Analyzing tRNA sequences and structures (original) (raw)
Introduction
The tRNA package provides access to tRNA feature information for subsetting and visualization. Visualization functions are implemented to compare feature parameters of multiple tRNA sets and to correlate them to additional data.
As input the package expects a GRanges object with certain metadata columns. The following columns are required: tRNA_length, tRNA_type,tRNA_anticodon, tRNA_seq, tRNA_str, tRNA_CCA.end. The tRNA_str column must contain a valid dot bracket annotation. For more details please have a look at the vignette of the Structstrings package.
Loading tRNA information
To work with the tRNA package, tRNA information can be retrieved or loaded into a R session in a number of ways:
- A
GRangesobject can be constructed manually containing the required colums mentioned above. - a tRNAscan result file can be loaded using the function
import.tRNAscanAsGRanges()from thetRNAscanImportpackage - selected tRNA information can be retrieved using the function
import.tRNAdb()from thetRNAdbImportpackage
For the examples in this vignette a number of predefined GRanges objects are loaded.
library(tRNA)
library(Structstrings)
data("gr", package = "tRNA")To retrieve the sequences for individual tRNA structure elements the functionsgettRNAstructureGRanges or gettRNAstructureSeqs can be used. Several optional arguments can be used to modify the result (See?gettRNAstructureSeqs).
# just get the coordinates of the anticodonloop
gettRNAstructureGRanges(gr, structure = "anticodonLoop")## $anticodonLoop
## IRanges object with 299 ranges and 0 metadata columns:
## start end width
## <integer> <integer> <integer>
## TGG 31 37 7
## TGC 32 38 7
## CAA 31 37 7
## AGA 31 37 7
## TAA 31 37 7
## ... ... ... ...
## CAT 32 38 7
## GAA 31 37 7
## TTA 31 37 7
## TAC 32 38 7
## CAT 32 38 7gettRNAstructureSeqs(gr, joinFeatures = TRUE, structure = "anticodonLoop")## $anticodonLoop
## RNAStringSet object of length 299:
## width seq names
## [1] 7 UUUGGGU TGG
## [2] 7 CUUGCAA TGC
## [3] 7 UUCAAGC CAA
## [4] 7 UUAGAAA AGA
## [5] 7 CUUAAGA TAA
## ... ... ...
## [295] 7 CUCAUAA CAT
## [296] 7 UUGAAGA GAA
## [297] 7 UUUUAGU TTA
## [298] 7 UUUACAC TAC
## [299] 7 GUCAUGA CATIn addition, the sequences can be returned already joined to get a fully blank padded set of sequences. The boundaries of the individual structures is returned as metadata of the RNAStringSet object.
seqs <- gettRNAstructureSeqs(gr[1L:10L], joinCompletely = TRUE)
seqs## RNAStringSet object of length 10:
## width seq
## [1] 85 GGGCGUGUGGUC-UAGU-GGUAU-GAUUCUCGC...------GCCUGGGUUCAAUUCCCAGCUCGCCCC
## [2] 85 GGGCACAUGGCGCAGUU-GGU-AGCGCGCUUCC...------GCAUCGGUUCGAUUCCGGUUGCGUCCA
## [3] 85 GGUUGUUUGGCC-GAGC-GGUAA-GGCGCCUGA...AA-GAUGCAAGAGUUCGAAUCUCUUAGCAACCA
## [4] 85 GGCAACUUGGCC-GAGU-GGUAA-GGCGAAAGA...U-GCCCGCGCAGGUUCGAGUCCUGCAGUUGUCG
## [5] 85 GGAGGGUUGGCC-GAGU-GGUAA-GGCGGCAGA...UUGUCCGCGCGAGUUCGAACCUCGCAUCCUUCA
## [6] 85 GCGGAUUUAGCUCAGUU-GGG-AGAGCGCCAGA...------GCCUGUGUUCGAUCCACAGAAUUCGCA
## [7] 85 GGUCUCUUGGCC-CAGUUGGUAA-GGCACCGUG...------ACAGCGGUUCGAUCCCGCUAGAGACCA
## [8] 85 GCGCAAGUGGUUUAGU--GGU-AAAAUCCAACG...-------CCCCGGUUCGAUUCCGGGCUUGCGCA
## [9] 85 GGCAACUUGGCC-GAGU-GGUAA-GGCGAAAGA...U-GCCCGCGCAGGUUCGAGUCCUGCAGUUGUCG
## [10] 85 GCUUCUAUGGCC-AAGUUGGUAA-GGCGCCACA...------ACAUCGGUUCAAAUCCGAUUGGAAGCA# getting the tRNA structure boundaries
metadata(seqs)[["tRNA_structures"]]## IRanges object with 15 ranges and 0 metadata columns:
## start end width
## <integer> <integer> <integer>
## acceptorStem.prime5 1 7 7
## Dprime5 8 9 2
## DStem.prime5 10 13 4
## Dloop 14 23 10
## DStem.prime3 24 27 4
## ... ... ... ...
## TStem.prime5 61 65 5
## Tloop 66 72 7
## TStem.prime3 73 77 5
## acceptorStem.prime3 78 84 7
## discriminator 85 85 1Be aware, that gettRNAstructureGRanges and gettRNAstructureSeqs might not be working as expected, if the tRNA sequences in questions are armless or deviate drastically from the canonical tRNA model. The functions in the tRNA packages were thouroughly tested using human mitochondrial tRNA and other tRNAs missing certain features. However, for fringe cases results may differ. If you encounter such a case, please report it with an example.
Subsetting tRNA sequences
Structure information of the tRNA can be queried for subsetting using several functions. For the following examples the functions hasAccpeptorStem andhasDloop are used.
gr[hasAcceptorStem(gr, unpaired = TRUE)]
# mismatches and bulged are subsets of unpaired
gr[hasAcceptorStem(gr, mismatches = TRUE)]
gr[hasAcceptorStem(gr, bulged = TRUE)]
# combination of different structure parameters
gr[hasAcceptorStem(gr, mismatches = TRUE) &
hasDloop(gr, length = 8L)]Please have a look at the man page ?hasAccpeptorStem for all available subsetting functions.
Visualization
To get an overview of tRNA features and compare different datasets, the functiongettRNAFeaturePlots is used. It accepts a named GRangesList as input. Internally it will calculate a list of features values based on the functions mentioned above and the data contained in the mcols of the GRanges objects.
# load tRNA data for E. coli and H. sapiens
data("gr_eco", package = "tRNA")
data("gr_human", package = "tRNA")
# get summary plots
grl <- GRangesList(Sce = gr,
Hsa = gr_human,
Eco = gr_eco)
plots <- gettRNAFeaturePlots(grl)plots$lengthFigure 1: tRNA length
plots$tRNAscan_scoreFigure 2: tRNAscan-SE scores
plots$gcFigure 3: tRNA GC content
plots$tRNAscan_intronFigure 4: tRNAs with introns
plots$variableLoop_lengthFigure 5: Length of the variable loop
To access the results without generating plots, use the functiongettRNASummary.
To check whether features correlate with additional scores, optional arguments can be added to gettRNAFeaturePlots or used from the score column of theGRanges objects. For the first case a list of scores with the same dimensions as the GRangesList object has to be provided as the argument scores. For the latter case, just set the argument plotScore = TRUE.
# score column will be used
plots <- gettRNAFeaturePlots(grl, plotScores = TRUE)plots <- gettRNAFeaturePlots(grl,
scores = list(runif(length(grl[[1L]]),0L,100L),
runif(length(grl[[2L]]),0L,100L),
runif(length(grl[[3L]]),0L,100L)))plots$lengthFigure 6: tRNA length and score correlation
plots$variableLoop_lengthFigure 7: variable loop length and score correlation
Since all plots returned by the functions mentioned above are ggplot2 objects, they can be modified manually and changed to suit your needs.
plots$length$layers <- plots$length$layers[c(-1L,-2L)]
plots$length + ggplot2::geom_boxplot()Figure 8: Customized plot switching out the point and violin plot into a boxplot
In addition, the data of the plots can be accessed directly.
head(plots$length$data)Options
The colours of the plots can be customized directly on creation with the following options.
options("tRNA_colour_palette")## $tRNA_colour_palette
## [1] "Set1"options("tRNA_colour_yes")## $tRNA_colour_yes
## [1] "green"options("tRNA_colour_no")## $tRNA_colour_no
## [1] "red"Dot bracket annotation
To retrieve detailed information on the base pairing the functiongettRNABasePairing() is used. Internally this will construct aDotBracketStringSet from the tRNA_str column, if this column does not already contain a DotBracketStringSet. It is then passed on to theStructstrings::getBasePairing function.
