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Pythium

Pythium is a genus of water molds that cause devastating plant diseases, particularly in agricultural and horticultural settings.
These fungus-like organisms infect a wide range of crops, including vegetables, ornamentals, and field crops, leading to root rot, damping-off, and other devastating effects.
Researchers studying Pythium require reliable, reproducible protocols to accurately identify and characterize these pathogens, as well as develop effective control strategies.
PubCompare.ai is an AI-driven tool that helps optimize Pythium research by intelligently comparing protocols from literature, preprints, and patents, enabling researchers to locate the best methodologies and enhance the quality and accuracy of their studies.
Experiance the future of research optimization today with PubCompare.ai's cutting-edge technology.

Most cited protocols related to «Pythium»

The P. ultimum genome annotations were created using the MAKER program [110 (link)]. The program was configured to use both spliced EST alignments as well as single exon ESTs greater than 250 bp in length as evidence for producing hint-based gene predictions. MAKER was also set to filter out gene models for short and partial gene predictions that produce proteins with fewer than 28 amino acids. The MAKER pipeline was set to produce ab initio gene predictions from both the repeat-masked and unmasked genomic sequence using SNAP [111 (link)], FGENESH [112 (link)], and GeneMark [113 (link)]. Hint-based gene predictions were derived from SNAP and FGENESH.
The EST sequences used in the annotation process were derived from Sanger and 454 sequenced P. ultimum DAOM BR144 ESTs [31 (link)] considered together with ESTs from dbEST [114 (link)] for Aphanomyces cochlioides, Phytophthora brassicae, Phytophthora capsici, Phytophthora parasitica, Ph. sojae, Ph. infestans, and Pythium oligandrum. Protein evidence was derived from the UniProt/Swiss-Prot protein database [115 (link),116 (link)] and from predicted proteins for Ph. infestans [28 (link)], Ph. ramorum [27 (link)], and Ph. sojae [27 (link)]. Repetitive elements were identified within the MAKER pipeline using the Repbase repeat library [117 (link)] and RepeatMasker [45 (link)] in conjunction with a MAKER internal transposable element database [118 (link)] and a P. ultimum specific repeat library prepared for this work (created using PILER [119 (link)] with settings suggested in the PILER documentation). Ab initio gene predictions and hint-based gene predictions [110 (link)] were produced within the MAKER pipeline using FGENESH trained for Ph. infestans, GeneMark trained for P. ultimum via internal self-training, and SNAP trained for P. ultimum from a conserved gene set identified by CEGMA [110 (link)].
Following the initial MAKER run, a total of 14,967 genes encoding 14,999 transcripts were identified, each of which were supported by homology to a known protein or had at least one splice site confirmed by EST evidence. Additional ab initio gene predictions not overlapping a MAKER annotation were scanned for protein domains using InterProScan [120 (link)-122 (link)]. This process identified an additional 323 gene predictions; these were added to the annotation set, producing a total of 15,290 genes encoding 15,322 transcripts (referred to as v3). Selected genes within the MAKER produced gene annotation set were manually annotated using the annotation-editing tool Apollo [123 (link)]. The final annotation set (v4) contained 15,297 genes encoding 15,329 transcripts, including six rRNA transcripts.
Putative functions were assigned to each predicted P. ultimum protein using BLASTP [124 (link)] to identify the best homologs from the UniProt/Swiss-Prot protein database and/or through manual curation. Additional functional annotations include molecular weight and isoelectric point (pI) calculated using the pepstats program from the EMBOSS package [125 (link)], subcellular localization predicted with TargetP using the non-plant network [126 (link)], prediction of transmembrance helices via TMHMM [127 (link)], and PFAM (v23.0) families using HMMER [128 ] in which only hits above the trusted cutoff were retained. Expert annotation of carbohydrate-related enzymes was performed using the Carbohydrate-Active Enzyme database (CAZy) annotation pipeline [68 (link)].
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Publication 2010
Amino Acids Aphanomyces Carbohydrates DNA Library DNA Transposable Elements Enzymes Exons Expressed Sequence Tags Gene Annotation Genes Genes, vif Genome Helix (Snails) Phytophthora Phytophthora parasitica Plants Protein Domain Proteins Pythium Repetitive Region Ribosomal RNA
A total of 376 Phytophthora isolates representing 142 described and 43 provisionally named species, plus one isolate of each Elongisporangium undulatum (basionym: Pythium undulatum), Halophytophthora fluviatilis, and Phytopythium vexans (basionym: Pythium vexans) as outgroup taxa were included (Table 1). These included 114 ex-types (Table 2). Also included were 164 authentic isolates that were designated as representative isolates by the originators of the respective species names (Table 1). The majority of these isolates were provided by the originators of the respective species, while the rest were purchased from the Westerdijk Fungal Biodiversity Institute (CBS), Utrecht, The Netherlands.
Publication 2017
Phytophthora Pythium
We identified gene families in S. japonica by performing an all-against-all BLASTp search against the protein sequences of 25 algae and plants with available whole-genome information. Among these algae, 13 belonged to Chromalveolata (S. japonica, E. siliculosus, Nannochloropsis gaditana, Nannochloropsis oceanica, Aureococcus anophagefferens, Phaeodactylum tricornutum, Thalassiosira pseudonana, Albugo laibachii, Phytophthora infestans, Pythium ultimum, Saprolegnia parasitica, Emiliania huxleyi and Guillardia theta CCMP2712); 1 was Rhizaria (Bigelowiella natans); 1 was Glaucophyta (Cyanophora paradoxa); 5 were Rhodophyta (Chondrus crispus, Cyanidioschyzon merolae, Galdieria sulphuraria, Porphyridium purpureum and Pyropia yezoensis); 3 were Chlorophyta (Chlamydomonas reinhardtii, Coccomyxa subellipsoidea and Volvox carteri); and 2 were plants (Arabidopsis thaliana and Physcomitrella patens).
The global protein identities of each BLAST match were calculated using InParanoid56 (link) to filter out matches exhibiting poor similarities (<20%) or poor gene coverage (<50%). Gene families were identified by MCL57 (link) with the ‘inflation' option as 1.2. Gene numbers were counted for each family and for each species, and were compared by using the K-means algorithm in R. To obtain a robust species tree, redundant sequences (90% identity or more) from the same organism were removed using CD-HIT58 (link), then, homologue clusters were predicted by comparing each pair of the 25 algal and plant genomes and further summarized by InParanoid and QuickParanoid. Subsequently, the clusters containing single-copy genes from each organism and clusters with species-specific duplications were selected for further consideration. For each cluster, multiple alignments were then performed using MUSCLE v3.8.31 (ref. 59 (link)) with the default parameters and were further trimmed using trimAl v1.4 (ref. 60 (link)) with the options ‘-gt 0.1 -resoverlap 0.75 -seqoverlap 80'. RAxML61 (link) was employed to reconstruct a maximum-likelihood phylogenetic tree for each cluster with an evolutionary model specified as ‘PROTCATJTT' and to perform a bootstrap significance test with 100 replicates. TreSpEx62 (link) was then applied to the tree of each cluster to evaluate taxa with long branches and to the trees of the 41 clusters with both long branch score heterogeneity and upper quartiles smaller than 30. The according clusters were selected for concatenation of their sequences within the same species into super genes.
A Dollo analysis was conducted on the homologue clusters of the 25 algal and plant proteomes using the Dollop tool in the PHYLIP package63 and custom Java scripts (available on request). To examine the evolutionary relationships between the duplicated homologues in the S. japonica genome before or after its divergence from E. siliculosus, synonymous (Ks) and non-synonymous (Ka) substitution rates were calculated using KaKs_Calculator64 (link). A gene function-enrichment analysis for the clustered genes was performed using Fisher's exact test to compare all of the genes in the S. japonica genome.
