In DPP4ResearchGroup/SyntenyViz: Visualize the synteny of a gene structure across species

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  error = TRUE
)

library(SyntenyViz)

## preload libs for better vignettes performance
library(grid)
library(dplyr)
pkgs <- c("org.Hs.eg.db", "org.Mm.eg.db", "org.Rn.eg.db", "TxDb.Hsapiens.UCSC.hg38.knownGene",
  "TxDb.Mmusculus.UCSC.mm10.knownGene", "TxDb.Rnorvegicus.UCSC.rn6.refGene")
for (pkg in pkgs) {
  if (!requireNamespace(pkg, quietly = TRUE)) {
        BiocManager::install(pkg)}
  library (pkg, character.only = TRUE)
}

The course below demonstrates a standard analysis pipeline with the SyntenyViz R package.

For the inpatients

Quick and minimum steps to get start a synteney conservation anaysis with SyntenyViz

• Define an investigation range We need to firstly define an investigation range to cover the target range in gene coordinate. We will use a mouse dipeptidyl dipeptidase 4 gene (DPP4-mm) in this example, where DPP4-mm locates at chromosome number 2 between 62,330,073-62,412,231 bp.

# orgm is a handle for organism
orgmName <- "Mmusculus"
# mycoords.list is the investigation range handler
mycoords <- "2:6.0e7:6.5e7"

• Convert mycoords.list into a GRange object

mycoords.gr <- SyntenyViz::coordFormat (mycoords.list = mycoords)

It is always a good habit to double check the input, so

mycoords.gr

• Construct a single synteny graph

synvizPlot(mycoords.gr, orgmName)

• Construct a multi synteny graph

Pick a few of targets

orgm.1 <- "Hsapiens"
mycoords.list.1 <- "2:15.95e7:16.45e7"
orgm.2 <- "Mmusculus"
mycoords.list.2 <- "2:6.0e7:6.5e7"
orgm.3 <- "Rnorvegicus"
mycoords.list.3 <- "3:4.6e7:5.1e7"

Then construct a multiple synteny query

orgmsList <- orgmsCollection.init (orgmsList)
orgmsList <- orgmsAdd (orgm.1, orgmTxDB, mycoords.list.1, orgmsList)
orgmsList <- orgmsAdd (orgm.2, orgmTxDB, mycoords.list.2, orgmsList)
orgmsList <- orgmsAdd (orgm.3, orgmTxDB, mycoords.list.3, orgmsList)

Now, construct a comparative multi-synteny graph

multiplot <- multisynvizPlots(orgmsList)

The Nitty Gritty of Synteny Analysis

Construct A Search Query

A search query includes the information of target organism(s) and the region(s) of interests. A typical work flow starts by locating the gene of interests. In this example, we will use a protease gene dipeptidyl dipeptidase-4 (DPP4) as a target.

DPP4 background

DPP4 is also known by a few other names including adenosine deaminase complexing protein 2 (ADCP2) and CD26. Human DPP4 gene encodes a 766 amino acids protein. DPP4 proteins dimmerise and then possesses potent rare post-proline hydrolytic activity in situ. In clinics, DPP4 has been demonstrated to involve in many important physiobiological functions including homeostasis, adaptive immune responses and numerous cancer biology. Due to its degradation property towards GLP and GIP, pharmacologically, DPP4 inhibitors have been prescribed as an alternative treatment to type 2 diabetics.

knitr::include_graphics('images/DPP4.png')

Locate DPP4 gene and define the investigation ranges

Locate gene (e.g. DPP4 gene)

To locate DPP4 gene, both Ensemble and GeneBank are good resources for this purpose.

Let's say we want to find the location of human DPP4 gene location.

• Ensemble query
• GeneBank query

indicate human DPP4 gene is located on chromosome 2 between 161992245-162074215 bp.

Define the investigation ranges

Given that human DPP4 related genes are clustered closely and we only interested in the synteny of DPP4 gene in this case, therefore, 0.25e7 bp on either side of DPP4 gene seems a good fit (i.e. 15.95e7-16.45e7 bp will be the investigation range).

Hence, we can now define the investigation range as

# orgm is a handle for organism
orgm <- "Hsapiens"
# mycoords.list is the investigation range handler
mycoords.list <- "2:15.95e7:16.45e7"

then we need to convert mycoords.list into a squence coordinate in GRange object, here we can call a convertion function

# Return mycoords.gr as a GRange object
mycoords.gr <- coordFormat (mycoords.list = mycoords.list)

Prepare the environment for analysis

SyntenyViz v0.0.0.9000 utilises UCSC transcriptomics database in TxDB object format. Available analysis can be performed on following databases.

knitr::kable(orgmTxDB, caption = "Available transcriptomics dataset for analysis as in SyntenyViz v0.0.0.9000")

Organisms can be analysised as in v0.0.0.9000 include

knitr::kable(orgmOrgDB, caption = "Available organisms for analysis as in SyntenyViz v0.0.0.9000")

A translation on the organism abbriviations may be useful here, so

knitr::kable(SynVizOrgms, results='asis', caption = "Reference Card for organisms Names")

Loading the orgnism databases for further analysis

orgm_OrgDB <- getPkgs(orgm, orgmOrgDB)
orgm_TxDB <- getPkgs(orgm, orgmTxDB)

Generate a dataset for a single Synteny Plot Construction

Function synvizPlotData can be used to automatically generate Gviz tracks for synteny plotting.

plotData <- synvizPlotData(mycoords.gr =  mycoords.gr, orgm = orgm)

Here is a good time to check the integraty of data, so let's have a look plotData

plotData

Generate a single Synteny Plot

We will now use function syntenyPlot to construct a single synteny plot.

synvizPlot (mycoords.gr = mycoords.gr, orgm = orgm)

Generate a Multiple Synteny Plot

In evolution biology, the conservation in synteny across species reveals important evolution tracks. So, let's have a look how DPP4 synteny conserved between human, mouse and rat.

orgm.1 <- "Hsapiens"
mycoords.list.1 <- "2:15.95e7:16.45e7"
orgm.2 <- "Mmusculus"
mycoords.list.2 <- "2:6.0e7:6.5e7"
orgm.3 <- "Rnorvegicus"
mycoords.list.3 <- "3:4.6e7:5.1e7"

orgmsList <- orgmsCollection.init (orgmsList)
orgmsList <- orgmsAdd (orgm.1, orgmTxDB, mycoords.list.1, orgmsList)
orgmsList <- orgmsAdd (orgm.2, orgmTxDB, mycoords.list.2, orgmsList)
orgmsList <- orgmsAdd (orgm.3, orgmTxDB, mycoords.list.3, orgmsList)

We now can call synvizPlot three times, or we can use function multiplot to do this for us.

multiplot <- multisynvizPlots(orgmsList)

DPP4ResearchGroup/SyntenyViz documentation built on Nov. 19, 2023, 1:16 a.m.