Mapping between genome, transcript and protein coordinates
8 May 2018
Package
ensembldb 2.4.1
1 Introduction
Besides retrieving genomic and protein annotations, ensembldb provides also
functionality to map between protein, transcript and genome coordinates. This
mapping relies on annotations of proteins (their sequences) to their encoding
transcripts which are stored in EnsDb databases.
The available functions and their input and result objects are:
genomeToTranscript: maps genomic coordinates to coordinates within the transcript(s) encoded at the specified coordinates. The function takes aGRangesas input and returns anIRangesListof length equal to the length of the input object. EachIRangesin theIRangesListprovides the coordinates within the respective transcript.genomeToProtein: maps genomic coordinates to positions within the sequence of the eventually encoded protein(s) in the genomic region. The function takes aGRangesas input and returns anIRangesListof the same length, each element (IRanges) providing the coordinates within the respective protein’s sequence.proteinToTranscript: maps protein-relative coordinates to positions within the encoding transcripts. Takes anIRangesas input and returns anIRangesListof the same length with each element (IRanges) providing the coordinates within the transcript (relative to the first nucleotide of the transcript).proteinToGenome: maps protein-relative coordinates to genomic region(s) encoding the amino acid sequence. The function takes anIRangesas input and returns alistof eitherGRanges(if Ensembl protein identifiers are provided in the input object) orGRangesList(if the protein identifier provided for the input range can be mapped to multiple Ensembl protein IDs).transcriptToGenome: maps coordinates within a transcript to genomic coordinates. Takes anIRangesas input and returns aGRangesList(within-transcript coordinates can be mapped to several exons and hence genomic locations). The returnedGRangesListhas the same length than the inputIRanges, with emptyGRangesfor transcripts that can not be found in the database (and thus can not be mapped to the genome).transcriptToProtein: maps regions within a transcript to the respective amino acid residues in the encoded protein’s sequence. The function takes anIRangesas input and returns anIRangesof the same length.transcriptToCds: maps between transcript-relative and CDS-relative coordinates (for protein-coding genes only).cdsToTranscript: maps between CDS-relative and transcript-relative coordinates (for protein-coding genes only).
All functions, except proteinToGenome and transcriptToGenome return IRanges with
negative coordinates if the mapping failed (e.g. because the identifier is
unknown to the database, or, for mappings to and from protein coordinates, the
input coordinates are not within the coding region of a
transcript). proteinToGenome and transcriptToGenome return empty GRanges if
mappings fail.
Each protein encoding transcript is annotated by Ensembl to an unique translation with an assigned Ensembl protein ID. In addition, Ensembl provides a mapping from Uniprot identifiers to Ensembl protein IDs. This is however in many cases one-to-many, i.e. a single Uniprot ID is assigned to multiple Ensembl protein IDs. As an additional complication, the coding region might not be complete for some transcripts and either their 3’ or 5’ ends (or both) are not defined (or can not be mapped to the genome). The length of the CDS does in such cases not match the length of the annotated protein sequence and position mappings between proteins and transcripts might hence not be correct.
The cdsToTranscript and transcriptToCds functions are helpful to enable the
mapping of variants in genes that are usually provided as positions within the
gene’s (actually transcript’s) coding sequence. An example for such a mapping is
provided in section Mapping transcript coordinates to genomic coordinates below.
Below we load all required libraries and filter the EnsDb database containing
the annotations from Ensembl release 86 to chromosome X. All genes of the
examples in this vignette are encoded on chromosome X and subsetting the EnsDb
to this chromosome speeds up all queries to the database.
library(ensembldb)
library(EnsDb.Hsapiens.v86)
edbx <- filter(EnsDb.Hsapiens.v86, filter = ~ seq_name == "X") 2 Mapping genomic coordinates to transcript-relative coordinates
Below we define a genomic region on chromosome X for which we want to identify the transcripts that are eventually encoded on that position and determine the respective coordinates of the genomic region within these (relative to their first nucleotide).
gnm <- GRanges("X:107716399-107716401") Before we map the coordinates we visualize the genomic region and all genes and transcripts overlapping it.
library(Gviz)
## Since we're using Ensembl chromosome names we have to set:
options(ucscChromosomeNames = FALSE)
## Define a genome axis track
gat <- GenomeAxisTrack(range = gnm)
## Get all genes in that region
gnm_gns <- getGeneRegionTrackForGviz(edbx, filter = GRangesFilter(gnm))
gtx <- GeneRegionTrack(gnm_gns, name = "tx", geneSymbol = TRUE, showId = TRUE)
## Generate a higlight track
ht <- HighlightTrack(trackList = list(gat, gtx), range = gnm)
## plot the region
plotTracks(list(ht))
The genomic position overlaps two transcripts of the gene TSC22D3, encoded on
the reverse strand on chromosome X. Below we map the genome position to
positions within the encoded transcripts using the genomeToTranscript function.