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Publication 2015
Amino Acid Sequence Arabidopsis thalianas Biological Evolution Chlamydomonas reinhardtii Chlorophyta Chondrus crispus Cyanophora paradoxa Emiliania Genes Genes, vif Genetic Heterogeneity Genome Genome, Plant Glaucophyta Muscle Tissue Operator, Genetic Physcomitrella Phytophthora infestans Plants Porphyridium Proteins Proteome Pythium Rhizaria Rhodophyta Saprolegnia Trees Volvox
A dataset of 33 Peronosporales genomes (Supplementary Table S1) was used for phylogenomic analysis. We also included Pythium ultimum as an outgroup. BUSCO analysis revealed 208 BUSCO families that are present and single copy in at least 90% of the species (i.e., at least 31 of the 34 species). Each BUSCO family was individually aligned with MUSCLE (v3.8.31) [79 (link)] and trimmed using trimAl (v1.4) [80 (link)] with the parameter “-automated1” to remove poorly aligned regions. Trimmed alignments were concatenated together resulting in a final supermatrix alignment of 106,315 amino acids. Maximum-likelihood (ML) phylogenetic reconstruction was performed using IQ-TREE (v1.6.12) [81 (link)] with the JTT+F+R5 model, which was the best fit model according to ModelFinder [82 (link)], and 100 bootstrap replicates were undertaken to infer branch support values. Bayesian analysis was also performed using PhyloBayes MPI (v1.8) [83 (link)] with the CAT model. Two independent chains were run for 10,000 cycles and convergence was assessed using bpcomp and tracecomp. A consensus Bayesian phylogeny was generated with a burn-in of 10%. The phylogeny was visualised and annotated using the Interactive Tree of Life (iTOL) [84 (link)].
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Publication 2020
Amino Acids Genome Muscle Tissue Pythium Trees
Sequences from eight loci were obtained from each sample; primers and annealing temperatures for amplification and sequencing are listed in S2 Table. Methods for obtaining and analyzing the ITS sequence of Phytophthora cyperi will be discussed in a separate manuscript (in preparation). PCR conditions are listed in S3 Table; different amplification conditions were used for nuclear and mitochondrial loci. The FRiz forward ITS primer was initially developed for routine amplification and sequencing of Pythium and Phytophthora but proved to be useful for potentially plant-contaminated downy mildew samples due to its apparent specificity to oomycetes. In both Bremia species, any amplicon containing the ITS2 region produced multiple bands, including some much larger than expected, a known issue with DMPH [68 (link)]; as a result, only the ITS1 was amplified and sequenced from the two samples. The combination of BTubF4 and BTubR3 proved able to amplify the beta tubulin locus without also amplifying host genes, which was particularly problematic for the Phytophthora cyperi sample. The reverse primer SecYtrnC-R was used for some of the downy mildew samples that did not amplify well with SecY-R. The internal primers SecY-F2 and SecY-R2 were developed because P. taxon mugwort contains homopolymers in both the 5' and 3' end of its secY ORF, which rendered downstream sequences difficult to read; the additional primers listed for the cox2-cox1 contig also reflect the presence of homopolymers in many samples, both in-frame and in the cox2-cox1 intergenic spacer. PCR products were cleaned with Exo-SAP-IT (Thermo Fisher Scientific, Waltham MA, USA) according to manufacturer's instructions and Sanger sequencing performed by the UC Davis UCDNA Sequencing Facility (Davis, CA, USA). Chromaseq was used to call bases and assemble contigs [69 –72 ]; sequences were uploaded to GenBank (S1 Table).
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Publication 2018
Artemisia beta-Tubulin Genes Mitochondria Oligonucleotide Primers Oomycetes Phytophthora Plants PTGS1 protein, human PTGS2 protein, human Pythium Reading Frames

