGCAGAGAGCCTCTCTTTCTTTCCTATTTAGGACTAAATCCAT

title treatment time
untreated_DonorI untreated Day 0
untreated_DonorII untreated Day 0
p601_d3_DonorII mCherry control Day 3
p604_d3_DonorII sT Day 3
p601_d8_DonorII mCherry control Day 8
p604_d8_DonorII sT Day 8
p601_d3_DonorI mCherry control Day 3
p604_d3_DonorI sT Day 3
p601_d8_DonorI mCherry control Day 8
p604_d8_DonorI sT Day 8
p600_d3_DonorII GFP control Day 3
p605_d3_DonorII LTtr Day 3
p600_d8_DonorII GFP control Day 8
p605_d8_DonorII LTtr Day 8
p600_d3_DonorI GFP control Day 3
p605_d3_DonorI Lttr Day 3
p600_d8_DonorI GFP control Day 8
p605_d8_DonorI Lttr Day 8
p602_d8_DonorII LT Day 8
p602_d8_DonorI LT Day 8
p600and601_d12_DonorI GFP+mCherry control Day 12
p604and605_d12_DonorI sT+LTtr Day 12
p600and601_d9_DonorII GFP+mCherry control Day 9
p604and605_d9_DonorII sT+LTtr Day 9
p602_d3_DonorI LT Day 3
p602_d3_DonorII LT Day 3
p602and604_d3_DonorI sT+LT Day 3
p602and604_d3_DonorII sT+LT Day 3

PCA_3D

  • untreated

  • p602 LT *

  • p687 LT K331A *

  • p605 LTtr * (vs. p600 GFP control)

  • p604 sT

  • p602+604 LT+sT (vs. p601 mCherry control)

  • p604+p605 sT+LTtr (vs. GFP+mCherry control p601+p600)

Filtering RNA-seq analysis results and Workbook Creation with R

    # Load required libraries
    if(!requireNamespace("readxl", quietly = TRUE)) install.packages("readxl")
    if(!requireNamespace("dplyr", quietly = TRUE)) install.packages("dplyr")
    if(!requireNamespace("writexl", quietly = TRUE)) install.packages("writexl")
    if(!requireNamespace("openxlsx", quietly = TRUE)) install.packages("openxlsx")

    library(readxl)
    library(dplyr)
    library(writexl)
    library(openxlsx)

    setwd("/media/jhuang/Seagate Expansion Drive/Data_Denise_RNASeq/results_24samples/featureCounts/degenes_2021")

    # Read the data from the specific sheet
    data <- read_excel("degenes_replicates.xls", sheet = "p604_d3_vs_p601_d3-all")
    print(data, n = 10, width = Inf)

    # Filter the data
    #filtered_data <- data %>% 
    #  filter(padj < 0.05, log2FoldChange >= 2)

    upregulated_genes <- data %>%
      filter(padj < 0.05, log2FoldChange >= 2)
    dim(upregulated_genes)

    downregulated_genes <- data %>%
      filter(padj < 0.05, log2FoldChange <= -2)
    dim(downregulated_genes)

    # Create a new Excel workbook
    wb <- createWorkbook()

    # Add sheets with data
    addWorksheet(wb, "Up-regulated")
    writeData(wb, "Up-regulated", upregulated_genes)

    addWorksheet(wb, "Down-regulated")
    writeData(wb, "Down-regulated", downregulated_genes)

    # Save the workbook
    saveWorkbook(wb, "sT_d3_up_and_down.xlsx", overwrite = TRUE)

    data <- read_excel("p604_vs_p601_d8.xls", sheet = "p604_d8_vs_p601_d8-all")
    print(data, n = 10, width = Inf)

    upregulated_genes <- data %>%
      filter(padj < 0.05, log2FoldChange >= 2)
    dim(upregulated_genes)

    downregulated_genes <- data %>%
      filter(padj < 0.05, log2FoldChange <= -2)
    dim(downregulated_genes)

    # Create a new Excel workbook
    wb2 <- createWorkbook()

    # Add sheets with data
    addWorksheet(wb2, "Up-regulated")
    writeData(wb2, "Up-regulated", upregulated_genes)

    addWorksheet(wb2, "Down-regulated")
    writeData(wb2, "Down-regulated", downregulated_genes)

    # Save the workbook
    saveWorkbook(wb2, "sT_d8_up_and_down.xlsx", overwrite = TRUE)

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