## Map genomic coordinates to within-transcript coordinates
gnm_tx <- genomeToTranscript(gnm, edbx) As a result we get an IRangesList object of length 1 (since we defined a single
genomic region as input). The IRanges in the first element of our result object
provides the mapped coordinates within each transcript that is encoded in the
specified genomic region.
gnm_tx ## IRangesList of length 1
## [[1]]
## IRanges object with 2 ranges and 6 metadata columns:
## start end width | exon_id exon_rank
## <integer> <integer> <integer> | <character> <integer>
## ENST00000372390 145 147 3 | ENSE00001457675 1
## ENST00000486554 1 3 3 | ENSE00001927337 1
## seq_start seq_end seq_name seq_strand
## <integer> <integer> <character> <character>
## ENST00000372390 107716399 107716401 X *
## ENST00000486554 107716399 107716401 X *In our example, the genomic region overlapped two transcripts and the
transcript-relative coordinates for both are reported. The ID of the transcripts
are reported as names of the IRanges. The original genomic coordinates are
provided as metadata columns (which can be accessed with the mcols method), as
well as the ID of the exon encoded at the genomic region and its index/rank
within the transcript.
To illustrate mapping of multiple genomic regions, we define below 2 genomic regions: twice the example region from above but once restricting to the reverse and once to the forward strand.
gnm_1 <- gnm
strand(gnm_1) <- "-"
gnm_2 <- gnm
strand(gnm_2) <- "+"
gnm <- c(gnm_1, gnm_2)
genomeToTranscript(gnm, edbx) ## Warning: 1 genomic region(s) could not be mapped to a transcript; hint: see ?
## seqlevelsStyle if you used UCSC chromosome names## IRangesList of length 2
## [[1]]
## IRanges object with 2 ranges and 6 metadata columns:
## start end width | exon_id exon_rank
## <integer> <integer> <integer> | <character> <integer>
## ENST00000372390 145 147 3 | ENSE00001457675 1
## ENST00000486554 1 3 3 | ENSE00001927337 1
## seq_start seq_end seq_name seq_strand
## <integer> <integer> <character> <character>
## ENST00000372390 107716399 107716401 X -
## ENST00000486554 107716399 107716401 X -
##
## [[2]]
## IRanges object with 1 range and 6 metadata columns:
## start end width | exon_id exon_rank seq_start seq_end
## <integer> <integer> <integer> | <character> <integer> <integer> <integer>
## -1 -1 1 | <NA> <NA> 107716399 107716401
## seq_name seq_strand
## <character> <character>
## X +The result for the first region is the same as above. The result for the second
region is an IRanges with negative coordinates, since there is no transcript
encoded on the forward strand at the genomic position.
3 Mapping genomic coordinates to protein-relative coordinates
We can use the genomeToProtein function to map genomic coordinates to
within-protein sequence coordinates. In addition to the genomeToTranscript
function, this function determines whether the transcript at the genomic
position encodes a protein, and if so, maps the genomic coordinates to
coordinates within the respective protein sequence. To this end, the
transcript-relative coordinates for the genomic region have to be located within
CDS of the transcript (excluding the stop codon, i.e. last 3 nucleotides of the
CDS, since they are not translated into an amino acid).
Below we define 4 genomic regions and map them to protein-relative coordinates: the first corresponds to the first 4 nucleotides of the CDS of ENST00000381578, the second to the last nucleotide of the CDS of the same transcript. The third region maps to the last nt before the stop codon of ENST00000381578 and the last region is located within an intron of the same transcript.
gnm <- GRanges("X", IRanges(start = c(630898, 644636, 644633, 634829),
width = c(5, 1, 1, 3)))
gnm_prt <- genomeToProtein(gnm, edbx)## Warning: 1 genomic region(s) could not be mapped to a transcript; hint: see ?
## seqlevelsStyle if you used UCSC chromosome names## Warning: Transcript(s) '' could not be found## Warning: Provided coordinates for 'ENST00000381578', 'ENST00000554971' are
## not within the coding regionThe resulting object has the length 4, one IRanges for each region in the input
GRanges. The warning messages indicate that not all of the regions could be
mapped to within-protein coordinates. We explore now the results for each input
region separately.
gnm_prt[[1]] ## IRanges object with 4 ranges and 8 metadata columns:
## start end width | tx_id cds_ok
## <integer> <integer> <integer> | <character> <logical>
## ENSP00000335505 1 2 2 | ENST00000334060 TRUE
## ENSP00000370987 1 2 2 | ENST00000381575 TRUE
## ENSP00000370990 1 2 2 | ENST00000381578 TRUE
## ENSP00000452016 1 2 2 | ENST00000554971 TRUE
## exon_id exon_rank seq_start seq_end seq_name
## <character> <integer> <integer> <integer> <character>
## ENSP00000335505 ENSE00001489177 2 630898 630902 X
## ENSP00000370987 ENSE00001489169 1 630898 630902 X
## ENSP00000370990 ENSE00001489177 2 630898 630902 X
## ENSP00000452016 ENSE00001489169 1 630898 630902 X
## seq_strand
## <character>
## ENSP00000335505 *
## ENSP00000370987 *
## ENSP00000370990 *
## ENSP00000452016 *The genomic region could be mapped to positions within the coding regions of 4
different transcripts, each of them being annotated to its own Ensembl protein
ID. The input region was mapped to the first 4 nucleotides of each transcripts’
CDS and was thus mapped to the amino acid residues 1 and 2 of the encoded
protein: the first 3 nucleotides to the first amino acid, the 4th to the second
amino acid. The encoding transcript ID, the exon ID, exon rank and the input
genomic region are provided as metadata columns in the result IRanges. A
metadata column cds_ok provides the additional information whether the length of
each transcripts’ CDS matches the length of the encoded protein sequence. This
is an important information, as not all protein coding transcripts in Ensembl
have complete CDS, either because their 3’ or their 5’ (or both) ends are
incomplete (or could not be mapped/aligned to the genome). Mappings to or from
protein coordinates with a cds_ok being FALSE might not be correct and should be
manually evaluated e.g. using the Ensembl genome browser.
