PHD1
S. cerevisiae
Phd1p
What the model saw
Gene: PHD1 Organism: Saccharomyces cerevisiae Known functions: Phd1p. DNA binding. DNA-binding transcription factor activity. sequence-specific DNA binding.
View unredacted entry
Phd1p. DNA binding. DNA-binding transcription factor activity. sequence-specific DNA binding.
Solver output
PHD1 encodes a sequence-specific DNA-binding transcription factor in S. cerevisiae that is a homolog of the filamentous growth regulator StuA in fungi. Phd1p promotes pseudohyphal/invasive growth and stress response programs by activating downstream transcriptional targets. Transcription factors that coordinate stress response and metabolic adaptation programs are frequently associated with extended lifespan in yeast, as they can upregulate protective gene expression. However, PHD1's primary characterized role is in developmental transitions (pseudohyphal growth) rather than canonical longevity pathways such as TOR or sirtuins, making the connection to longevity indirect. The pro-longevity prediction is tentative, based on the general principle that transcription factors driving stress-responsive and adaptive gene expression programs tend to support organismal fitness and longevity.
GenAge curators classify each gene's normal function as promoting (Pro-Longevity) or opposing (Anti-Longevity) longevity, based on synthesis across studies. Loss-of-function effects can vary from this depending on the manipulation.
Advisor judgment
The model predicted pro_longevity while the ground truth is anti_longevity. The model's reasoning is speculative and generic - it applies a broad heuristic that "stress-responsive transcription factors tend to support longevity" without specific knowledge of PHD1's actual role in yeast aging. PHD1 is actually anti-longevity in yeast, likely because it promotes pseudohyphal/invasive growth programs that divert resources from maintenance. The model correctly identified PHD1's role in pseudohyphal growth but then incorrectly extrapolated this to a pro-longevity effect. The confidence of 0.52 is low but still leans wrong. The reasoning quality is poor because it relies on generic principles rather than specific mechanistic knowledge, and the conclusion is incorrect.
Raw API responses
solver
{
"reasoning": "PHD1 encodes a sequence-specific DNA-binding transcription factor in S. cerevisiae that is a homolog of the filamentous growth regulator StuA in fungi. Phd1p promotes pseudohyphal/invasive growth and stress response programs by activating downstream transcriptional targets. Transcription factors that coordinate stress response and metabolic adaptation programs are frequently associated with extended lifespan in yeast, as they can upregulate protective gene expression. However, PHD1's primary characterized role is in developmental transitions (pseudohyphal growth) rather than canonical longevity pathways such as TOR or sirtuins, making the connection to longevity indirect. The pro-longevity prediction is tentative, based on the general principle that transcription factors driving stress-responsive and adaptive gene expression programs tend to support organismal fitness and longevity.",
"confidence": 0.52,
"key_pathways": [
"sequence-specific transcriptional regulation",
"pseudohyphal/invasive growth program",
"stress-responsive gene expression"
],
"mechanism_class": "other",
"longevity_influence": "pro_longevity"
}advisor
{
"notes": "The model predicted pro_longevity while the ground truth is anti_longevity. The model's reasoning is speculative and generic - it applies a broad heuristic that \"stress-responsive transcription factors tend to support longevity\" without specific knowledge of PHD1's actual role in yeast aging. PHD1 is actually anti-longevity in yeast, likely because it promotes pseudohyphal/invasive growth programs that divert resources from maintenance. The model correctly identified PHD1's role in pseudohyphal growth but then incorrectly extrapolated this to a pro-longevity effect. The confidence of 0.52 is low but still leans wrong. The reasoning quality is poor because it relies on generic principles rather than specific mechanistic knowledge, and the conclusion is incorrect.",
"failure_mode": "confident_wrong",
"answer_correct": false,
"mechanism_correct": false,
"reasoning_quality": 2,
"ground_truth_questionable": false
}