Cyst nematodes are important agricultural pests responsible for billions of dollars of losses each year. Plant resistance is the most effective management tool, but it requires a close monitoring of population genetics. Current technologies for pathotyping and genotyping cyst nematodes are time-consuming, expensive and imprecise. In this study, we capitalized on the reproduction mode of cyst nematodes to develop a simple population genetic analysis pipeline based on genotyping-by-sequencing and Pool-Seq. This method yielded thousands of SNPs and allowed us to study the relationships between populations of different origins or pathotypes. Validation of the method on well-characterized populations also demonstrated that it was a powerful and accurate tool for population genetics. The genomewide allele frequencies of 23 populations of golden nematode, from nine countries and representing the five known pathotypes, were compared. A clear separation of the pathotypes and fine genetic relationships between and among global populations were obtained using this method. In addition to being powerful, this tool has proven to be very time- and cost-efficient and could be applied to other cyst nematode species.
Sample description
Details about the origin (Country, province and field) of the samples, which experiment and figures they were used in and accession numbers (bioproject and biosample numbers).
Detail on samples.xlsx
Supplemental Table 1
Population differentiation (Fst) of 23 worldwide populations of Globodera rostochiensis estimated from genome-wide allele frequencies at 604 loci.
Suppl Table1.docx
Custom scripts and softwares
A link where all the custom scripts and softwares used in this paper can be found.
scripts.txt
PstI-MspI SNP table - UNEAK - 23 worldwide populations
Generated with mnC=0.8, minCov=1 and a MAF=0.01. Use this file as input to generate the “UNEAK-PstI/MspI” SNP tables with different parameters (mnC, minCov and MAF) using the countCleaner script found at https://bitbucket.org/mimeeb/gbs (Windows-based software).
UNEAK_PstI-MspI_23pop_0,8_0,01_SNP.txt
PstI-MspI SNP table - PoPoolation2 - 23 worldwide populations
Generated with mnC=1, minCov=5 and a MAF=0.01. Use this file as input to generate the “PoPoolation2-PstI/MspI” SNP tables with different parameters (minCov and MAF) using the countCleaner script found at https://bitbucket.org/mimeeb/gbs (Windows-based software).
Popoolation2_PstI-MspI_23pop_0,01_5_rc_cnt
ApeKI SNP table - UNEAK - 23 worldwide populations
Generated with mnC=0.8, minCov=1 and a MAF=0.01. Use this file as input to generate the “UNEAK-ApeKI” SNP tables with different parameters (mnC, minCov and MAF) using the countCleaner script found at https://bitbucket.org/mimeeb/gbs (Windows-based software).
UNEAK_ApekI_23pop_0,8_0,01_SNP.txt
ApeKI SNP table - PoPoolation2 - 23 worldwide populations
Generated with mnC=1, minCov=5 and a MAF=0.01. Use this file as input to generate the “PoPoolation2- ApeKI” SNP tables with different parameters (minCov and MAF) using the countCleaner script found at https://bitbucket.org/mimeeb/gbs (Windows-based software).
Popoolation2_ApekI_23pop_0,01_5_rc_cnt
Input file for PHYLIP - 23 worldwide populations
Allele frequencies calculated from UNEAK exact counts (mnC=1, minCov=20 and MAF=0.01) and used for phylogenetic tree analysis of the 23 Globodera rostochiensis worldwide populations.
Phylip_23pop_1_0,01_20.txt
UNEAK PstI-MspI allele frequencies - Validation assay - 28 Quebec populations from 2 fields + 1 outgroup
Allele frequencies calculated from UNEAK exact counts (mnC=1, minCov=20 and MAF=0.01) and used for principal component analysis (PCA) of Globodera rostochiensis populations from two fields of the province of Quebec, Canada and an unrelated population from France.
UNEAK_PstI-MspI_29pop_1_0,01_20_SNP.txt
Input file for PHYLIP - Validation assay - 28 Quebec populations from 2 fields + 1 outgroup
Allele frequencies calculated from UNEAK exact counts (mnC=1, minCov=20 and MAF=0.01) and used for phylogenetic tree analysis of Globodera rostochiensis populations from two fields of the province of Quebec, Canada and an unrelated population from France.
Phylip_29pop_1_0,01_20.txt
Supplemental Figure 1
Relationship between the median coverage (median number of reads/locus/population supporting each SNP) and the number of SNPs retained by the two pipelines at a minimum allele frequency of 1% (MAF = 0.01) and 5% (MAF = 0.05).
Suppl Fig1.png
Supplemental Figure 2
Number of SNPs retained by UNEAK and PoPoolation2 pipelines at different parameter values on an ApeKI library from 23 worldwide populations of Globodera rostochiensis. ‘MAF’ is the minimum allele frequency; ‘minCov’ is the minimum number of reads/locus/population required to accept a SNP; ‘mnC’ is the minimum proportion of populations in which a locus must have been scored to be accepted. PoPoolation2 does not allow missing data (mnC = 1.0). *The number of SNPs identified by UNEAK was not influenced by the ‘mnC’ value when the minimum allele frequency was set to 5% (MAF = 0.05).
Suppl Fig2.png
Supplemental Figure 3
Principal component analyses of 23 worldwide populations of Globodera rostochiensis from different pathotypes (Ro1, Ro2, Ro3, Ro4, Ro5 and a mixed population of Ro2/Ro3). Calculated with the prcomp() function in R. Based on genome-wide allele frequencies of different number of loci obtained from the PstI/MspI library supported by six different minimum coverage values (minCov = 5, 10, 20, 30, 40 or 50 reads/locus/population). Computed by the PoPoolation2 pipeline with a minimum allele frequency of 1% (MAF = 0.01) and no missing data allowed (mnC = 1.0).
Suppl Fig3.png
Supplemental Figure 4
Principal component analysis of 23 worldwide populations of Globodera rostochiensis. Calculated with the prcomp() function in R. Based on genome-wide allele frequencies of 1,277 loci obtained from the PstI/MspI library, and computed by the PoPoolation2 pipeline with a minimum allele frequency of 1% (MAF = 0.01), no missing data allowed (mnC = 1.0) and a minimum coverage of 20 reads/SNP/population (minCov = 20). Colors represent the different pathotypes: Black = Ro1; Yellow = Ro2; Green = Ro3; Red = Ro4; Blue = Ro5 and Grey is the mixed Ro2/3 sample.
Suppl Fig4.png