Quick Start

The objective of this tutorial is to reproduce part of the results presented in Baurens et al (2019) and Ahmed et al (2019), using respectively VCFHunter and TraceAncestor.

The outputs of these programs can then be used in the GeMo webapps.

Installation requirements

This tutorial is developed to run on Linux or Apple (MAC OS X) operating systems. There are no versions planned for Windows.

Software requirements:

• Perl 5 for TraceAncestor

• Python 3 for VCFHunter

Testing your Perl installation

To test that Perl 5 is installed, enter on the command line

perl -version

Testing your Python installation

To test that Python 3 is installed, enter on the command line

python3 --version

Now, you can clone the repository, create a virtualenv and install several additionnal package using pip.

git clone https://github.com/gdroc/GeMo_tutorials.git
cd GeMo_tutorials
python3 -m venv $PWD/venv
source venv/bin/activate
pip install numpy
pip install matplotlib
pip install scipy

Download Dataset

For this tutorial, Dataset that will be used by TraceAncestor or by VCFHunter are accessible on Zenodo https://doi.org/10.5281/zenodo.6539270

To download this, you only need to launch the script download_dataset.pl without any parameter

perl download_dataset.pl

This script create a new directory data

data/
├── Ahmed_et_al_2019_color.txt
├── Ahmed_et_al_2019_individuals.txt
├── Ahmed_et_al_2019_origin.txt
├── Ahmed_et_al_2019.vcf
├── Baurens_et_al_2019_color.txt
├── Baurens_et_al_2019_individuals.txt
├── Baurens_et_al_2019_origin.txt
├── Baurens_et_al_2019_chromosome.txt
└── Baurens_et_al_2019.vcf

These files are require for this tutorial to run VCFHunter or TraceAncestor

Input

• Baurens_et_al_2019_origin.txt : A two column file with individuals in the first column and group tag (i.e. origin) in the second column

individuals	origin
P2	AA
T01	BB
T02	BB
T03	AA
T04	AA
T05	AA
T06	AA
T07	AA
T08	BB

• Baurens_et_al_2019.vcf : A vcf file with ancestral and admixed individuals

grep #CHROM data/Baurens_et_al_2019.vcf
#CHROM       POS     ID      REF     ALT     QUAL    FILTER  INFO    FORMAT  ACC48-FPG       ACC48-FPN       ACC48-P_Ceylan  ACC48-Red_Yade  DYN163-Kunnan   DYN275-Pelipita DYN359-Safet_Velchi     GP1     GP2     P1      P2      T01     T02     T03     T04     T05     T06     T07     T08     T10     T11

• Baurens_et_al_2019_individuals.txt : A two column file with individuals to scan for origin (same as defined in the VCF headerline) in the first column and the ploidy in the second column.

• Baurens_et_al_2019_color.txt : A color file with 4 columns: col1=group and the three last column corresponded to RGB code.

group	name	r	g	b
AA	acuminata	0	255	0
BB	balbisiana	255	0	0

Run workflow using create_gemo_input.pl

perl create_gemo_input.pl --help
Parameters :
    -v, --vcf         A vcf file [required]
    -o, --origin      A two column file with individuals in the first column and group tag (i.e. origin) in the second column [Required]
    -i, --individuals List of individuals to scan from vcf, as defined in the VCF headerline [Required]
    -m, --method      Permissible values: vcfhunter traceancestor (String). Default vcfhunter
    -c, --color       A color file with 4 columns: col1=group and the three last column corresponded to RGB code.
    -t, --threads     Number of threads
    -d, --dirout      Path to the output directory (Default method option name)
    -h, --help        display this help

1. With VCFHunter method

You must use the dataset prefixed with Baurens_et_al.

perl create_gemo_input.pl --vcf data/Baurens_et_al_2019.vcf --origin data/Baurens_et_al_2019_origin.txt --individuals data/Baurens_et_al_2019_individuals.txt --method vcfhunter --color data/Baurens_et_al_2019_color.txt --threads 4