The second genomic region maps to last nucleotide of the CDS of
ENST00000381578. The last 3 nucleotides of the CDS correspond to the stop codon
which is not translated. The coordinates can therefore not be mapped to the
protein sequence and an IRanges with negative start position is thus returned.
gnm_prt[[2]] ## IRanges object with 2 ranges and 8 metadata columns:
## start end width | tx_id cds_ok exon_id
## <integer> <integer> <integer> | <character> <logical> <character>
## -1 -1 1 | ENST00000381578 <NA> ENSE00001489174
## -1 -1 1 | ENST00000554971 <NA> ENSE00002438186
## exon_rank seq_start seq_end seq_name seq_strand
## <integer> <integer> <integer> <character> <character>
## 6 644636 644636 X *
## 5 644636 644636 X *The third region can be mapped to the last nucleotide before the stop codon and can thus be mapped to the last amino acid of the encoded protein.
gnm_prt[[3]] ## IRanges object with 2 ranges and 8 metadata columns:
## start end width | tx_id cds_ok
## <integer> <integer> <integer> | <character> <logical>
## ENSP00000370990 292 292 1 | ENST00000381578 TRUE
## ENSP00000452016 292 292 1 | ENST00000554971 TRUE
## exon_id exon_rank seq_start seq_end seq_name
## <character> <integer> <integer> <integer> <character>
## ENSP00000370990 ENSE00001489174 6 644633 644633 X
## ENSP00000452016 ENSE00002438186 5 644633 644633 X
## seq_strand
## <character>
## ENSP00000370990 *
## ENSP00000452016 *The region maps to coordinates within two transcripts each with their own translation. Below we retrieve the protein sequences for both protein IDs to evaluate whether it corresponds indeed to the last amino acid for the protein encoded by ENST00000381578.
prt <- proteins(edbx, filter = ProteinIdFilter(names(gnm_prt[[3]])))
nchar(prt$protein_sequence) ## [1] 292 292For both protein IDs, the mapped position corresponds to the last amino acid. In fact, the protein sequences for both are identical.
The result for the last region can, as expected, not be mapped to any
transcript-relative coordinates and hence also not to any protein. As a result,
an IRanges with negative coordinates is returned.
gnm_prt[[4]] ## IRanges object with 1 range and 8 metadata columns:
## start end width | tx_id cds_ok exon_id
## <integer> <integer> <integer> | <character> <logical> <character>
## -1 -1 1 | <NA> <NA>
## exon_rank seq_start seq_end seq_name seq_strand
## <integer> <integer> <integer> <character> <character>
## <NA> 634829 634831 X *4 Mapping protein coordinates to transcript coordinates
The proteinToTranscript method allows to map protein-sequence relative
coordinates to the encoding region in the transcript. A protein identifier and
the coordinates within the protein sequence have to be provided with an IRanges
object, the protein identifiers (ideally Ensembl protein IDs or also Uniprot
IDs) either provided as names of the object, or in one of its metadata columns.
The function will first try to find the protein identifiers in the database and,
if found, map the provided coordinates to transcript-relative positions.
In our first example we retrieve the transcript-relative coordinates of
positions 5 to 9 within the amino acid sequence of the gene GAGE10. Below we
first get the protein ID for this gene from the database and define then the
IRanges with the within-protein coordinates.
GAGE10 <- proteins(edbx, filter = ~ genename == "GAGE10")
GAGE10## DataFrame with 1 row and 4 columns
## tx_id protein_id
## <character> <character>
## 1 ENST00000407599 ENSP00000385415
## protein_sequence
## <character>
## 1 MSWRGRSTYRPRPRRYVEPPEMIGPMLPEQFSDEVEPATPEEGEPATQRQDPAAAQEGEDEGASAGQGPKPEADSQEQVHPKTGCECGDGPDGQEMGLPNPEEVKRPEEGEKQSQC
## gene_name
## <character>
## 1 GAGE10## Define the IRanges object.
GAGE10_prt <- IRanges(start = 5, end = 9, names = GAGE10$protein_id) Now we use the proteinToTranscript function to map the coordinates. The function
also compares the length of the CDS with the length of the encoded protein
sequence and, if they are not matching, returns a FALSE in the result object’s
cds_ok metadata column. In such cases (i.e. when the CDS of the transcript is
incomplete), the returned coordinates could be wrong.
GAGE10_tx <- proteinToTranscript(GAGE10_prt, edbx) The result is a list with the same length as the input IRanges, each element
representing the mapping the protein-relative coordinates to positions within
all encoding transcripts. Note that the transcript coordinates are relative to
their first nucleotide of the 5’ UTR, not of the CDS.
