PPNID

PPNID identifies plant-parasitic nematode species using authenticated barcoding sequences and phylogenetic and distance-based analyses to support taxonomic, ecological, and agricultural research.


Key Features:

  • Manually Curated Database: Provides a collection of authenticated barcoding sequences for plant-parasitic nematodes.
  • Automatic Pipeline: Executes an automated pipeline for rapid species identification from query sequences.
  • Alignment Functionality: Performs sequence alignments to examine mutation distribution and detect nucleotide autapomorphies for species delimitation.
  • Genetic Distance Analysis: Computes genetic distances to assess relationships among sequences.
  • Plot and Maximum Likelihood Phylogeny Analysis: Produces plots and infers maximum likelihood phylogenies to support phylogenetic species delimitation beyond simple similarity searching.

Scientific Applications:

  • Ecological Studies: Enables accurate identification of plant-parasitic nematodes for ecological surveys and biodiversity assessments.
  • Agricultural Management: Supports diagnosis and monitoring of PPNs to mitigate the economic impact of these pests on agriculture.
  • Taxonomic Classification: Assists taxonomic classification and species delimitation through autapomorphy detection and phylogenetic analyses.
  • Phylogenetic Research: Facilitates reconstruction of nematode evolutionary relationships using maximum likelihood phylogenies and genetic distance analyses.

Methodology:

Uses an automated species-identification pipeline, sequence alignment to examine mutation distribution and identify nucleotide autapomorphies, genetic distance analysis, plotting, and maximum likelihood phylogeny inference, alongside similarity searching.

Topics

Details

License:
GPL-3.0
Added:
11/14/2019
Last Updated:
1/17/2021

Operations

Publications

Qing X, Wang M, Karssen G, Bucki P, Bert W, Braun-Miyara S. PPNID: a reference database and molecular identification pipeline for plant-parasitic nematodes. Bioinformatics. 2019;36(4):1052-1056. doi:10.1093/bioinformatics/btz707. PMID:31529041.

PMID: 31529041
Funding: - Chief Scientist of the Ministry of Agriculture and Rural Development, Israel: 20-07-0012

Documentation