2. With TraceAncestor method

You must use the dataset prefixed with with Ahmed_et_al.

perl create_gemo_input.pl --vcf data/Ahmed_et_al_2019.vcf --origin data/Ahmed_et_al_2019_origin.txt --individuals data/Ahmed_et_al_2019_individuals.txt --method traceancestor --color data/Ahmed_et_al_2019_color.txt

Explanation of outputs

A directory was create depending on parameter dirout (default method name)

For example, for VCFHunter, for each individual present in the file data/Baurens_et_al_2019_individuals.txt, 4 outputs are produced in this directory, prefixed with the name of indivual :

• DYN163-Kunnan_ideo.txt : A text file of the position of genomic blocks the ancestry mosaic with a succession of genomic blocks along the chromosome

chr	haplotype	start	end	ancestral_group
chr01	0	0	20888	AA
chr01	0	20888	451633	AA
chr01	0	451633	848109	AA
chr01	0	848109	1198648	AA
chr01	0	1198648	1555128	un
chr01	0	1555128	1899887	AA
chr01	0	1899887	2296417	un
chr01	0	2296417	2759817	un

• DYN163-Kunnan_chrom.txt : A tab file with name, length and karyotype based on ploidy (optionaly the location of centromere).

chr	len	centromereInf	centromereSup	label
chr01	29070452	14535226	14535228	AB
chr02	29511734	14755867	14755869	AB
chr03	35020413	17510206	17510208	AB
chr04	37105743	18552871	18552873	AB
chr05	41853232	20926616	20926618	AB
chr06	37593364	18796682	18796684	AB
chr07	35028021	17514010	17514012	AB
chr08	44889171	22444585	22444587	AB
chr09	41306725	20653362	20653364	AB
chr10	37674811	18837405	18837407	AB
chr11	27954350	13977175	13977177	AB

• BDYN163-Kunnan_color.txt : Frequency of ancestors alleles along chromosome for the particular hybrid focused.

group	name	hex
AA	acuminata	#00ff00
BB	balbisiana	#ff0000
un	un	#bdbdbd

• DYN163-Kunnan_curve.txt : Frequency of ancestors alleles along chromosome for the GeMo visualization tool.

chr	start	end	AA	BB
chr01	20888	525207	0.660757486645395	0.30378982223766354
chr01	525207	1086954	0.6425583592191819	0.3508607451997505
chr01	1086954	1563263	0.7355412887547506	0.2661255866893344
chr01	1563263	2058335	0.6136974042002844	0.3851682528896984
chr01	2058335	2638987	0.5543371247412866	0.39469329280411
chr01	2638987	3190388	0.6752108036341729	0.3208947817296506
chr01	3190388	3905155	0.6951554613138214	0.3155181655339866
chr01	3905155	4800522	0.6813746934348566	0.32271710110143237

Visualization and block refinement with GeMo

Go to GeMo WebApp

• Ideogram Mode

• Curve mode

References

• Summo, Marilyne. (2022). GeMo : a web-based platform for the visualization and curation of mosaic genomes [Data set]. Zenodo.

• Baurens,F.-C. et al.(2019) Recombination and Large Structural Variations Shape Interspecific Edible Bananas Genomes. Mol Biol Evol, 36, 97–111.

• Martin et al., 2020a. Martin G, Cardi C, Sarah G, Ricci S, Jenny C, Fondi E, Perrier X, Glaszmann J-C, D’Hont A, Yahiaoui N. 2020. Genome ancestry mosaics reveal multiple and cryptic contributors to cultivated banana. Plant J. 102:1008–1025.

• Ahmed,D. et al. (2019) Genotyping by sequencing can reveal the complex mosaic genomes in gene pools resulting from reticulate evolution: a case study in diploid and polyploid citrus. Annals of Botany, 123, 1231–1251.