Recombination of standing variation in a multi-hybrid swarm drove adaptive radiation in a fungal pathogen and gave rise to two pandemic plant diseases

Adaptive radiations fuel speciation and are characterized by rapid genetic diversification and expansion into new ecological niches. Historically, these processes were believed to be driven by selection on novel mutations but genomic analyses now indicate that standing variation and gene flow often have prominent roles. How "old" variation is combined, however, and its resulting genetic architecture within newly adapted populations is not well understood. We reconstructed a recent radiation in the fungus, Pyricularia oryzae, that spawned a population pathogenic to eleven grass genera, and caused two new plant diseases: wheat blast - already a serious threat to global agriculture - and gray leaf spot of ryegrasses. We show that the new population evolved in a multi-hybrid swarm using only the standing variation that was present in seven individuals from five distinct, host-specialized lineages. Sexual and parasexual recombination within the swarm reassorted key host-specificity factors and generated more diversity in possibly just a few weeks than existing lineages had accumulated over hundreds to thousands of years. We suggest that the process was initiated by sexual opportunity arising when a fertile fungal strain was imported into Brazil on Urochloa introduced as forage for beef production; and we further contend that the host range expansion was largely fortuitous, with host selection playing little, if any, role in driving the process. Finally, we believe that our findings point to an overlooked role for happenstance in creating situations that allow organisms to skirt rules that would normally hold evolution in check.

Plant Disease Identification Using Shallow Convolutional Neural Network

Various plant diseases are major threats to agriculture. For timely control of different plant diseases in effective manner, automated identification of diseases are highly beneficial. So far, different techniques have been used to identify the diseases in plants. Deep learning is among the most widely used techniques in recent times due to its impressive results. In this work, we have proposed two methods namely shallow VGG with RF and shallow VGG with Xgboost to identify the diseases. The proposed model is compared with other hand-crafted and deep learning-based approaches. The experiments are carried on three different plants namely corn, potato, and tomato. The considered diseases in corns are Blight, Common rust, and Gray leaf spot, diseases in potatoes are early blight and late blight, and tomato diseases are bacterial spot, early blight, and late blight. The result shows that our implemented shallow VGG with Xgboost model outperforms different deep learning models in terms of accuracy, precision, recall, f1-score, and specificity. Shallow Visual Geometric Group (VGG) with Xgboost gives the highest accuracy rate of 94.47% in corn, 98.74% in potato, and 93.91% in the tomato dataset. The models are also tested with field images of potato, corn, and tomato. Even in field image the average accuracy obtained using shallow VGG with Xgboost are 94.22%, 97.36%, and 93.14%, respectively.

The Sm Gene Conferring Resistance to Gray Leaf Spot Disease Encodes a NBS-LRR Plant Resistance Protein in Tomato

Gray leaf spot (GLS), caused by Stemphylium lycopersici (S. lycopersici), is one of the most devastating diseases in tomato (Solanum lycopersicum). The resistance (R) gene, Sm, conferring high resistance to S. lycopersici, was introgressed into cultivated tomatoes from the wild tomato species Solanum pimpinellifolium (S. pimpinellifolium). Recently, several studies reported the mapping of the Sm gene. To date, however, it has not been cloned yet. Here, we cloned this resistance gene using a map-based cloning strategy. The Sm gene was mapped in a 160 kb interval of Chromosome 11 between two markers, M390 and M410, by using an F2 population from a cross between the resistant cultivar ‘Motelle’ (Mt) and susceptible line ‘Moneymaker’ (Mm). Three clustered NBS-LRR resistance genes, Solyc11g020080 (R1), Solyc11g020090 (R2) and Solyc11g020100 (R3) were identified in this interval. Nonsynonymous SNPs were identified only in the ORF of R3, supporting it may be a strong candidate gene for Sm. Furthermore, gene silencing of R3 abolished the high resistance to S. lycopersici in Motelle, demonstrating that it is the gene that confers high resistance to S. lycopersici. The clone of Sm gene will provide new opportunities for innovative breeding strategies to breed multi-resistant tomato cultivars.

