Y2H-SCORES

Y2H-SCORES computes statistical scores to infer protein-protein interactions from next-generation yeast-two-hybrid (Y2H-NGIS) sequencing data for high-throughput interaction screening.

Key Features:

• Statistical Framework: Integrates normalization and control considerations to evaluate protein-protein interactions from Y2H-NGIS data.
• Quantitative Ranking Scores: Implements three scores—Significant Enrichment Score to measure enrichment under selection, Specificity Score to compare multi-bait scenarios and discern specific from non-specific interactions, and In-frame Interactor Selection to prioritize in-frame prey likely to be biologically relevant.
• Simulation and Empirical Validation: Uses simulation models and empirical datasets to assess and predict interacting partners and to facilitate independent confirmation via one-to-one bait-prey tests.
• Optimization Strategies: Identifies optimal experimental conditions such as prey library normalization, maintaining larger culture volumes, and replicating treatments to improve detection of true interactors.
• Versatility Across Yeast-Based Screens: Adapts to different yeast-based interaction screenings by applying enrichment, specificity, and in-frame selection principles.

Scientific Applications:

• Interactome Construction: Provides high-confidence metrics to support genome-wide interactome mapping and the exploration of complex protein interaction networks.
• Experimental Prioritization and Validation: Ranks candidate interactors for follow-up testing and was used to identify and validate the interaction between the barley powdery mildew effector AVRA13 and HvTHF1.
• Multi-Bait Specificity Analysis: Enables discrimination of specific versus non-specific interactors across multi-bait Y2H experiments.

Methodology:

Performs computational and statistical evaluation of Y2H-NGIS data by integrating normalization and control considerations, calculating three quantitative scores (Significant Enrichment, Specificity, In-frame), and using simulation models alongside empirical datasets for score assessment.