Reference Quality Genome Assemblies of Three Parastagonospora nodorum Isolates Differing in Virulence on Wheat

Abstract

Parastagonospora nodorum, the causal agent of Septoria nodorum blotch in wheat, has emerged as a model necrotrophic fungal organism for the study of host–microbe interactions. To date, three necrotrophic effectors have been identified and characterized from this pathogen, including SnToxA, SnTox1, and SnTox3. Necrotrophic effector identification was greatly aided by the development of a draft genome of Australian isolate SN15 via Sanger sequencing, yet it remained largely fragmented. This research presents the development of nearly finished genomes of P. nodorum isolates Sn4, Sn2000, and Sn79-1087 using long-read sequencing technology. RNAseq analysis of isolate Sn4, consisting of eight time points covering various developmental and infection stages, mediated the annotation of 13,379 genes. Analysis of these genomes revealed large-scale polymorphism between the three isolates, including the complete absence of contig 23 from isolate Sn79-1087, and a region of genome expansion on contig 10 in isolates Sn4 and Sn2000. Additionally, these genomes exhibit the hallmark characteristics of a “two-speed” genome, being partitioned into two distinct GC-equilibrated and AT-rich compartments. Interestingly, isolate Sn79-1087 contains a lower proportion of AT-rich segments, indicating a potential lack of evolutionary hotspots. These newly sequenced genomes, consisting of telomere-to-telomere assemblies of nearly all 23 P. nodorum chromosomes, provide a robust foundation for the further examination of effector biology and genome evolution.

Local adaptation drives the diversification of effectors in the fungal wheat pathogen Parastagonospora nodorum in the United States

“…Until recently, effector biology and genome research within P. nodorum has relied on relatively few genomic resources. Complementing the recently refined SN15 genome [31] and the establishment of nearly complete telomere to telomere reference genomes of three additional P. nodorum isolates [32], this research enhances our knowledge of genomic diversity within P. nodorum by revealing locale specific effector diversification and evidence of host susceptibility genes influencing population structure. This investigation also gives insight into the classes of genes undergoing diversifying selection through the accumulation of nonsynonymous SNPs, LOF mutations, and PAV, as well as identifying repetitive elements as a contributing factor to this diversification.…”

“…Quality of sequencing reads were analyzed using FastQC [70] and subsequently trimmed using trimmomatic [71]. Trimmed reads were mapped to the P. nodorum isolate Sn4 [32] reference genome (NCBI BioProject PRJNA398070) using BWA-MEM [72]. Sequencing coverage of the genome was calculated per isolate using GATK ‘Depth of Coverage’ using default settings.…”

“…Initially, the P. nodorum Australian isolate SN15 was sequenced with Sanger sequencing and subsequently improved via re-sequencing with short-read Illumina technology, RNA-seq data, and protein datasets [29,30,31]. Recently, we developed reference quality genome assemblies of P. nodorum isolates LDN03-Sn4 (hereafter referred to as Sn4), Sn2000, and Sn79-1087 using long-read sequencing technology [32]. These telomere to telomere sequences of nearly every P. nodorum chromosome, in addition to the annotation of 13,379 genes using RNA-seq, greatly improved the framework for effector discovery.…”

The genetic architecture of emerging fungicide resistance in populations of a global wheat pathogen

“…Richards et al 2017). Reference genome mapping was performed using the short-read aligner188 Bowtie2 version 2.3.3 (Langmead & Salzberg 2012), using the -very-sensitive-local option.…”

Natural selection drives population divergence for local adaptation in a wheat pathogen

“…were determined for each isolate as the ratio between growth rates under different 158 fungicide concentrations compared to the absence of fungicide, and growth rates at The generated raw reads were trimmed for remaining Illumina adapters and read 178 quality with Trimmomatic v0.36 (Bolger, Lohse, & Usadel, 2014), using the following 179 settings: illuminaclip = TruSeq3-PE.fa:2:30:10, leading = 10, trailing = 10, slidingwindow = 180 5:10, minlen = 50. Trimmed reads were aligned with the reference isolate SN2000 181 (Richards, Wyatt, Liu, Faris, & Friesen, 2017), which is assembled into chromosomes. The 182 alignment was performed with the short-read aligner Bowtie 2 version 2.3.3 (Langmead & 183 Salzberg, 2012), using the --very-sensitive-local option.…”