GAGE10_tx ## IRangesList of length 1
## $ENSP00000385415
## IRanges object with 1 range and 5 metadata columns:
## start end width | protein_id
## <integer> <integer> <integer> | <character>
## ENST00000407599 106 120 15 | ENSP00000385415
## tx_id cds_ok protein_start protein_end
## <character> <logical> <integer> <integer>
## ENST00000407599 ENST00000407599 TRUE 5 9If Ensembl protein identifiers are used, the mapping between protein- and
transcript coordinates will be 1:1. Many Uniprot identifiers are however
annotated to more than one Ensembl protein ID and the result IRanges for one
input region might thus be of length > 1. Below we define regions in protein
sequences identified by Uniprot IDs. In addition, to illustrate a failing
mapping, we add a region with an invalid ID.
ids <- c("O15266", "Q9HBJ8", "unexistant")
prt <- IRanges(start = c(13, 43, 100), end = c(21, 80, 100))
names(prt) <- ids
prt_tx <- proteinToTranscript(prt, edbx, idType = "uniprot_id") ## Warning: No CDS found for 'unexistant'The region within the first protein with a Uniprot ID can be mapped to 4 different Ensembl protein IDs and the coordinates are thus mapped to regions within 4 transcripts.
prt_tx[[1]] ## IRanges object with 4 ranges and 6 metadata columns:
## start end width | protein_id
## <integer> <integer> <integer> | <character>
## ENST00000334060 728 754 27 | ENSP00000335505
## ENST00000381575 128 154 27 | ENSP00000370987
## ENST00000381578 728 754 27 | ENSP00000370990
## ENST00000554971 128 154 27 | ENSP00000452016
## tx_id cds_ok protein_start protein_end
## <character> <logical> <integer> <integer>
## ENST00000334060 ENST00000334060 TRUE 13 21
## ENST00000381575 ENST00000381575 TRUE 13 21
## ENST00000381578 ENST00000381578 TRUE 13 21
## ENST00000554971 ENST00000554971 TRUE 13 21
## uniprot_id
## <character>
## ENST00000334060 O15266
## ENST00000381575 O15266
## ENST00000381578 O15266
## ENST00000554971 O15266The Uniprot identifier for the second region can be mapped to a single Ensembl protein ID and we get thus coordinates within a single transcript.
prt_tx[[2]] ## IRanges object with 1 range and 6 metadata columns:
## start end width | protein_id
## <integer> <integer> <integer> | <character>
## ENST00000380342 383 496 114 | ENSP00000369699
## tx_id cds_ok protein_start protein_end
## <character> <logical> <integer> <integer>
## ENST00000380342 ENST00000380342 TRUE 43 80
## uniprot_id
## <character>
## ENST00000380342 Q9HBJ8The last identifier can not be mapped to any Ensembl protein, and a region with negative coordinates is thus returned.
prt_tx[[3]] ## IRanges object with 1 range and 6 metadata columns:
## start end width | protein_id tx_id cds_ok
## <integer> <integer> <integer> | <character> <character> <logical>
## [1] -1 -1 1 | <NA> <NA> <NA>
## protein_start protein_end uniprot_id
## <integer> <integer> <character>
## [1] 100 100 unexistant5 Mapping protein coordinates to the genome
The proteinToGenome function allows to map coordinates within the amino acid
sequence of a protein to the corresponding DNA sequence on the genome. A protein
identifier and the coordinates of the sequence within the amino acid sequence
are required and have to be passed as an IRanges object to the function. The
protein identifier can either be used as names of this object, or added to a
metadata column (mcols).
In our first example we map the positions 5 to 9 within the amino acid sequence of the protein ENSP00000385415 from gene GAGE10 to the genome.
## Define the IRanges object.
GAGE10_prt <- IRanges(start = 5, end = 9, names = "ENSP00000385415")We can now map the protein-relative coordinates to genomic coordinates. By
default the proteinToGenome function assumes the names of the provided IRanges
object to contain the protein identifier, and that these identifiers are Ensembl
protein IDs.
GAGE10_gnm <- proteinToGenome(GAGE10_prt, edbx) proteinToGenome returns a list, one element for each range in the input
IRanges. We did only map a single range and hence the result is a list of
length 1. The GRanges object in the first element of GAGE10_gnm represents the
coordinates of the DNA sequence encoding positions 5 to 9 in the protein.
GAGE10_gnm ## $ENSP00000385415
## GRanges object with 1 range and 7 metadata columns:
## seqnames ranges strand | protein_id tx_id
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] X 49304872-49304886 + | ENSP00000385415 ENST00000407599
## exon_id exon_rank cds_ok protein_start protein_end
## <character> <integer> <logical> <integer> <integer>
## [1] ENSE00001692657 2 TRUE 5 9
## -------
## seqinfo: 1 sequence from GRCh38 genomeThis GRanges contains also useful additional information as metadata columns,
such as the ID of the encoding transcript (column “tx_id”) the ID and index of
the exon within the protein region is encoded (columns “exon_id” and exon_rank),
the start and end coordinates from the input IRanges object (columns
protein_start and protein_end) and a logical indicating whether the length of
the encoding transcript’s CDS matches the protein sequence (“cds_ok”). Special
care should be taken if FALSE is reported in this last column. In such cases the
returned genomic coordinates might not be correct and they should be manually
checked using the Ensembl genome browser.
The result object being a list and not, e.g. a GRangesList is required due to
the one to many mappings between Uniprot identifiers and Ensembl protein IDs. To
illustrate this, we map positions within 3 proteins identified by their Uniprot
identifiers to genomic regions.
## Define the IRanges providing Uniprot IDs.
uni_rng <- IRanges(start = c(2, 12, 8), end = c(2, 15, 17),
names = c("D6RDZ7", "O15266", "H7C2F2"))
## We have to specify that the IDs are Uniprot IDs
uni_gnm <- proteinToGenome(uni_rng, edbx, idType = "uniprot_id") ## Warning: Could not find a CDS whith the expected length for protein:
## 'D6RDZ7'. The returned genomic coordinates might thus not be correct for this
## protein.## Warning: Could not find a CDS whith the expected length for protein:
## 'H7C2F2'. The returned genomic coordinates might thus not be correct for this
## protein.The length of the protein coding region of the encoding transcript for two of
the 3 proteins (D6RDZ7 and H7C2F2) do not match the length of the protein
sequence. For some transcripts the CDS is not complete (either at the 3’, 5’ or
both ends). Mapped coordinates might not be correct in such cases and it is
strongly suggested to manually check the mapped coordinates. The result from the
comparison of the protein sequence and the CDS length is provided in the cds_ok
metadata column of the GRanges with the genomic coordinates. Below we print the
mapping result for the H7C2F2 protein; note the value in the cds_ok column.
uni_gnm[[3]] ## GRanges object with 1 range and 8 metadata columns:
## seqnames ranges strand | uniprot_id tx_id
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] X 2691521-2691550 + | H7C2F2 ENST00000449611
## protein_id exon_id exon_rank cds_ok protein_start
## <character> <character> <integer> <logical> <integer>
## [1] ENSP00000405544 ENSE00001702313 1 FALSE 8
## protein_end
## <integer>
## [1] 17
## -------
## seqinfo: 1 sequence from GRCh38 genomeMappings between Uniprot and Ensembl protein IDs can be one-to-many. In such
cases proteinToGenome returns a GRangesList with each element being the
coordinates calculated for each annotated Ensembl protein. In our example, each
of the first two proteins was annotated to 4 Ensembl proteins.
## To how many Ensembl proteins was each Uniprot ID mapped?
lengths(uni_gnm) ## D6RDZ7 O15266 H7C2F2
## 1 4 1Below we show the genomic coordinates for the within-protein positions calculated for all 4 Ensembl protein IDs for O15266.
uni_gnm[["O15266"]] ## GRangesList object of length 4:
## $ENSP00000335505
## GRanges object with 1 range and 8 metadata columns:
## seqnames ranges strand | uniprot_id tx_id
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] X 630931-630942 + | O15266 ENST00000334060
## protein_id exon_id exon_rank cds_ok protein_start
## <character> <character> <integer> <logical> <integer>
## [1] ENSP00000335505 ENSE00001489177 2 TRUE 12
## protein_end
## <integer>
## [1] 15
##
## $ENSP00000370987
## GRanges object with 1 range and 8 metadata columns:
## seqnames ranges strand | uniprot_id tx_id
## [1] X 630931-630942 + | O15266 ENST00000381575
## protein_id exon_id exon_rank cds_ok protein_start
## [1] ENSP00000370987 ENSE00001489169 1 TRUE 12
## protein_end
## [1] 15
##
## $ENSP00000370990
## GRanges object with 1 range and 8 metadata columns:
## seqnames ranges strand | uniprot_id tx_id
## [1] X 630931-630942 + | O15266 ENST00000381578
## protein_id exon_id exon_rank cds_ok protein_start
## [1] ENSP00000370990 ENSE00001489177 2 TRUE 12
## protein_end
## [1] 15
##
## ...
## <1 more element>
## -------
## seqinfo: 1 sequence from GRCh38 genomeAs a last example we fetch all protein domains for the gene SYP and map all of
them to the genome. To fetch protein domain information we select all columns
from the protein_domain table. In addition, we retrieve the result as a
AAStringSet. Additional annotations will be available in the mcols of this
result object.
SYP <- proteins(edbx, filter = ~ genename == "SYP",
columns = c("protein_id", "tx_id",
listColumns(edbx, "protein_domain")),
return.type = "AAStringSet")
