Dataset Information

Prediction of the in planta Phakopsora pachyrhizi secretome and potential effector families.

ABSTRACT: Asian soybean rust (ASR), caused by the obligate biotrophic fungus Phakopsora pachyrhizi, can cause losses greater than 80%. Despite its economic importance, there is no soybean cultivar with durable ASR resistance. In addition, the P. pachyrhizi genome is not yet available. However, the availability of other rust genomes, as well as the development of sample enrichment strategies and bioinformatics tools, has improved our knowledge of the ASR secretome and its potential effectors. In this context, we used a combination of laser capture microdissection (LCM), RNAseq and a bioinformatics pipeline to identify a total of 36 350 P. pachyrhizi contigs expressed in planta and a predicted secretome of 851 proteins. Some of the predicted secreted proteins had characteristics of candidate effectors: small size, cysteine rich, do not contain PFAM domains (except those associated with pathogenicity) and strongly expressed in planta. A comparative analysis of the predicted secreted proteins present in Pucciniales species identified new members of soybean rust and new Pucciniales- or P. pachyrhizi-specific families (tribes). Members of some families were strongly up-regulated during early infection, starting with initial infection through haustorium formation. Effector candidates selected from two of these families were able to suppress immunity in transient assays, and were localized in the plant cytoplasm and nuclei. These experiments support our bioinformatics predictions and show that these families contain members that have functions consistent with P. pachyrhizi effectors.

SUBMITTER: de Carvalho MC

PROVIDER: S-EPMC6638266 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Prediction of the in planta Phakopsora pachyrhizi secretome and potential effector families.

de Carvalho Mayra C da C G MC Costa Nascimento Leandro L Darben Luana M LM Polizel-Podanosqui Adriana M AM Lopes-Caitar Valéria S VS Qi Mingsheng M Rocha Carolina S CS Carazzolle Marcelo Falsarella MF Kuwahara Márcia K MK Pereira Goncalo A G GA Abdelnoor Ricardo V RV Whitham Steven A SA Marcelino-Guimarães Francismar C FC

Molecular plant pathology 20160609 3

Asian soybean rust (ASR), caused by the obligate biotrophic fungus Phakopsora pachyrhizi, can cause losses greater than 80%. Despite its economic importance, there is no soybean cultivar with durable ASR resistance. In addition, the P. pachyrhizi genome is not yet available. However, the availability of other rust genomes, as well as the development of sample enrichment strategies and bioinformatics tools, has improved our knowledge of the ASR secretome and its potential effectors. In this conte ...[more]

PMID: 27010366

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Project description:Soybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to identify the markers associated with SBR resistance by 30,314 high quality single nucleotide polymorphism (SNPs). Then five genomic selection (GS) models, including Ridge regression best linear unbiased predictor (rrBLUP), Genomic best linear unbiased predictor (gBLUP), Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), Random Forest (RF), and Support vector machines (SVM), were used to predict breeding values of SBR resistance using whole genome SNP sets and GWAS-based marker sets. Four SNPs, namely Gm18_57,223,391 (LOD = 2.69), Gm16_29,491,946 (LOD = 3.86), Gm06_45,035,185 (LOD = 4.74), and Gm18_51,994,200 (LOD = 3.60), were located near the reported P. pachyrhizi R genes, Rpp1, Rpp2, Rpp3, and Rpp4, respectively. Other significant SNPs, including Gm02_7,235,181 (LOD = 7.91), Gm02_7234594 (LOD = 7.61), Gm03_38,913,029 (LOD = 6.85), Gm04_46,003,059 (LOD = 6.03), Gm09_1,951,644 (LOD = 10.07), Gm10_39,142,024 (LOD = 7.12), Gm12_28,136,735 (LOD = 7.03), Gm13_16,350,701(LOD = 5.63), Gm14_6,185,611 (LOD = 5.51), and Gm19_44,734,953 (LOD = 6.02), were associated with abundant disease resistance genes, such as Glyma.02G084100, Glyma.03G175300, Glyma.04g189500, Glyma.09G023800, Glyma.12G160400, Glyma.13G064500, Glyma.14g073300, and Glyma.19G190200. The annotations of these genes included but not limited to: LRR class gene, cytochrome 450, cell wall structure, RCC1, NAC, ABC transporter, F-box domain, etc. The GWAS based markers showed more accuracies in genomic prediction than the whole genome SNPs, and Bayesian LASSO model was the ideal model in SBR resistance prediction with 44.5% ~ 60.4% accuracies. This study aids breeders in predicting selection accuracy of complex traits such as disease resistance and can shorten the soybean breeding cycle by the identified markers.

Project description:BACKGROUND: Phakopsora pachyrhizi is an obligate fungal pathogen causing Asian soybean rust (ASR). A dual approach was taken to examine the molecular and biochemical processes occurring during the development of appressoria, specialized infection structures by which P. pachyrhizi invades a host plant. Suppression subtractive hybridization (SSH) was utilized to generate a cDNA library enriched for transcripts expressed during appressoria formation. Two-dimensional gel electrophoresis and mass spectroscopy analysis were used to generate a partial proteome of proteins present during appressoria formation. RESULTS: Sequence analysis of 1133 expressed sequence tags (ESTs) revealed 238 non-redundant ESTs, of which 53% had putative identities assigned. Twenty-nine of the non-redundant ESTs were found to be specific to the appressoria-enriched cDNA library, and did not occur in a previously constructed germinated urediniospore cDNA library. Analysis of proteins against a custom database of the appressoria-enriched ESTs plus Basidiomycota EST sequences available from NCBI revealed 256 proteins. Fifty-nine of these proteins were not previously identified in a partial proteome of P. pachyrhizi germinated urediniospores. Genes and proteins identified fell into functional categories of metabolism, cell cycle and DNA processing, protein fate, cellular transport, cellular communication and signal transduction, and cell rescue. However, 38% of ESTs and 24% of proteins matched only to hypothetical proteins of unknown function, or showed no similarity to sequences in the current NCBI database. Three novel Phakopsora genes were identified from the cDNA library along with six potentially rust-specific genes. Protein analysis revealed eight proteins of unknown function, which possessed classic secretion signals. Two of the extracellular proteins are reported as potential effector proteins. CONCLUSIONS: Several genes and proteins were identified that are expressed in P. pachyrhizi during appressoria formation. Understanding the role that these genes and proteins play in the molecular and biochemical processes in the infection process may provide insight for developing targeted control measures and novel methods of disease management.

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Dataset Information

Prediction of the in planta Phakopsora pachyrhizi secretome and potential effector families.

Publications

Prediction of the in planta Phakopsora pachyrhizi secretome and potential effector families.

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