Transcriptomic Analysis Reveals Candidate Genes Responding Maize Gray Leaf Spot Caused by Cercospora zeina

Gray leaf spot (GLS), caused by the fungal pathogen Cercospora zeina (C. zeina), is one of the most destructive soil-borne diseases in maize (Zea mays L.), and severely reduces maize production in Southwest China. However, the mechanism of resistance to GLS is not clear and few resistant alleles have been identified. Two maize inbred lines, which were shown to be resistant (R6) and susceptible (S8) to GLS, were injected by C. zeina spore suspensions. Transcriptome analysis was carried out with leaf tissue at 0, 6, 24, 144, and 240 h after inoculation. Compared with 0 h of inoculation, a total of 667 and 419 stable common differentially expressed genes (DEGs) were found in the resistant and susceptible lines across the four timepoints, respectively. The DEGs were usually enriched in ‘response to stimulus’ and ‘response to stress’ in GO term analysis, and ‘plant–pathogen interaction’, ‘MAPK signaling pathways’, and ‘plant hormone signal transduction’ pathways, which were related to maize’s response to GLS, were enriched in KEGG analysis. Weighted-Genes Co-expression Network Analysis (WGCNA) identified two modules, while twenty hub genes identified from these indicated that plant hormone signaling, calcium signaling pathways, and transcription factors played a central role in GLS sensing and response. Combing DEGs and QTL mapping, five genes were identified as the consensus genes for the resistance of GLS. Two genes, were both putative Leucine-rich repeat protein kinase family proteins, specifically expressed in R6. In summary, our results can provide resources for gene mining and exploring the mechanism of resistance to GLS in maize.

Fine Mapping of a New Major QTL-qGLS8 for Gray Leaf Spot Resistance in Maize

Gray leaf spot (GLS), caused by different species of Cercospora, is a fungal, non-soil-borne disease that causes serious reductions in maize yield worldwide. The identification of major quantitative trait loci (QTLs) for GLS resistance in maize is essential for developing marker-assisted selection strategies in maize breeding. Previous research found a significant difference (P < 0.01) in GLS resistance between T32 (highly resistant) and J51 (highly susceptible) genotypes of maize. Initial QTL analysis was conducted in an F2 : 3 population of 189 individuals utilizing genetic maps that were constructed using 181 simple sequence repeat (SSR) markers. One QTL (qGLS8) was detected, defined by the markers umc1130 and umc2354 in three environments. The qGLS8 QTL detected in the initial analysis was located in a 51.96-Mb genomic region of chromosome 8 and explained 7.89–14.71% of the phenotypic variation in GLS resistance in different environments. We also developed a near isogenic line (NIL) BC3F2 population with 1,468 individuals and a BC3F2-Micro population with 180 individuals for fine mapping. High-resolution genetic and physical maps were constructed using six newly developed SSRs. The QTL-qGLS8 was narrowed down to a 124-kb region flanked by the markers ym20 and ym51 and explained up to 17.46% of the phenotypic variation in GLS resistance. The QTL-qGLS8 contained seven candidate genes, such as an MYB-related transcription factor 24 and a C3H transcription factor 347), and long intergenic non-coding RNAs (lincRNAs). The present study aimed to provide a foundation for the identification of candidate genes for GLS resistance in maize.

First Report of Gray Leaf Spot Caused by Pyricularia oryzae (synonym: Magnaporthe oryzae) in Oat (Avena sativa) in Georgia, USA.