A valid DotBracket annotation is expected to contain only pairs of <>{}[]()and the . character (Please note the orientation. For <> the orientation is variable, since the tRNAscan files use the >< annotation by default. However upon creation of a DotBracketStringSet this annotation will be converted).
head(gettRNABasePairing(gr)[[1L]])## DotBracketDataFrame with 6 rows and 4 columns
## pos forward reverse character
## <integer> <integer> <integer> <character>
## 1 1 1 70 <
## 2 2 2 69 <
## 3 3 3 68 <
## 4 4 4 67 <
## 5 5 5 66 <
## 6 6 0 0 .head(getBasePairing(gr[1L]$tRNA_str)[[1L]])## DotBracketDataFrame with 6 rows and 4 columns
## pos forward reverse character
## <integer> <integer> <integer> <character>
## 1 1 1 70 <
## 2 2 2 69 <
## 3 3 3 68 <
## 4 4 4 67 <
## 5 5 5 66 <
## 6 6 0 0 .The loop ids for the structure elements can be retrieved with thegettRNALoopIDs() function, which relies on the Structstrings::getLoopIndicesfunction. (For more details, please have a look at the ?getLoopIndices)
gettRNALoopIDs(gr)[[1L]]## [1] 1 2 3 4 5 5 6 6 6 7 8 9 9 9 9 9 9 9 9 9 9 9 8 7 6
## [26] 10 11 12 13 14 14 14 14 14 14 14 14 14 13 12 11 10 6 6 6 6 15 16 17 18
## [51] 19 19 19 19 19 19 19 19 19 18 17 16 15 6 5 5 4 3 2 1 0getLoopIndices(gr[1L]$tRNA_str)## LoopIndexList of length 1
## [[""]] 1 2 3 4 5 5 6 6 6 7 8 9 9 9 9 9 ... 19 19 19 18 17 16 15 6 5 5 4 3 2 1 0Session info
sessionInfo()## R version 4.5.0 RC (2025-04-04 r88126)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 24.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0 LAPACK version 3.12.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] tRNA_1.26.0 Structstrings_1.24.0 Biostrings_2.76.0
## [4] XVector_0.48.0 GenomicRanges_1.60.0 GenomeInfoDb_1.44.0
## [7] IRanges_2.42.0 S4Vectors_0.46.0 BiocGenerics_0.54.0
## [10] generics_0.1.3 BiocStyle_2.36.0
##
## loaded via a namespace (and not attached):
## [1] sass_0.4.10 stringi_1.8.7 digest_0.6.37
## [4] magrittr_2.0.3 evaluate_1.0.3 grid_4.5.0
## [7] RColorBrewer_1.1-3 bookdown_0.43 fastmap_1.2.0
## [10] jsonlite_2.0.0 tinytex_0.57 BiocManager_1.30.25
## [13] httr_1.4.7 UCSC.utils_1.4.0 scales_1.3.0
## [16] jquerylib_0.1.4 cli_3.6.4 rlang_1.1.6
## [19] crayon_1.5.3 munsell_0.5.1 withr_3.0.2
## [22] cachem_1.1.0 yaml_2.3.10 tools_4.5.0
## [25] dplyr_1.1.4 colorspace_2.1-1 ggplot2_3.5.2
## [28] GenomeInfoDbData_1.2.14 vctrs_0.6.5 R6_2.6.1
## [31] magick_2.8.6 lifecycle_1.0.4 stringr_1.5.1
## [34] Modstrings_1.24.0 pkgconfig_2.0.3 bslib_0.9.0
## [37] pillar_1.10.2 gtable_0.3.6 Rcpp_1.0.14
## [40] glue_1.8.0 xfun_0.52 tibble_3.2.1
## [43] tidyselect_1.2.1 knitr_1.50 farver_2.1.2
## [46] htmltools_0.5.8.1 rmarkdown_2.29 labeling_0.4.3
## [49] compiler_4.5.0