Whole genome resequencing of Botrytis cinerea isolates identifies high levels of standing diversity

Abstract

How standing genetic variation within a pathogen contributes to diversity in host/pathogen interactions is poorly understood, partly because most studied pathogens are host-specific, clonally reproducing organisms which complicates genetic analysis. In contrast, Botrytis cinerea is a sexually reproducing, true haploid ascomycete that can infect a wide range of diverse plant hosts. While previous work had shown significant genomic variation between two isolates, we proceeded to assess the level and frequency of standing variation in a population of B. cinerea. To begin measuring standing genetic variation in B. cinerea, we re-sequenced the genomes of 13 different isolates and aligned them to the previously sequenced T4 reference genome. In addition one of these isolates was resequenced from four independently repeated cultures. A high level of genetic diversity was found within the 13 isolates. Within this variation, we could identify clusters of genes with major effect polymorphisms, i.e., polymorphisms that lead to a predicted functional knockout, that surrounded genes involved in controlling vegetative incompatibility. The genotype at these loci was able to partially predict the interaction of these isolates in vegetative fusion assays showing that these loci control vegetative incompatibility. This suggests that the vegetative incompatibility loci within B. cinerea are associated with regions of increased genetic diversity. The genome re-sequencing of four clones from the one isolate (Grape) that had been independently propagated over 10 years showed no detectable spontaneous mutation. This suggests that B. cinerea does not display an elevated spontaneous mutation rate. Future work will allow us to test if, and how, this diversity may be contributing to the pathogen's broad host range.

Keywords: Botrytis cinerea; diversity; genome resequencing; standing genetic variation; vegetative incompatibility loci.

Figure 1

Allele diversity in comparison to reference T4. The number of isolates that share a polymorphic allele in comparison to the reference T4 isolate was plotted against the total number of polymorphisms with that level of diversity.

Figure 2

Radial neighbor-joining phylogenetic trees of nuclear and mitochondrial diversity within B. cinerea. (A) Unrooted genomic phylogeny determined based on pairwise SNP differences in the alignments of 17 B. cinerea strains to the reference T4 (including T4 reference and three replicate lineages independently propagated from the Grape isolate). Branch lengths are proportional to the number of segregating sites that differentiate each pair of isolates. (B) Unrooted mitochondrial phylogeny determined based on pairwise SNP differences to B05.10 in the alignments of 17 B. cinerea strains (including BO5.10 reference and three replicate lineages independently propagated from the Grape isolate). Branch lengths are based on very few polymorphisms and are proportional to the number of segregating sites that differentiate each pair of isolates.

Figure 3

Genomic distribution of polymorphism amongst the 14 isolates. (A) A sliding window analysis of genomic polymorphisms per 10 kb across the genome is shown. (B) Shown is a 10 gene sliding window analysis of the number of genes with major effect polymorphisms based on comparison to the isolate T4. (C) Again a 10 gene sliding window analysis of the number of genes with major effect polymorphisms based on comparison to the isolate T4, but with polymorphisms per gene given a binary value. This enabled clusters of seven or more genes in 10 gene windows affected by major effect polymorphisms to be visually determined more easily. Thousands of permutations of the major effect polymorphisms established a significance threshold of six genes per window, which is drawn for reference. No one isolate is key cause of these clusters.

Figure 4

Pairwise Vegetative Incompatibility. All pairwise crosses were tested in at least triplicate and the incompatibility was scored as compatible (C), weakly incompatible (W), and incompatible (I) and results are shown above. χ² was used to test if there was a difference in incompatibility when crossing within or between the Major Effect Haplotypes (χ² = 4.9, P = 0.02, N = 66, df = 2).

Figure 5

Genomic distribution of non-synonymous and synonymous SNPs. Polymorphisms were assigned as non-synonymous or synonymous amongst the 14 isolates (including T4) and then measured in a 10 gene sliding window as the number of segregating sites (S). The top mirrored plot shows the sliding window of non-synonymous polymorphisms while the bottom shows the corresponding synonymous analysis.

Figure 6

Relationship of Synonymous vs. Non-synonymous SNP frequencies. (A) An X/Y scatter plot showing the frequency of Synonymous vs. Non-synonymous SNPs per 10 kb bins. The x and y axis show the fraction of SNPs per kb for each window. No significant correlation was found using either pearson or spearman rank. (B) A zoomed in view of (A), focused on the regions up to four polymorphisms per kb per 10 kb bin.