# Working with the RefSeq database

Load the library.

    library(refseqR)

### 0. Introduction

This vignette shows a tutorial of how I have been using `refseqR` to automate some common processes of my research. The package `refseqR` is built on top of `rentrez`, the excellent library written by David Winter to query the NCBI’s API and fetch the resulting data.

In short, `refseqR` provides summary information at three different levels:

- gene
- transcript
- protein

### 1. Gene

Given a gene symbol/name obtained from the ‘Gene’ database, the `refseqR` library enables us to retrieve the associated mRNA/transcript and protein accessions.

    GeneID <- c("LOC101512347")
    transcript <- refseq_fromGene(GeneID, sequence = "transcript")
    #> NCBI servers are busy. Please try again a bit later.
    protein <- refseq_fromGene(GeneID, sequence = "protein")
    #> NCBI servers are busy. Please try again a bit later.

The mRNA transcript identifier (id) for LOC101512347 = .
The protein identifier (id) for LOC101512347 = .

Similarly, the function is effective when utilizing gene symbols that encode for multiple transcripts.

    GeneID <- c("LOC105852298")
    transcript <- refseq_fromGene(GeneID, sequence = "transcript")
    #> NCBI servers are busy. Please try again a bit later.
    protein    <- refseq_fromGene(GeneID, sequence = "protein")
    #> NCBI servers are busy. Please try again a bit later.

The mRNA transcript ids. for LOC105852298 = .
The protein ids. for LOC105852298 = .

The function `refseq_description` returns the sequence description corresponding to a given accession. The identifier (id) can be either a transcript, protein, or Gene identifier.

    id <- c("LOC101512347")
    refseq_description(id)

It is important to note that gene symbols (e.x. “LOC105852298”) are not unique, and a single gene symbol search may map to multiple sequences. To avoid inconsistencies in function, it is highly recommended to use the actual GeneID (e.x. “105852298) as the first argument.

### 2. Transcript

Using the `rentrez` package, we can fetch data from NCBI. Here, the first 30 lines for accession “XM_004487701” :

    mrna_gb <- rentrez::entrez_fetch(db= 'nuccore', id = "XM_004487701", rettype = 'gp')
    strsplit(mrna_gb, "\n")[[1]][1:30]

The `refseq_mRNAfeat` function serves as a wrapper built on top of `entrez_summary` from the `rentrez` package, designed to extract specific features from the obtained data. Typically, my focus lies on key features like id, accession, title, update, or sequence length (bp). However, you have the flexibility to tailor the function to extract additional features of interest from the `esummary_list` object.

    transcript = c("XM_004487701", "XM_004488493", "XM_004501904")
    feat = c("caption", "moltype", "sourcedb", "slen", "title")
    refseq_mRNAfeat(transcript, feat)

Another interesting function is `refseq_RNA2protein`, which retrieves the protein accession associated with the provided mRNA.

    transcript <- "XM_004487701"
    refseq_RNA2protein(transcript)

The CDS coordinates come in handy when we want to get the fasta sequence. We sometimes do not want the 5’UTR or 3’UTR contained in the mRNA sequence and are interested just in the CDS.

The function `refseq_CDScoords` creates an `IRanges` object with the CDS coordinates from an mRNA accession. The output object is the basis for `refseq_CDSseq`, which fetches the NCBI data, uses that coordinates and returns a `DNAString` object with the CDS nucleotide sequence.

    refseq_CDScoords(transcript)
    #> IRanges object with 0 ranges and 0 metadata columns:
    #>        start       end     width
    #>    <integer> <integer> <integer>
    refseq_CDSseq(transcript)
    #> DNAStringSet object of length 0

Here, the first 500 nucleotides of the mRNA ‘XM_004487701’:

    transcript <- "XM_004487701"
    mrna_fasta = rentrez::entrez_fetch(db="nuccore", id=transcript, rettype="fasta")
    # take a look at the first 500 chars.
    cat(strwrap(substr(mrna_fasta, 1, 500)), sep="\n")
    #> >XM_004487701.3 PREDICTED: Cicer arietinum aldehyde dehydrogenase 22A1
    #> (LOC101512347), mRNA
    #> GTTACCATGTCAACAAAAACTCTCAAGTCACTTTCTATTTGAAGCCGAGAAACCTATTATCTTTATGTCA
    #> TGACAATTCCAAAATACATAACCCACATCTTTGCATGAATAGCATCACAATTCCCTAATTTTTTTATAAT
    #> ACCCCTTAATCCATTTGTGGTCTACATATCGAAGTAAACCACTACACCCCCACTTTCTCTATAGATCTGT
    #> GAGCTCGATCGCAATTTAGTTTGATTGTTACTTTATTTATTTATTAATCTCATTTTATATGTTTTCATTT
    #> TCTTCTTGGAACCGATAAAGTCGTAGTTTATTCCTTTCTCAATTTGATGAAAAGTGCAAACTTGGAAAAG
    #> AAAACAGGTTCACCTTTGAACTCAAATAAACAAGTACTACAATATCAAAACCC

Here, the first 60 nucleotides of the CDS from the mRNA ‘XM_004487701’:

    substr(toString(refseq_CDSseq(transcript)), 1, 60)
    #> [1] "ATGGCGTTTTGGTGGTCTTTGCTCGTTCTAGCATTCGCTTTCGCTATCTGCAAGTTCCTT"

As previously said, the function `refseq_description` returns the sequence description corresponding to a given accession. The identifier (id) can be either a transcript, protein, or Gene identifier.

    id <- "XM_004487701"
    refseq_description(id)

### 3. Protein

Similarly to nucleotide sequences, `refseq_protein2RNA`, retrieves the mRNA associated with the provided protein accession.

    protein <- "XP_020244413"
    refseq_protein2RNA(protein)

Two specific functions prove useful for managing protein accessions: `refseq_AAlen` offers the amino acid length of the sequence, while `refseq_mol.wt` provides the molecular weight in Daltons.

    refseq_AAlen(protein)
    refseq_AAmol_wt(protein)

The `refseq_AAseq` function, fetches the NCBI data, and returns a `DNAString` object with the amino acid sequence.

    refseq_AAseq(protein)
    #> AAStringSet object of length 0

As previously mentioned, the `refseq_description` function ultimately provides the sequence description associated with a given accession. The identifier (id) can take the form of either a transcript, protein, or Gene identifier.

    id <- "XP_020244413"
    refseq_description(id)

### 4. Concluding Remarks

The package `refseqR` contains a number of functions to programmatically automatize some common operations.

Functions to apply on GeneID accessions

- `refseq_description`
- `refseq_fromGene`

Functions to apply on transcript id. accessions

- `refseq_GeneID`
- `refseq_CDScoords`
- `refseq_CDSseq`
- `refseq_RNA2protein`

Functions to apply on protein id. accessions

- `refseq_GeneID`
- `refseq_AAseq`
- `refseq_AAmol_wt`
- `refseq_AAlen`
- `refseq_protein2RNA`

I’d really appreciate your feedback. The whole code used in this tutorial is available from my Github repository. You can contact me by email or visit my website.

Córdoba, (Spain), 2024-10-30.