Dataset Information

Development of oligonucleotide microarrays for simultaneous multi-species identification of Phellinus tree-pathogenic fungi.

ABSTRACT: Polyporoid Phellinus fungi are ubiquitously present in the environment and play an important role in shaping forest ecology. Several species of Phellinus are notorious pathogens that can affect a broad variety of tree species in forest, plantation, orchard and urban habitats; however, current detection methods are overly complex and lack the sensitivity required to identify these pathogens at the species level in a timely fashion for effective infestation control. Here, we describe eight oligonucleotide microarray platforms for the simultaneous and specific detection of 17 important Phellinus species, using probes generated from the internal transcribed spacer regions unique to each species. The sensitivity, robustness and efficiency of this Phellinus microarray system was subsequently confirmed against template DNA from two key Phellinus species, as well as field samples collected from tree roots, trunks and surrounding soil. This system can provide early, specific and convenient detection of Phellinus species for forestry, arboriculture and quarantine inspection, and could potentially help to mitigate the environmental and economic impact of Phellinus-related diseases.

SUBMITTER: Tzean Y

PROVIDER: S-EPMC4767280 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Development of oligonucleotide microarrays for simultaneous multi-species identification of Phellinus tree-pathogenic fungi.

Tzean Yuh Y Shu Po-Yao PY Liou Ruey-Fen RF Tzean Shean-Shong SS

Microbial biotechnology 20160208 2

Polyporoid Phellinus fungi are ubiquitously present in the environment and play an important role in shaping forest ecology. Several species of Phellinus are notorious pathogens that can affect a broad variety of tree species in forest, plantation, orchard and urban habitats; however, current detection methods are overly complex and lack the sensitivity required to identify these pathogens at the species level in a timely fashion for effective infestation control. Here, we describe eight oligonu ...[more]

PMID: 26853539

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Project description:BACKGROUND: Genome-wide detection of single feature polymorphisms (SFP) in swine using transcriptome profiling of day 25 placental RNA by contrasting probe intensities from either Meishan or an occidental composite breed with Affymetrix porcine microarrays is presented. A linear mixed model analysis was used to identify significant breed-by-probe interactions. RESULTS: Gene specific linear mixed models were fit to each of the log2 transformed probe intensities on these arrays, using fixed effects for breed, probe, breed-by-probe interaction, and a random effect for array. After surveying the day 25 placental transcriptome, 857 probes with a q-value < or = 0.05 and |fold change| > or = 2 for the breed-by-probe interaction were identified as candidates containing SFP. To address the quality of the bioinformatics approach, universal pyrosequencing assays were designed from Affymetrix exemplar sequences to independently assess polymorphisms within a subset of probes for validation. Additionally probes were randomly selected for sequencing to determine an unbiased confirmation rate. In most cases, the 25-mer probe sequence printed on the microarray diverged from Meishan, not occidental crosses. This analysis was used to define a set of highly reliable predicted SFPs according to their probability scores. CONCLUSION: By applying a SFP detection method to two mammalian breeds for the first time, we detected transition and transversion single nucleotide polymorphisms, as well as insertions/deletions which can be used to rapidly develop markers for genetic mapping and association analysis in species where high density genotyping platforms are otherwise unavailable.SNPs and INDELS discovered by this approach have been publicly deposited in NCBI's SNP repository dbSNP. This method is an attractive bioinformatics tool for uncovering breed-by-probe interactions, for rapidly identifying expressed SNPs, for investigating potential functional correlations between gene expression and breed polymorphisms, and is robust enough to be used on any Affymetrix gene expression platform.

Project description:The rapid and accurate identification of pathogen yeast species is crucial for clinical diagnosis due to the high level of mortality and morbidity induced, even after antifungal therapy. For this purpose, new rapid, high-throughput and reliable identification methods are required. In this work we described a combined approach based on two high-throughput techniques in order to improve the identification of pathogenic yeast strains. Next Generation Sequencing (NGS) of ITS and D1/D2 LSU marker regions together with FTIR spectroscopy were applied to identify 256 strains belonging to Candida genus isolated in nosocomial environments. Multivariate data analysis (MVA) was carried out on NGS and FT-IR data-sets, separately. Strains of Candida albicans, C. parapsilosis, C. glabrata and C. tropicalis, were identified with high-throughput NGS sequencing of ITS and LSU markers and then with FTIR. Inter- and intra-species variability was investigated by consensus principal component analysis (CPCA) which combines high-dimensional data of the two complementary analytical approaches in concatenated PCA blocks normalized to the same weight. The total percentage of correct identification reached around 97.4% for C. albicans and 74% for C. parapsilosis while the other two species showed lower identification rates. Results suggested that the identification success increases with the increasing number of strains actually used in the PLS analysis. The absence of reliable FT-IR libraries in the current scenario is the major limitation in FTIR-based identification of strains, although this metabolomics fingerprint represents a valid and affordable aid to rapid and high-throughput to clinical diagnosis. According to our data, FT-IR libraries should include some tens of certified strains per species, possibly over 50, deriving from diverse sources and collected over an extensive time period. This implies a multidisciplinary effort of specialists working in strain isolation and maintenance, molecular taxonomy, FT-IR technique and chemo-metrics, data management and data basing.

Dataset Information

Development of oligonucleotide microarrays for simultaneous multi-species identification of Phellinus tree-pathogenic fungi.

Publications

Development of oligonucleotide microarrays for simultaneous multi-species identification of Phellinus tree-pathogenic fungi.

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