NLRscape

NLRscape catalogs and analyzes NOD-like receptor (NLR) protein sequences in plants to characterize domain architectures, sequence diversity, and taxonomic distribution for studies of NLR diversity and evolution, using a curated dataset of over 80,000 plant protein sequences from UniProtKB and integrated domain and motif annotations from multiple third-party databases together with in‑house annotations.

Key Features:

• Curated dataset: A collection of over 80,000 plant protein sequences from UniProtKB identified as containing NOD-like receptor signatures.
• Integrated annotations: Domain and motif annotations combined from multiple third-party databases and advanced in‑house annotations.
• Sequence organization: Sequences organized by domain organization layout, global homology, and taxonomic distribution.
• Analytical perspectives: Supports both landscape-wide (top-down) analyses and sequence-centered (bottom-up) analyses.
• Clustering: Generation of custom clusters centered around specific sequences to examine local homology relationships.
• Sequence and structural analyses: Production of multiple sequence alignments (MSAs) and identity matrices with synchronized secondary structure predictions and motif annotations.
• Visualization outputs: Generation of taxonomy distribution plots and homology cluster graphs.

Scientific Applications:

• Evolutionary analysis: Characterizing the diversity and evolutionary dynamics of plant NLR proteins across taxa.
• Trait distribution studies: Analyzing how specific domain architectures, motifs, or other traits within NLR families are distributed across the plant kingdom.
• Homology inference: Inferring homology relationships and constructing homology clusters and identity matrices for comparative analyses.
• Domain and motif annotation: Annotating and comparing domain layouts, conserved motifs, and secondary structure features within NLR repertoires.

Methodology:

Curates sequences from UniProtKB; integrates domain and motif annotations from multiple third-party databases and in‑house annotations; organizes sequences by domain layout, global homology, and taxonomy; and generates custom clusters, MSAs, identity matrices, homology cluster graphs, and taxonomy distribution plots with secondary structure predictions synchronized to motif annotations.