Analysis of common intron properties

Introduction

This vignette introduces functions for characterizing common properties of introns.

MaxEntScan: Splicing site strength using the MaxEntScan program.
phastCons: Conservation scoring using phastCons program outputs (bigwig of scores and bed of identified conserved regions).
BranchPointScan: Motif scanning to characterize distance from branchpoint to 3’SS using universalmotif.

We will use several random introns and exons from the dm6 Bioconductor databases in this vignette. For your own applications, read in your introns into a GenomicRanges::GRanges object and then the same workflow can be easily adopted. The Bioconductor BiocIO::import() may be helpful if you have UCSC BED files in hand.

Randomly sample a bunch of exons and introns.

library(gsAnalysis)
requireNamespace("TxDb.Dmelanogaster.UCSC.dm6.ensGene", quietly = TRUE)
requireNamespace("BSgenome.Dmelanogaster.UCSC.dm6", quietly = TRUE)

MaxEntScan: splicing site strength

MaxEntScan reports splicing site strength. It is a simple wrapper around the original MaxEntScan perl routine.

Preparation

You need to gather MaxEntScan program on your own. This can be done in one of the following ways. Also, you need perl to be in your system paths.

Download the perl wrappers from the original MaxEntScan site. Then, compress all files into a zip without any root folder.
Download prezipped archive of the MaxEntScan from my Github archive repo. The burgelab.maxent.zip will be the MaxEntScan perl wrappers.

Required inputs:

path.zip.MES: Path to the zipped MaxEntScan perl scripts
BSgenome: BSgenome for obtaining splice site sequences. You must make sure that the same genome build is used.
GRange.intron: GRanges of your introns.

Sample usage

# The package itself does not bundle the MaxEntScan program and 
#  the following is NOT run.
# Expected outputs are shown in comments at the end.

phastCons: conservation scoring

phastCons reads conservation scores (bigwig) and conserved elements (bed) reported by the phastCons program and compute convervation scores for your genomic ranges.

Preparation

Phastcons score and conserved element files must be provided independently. One location to fetch these data is from UCSC. To get 124-way score and element files for Drosophila melanogaster dm6 genome:

bigWig of scores: https://hgdownload.soe.ucsc.edu/goldenPath/dm6/phastCons124way/dm6.phastCons124way.bw
BED of elements: https://hgdownload.soe.ucsc.edu/goldenPath/dm6/database/phastConsElements124way.txt.gz

Unzip the .gz file. Provide .bw and .txt to the phastCons function.

Required inputs:

GRange.intron: GRanges of your introns. Alternatively, any other genome ranges may be used. This is a generally applicable function.
bw.phastCons.path: Path to the phastCons score bigWig file.
bed.phastCons.path: Path to the phastCons conserved element BED file.

Sample usage

# The package itself does not bundle the score data and 
#  the following is NOT run.
# Expected outputs are shown in comments at the end.

BranchPointScan: distance of branchpoint to the 3’ splice site

BranchPointScan is a wrapper of the universalmotif package for identifying the highest-scored branchpoint motif position w.r.t. 3’-SS.

Preparation

You will need to provide a branchpoint motif matrix generated from motif discovery packages, e.g., HOMER or the MEME Suite. The workflow below starts with a precomputed MEME motif for branchpoint of the fruit fly. A tutorial of using the MEME suite to generate branchpoint motif will be released elsewhere TODO.

Required inputs:

GRanges.intron: GRanges of your introns.
branchpoint.motif: Motif read using the universalmotif package.
BSgenome: BSgenome for obtaining splice site sequences. You must make sure that the same genome build is used.

Sample usage

# The package itself bundles a MEME-generated branchpoint motif of flies.
# This example uses the bundled motif on randomly sampled introns.