Most recents protocols related to «Pythium»

Phylogenetic trees of the isolated P. cactorum strain Pca-NJ-1 with other oomycetes including several Phytophthora pathogens and Pythium were constructed based on the ITS sequence using the maximum-likelihood (ML) method in MEGA 7.0 software.
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Publication 2023
Oomycetes Pathogenicity Phytophthora Pythium Strains
The bacterial strains of E. coli (MTCC-118) and P. aeruginosa (MTCC-1035) were inoculated in Luria broth and were kept at 37 °C overnight to obtain an exponential growth phase to use for further study.
The THY-1 sequence was submitted to GenBank by Paul, B and Voglmayr, H (2013) under the GeneBank accession of KF806442. This strain was isolated from Nagpur, India, by Prof. Paul, where the aforementioned professor has graciously consigned it to the author. Although the oomycete strain THY-1 was named Pythium siamicum, it was never described as a new species. A BLAST search shows that it closely resembles Pythium nunn (97.74% identity, Globisporangium nunn). THY-1 was used for the microbial studies, and the strains were cultured in PDA slants, while fresh potato dextrose broth (PDB) was used for the inoculation process. All experiments were performed at 25 °C. Fungal species confirmation was performed using an 18s rDNA sequence. A fragment of amplified 18s rDNA was compared to the NCBI GenBank database.
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Publication 2023
Bacteria DNA, Ribosomal Escherichia coli Glucose Oomycetes Pseudomonas aeruginosa Pythium Solanum tuberosum Strains Vaccination
A total of 166 core genes in the genomes of 10 Pythium insidiosum strains and 5 other Pythium species (Table S1) were used for phylogenetic analysis. These genes were selected by scanning through our homologous gene cluster data for genes present in all 15 genomes that did not possess length variations of more than 45% relative to the longest representative gene in each cluster (or each row in the Pythium Gene Table). Nucleotide sequences of each gene from all genomes were aligned using ClustalW version 2 with default parameters [36 (link)]. All ClustalW alignment results were then subjected to gap removal and concatenated to produce a single multiple-sequence alignment file. FastTree2 was then used to create a maximum-likelihood tree [37 (link)]. A bootstrap analysis was carried out to test the reliability of the tree. Finally, the phylogenetic tree was visualized using FigTree v1.4.4 (http://tree.bio.ed.ac.uk/software/figtree/; accessed on 4 July 2022).
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Publication 2023
Base Sequence Gene Clusters Genes Genes, vif Genome Pythium Sequence Alignment Strains Trees
We compared gene contents across multiple genomes to investigate their genomic variability. All genes found in the genome of 10 P. insidiosum strains, together with the genome of 5 other Pythium species (Table 1), were subjected to a sequence-similarity-based gene-grouping process using our previously published protocol [35 (link)]. We used the following thresholds for each sequence comparison to group genes into the same cluster: BLAST E-value of 10−6, pairwise sequence identity of at least 30%, and pairwise sequence alignment coverage for both query and subject of at least 50%. These lenient criteria allowed the grouping of distant homologs and helped to minimize false positives in identifying group- or genome-specific genes (only present in a subset of genomes). With such criteria, if a particular gene is still not found in a genome, it is very likely that the gene is truly absent as opposed to present but may be significantly diverged from its corresponding orthologous genes found in other genomes. The final homologous gene cluster result is presented in table format, namely the Pythium Gene Table, where each row represents a gene and columns represent the 15 Pythium genomes used in this study. Each cell in the table contains information regarding homologous genes or genomic regions found in the corresponding genome.
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Publication 2023
Cells Gene Clusters Genes Genome Multiple Birth Offspring Pythium Sequence Alignment Strains
The next-generation-sequencing-derived genomes of 10 P. insidiosum strains isolated from humans, animals, and the environment of different locations around the world, as well as 5 other Pythium species (i.e., P. irregulare strain DAOM BR486, P. ultimum strain DAOM BR144, P. iwayamai strain DAOM BR242034, P. aphanidermatum strain DAOM BR444, and P. arrhenomanes strain ATCC 12531) from the public repository, were recruited and used in this study (Table 1). The rDNA ITS-based genotype (i.e., clade I, II, or III) was assigned to all P. insidiosum strains. The resulting contig sequences were subjected to gene prediction using the MAKER2 pipeline [32 (link)]. All predicted protein sequences were annotated by comparing them to the NCBI non-redundant database using BLASTP [33 (link)].
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Publication 2023
Amino Acid Sequence Animals DNA, Ribosomal Genes Genome Genotype Homo sapiens Pythium Strains

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More about "Pythium"

Pythium, a genus of water molds, is a significant concern for agricultural and horticultural professionals, causing devastating plant diseases across a wide range of crops.
These fungus-like organisms can infect vegetables, ornamentals, and field crops, leading to root rot, damping-off, and other devastating effects.
To effectively study and manage Pythium, researchers require reliable and reproducible protocols for accurate identification and characterization of these pathogens.
PubCompare.ai, an AI-driven tool, helps optimize Pythium research by intelligently comparing protocols from literature, preprints, and patents, enabling researchers to locate the best methodologies and enhance the quality and accuracy of their studies.
Experiance the future of research optimization with PubCompare.ai's cutting-edge technology.
This tool leverages advanced AI algorithms to analyze a vast collection of scientific literature, preprints, and patents, allowing researchers to quickly identify the most effective and reliable protocols for Pythium research.
By comparing and contrasting various methodologies, PubCompare.ai helps researchers make informed decisions, leading to more accurate and reproducible results.
Effective Pythium research often relies on specialized equipment and reagents, such as the CFX96 and QuantStudio 6 real-time PCR systems, the Rapid Extraction Kit for Fungi Genomic DNA, and the Phusion Hot Start II DNA Polymerase.
Additionally, the use of Phosphate-buffered saline (PBS) and Stellar competent cells can facilitate DNA extraction and cloning processes, while the Infinium BARCSoySNP6K BeadChip can aid in genetic studies of Pythium.
The DNAsecure Plant Kit is another valuable tool for extracting high-quality DNA from plant samples, essential for Pythium identification and characterization.
Metlaxyl, a fungicide commonly used to control Pythium, can also be an important consideration in Pythium research, as researchers may need to study the pathogen's response to this and other control measures.
By incorporating these resources and insights, researchers can optimize their Pythium studies, leading to more effective disease management strategies and a better understanding of these devastating plant pathogens.