SYP ## A AAStringSet instance of length 27
## width seq names
## [1] 313 MLLLADMDVVNQLVAGGQFRV...GDYGQQGYGPQGAPTSFSNQM ENSP00000263233
## [2] 313 MLLLADMDVVNQLVAGGQFRV...GDYGQQGYGPQGAPTSFSNQM ENSP00000263233
## [3] 313 MLLLADMDVVNQLVAGGQFRV...GDYGQQGYGPQGAPTSFSNQM ENSP00000263233
## [4] 313 MLLLADMDVVNQLVAGGQFRV...GDYGQQGYGPQGAPTSFSNQM ENSP00000263233
## [5] 313 MLLLADMDVVNQLVAGGQFRV...GDYGQQGYGPQGAPTSFSNQM ENSP00000263233
## ... ... ...
## [23] 118 MLLLADMDVVNQLVAGGQFRV...YLPPQVAPAQLPPRGYIHWDH ENSP00000418987
## [24] 118 MLLLADMDVVNQLVAGGQFRV...YLPPQVAPAQLPPRGYIHWDH ENSP00000418987
## [25] 118 MLLLADMDVVNQLVAGGQFRV...YLPPQVAPAQLPPRGYIHWDH ENSP00000420774
## [26] 118 MLLLADMDVVNQLVAGGQFRV...YLPPQVAPAQLPPRGYIHWDH ENSP00000420774
## [27] 118 MLLLADMDVVNQLVAGGQFRV...YLPPQVAPAQLPPRGYIHWDH ENSP00000420774Each protein sequence of the gene SYP has multiple protein domains annotated to
it, thus protein IDs and sequences are redundant in the AAStringSet. We restrict
the result below to a single protein.
## How many proteins are annotated to SYP?
unique(mcols(SYP)$protein_id)## [1] "ENSP00000263233" "ENSP00000365480" "ENSP00000418169" "ENSP00000418387"
## [5] "ENSP00000418987" "ENSP00000420774"## Reduce the result to a single protein
SYP <- SYP[names(SYP) == "ENSP00000263233"]
## List the available protein domains and additional annotations
mcols(SYP) ## DataFrame with 8 rows and 8 columns
## protein_id tx_id protein_domain_id protein_domain_source
## <character> <character> <character> <character>
## 1 ENSP00000263233 ENST00000263233 PS51225 pfscan
## 2 ENSP00000263233 ENST00000263233 PS00604 scanprosite
## 3 ENSP00000263233 ENST00000263233 PF01284 pfam
## 4 ENSP00000263233 ENST00000263233 PR00220 prints
## 5 ENSP00000263233 ENST00000263233 PR00220 prints
## 6 ENSP00000263233 ENST00000263233 PR00220 prints
## 7 ENSP00000263233 ENST00000263233 PR00220 prints
## 8 ENSP00000263233 ENST00000263233 PR00220 prints
## interpro_accession prot_dom_start prot_dom_end gene_name
## <character> <integer> <integer> <character>
## 1 IPR008253 21 227 SYP
## 2 IPR001285 53 61 SYP
## 3 IPR008253 22 221 SYP
## 4 IPR001285 29 51 SYP
## 5 IPR001285 53 78 SYP
## 6 IPR001285 106 130 SYP
## 7 IPR001285 138 161 SYP
## 8 IPR001285 205 223 SYPNext we create the IRanges object, one range for each protein domain, and
perform the mapping of the protein domains to the genome. This time we provide
the protein identifiers with one of the metadata columns and pass the name of
this column with the id parameter.
SYP_rng <- IRanges(start = mcols(SYP)$prot_dom_start,
end = mcols(SYP)$prot_dom_end)
mcols(SYP_rng) <- mcols(SYP)
## Map the domains to the genome. We set "id" to the name
## of the metadata columns containing the protein IDs
SYP_gnm <- proteinToGenome(SYP_rng, edbx, id = "protein_id") The function mapped each domain to the genome and returned a list with the
mapping result for each as a GRanges object. As an example we show the mapping
result for the second protein domain (PF01284).
SYP_gnm[[2]] ## GRanges object with 1 range and 7 metadata columns:
## seqnames ranges strand | protein_id tx_id
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] X 49197759-49197785 - | ENSP00000263233 ENST00000263233
## exon_id exon_rank cds_ok protein_start protein_end
## <character> <integer> <logical> <integer> <integer>
## [1] ENSE00001094897 3 TRUE 53 61
## -------
## seqinfo: 1 sequence from GRCh38 genomeThe protein domain is encoded by a sequence spanning exons 2 to 5 of the transcript ENST00000263233. Note that the gene is encoded on the reverse strand. The individual ranges are ordered by the index of the respective exon within the transcript.
At last we plot the encoding transcript and all of the mapped protein domains for the protein ENSP00000263233 of SYP.
library(Gviz)
## Define a genome axis track
gat <- GenomeAxisTrack()
## Get the transcript ID:
txid <- SYP_gnm[[1]]$tx_id[1]
## Get a GRanges for the transcript
trt <- getGeneRegionTrackForGviz(edbx, filter = TxIdFilter(txid))
## Define a GRanges for the mapped protein domains and add
## metadata columns with the grouping of the ranges and the
## IDs of the corresponding protein domains, so they can be
## identified in the plot
dmns <- unlist(GRangesList(SYP_gnm))
dmns$grp <- rep(1:length(SYP_rng), lengths(SYP_gnm))
dmns$id <- rep(mcols(SYP_rng)$protein_domain_id, lengths(SYP_gnm))
## Since we're using Ensembl chromosome names we have to set
options(ucscChromosomeNames = FALSE)
## Plotting the transcript and the mapped protein domains.
plotTracks(list(gat,
GeneRegionTrack(trt, name = "tx"),
AnnotationTrack(dmns, group = dmns$grp,
id = dmns$id,
groupAnnotation = "id",
just.group = "above",
shape = "box",
name = "Protein domains")),
transcriptAnnotation = "transcript")
6 Mapping transcript coordinates to genomic coordinates
Coordinates within transcript sequences can be mapped to genomic coordinates
with the transcriptToGenome function. In the example below we map coordinates
within 2 transcript to the genome.
