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Suppose that you want to do local mapping of upstream regions of a given RefSeq IDs in a particular genome in R using Bioconductor. Download the script here.

In this case, you may take a look at the Bioconductor AnnotationData Packages here: http://www.bioconductor.org/packages/release/data/annotation/

The goal of this post is that for example I have the following RefSeq IDs and want to extract 250 bases upstream of each gene in a single list with another useful information such the entrez.id, the symbol and the gene description.

# RefSeqs IDs: gene.list.refseq <- c("NM_003588","NM_001145436", "NM_001135188","NM_020760","NM_173362", "NM_198393","NM_022736","NM_025074","NM_033449","NM_015726", "NM_022110","NM_016478","NM_020634","NM_002291","NM_000418", "NM_001862","NM_017752","NM_006591","NM_000124","NM_144610") # How many bases upstream of each gene:     bases.upstream <- 250

Before starting, please download the following packages in R:

       source("http://bioconductor.org/biocLite.R")        biocLite("BSgenome.Hsapiens.UCSC.hg19")                                      biocLite("Biostrings")        biocLite("org.Hs.eg.db") Load the function using:

source("extract.five.utr.sequence.R")
And finally make the computations:

output.sequences <- extract.five.utr.sequence(gene.list.refseq,bases.upstream)

CODE:

# ******************************************************************************
#       FUNCTION: extract.five.utr.sequence | 29/JULY/2012 | BENJAMIN TOVAR
# ******************************************************************************
extract.five.utr.sequence <- function(gene.list.refseq,
                                      number.bases.upstream=1000){
    
    
    # *****************************************************************
    # RUNNING NOTES: Please download this packages from Bioconductor
    # http://www.bioconductor.org/packages/release/data/annotation/
    # ***************************************************************** 
    #   source("http://bioconductor.org/biocLite.R")
    #   biocLite("BSgenome.Hsapiens.UCSC.hg19")                                
    #   biocLite("Biostrings")
    #   biocLite("org.Hs.eg.db")
                                      
    # *****************************************************************
    # RUNNING EXAMPLE
    # *****************************************************************                              
    #
    ## Extract 250 bases upstream of each gene in gene.list.refseq 
    #
    # gene.list.refseq <- c("NM_003588","NM_001145436", "NM_001135188","NM_020760","NM_173362",   
    #                    "NM_198393","NM_022736","NM_025074","NM_033449","NM_015726",   
    #                    "NM_022110","NM_016478","NM_020634","NM_002291","NM_000418",   
    #                    "NM_001862","NM_017752","NM_006591","NM_000124","NM_144610") 
    #
    # bases.upstream <- 250
    #  
    # result <- extract.five.utr.sequence(gene.list.refseq,bases.upstream)                             
                             
    # *****************************************************************
    # LOAD THE LIBRARIES
    # ***************************************************************** 
    cat("Loading libraries",date(),"\n")   
    # human genome DNA sequences
        library(BSgenome.Hsapiens.UCSC.hg19) 
    # human genome wide annotations 
        library(org.Hs.eg.db) 
    # load IDs, symbol and gene descriptions
        refseq.id <- toTable(org.Hs.egREFSEQ)
        symbol <- toTable(org.Hs.egSYMBOL)
        gene.description <- toTable(org.Hs.egGENENAME)
    
    # *****************************************************************
    # LOAD THE UPSTREAM SEQUENCES
    # *****************************************************************

    if(number.bases.upstream <= 1000){
        # load the 1000 bases upstream of all genes in the human genome 
        # in the BSgenome.Hsapiens.UCSC.hg19 package
        upstream <- Hsapiens$upstream1000
    }
    
    if(number.bases.upstream > 1000 && number.bases.upstream <= 2000){
        # load the 1000 bases upstream of all genes in the human genome 
        # in the BSgenome.Hsapiens.UCSC.hg19 package
        upstream <- Hsapiens$upstream2000
    }
    
    if(number.bases.upstream > 2000 && number.bases.upstream <= 5000){
        # load the 1000 bases upstream of all genes in the human genome 
        # in the BSgenome.Hsapiens.UCSC.hg19 package
        upstream <- Hsapiens$upstream5000
    }        
    
    if(number.bases.upstream > 5000){
        cat("ERROR: The number of bases upstream of 5'UTR is too large (max value = 5000)\n")
        return(0);
    } 
    
    if(number.bases.upstream < 1){
        cat("ERROR: The number of bases upstream of 5'UTR cannot be less than 1 nucleotide (min value = 1)\n")
        return(0);
    }                   
        
    # extract the names of each gene
    names.genes.upstream <- names(upstream)

    # extract the refseq of each gene  
    refseq.upstream.id <- vector("character",length(names.genes.upstream))
    for(i in 1:length(names.genes.upstream)){
        refseq.upstream.id[i] <- gsub(", ","_",toString(unlist(strsplit(names.genes.upstream[i],
                                      "\\_"))[c language="(1,2)"][/c],sep=""))
    }    
    names(refseq.upstream.id) <- 1:length(refseq.upstream.id)

    # *****************************************************************
    # CREATE OUTPUT OBJECT
    # *****************************************************************    
    output.params <- c("entrez.id","symbol","gene.description","five.UTR.sequence")
                        
    output.list <- list()
    for(i in 1:length(gene.list.refseq)){
        output.list[[i]] <- list()
        for(j in 1:length(output.params)){
            output.list[[i]][[j]] <- list()
        }
        names(output.list[[i]]) <- output.params
    }
    names(output.list) <- gene.list.refseq

    # *****************************************************************
    # LET THE COMPUTER DECIDE
    # *****************************************************************     
    cat("Extracting data",date(),"\n")
    
    for(i in 1:length(gene.list.refseq)){
        cat(rep(".",1))

        # extract the entrez.id of each gene in geneList 
        output.list[[i]]$entrez.id <- refseq.id[which(refseq.id$accession==gene.list.refseq[i]),]$gene_id

        # extract the symbol of each gene in geneList 
        output.list[[i]]$symbol <- symbol[which(symbol==output.list[[i]]$entrez.id),]$symbol
        
        # extract the gene description of each gene in geneList 
        output.list[[i]]$gene.description <- gene.description[which(gene.description==output.list[[i]]$entrez.id),]$gene_name  
        
        # Return the index of the target genes
        index.target.gene <- sequence <- NA;
        index.target.gene <- as.numeric(names(refseq.upstream.id[which(refseq.upstream.id==gene.list.refseq[i])]))
        
        # NOTE: some genes have repeated RefSeq.id which corresponds to the same gene in other Chromosomes.
        # by using index.target.gene[1] we are selecting only the first RefSeq entry.
        sequence <- upstream[index.target.gene[1]]
        sequence.length <- nchar(sequence)
        start.position <- ((sequence.length-number.bases.upstream)+1)
        sequence <- substring(toString(sequence),1:sequence.length,1:sequence.length)
        sequence <- sequence[start.position:sequence.length]
        output.list[[i]]$five.UTR.sequence <- sequence
    }
    cat("\n")
    cat("Computations DONE",date(),"\n")
    return(output.list)
}

Benjamin.

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