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Conversion of Ensembl Gene Ids to Uniprot Ids

Hi, I'm a computer scientist with no knowledge of biology. I'm working with protein-protein interaction and didn't understand how to make a conversion.

Usually, I use the UniProt Id conversion page to convert Ensembl Gene Ids into UniProt Entries or Ids. However, several mappings fall into the case: 1 Ensembl id I get multiple rows/UniProt entries id. My question is: how can I choose safely a unique entry? Should I filter by something like reviewed or unreviewed entries?

The same happens when I try to convert gene names to UniProt ids. I understand that a gene can make more than one protein but, for the best of my knowledge, that case should be rare, no?

Thanks in advance, I'm struggling with that.

gene software error
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updated by Kevin Blighe Kevin Blighe • written by deddu • deddu

I understand that a gene can make more than one protein but, for the best of my knowledge, that case should be rare,

No that is not the case. Here is a list of alternate spicing databases. Here is one random human genen example. Each of those transcripts can potentially form a different protein isoform.

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written by GenoMax GenoMax

1 answer

To answer the specific question and build upon Genomax's comment, you can map these via biomaRt, in R:

require('biomaRt')

mart <- useMart('ENSEMBL_MART_ENSEMBL')
mart <- useDataset('hsapiens_gene_ensembl', mart)

annotLookup <- getBM(
  mart = mart,
  attributes = c(
    'ensembl_gene_id',
    'gene_biotype',
    'external_gene_name',
    'uniprot_gn_symbol',
    'uniprot_gn_id'),
  uniqueRows=TRUE)

head(subset(annotLookup, uniprot_gn_id != ''), 20)[,-4]
   ensembl_gene_id   gene_biotype external_gene_name uniprot_gn_id
6  ENSG00000198888 protein_coding             MT-ND1        P03886
7  ENSG00000198888 protein_coding             MT-ND1        U5Z754
11 ENSG00000198763 protein_coding             MT-ND2        P03891
12 ENSG00000198763 protein_coding             MT-ND2        Q7GXY9
18 ENSG00000198804 protein_coding             MT-CO1        P00395
19 ENSG00000198804 protein_coding             MT-CO1        U5YWV7
22 ENSG00000198712 protein_coding             MT-CO2        P00403
23 ENSG00000198712 protein_coding             MT-CO2        U5Z487
25 ENSG00000228253 protein_coding            MT-ATP8        P03928
26 ENSG00000228253 protein_coding            MT-ATP8        U5YV54
27 ENSG00000198899 protein_coding            MT-ATP6        P00846
28 ENSG00000198899 protein_coding            MT-ATP6        Q0ZFE3
29 ENSG00000198938 protein_coding             MT-CO3        P00414
30 ENSG00000198938 protein_coding             MT-CO3        Q7GIM7
32 ENSG00000198840 protein_coding             MT-ND3        P03897
33 ENSG00000198840 protein_coding             MT-ND3        Q7GXZ5
35 ENSG00000212907 protein_coding            MT-ND4L        P03901
36 ENSG00000212907 protein_coding            MT-ND4L        Q7GXZ4
37 ENSG00000198886 protein_coding             MT-ND4        P03905
38 ENSG00000198886 protein_coding             MT-ND4        H9EC08

^^ here, annotLookup contains a mapping of all genes. So, you can use it as a 'master' lookup table.

You can also look up specific Ensembl gene IDs, like this:

getBM(
  mart = mart,
  attributes = c(
        'ensembl_gene_id',
        'gene_biotype',
        'external_gene_name',
        'uniprot_gn_symbol',
        'uniprot_gn_id'),
  filter = 'ensembl_gene_id',
  values = c('ENSG00000132768','ENSG00000118507',
    'ENSG00000196150','ENSG00000198077',
    'ENSG00000110717','ENSG00000109471',
    'ENSG00000206292'),
  uniqueRows = TRUE)

Kevin

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written by Kevin Blighe Kevin Blighe

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