rng_tx <- IRanges(start = c(501, 1), width = c(5, 5),
names = c("ENST00000486554", "ENST00000381578"))
rng_gnm <- transcriptToGenome(rng_tx, edbx) The function returns a GRangesList with the GRanges in each element containing
the genomic coordinates to which the positions could be mapped (or an empty
GRanges if the transcript identifier can not be found in the database). The
length of each GRanges depends on the number of exons the region in the
transcript spans.
rng_gnm ## GRangesList object of length 2:
## $ENST00000486554
## GRanges object with 2 ranges and 5 metadata columns:
## seqnames ranges strand | exon_id tx_id
## <Rle> <IRanges> <Rle> | <character> <character>
## [1] X 107715899-107715901 - | ENSE00001927337 ENST00000486554
## [2] X 107714748-107714749 - | ENSE00001837666 ENST00000486554
## exon_rank tx_start tx_end
## <integer> <integer> <integer>
## [1] 1 501 505
## [2] 2 501 505
##
## $ENST00000381578
## GRanges object with 1 range and 5 metadata columns:
## seqnames ranges strand | exon_id tx_id
## [1] X 624344-624348 + | ENSE00001489178 ENST00000381578
## exon_rank tx_start tx_end
## [1] 1 1 5
##
## -------
## seqinfo: 1 sequence from GRCh38 genomeThe region in the first transcript (ENST00000486554) is mapped to two genomic regions, because part of it is located in the first, and part in the second exon of the transcript. All 5 nucleotides of the second region are within the transcript’s first exon and are thus mapped to only a single genomic region.
Next we map variants in the gene PKP2 to the corresponding genomic
coordinates. The variants are PKP2 c.1643DelG and c.1881DelC and the positions
we are looking for are thus nucleotides 1643 and 1881 within the CDS of the
gene/transcript. Looking up the available transcripts for this gene we
identified ENST00000070846 as the representative transcript for the gene. Since
the positions are not relative to the transcription start site we can not use
the transcriptToGenome function for the mapping, but we have to map the
cds-relative positions first to transcript-relative coordinates. We do this
below using the cdsToTranscript function.
## Define the position within the CDS of the transcript
pkp2_cds <- IRanges(start = c(1643, 1881), width = c(1, 1),
name = rep("ENST00000070846", 2))
## Convert cds-relative to transcript-relative coordinates
pkp2 <- cdsToTranscript(pkp2_cds, EnsDb.Hsapiens.v86)
pkp2 ## IRanges object with 2 ranges and 2 metadata columns:
## start end width | cds_start cds_end
## <integer> <integer> <integer> | <integer> <integer>
## ENST00000070846 1668 1668 1 | 1643 1643
## ENST00000070846 1906 1906 1 | 1881 1881With the coordinates being now relative to the first nucleotide of the
transcript we can use the transcriptToGenome function for the final mapping of
the position to the genome.
pkp2_gnm <- transcriptToGenome(pkp2, EnsDb.Hsapiens.v86)
pkp2_gnm ## GRangesList object of length 2:
## $ENST00000070846
## GRanges object with 1 range and 5 metadata columns:
## seqnames ranges strand | exon_id tx_id exon_rank
## <Rle> <IRanges> <Rle> | <character> <character> <integer>
## [1] 12 32841073 - | ENSE00000936503 ENST00000070846 7
## tx_start tx_end
## <integer> <integer>
## [1] 1668 1668
##
## $ENST00000070846
## GRanges object with 1 range and 5 metadata columns:
## seqnames ranges strand | exon_id tx_id exon_rank
## [1] 12 32822557 - | ENSE00003560237 ENST00000070846 9
## tx_start tx_end
## [1] 1906 1906
##
## -------
## seqinfo: 1 sequence from GRCh38 genomeTo verify that the nucleotides at the positions are indeed G and C as stated in the definition of the variant (c.1643DelG and c.1881DelC) we extract below the nucleotide at the identified genomic position. We thus load the package providing the genome sequence for GRCh38 on which Ensembl release 86 is based.
library(BSgenome.Hsapiens.NCBI.GRCh38)## Loading required package: BSgenome## Loading required package: Biostrings## Loading required package: XVector##
## Attaching package: 'Biostrings'## The following object is masked from 'package:base':
##
## strsplit## Loading required package: rtracklayergetSeq(BSgenome.Hsapiens.NCBI.GRCh38, pkp2_gnm) ## DNAStringSetList of length 2
## [["ENST00000070846"]] G
## [["ENST00000070846"]] C7 Mapping transcript coordinates to protein coordinates
The transcriptToProtein function can be used to map coordinates within a
transcript to the corresponding coordinates within the encoded protein. Note
that only regions within protein coding transcripts can be mapped and that
coordinates within the transcript are assumed to be relative to the first
nucleotide of the transcript (not of the CDS).
