Dataset Information

Reference Genes in the Pathosystem Phakopsora pachyrhizi/ Soybean Suitable for Normalization in Transcript Profiling.

ABSTRACT: Phakopsora pachyrhizi is a devastating pathogen on soybean, endangering soybean production worldwide. Use of Host Induced Gene Silencing (HIGS) and the study of effector proteins could provide novel strategies for pathogen control. For both approaches quantification of transcript abundance by RT-qPCR is essential. Suitable stable reference genes for normalization are indispensable to obtain accurate RT-qPCR results. According to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines and using algorithms geNorm and NormFinder we tested candidate reference genes from P. pachyrhizi and Glycine max for their suitability in normalization of transcript levels throughout the infection process. For P. pachyrhizi we recommend a combination of CytB and PDK or GAPDH for in planta experiments. Gene expression during in vitro stages and over the whole infection process was found to be highly unstable. Here, RPS14 and UbcE2 are ranked best by geNorm and NormFinder. Alternatively CytB that has the smallest Cq range (Cq: quantification cycle) could be used. We recommend specification of gene expression relative to the germ tube stage rather than to the resting urediospore stage. For studies omitting the resting spore and the appressorium stages a combination of Elf3 and RPS9, or PKD and GAPDH should be used. For normalization of soybean genes during rust infection Ukn2 and cons7 are recommended.

SUBMITTER: Hirschburger D

PROVIDER: S-EPMC4613351 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Reference Genes in the Pathosystem Phakopsora pachyrhizi/ Soybean Suitable for Normalization in Transcript Profiling.

Hirschburger Daniela D Müller Manuel M Voegele Ralf T RT Link Tobias T

International journal of molecular sciences 20150923 9

Phakopsora pachyrhizi is a devastating pathogen on soybean, endangering soybean production worldwide. Use of Host Induced Gene Silencing (HIGS) and the study of effector proteins could provide novel strategies for pathogen control. For both approaches quantification of transcript abundance by RT-qPCR is essential. Suitable stable reference genes for normalization are indispensable to obtain accurate RT-qPCR results. According to the Minimum Information for Publication of Quantitative Real-Time P ...[more]

PMID: 26404265

Similar Datasets

Project description:The management of soybean rust (SBR) caused by the obligate fungus Phakopsora pachyrhizi mostly relies on the use of synthetic fungicides, especially in areas where the disease inflicts serious yield losses. The reliance on synthetic fungicides to manage this disease has resulted in resistance of P. pachyrhizi populations to most fungicides. In this study, bacteria isolated from diverse environments were evaluated for their biocontrol potential against P. pachyrhizi using soybean detached-leaf method and on-plant in the growth chamber, greenhouse, and field. Among 998 bacterial isolates evaluated using the detached-leaf method; 58% were isolated from plant-related materials, 27% from soil, 10% from insects, and 5% from other environments. Of the isolates screened, 73 were active (they had ⪖ 75% rust reduction) with an active rate of 7.3%. From the active isolates, 65 isolates were re-tested on-plant in the growth chamber for activity confirmation. In the confirmation test, 49 bacteria isolated from plant-related materials maintained their activity with a confirmation rate of 75%. The majority of bacteria with confirmed activity belonged to the taxonomic classes Bacilli and Gammaproteobacteria (70%). Active isolates were prioritized for greenhouse and field testing based on activity in the initial screen and confirmation test. Six bacterial isolates AFS000009 (Pseudomonas_E chlororaphis), AFS032321 (Bacillus subtilis), AFS042929 (Bacillus_C megaterium), AFS065981 (Bacillus_X simplex_A), AFS090698 (Bacillus_A thuringiensis_S), and AFS097295 (Bacillus_A toyonensis) were selected from those bacteria that maintained activity in the confirmation test and were evaluated in the greenhouse, and five among them were evaluated in the field. From the Alabama field evaluation, all bacterial isolates reduced rust infection as well as azoxystrobin (Quadris® at 0.3 L/ha) used as the fungicide control (P > 0.05). Moreover, the scanning electron micrographs demonstrated evidence of antagonistic activity of AFS000009 and AFS032321 against P. pachyrhizi urediniospores. Bacterial isolates that consistently showed activity comparable to that of azoxystrobin can be improved through fermentation and formulation optimization, developed, and deployed. These bacteria strains would provide a valuable alternative to the synthetic fungicides and could play a useful role in integrated disease management programs for this disease.

Project description:Phakopsora pachyrhizi, the causal agent responsible for soybean rust, is among the top hundred most virulent plant pathogens and can cause soybean yield losses of up to 80% when appropriate conditions are met. We used mRNA-Seq by Illumina to analyze pathogen transcript abundance at 15 seconds (s), 7 hours (h), 48 h, and 10 days (d) after inoculation (ai) of susceptible soybean leaves with P. pachyrhizi to gain new insights into transcript abundance in soybean and the pathogen at specific time-points during the infection including the uredinial stage.Over three million five hundred thousand sequences were obtained for each time-point. Energy, nucleotide metabolism, and protein synthesis are major priorities for the fungus during infection and development as indicated by our transcript abundance studies. At all time-points, energy production is a necessity for P. pachyrhizi, as indicated by expression of many transcripts encoding enzymes involved in oxidative phosphorylation and carbohydrate metabolism (glycolysis, glyoxylate and dicarboxylate, pentose phosphate, pyruvate). However, at 15 sai, transcripts encoding enzymes involved in ATP production were highly abundant in order to provide enough energy for the spore to germinate, as observed by the expression of many transcripts encoding proteins involved in electron transport. At this early time-point, transcripts encoding proteins involved in RNA synthesis were also highly abundant, more so than transcripts encoding genes involved in DNA and protein synthesis. At 7 hai, shortly after germination during tube elongation and penetration, transcripts encoding enzymes involved in deoxyribonucleotide and DNA synthesis were highly abundant. At 48 hai, transcripts encoding enzymes involved in amino acid metabolism were highly abundant to provide for increased protein synthesis during haustoria maturation. During sporulation at 10 dai, the fungus still required carbohydrate metabolism, but there also was increased expression of transcripts encoding enzymes involved in fatty acid metabolism.This information provides insight into molecular events and their timing throughout the life cycle of the P. pachyrhizi, and it may be useful in the development of new methods of broadening resistance of soybean to soybean rust.

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.

Dataset Information

Reference Genes in the Pathosystem Phakopsora pachyrhizi/ Soybean Suitable for Normalization in Transcript Profiling.

Publications

Reference Genes in the Pathosystem Phakopsora pachyrhizi/ Soybean Suitable for Normalization in Transcript Profiling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets