- Overview of crisprBowtie
- Installation and getting started
- Building a bowtie index
- Alignment using
runCrisprBowtie - Applications beyond CRISPR
- Reproducibility
- References
Authors: Jean-Philippe Fortin
Date: July 13, 2022
crisprBowtie provides two main functions to align short DNA sequences
to a reference genome using the short read aligner bowtie (Langmead et
al. 2009) and return the alignments as R objects: runBowtie and
runCrisprBowtie. It utilizes the Bioconductor package Rbowtie to
access the bowtie program in a platform-independent manner. This means
that users do not need to install bowtie prior to using crisprBowtie.
The latter function (runCrisprBowtie) is specifically designed to map
and annotate CRISPR guide RNA (gRNA) spacer sequences using CRISPR
nuclease objects and CRISPR genomic arithmetics defined in the
Bioconductor crisprBase package. This enables a fast and accurate
on-target and off-target search of gRNA spacer sequences for virtually
any type of CRISPR nucleases.
This package is supported for macOS, Linux and Windows machines. Package was developed and tested on R version 4.2.
- crisprBase: https://github.com/Jfortin1/crisprBase
- RBowtie: https://bioconductor.org/packages/release/bioc/html/Rbowtie.html
crisprBowtie and its dependencies can be installed by typing the
following commands inside of an R session:
install.packages("BiocManager")
install.packages("devtools")
BiocManager::install("Rbowtie")
devtools::install_github("Jfortin1/crisprBase")
devtools::install_github("Jfortin1/crisprBowtie")crisprBowtie can be installed from Bioconductor using the following
commands in a fresh R session:
install.packages("BiocManager")
BiocManager::install("crisprBowtie")To use runBowtie or runCrisprBowtie, users need to first build a
bowtie genome index. For a given genome, this step has to be done only
once. The Rbowtie package convenitenly provides the function
bowtie_build to build a bowtie index from any custom genome from a
FASTA file.
As an example, we build a bowtie index for a small portion of the human
chromosome 1 (chr1.fa file provided in the crisprBowtie package) and
save the index file as myIndex to a temporary directory:
library(Rbowtie)
fasta <- file.path(find.package("crisprBowtie"), "example/chr1.fa")
tempDir <- tempdir()
Rbowtie::bowtie_build(fasta,
outdir=tempDir,
force=TRUE,
prefix="myIndex")As an example, we align 6 spacer sequences (of length 20bp) to the custom genome built above, allowing a maximum of 3 mismatches between the spacer and protospacer sequences.
We specify that the search is for the wildtype Cas9 (SpCas9) nuclease by
providing the CrisprNuclease object SpCas9 available through the
crisprBase package. The argument canonical=FALSE specifies that
non-canonical PAM sequences are also considered (NAG and NGA for
SpCas9). The function getAvailableCrisprNucleases in crisprBase
returns a character vector of available crisprNuclease objects found
in crisprBase.
library(crisprBowtie)
data(SpCas9, package="crisprBase")
crisprNuclease <- SpCas9
spacers <- c("TCCGCGGGCGACAATGGCAT",
"TGATCCCGCGCTCCCCGATG",
"CCGGGAGCCGGGGCTGGACG",
"CCACCCTCAGGTGTGCGGCC",
"CGGAGGGCTGCAGAAAGCCT",
"GGTGATGGCGCGGGCCGGGC")
runCrisprBowtie(spacers,
crisprNuclease=crisprNuclease,
n_mismatches=3,
canonical=FALSE,
bowtie_index=file.path(tempDir, "myIndex"))## [runCrisprBowtie] Searching for SpCas9 protospacers
## spacer protospacer pam chr pam_site strand
## 1 CCACCCTCAGGTGTGCGGCC CCACCCTCAGGTGTGCGGCC TGG chr1 679 +
## 2 CCGGGAGCCGGGGCTGGACG CCGGGAGCCGGGGCTGGACG GAG chr1 466 +
## 3 CGGAGGGCTGCAGAAAGCCT CGGAGGGCTGCAGAAAGCCT TGG chr1 706 +
## 4 GGTGATGGCGCGGGCCGGGC GGTGATGGCGCGGGCCGGGC CGG chr1 831 +
## 5 TGATCCCGCGCTCCCCGATG TGATCCCGCGCTCCCCGATG CAG chr1 341 +
## n_mismatches canonical
## 1 0 TRUE
## 2 0 FALSE
## 3 0 TRUE
## 4 0 TRUE
## 5 0 FALSE
The function runBowtie is similar to runCrisprBowtie, but does not
impose constraints on PAM sequences. It can be used to search for any
short read sequence in a genome.
Seed-related off-targets caused by mismatch tolerance outside of the
seed region is a well-studied and characterized problem observed in RNA
interference (RNA) experiments. runBowtie can be used to map
shRNA/siRNA seed sequences to reference genomes to predict putative
off-targets:
seeds <- c("GTAAAGGT", "AAGGATTG")
runBowtie(seeds,
n_mismatches=2,
bowtie_index=file.path(tempDir, "myIndex"))## query target chr pos strand n_mismatches
## 1 AAGGATTG AAAGAATG chr1 163 - 2
## 2 AAGGATTG AAGCCTTG chr1 700 + 2
## 3 AAGGATTG AAGGCTTT chr1 699 - 2
## 4 AAGGATTG CAGGCTTG chr1 905 - 2
## 5 GTAAAGGT GGGAAGGT chr1 724 + 2
sessionInfo()## R Under development (unstable) (2022-03-21 r81954)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] crisprBowtie_1.1.1 Rbowtie_1.35.0
##
## loaded via a namespace (and not attached):
## [1] SummarizedExperiment_1.25.3 tidyselect_1.1.2
## [3] xfun_0.30 purrr_0.3.4
## [5] lattice_0.20-45 vctrs_0.3.8
## [7] htmltools_0.5.2 stats4_4.2.0
## [9] rtracklayer_1.55.4 yaml_2.3.5
## [11] utf8_1.2.2 XML_3.99-0.9
## [13] rlang_1.0.2 pillar_1.7.0
## [15] glue_1.6.2 BiocParallel_1.29.18
## [17] bit64_4.0.5 BiocGenerics_0.41.2
## [19] matrixStats_0.61.0 GenomeInfoDbData_1.2.7
## [21] lifecycle_1.0.1 stringr_1.4.0
## [23] zlibbioc_1.41.0 MatrixGenerics_1.7.0
## [25] Biostrings_2.63.2 evaluate_0.15
## [27] restfulr_0.0.13 Biobase_2.55.0
## [29] knitr_1.37 tzdb_0.2.0
## [31] IRanges_2.29.1 fastmap_1.1.0
## [33] GenomeInfoDb_1.31.6 parallel_4.2.0
## [35] fansi_1.0.2 crisprBase_1.1.2
## [37] readr_2.1.2 BSgenome_1.63.5
## [39] DelayedArray_0.21.2 S4Vectors_0.33.11
## [41] vroom_1.5.7 XVector_0.35.0
## [43] bit_4.0.4 Rsamtools_2.11.0
## [45] rjson_0.2.21 hms_1.1.1
## [47] digest_0.6.29 stringi_1.7.6
## [49] BiocIO_1.5.0 GenomicRanges_1.47.6
## [51] grid_4.2.0 cli_3.3.0
## [53] tools_4.2.0 bitops_1.0-7
## [55] magrittr_2.0.2 RCurl_1.98-1.6
## [57] tibble_3.1.6 crayon_1.5.0
## [59] pkgconfig_2.0.3 ellipsis_0.3.2
## [61] Matrix_1.4-0 rmarkdown_2.13
## [63] rstudioapi_0.13 R6_2.5.1
## [65] GenomicAlignments_1.31.2 compiler_4.2.0
Langmead, Ben, Cole Trapnell, Mihai Pop, and Steven L. Salzberg. 2009. “Ultrafast and Memory-Efficient Alignment of Short DNA Sequences to the Human Genome.” Genome Biology 10 (3): R25. https://doi.org/10.1186/gb-2009-10-3-r25.