Below we define regions within several transcripts and map these to the corresponding amino acid residues in the protein.
rng_tx <- IRanges(start = c(501, 1, 200), width = c(5, 5, 4),
names = c("ENST00000486554", "ENST00000381578",
"ENST00000431238"))
rng_prt <- transcriptToProtein(rng_tx, edbx) ## Warning: Transcript(s) 'ENST00000431238' do/does not encode a protein## Warning: Provided coordinates for 'ENST00000381578' are not within the coding
## region## Warning: The CDS of 'ENST00000486554' does not match the length of the
## encoded protein. Returned protein coordinates for this/these transcript(s)
## might not be correctThe mapping did throw several warnings. The region within transcript ENST00000431238 can not be mapped to protein coordinates, because the transcript does not encode a protein. Transcript ENST00000381578 encodes a protein, but the specified nucleotides 1 to 5 are located in the 5’ UTR of the transcript and can therefore also not be mapped. Finally, the CDS of the transcript ENST00000486554 is not complete and, while the coordinates were mapped to protein residues, they might not be correct.
rng_prt ## IRanges object with 3 ranges and 4 metadata columns:
## start end width | tx_id tx_start
## <integer> <integer> <integer> | <character> <integer>
## ENSP00000425414 1 2 2 | ENST00000486554 501
## -1 -1 1 | ENST00000381578 1
## -1 -1 1 | ENST00000431238 200
## tx_end cds_ok
## <integer> <logical>
## ENSP00000425414 505 FALSE
## 5 <NA>
## 203 <NA>For transcript coordinates that could not be mapped regions with negative
coordinates are returned (see lines/elements 2 and 3 above). The first region
could be mapped, but the returned protein-relative coordinates might be wrong,
because the CDS of the transcript is incomplete (hence a FALSE is reported in
metadata column "cds_ok"). In fact, only the 3’ end of the CDS is incomplete for
this transcript and the returned coordinates are thus correct.
8 Session information
sessionInfo() ## R version 3.5.0 Patched (2018-05-03 r74699)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows Server 2012 R2 x64 (build 9600)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=C
## [2] LC_CTYPE=English_United States.1252
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.1252
##
## attached base packages:
## [1] grid stats4 parallel stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] BSgenome.Hsapiens.NCBI.GRCh38_1.3.1000
## [2] BSgenome_1.48.0
## [3] rtracklayer_1.40.2
## [4] Biostrings_2.48.0
## [5] XVector_0.20.0
## [6] Gviz_1.24.0
## [7] EnsDb.Hsapiens.v86_2.99.0
## [8] ensembldb_2.4.1
## [9] AnnotationFilter_1.4.0
## [10] GenomicFeatures_1.32.0
## [11] AnnotationDbi_1.42.1
## [12] Biobase_2.40.0
## [13] GenomicRanges_1.32.2
## [14] GenomeInfoDb_1.16.0
## [15] IRanges_2.14.5
## [16] S4Vectors_0.18.1
## [17] BiocGenerics_0.26.0
## [18] BiocStyle_2.8.0
##
## loaded via a namespace (and not attached):
## [1] httr_1.3.1 bit64_0.9-7
## [3] splines_3.5.0 Formula_1.2-3
## [5] assertthat_0.2.0 latticeExtra_0.6-28
## [7] blob_1.1.1 GenomeInfoDbData_1.1.0
## [9] Rsamtools_1.32.0 yaml_2.1.19
## [11] progress_1.1.2 pillar_1.2.2
## [13] RSQLite_2.1.1 backports_1.1.2
## [15] lattice_0.20-35 biovizBase_1.28.0
## [17] digest_0.6.15 checkmate_1.8.5
## [19] RColorBrewer_1.1-2 colorspace_1.3-2
## [21] htmltools_0.3.6 Matrix_1.2-14
## [23] plyr_1.8.4 XML_3.98-1.11
## [25] pkgconfig_2.0.1 biomaRt_2.36.0
## [27] bookdown_0.7 zlibbioc_1.26.0
## [29] scales_0.5.0 BiocParallel_1.14.1
## [31] htmlTable_1.11.2 tibble_1.4.2
## [33] ggplot2_2.2.1 SummarizedExperiment_1.10.0
## [35] nnet_7.3-12 lazyeval_0.2.1
## [37] survival_2.42-3 magrittr_1.5
## [39] memoise_1.1.0 evaluate_0.10.1
## [41] foreign_0.8-70 data.table_1.11.0
## [43] tools_3.5.0 prettyunits_1.0.2
## [45] matrixStats_0.53.1 stringr_1.3.0
## [47] munsell_0.4.3 cluster_2.0.7-1
## [49] DelayedArray_0.6.0 compiler_3.5.0
## [51] rlang_0.2.0 RCurl_1.95-4.10
## [53] dichromat_2.0-0 rstudioapi_0.7
## [55] VariantAnnotation_1.26.0 htmlwidgets_1.2
## [57] bitops_1.0-6 base64enc_0.1-3
## [59] rmarkdown_1.9 gtable_0.2.0
## [61] DBI_1.0.0 curl_3.2
## [63] R6_2.2.2 gridExtra_2.3
## [65] GenomicAlignments_1.16.0 knitr_1.20
## [67] bit_1.1-12 Hmisc_4.1-1
## [69] rprojroot_1.3-2 ProtGenerics_1.12.0
## [71] stringi_1.2.2 Rcpp_0.12.16
## [73] rpart_4.1-13 acepack_1.4.1
## [75] xfun_0.1