Jul 30, 2020
Version 1
construct a taro linkage map using onemap V.1
- Michael Kantar1,
- M Renee Bellinger2,
- Roshan Paudel1
- 1University of Hawaii at Manoa;
- 2University of Hawaii at Hilo
Protocol Citation: Michael Kantar, M Renee Bellinger, Roshan Paudel 2020. construct a taro linkage map using onemap. protocols.io https://dx.doi.org/10.17504/protocols.io.85xhy7n
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
This protocol was implemented in the G3 paper "Taro Genome Assembly and Linkage Map Reveal QTLs for Resistance to Taro Leaf Blight". Authors: M Renee Bellinger, Roshan Paudel, Steven Starnes, Lukas Kambic, Michael Kantar, Thomas Wolfgruber, Kurt Lamour, Scott Geib, Sheina Sim, Susan Miyasaka, Martin Helmkampf, Michael Shintaku. Publication Date: August 2020.
Created: November 08, 2019
Last Modified: July 30, 2020
Protocol Integer ID: 29591
Abstract
R script for taro linkage mapping using program onemap.
This script was applied to create a linkage map for a taro mapping population resistant to taro leaf blight.
The genotype file was constructed by calling SNPs using genotyping by sequencing data set using a taro genome reference genome available from NCBI's genbank under Bioproject PRJNA567267.
Attachments
Before start
Requires R version >3.5 or >3.6
download this file imputed_loci_06052019.vcf.txt and re-name it imputed_loci_06052019.vcf
Set up your R working environment
Set up your R working environment
### There are two ways to install onemap
###-------------------###
### Option 1.
####Download and install Rtools in your computer before running this script
find_rtools(debug = TRUE)
###Install required packages
install.packages("devtools")
library(devtools)
### The above installation is supposed to run in R version to 3.5 but I had issue with getting it to install.
devtools::install_github("Cristianetaniguti/onemap")
library("onemap")
###-------------------###
### Option 2. If using R 5.6 this package is compatible with the CRAN version
###
install.packages(onemap)
libarary(onemap)
install.packages("vcfR")
library("vcfR")
#######Set working directory
setwd("/your/working/directory/")
#####Convert the vcf file into onemap format.
## BE SURE THE txt is removed from the end of the vcf file name
vcfR.object <- read.vcfR("imputed_loci_06052019.vcf")
example_out <- onemap_read_vcfR(vcfR.object = vcfR.object,
parent1 = "P230.sam.mapped.bam",
parent2 = "P255.sam.mapped.bam",
cross = "outcross")
####Get the information on marker genotypes.
plot(example_out)
###Number of markers by segregation type
plot_by_segreg_type(example_out)
###Find redundant markers
bins <- find_bins(example_out, exact = FALSE)
bins
###Create onemap file after removing redundant markers
bins_example <- create_data_bins(example_out, bins)
bins_example
###testing segregation pattern of the markers
segreg_test <- test_segregation(bins_example)
print(segreg_test)
#####to show the markers names with segregation distortion
select_segreg(segreg_test, distorted = TRUE)
###to show the markers numbers with segregation distortion
dist <- select_segreg(segreg_test, distorted = TRUE, numbers = TRUE)
#to show the markers numbers without segregation distortion
no_dist <- select_segreg(segreg_test, distorted = FALSE, numbers = TRUE)
no_dist
####See the segregation test graphically
plot(segreg_test)
##calculate a suggested LOD score
LOD_sug <- suggest_lod(bins_example)
LOD_sug
###Estimating two-point recombination fractions
twopts <- rf_2pts(bins_example, LOD = LOD_sug, max.rf = 0.3)
twopts
###Create the sequences of markers without segregation distortion
mark_no_dist <- make_seq(twopts, c(no_dist))
###Number of linkage groups
lg <- group(mark_no_dist, LOD=LOD_sug, max.rf = 0.3)
print(lg, detailed = FALSE)
###Estimate a genetic map
maps<-vector("list", lg$n.groups)
for(i in 1:lg$n.groups)
maps[[i]]<- make_seq(order_seq(input.seq= make_seq(lg,i),twopt.alg =
"rcd"), "force")
##Draw the maps
##Draw the maps
draw_map(maps, names = FALSE, grid = TRUE, cex.mrk = 0.7)
draw_map2(maps,output="maps.png")
####Name the map and extract it into external file
file.out<-"map_LOD=5.97,max.rf=0.3.csv"
write_map(map1, file.out)