In southeastern U.S., oat (Avena sativa L.) is predominantly grown as a grain or forage crop due to its exceptional palatability (Buntin et al. 2009). In November 2020, leaf spot symptoms were observed in an oat field (cv. Horizon 720) in Screven County, Georgia (GPS: 32°38'57.6"N 81°31'32.178"W). Lesions were oblong, whitish to gray in color, and surrounded by dark brown borders. Symptomatic oat leaves were sampled from the field and cut into 1 cm2 sections that were surface sterilized, plated onto Potato Dextrose Agar (PDA) media and incubated in the dark at 23°C. To obtain pure cultures, fungal hyphal tips were transferred onto fresh PDA plates 3 times. The pathogen was identified as Pyricularia (Magnaporthe) based on typical conidial morphology (Ellis 1971). Conidia were hyaline, pyriform, 2-septate, and displayed a basal hilum. Conidia measured 5.32 to 10.64 μm (average 8.24 μm) wide by 15.96 to 29.26 μm (average 25.40 μm) long. The identification of Pyricularia was further confirmed genetically via PCR amplification followed by sequencing. Genomic DNA was extracted from a 14-day old pure culture using a CTAB method (Doyle and Doyle 1987). The internal transcribed spacer (ITS) region of ribosomal DNA, calmodulin (CaM) gene, and -tubulin (TUB) gene were amplified using ITS5-ITS4 (White et al. 1990), CMD5-CMD6 (Hong et al. 2005), and Bt2a- Bt2b (Glass and Donaldson 1995) primer sets, respectively. Amplicons were Sanger sequenced and blasted against the NCBI database. Results exhibited 100% (ITS), 100% (CaM), and 99.61% (TUB) homology with Pyricularia oryzae Cavara (GenBank accession no. LC554423.1, CP050920.1, and CP050924.1, respectively). The ITS, CaM, and TUB sequences of the isolate were deposited in GenBank as MZ295207, MZ342893, and MZ342894, respectively. In a greenhouse (23°C, 80% RH), Koch’s postulates were carried out by using oat seedlings cv. Horizon 270 grown in Kord sheet pots filled with Sun Gro professional growing mix, and a P. oryzae spore suspension containing 104 conidia ml−1. The spore suspension (10 ml) was sprayed with an air sprayer onto 7 pots of oat seedlings at the two-leaf stage. Seven supplementary pots of oat seedlings of the same cultivar were sprayed with sterile water to act as controls. After inoculation, plants were covered with black plastic bags that had been sprayed with sterile water to maintain high humidity and incubated overnight in the greenhouse. The bags were removed the next day, and plants were evaluated for symptoms in the following days. Seven days after inoculation, plants displayed symptoms similar to those found in the original field sample. Control plants showed no symptoms. Pyricularia oryzae was consistently re-isolated from inoculated symptomatic oat tissues. To our knowledge, this is the first report of gray leaf spot caused by P. oryzae on oat in the state of Georgia and in the continental United States. Pyricularia oryzae can infect several graminaceous plants, including agronomically important crops such as rice (Oryza sativa) and wheat (Triticum spp.) (Chung et al. 2020). Phylogenetic analysis on the ITS region using 6 different host lineages was performed and revealed that this oat isolate was most closely related to the Lolium lineage. This outbreak could have economic implications in oat production.

Identification of Gray Leaf Spot Disease Candidate Gene in Narrow-Leafed Lupin (Lupinus angustifolius L.)

Selection for resistance against gray leaf spot (GLS) is a major objective in the lupin breeding programs. A segregation ratio of 1:1 (resistant:susceptible) in F8 recombinant inbred lines (RIL8) derived from a cross between a breeding line 83A:476 (resistant to GLS) and a wild accession P27255 (susceptible to GLS) indicated that GLS was controlled by a single major gene. To develop molecular markers linked to GLS, in the beginning, only 11 resistant lines and six susceptible lines from the 83A:476 and P27255 population were genotyped with MFLP markers, and three MFLP markers were identified to be co-segregated with GLS. This method was very efficient, but the markers were located outside of the gene, and could not be used in other germplasms. Then QTL analysis and fine mapping were conducted to identify the gene. Finally, the gene was narrowed down to a 241-kb region containing two disease resistance genes. To further identify the candidate gene, DNA variants between accessions Tanjil (resistant to GLS) and Unicrop (susceptible to GLS) were analyzed. The results indicated that only one SNP was detected in the 241 kb region. This SNP was located in the TMV resistance protein N-like gene region and also identified between 83A:476 and P27255. Genotyping the Tanjil/Unicrop RIL8 population showed that this SNP co-segregated with GLS resistance. The phylogenetic tree analysis of this gene among 18 lupin accessions indicates that Australian resistant breeding line/varieties were clustered into one group and carry two resistant alleles, while susceptible accessions were clustered into different groups.