Crisprbase

crisprBase

Workflows

Standard Workflow

Define and manipulate S4 classes representing restriction enzymes, CRISPR nucleases, base editors, and nickases.

library(crisprBase)

# 1. Define SpCas9 Nuclease (3' PAM)
SpCas9 <- CrisprNuclease(
  "SpCas9", 
  targetType = "DNA",
  pams = c("(3/3)NGG", "(3/3)NAG", "(3/3)NGA"),
  weights = c(1, 0.2593, 0.0694),
  pam_side = "3prime", 
  spacer_length = 20
)

# 2. Define AsCas12a Nuclease (5' PAM)
AsCas12a <- CrisprNuclease(
  "AsCas12a", 
  targetType = "DNA",
  pams = "TTTV(18/23)",
  pam_side = "5prime", 
  spacer_length = 23
)

# 3. Define a Cytosine Base Editor (BE4max) with custom editing weights
weightsFile <- system.file("be/b4max.csv", package = "crisprBase", mustWork = TRUE)
ws <- t(read.csv(weightsFile))
ws <- as.data.frame(ws)
colnames(ws) <- ws["Position", ]
ws <- ws[-c(match("Position", rownames(ws))), , drop = FALSE]
ws <- as.matrix(ws)

BE4max <- BaseEditor(
  SpCas9, 
  baseEditorName = "BE4max",
  editingStrand = "original", 
  editingWeights = ws, 
  scale = TRUE
)

# 4. Define CRISPR Nickases (Cas9D10A)
Cas9D10A <- CrisprNickase(
  "Cas9D10A", 
  nickingStrand = "opposite", 
  pams = c("(3)NGG", "(3)NAG", "(3)NGA"),
  weights = c(1, 0.2593, 0.0694),
  pam_side = "3prime", 
  spacer_length = 20
)

Note on inputs/outputs: Input is nuclease specifications and weight files; output is S4 objects representing custom CRISPR nucleases, base editors, and nickases.

When to Use

• Nuclease Representation: Represent CRISPR nucleases (e.g., SpCas9, SaCas9, AsCas12a) and restriction enzymes (e.g., EcoRI, HgaI) using S4 classes CrisprNuclease and Nuclease.
• Genomic Range Extraction: Extract genomic coordinates of PAM, protospacer, and target sequences using getPamRanges, getProtospacerRanges, and getTargetRanges.
• Base Editor Modeling: Represent base editors (e.g., BE4max) with custom editing weights using BaseEditor.
• CRISPR Nickase Modeling: Represent CRISPR nickases (e.g., Cas9D10A, Cas9H840A) that create single-strand breaks using CrisprNickase.
• Sequence Extraction: Extract protospacer and PAM sequences from target sequences using extractProtospacerFromTarget and extractPamFromTarget.

When NOT to Use

• Full Guide RNA Design: For comprehensive guide RNA design, off-target search, or genomic alignment, use higher-level packages in the crisprVerse ecosystem (like crisprDesign) rather than the low-level representation classes in crisprBase.
• General Genomic Arithmetic: For general genomic arithmetic unrelated to CRISPR spacer/PAM coordinates, use standard GenomicRanges functions directly.

Data Requirements

• Target Sequences: Character vectors of target sequences (protospacer + PAM) or genomic coordinates (chromosome, PAM site, strand).
• Example Structure:

  targets <- c("AGGTGCTGATTGTAGTGCTGCGG", "AGGTGCTGATTGTAGTGCTGAGG")
  chr <- rep("chr7", 2)
  pam_site <- rep(200, 2)
  strand <- c("+", "-")
  

Key Parameters

• nucleaseName: A string specifying the name of the nuclease.
• targetType: Specifies if the nuclease targets "DNA" or "RNA".
• pams: Character vector of PAM sequences recognized by the nuclease.
• pam_side: Side of the PAM sequence relative to the protospacer ("5prime" or "3prime").
• spacer_length: Default spacer length (e.g., 20 for SpCas9).
• nickingStrand: Strand cleaved by a nickase ("original" or "opposite").
• editingStrand: Strand where editing happens with respect to the target protospacer ("original" or "opposite").
• scale (TRUE): Logical indicating whether to scale editing weights between 0 and 1.

Best Practices

• Rebase Convention: Use the Rebase convention to represent motif sequences (e.g., adding ^ to specify the cleavage site).
• Expand Motifs: Use expand = TRUE in motifs() to expand IUPAC nucleotide codes into all valid combinations of A/C/G/T.
• Cut Site Extraction: Use cutSites() to extract cut site coordinates relative to the PAM site to ensure correct genomic coordinate mapping.
• Scale Editing Weights: Scale custom editing weights using scale = TRUE in BaseEditor to ensure they are normalized between 0 and 1.

Common Pitfalls

• Confusing Spacer and Protospacer Sequences: Remember that for RNA-targeting nucleases (like Cas13d), the spacer sequence is the reverse complement of the protospacer sequence, whereas for DNA-targeting nucleases they are identical.
• Incorrect Row Names in Base Editor Weight Matrices: Ensure row names correspond exactly to nucleotide substitutions (e.g., "C2T", "G2A") and column names correspond to relative positions with respect to the PAM site.

Alternatives

• crisprDesign: For comprehensive gRNA design, annotation, and off-target analysis.
• Biostrings: For general biological sequence manipulation and motif matching without CRISPR-specific S4 classes.

Citations

• Arbab et al. 2020, Cell (Base editing outcomes and weights)
• Komor et al. 2016, Nature (Cytosine base editors)
• Roberts et al. 2010, Nucleic Acids Research (REBASE database)

References

• Homepage: https://bioconductor.org/packages/crisprBase
• Vignette: https://bioconductor.org/packages/release/bioc/vignettes/crisprBase/inst/doc/crisprBase.html