Dataset Information

Genetic Diversity of Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici in Yunnan, China.

ABSTRACT: The stripe rust of wheat is one of the devastating diseases in China, which is caused by fungus Puccinia striiformis f. sp. tritici (Pst). The Yunnan Province of China is located in the south-western part, and holds distinctive geographical and climate features, while wheat growth and epidemics of stripe rust fungus are fully dissimilar to the major wheat-growing regions of China. It is important to discover its origin and migration to control the disease. In this study, 352 isolates were sampled from 11 spots of the Yunnan Province during the wheat growing season from 2004 to 2015 and analyzed with SNPs markers of housekeeping genes. Results revealed that 220 haplotypes were inferred from the concatenating sequences; among them, 5 haplotypes (viz., 'H86', 'H18', 'H8', 'H15' and 'H23') comprised over 24.5% of the population. The haplotype diversity, nucleotide diversity, mutation rate and recombination events were 0.992, 6.04 × 10^-3, 4.46 × 10^-3 and 18.0 respectively, which revealed the genetic diversity of Pst populations among all locations. Four grouping methods, such as UPGMA-tree, PCA, PLS-DA and STRUCTURE, were employed for the categorization of the Pst populations conferring to their races and topographical localities. All methods were found significant and mostly had co-linear relations with each other. The analysis of molecular variance (AMOVA) conferred total variation was 9.09%, and 86.20% of variation was within the populations. The current study also exposed a comparatively high genetic multiplicity within the population, while low genetic inconsistency among the populations. Furthermore, the molecular records on the gene pole (Nm = 18.45) established that the migration of the stripe rust pathogen occurred among all locations in Yunnan province. The ancestral haplotype was detected in Yuxi. Based on the trajectories of upper airflow and genetic diversity of Pst populations in different locations, it is suggested that the locations Dehong, Dali, Lincang and Baoshan are probably a major source of Pst in Yunnan.

SUBMITTER: Alam MA

PROVIDER: S-EPMC8399030 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici, is a costly global disease that burdens farmers with yield loss and high fungicide expenses. This sophisticated biotrophic parasite infiltrates wheat leaves and develops infection structures inside host cells, appropriating nutrients while suppressing the plant defense response. Development in most eukaryotes is regulated by small RNA molecules, and the success of host-induced gene silencing technology in Puccinia spp. implies the existence of a functional RNAi system. However, some fungi lack this capability, and small RNAs have not yet been reported in rust fungi. The objective of this study was to determine whether P. striiformis carries an endogenous small RNA repertoire.We extracted small RNA from rust-infected wheat flag leaves and performed high-throughput sequencing. Two wheat cultivars were analyzed: one is susceptible; the other displays partial high-temperature adult plant resistance. Fungal-specific reads were identified by mapping to the P. striiformis draft genome and removing reads present in uninfected control libraries. Sequencing and bioinformatics results were verified by RT-PCR. Like other RNAi-equipped fungi, P. striiformis produces large numbers of 20-22 nt sequences with a preference for uracil at the 5' position. Precise post-transcriptional processing and high accumulation of specific sRNA sequences were observed. Some predicted sRNA precursors possess a microRNA-like stem-loop secondary structure; others originate from much longer inverted repeats containing gene sequences. Finally, sRNA-target prediction algorithms were used to obtain a list of putative gene targets in both organisms. Predicted fungal target genes were enriched for kinases and small secreted proteins, while the list of wheat targets included homologs of known plant resistance genes.This work provides an inventory of small RNAs endogenous to an important plant pathogen, enabling further exploration of gene regulation on both sides of the host/parasite interaction. We conclude that small RNAs are likely to play a role in regulating the complex developmental processes involved in stripe rust pathogenicity.

Project description:A long-standing biological question is how evolution has shaped the genomic architecture of dikaryotic fungi. To answer this, high-quality genomic resources that enable haplotype comparisons are essential. Short-read genome assemblies for dikaryotic fungi are highly fragmented and lack haplotype-specific information due to the high heterozygosity and repeat content of these genomes. Here, we present a diploid-aware assembly of the wheat stripe rust fungus Puccinia striiformis f. sp. tritici based on long reads using the FALCON-Unzip assembler. Transcriptome sequencing data sets were used to infer high-quality gene models and identify virulence genes involved in plant infection referred to as effectors. This represents the most complete Puccinia striiformis f. sp. tritici genome assembly to date (83 Mb, 156 contigs, N50 of 1.5 Mb) and provides phased haplotype information for over 92% of the genome. Comparisons of the phase blocks revealed high interhaplotype diversity of over 6%. More than 25% of all genes lack a clear allelic counterpart. When we investigated genome features that potentially promote the rapid evolution of virulence, we found that candidate effector genes are spatially associated with conserved genes commonly found in basidiomycetes. Yet, candidate effectors that lack an allelic counterpart are more distant from conserved genes than allelic candidate effectors and are less likely to be evolutionarily conserved within the P. striiformis species complex and Pucciniales In summary, this haplotype-phased assembly enabled us to discover novel genome features of a dikaryotic plant-pathogenic fungus previously hidden in collapsed and fragmented genome assemblies.IMPORTANCE Current representations of eukaryotic microbial genomes are haploid, hiding the genomic diversity intrinsic to diploid and polyploid life forms. This hidden diversity contributes to the organism's evolutionary potential and ability to adapt to stress conditions. Yet, it is challenging to provide haplotype-specific information at a whole-genome level. Here, we take advantage of long-read DNA sequencing technology and a tailored-assembly algorithm to disentangle the two haploid genomes of a dikaryotic pathogenic wheat rust fungus. The two genomes display high levels of nucleotide and structural variations, which lead to allelic variation and the presence of genes lacking allelic counterparts. Nonallelic candidate effector genes, which likely encode important pathogenicity factors, display distinct genome localization patterns and are less likely to be evolutionary conserved than those which are present as allelic pairs. This genomic diversity may promote rapid host adaptation and/or be related to the age of the sequenced isolate since last meiosis.

Project description:Accurate severity assessment of wheat stripe rust caused by Puccinia striiformis f. sp. tritici is of great significance for phenotypic determination, prediction, and control of the disease. To achieve accurate severity assessment of the disease based on the actual percentages of lesion areas in the areas of the corresponding whole diseased leaves, two new methods were proposed for severity assessment of the disease. In the Adobe Photoshop 2022 software, the acquired images of single diseased leaves of each severity class of the disease were manually segmented, and the numbers of the leaf region pixels and lesion pixels of each diseased leaf were obtained by pixel statistics. After calculation of the actual percentages of lesion areas in the areas of the corresponding whole diseased leaves based on the obtained pixel numbers, the training sets and testing sets were constructed for each severity class by using the system sampling method with two sampling ratios of 4:1 and 3:2. Then the mean and standard deviation of the actual percentages of lesion areas contained in each training set were calculated, respectively. For each sampling ratio, two methods, one based on the midpoint value of the means of the actual percentages of lesion areas corresponding to two adjacent severity classes and the other based on the distribution range of most of the actual percentages of lesion areas, were used to determine the midpoint-of-two-adjacent-means-based actual percentage reference range and the 90%, 95%, and 99% reference ranges of the actual percentages of lesion areas for each severity class. According to the determined reference ranges, the severity of each diseased leaf in the training sets and testing sets was assessed. The results showed that high assessment accuracies (not lower than 85%) for the training sets and testing sets were achieved, demonstrating that the proposed methods could be used to conduct severity assessment of wheat stripe rust based on the actual percentages of lesion areas. This study provides a reference for accurate severity assessments of plant diseases.

Dataset Information

Genetic Diversity of Wheat Stripe Rust Fungus Puccinia striiformis f. sp. tritici in Yunnan, China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets