Identifying transcription factor functions and targets by phenotypic activation

Gordon Chua [1], Quaid D. Morris [1,2,3], Richelle Sopko [4], Mark D. Robinson [1,3], Owen Ryan [4], Esther T. Chan [4], Brendan J. Frey [1,3], Brenda J. Andrews [1,4], Charles Boone [1,4], Timothy R. Hughes[1,4§]

[1] Banting and Best Department of Medical Research
[2] Department of Computer Science
[3] Department of Electrical and Computer Engineering
[4] Department of Medical Genetics and Microbiology
University of Toronto, 160 College Street, Toronto, Ontario, M5S 1A8

§Corresponding author: t.hughes@utoronto.ca 416-946-7838 FAX: 416-978-8528

Summary

Mapping transcriptional regulatory networks is difficult because many transcription factors are activated only under specific conditions. We describe a generic strategy for identifying genes and pathways induced by individual transcription factors that does not require knowledge of their normal activation cues. Microarray analysis of 55 yeast transcription factors that caused a growth phenotype when overexpressed showed that the majority caused increased transcript levels of genes in specific physiological categories, suggesting a mechanism for growth inhibition. Induced genes typically included established targets and genes with consensus promoter motifs, if known, suggesting that these data are useful for identifying potential new target genes and binding sites. We identified the sequence 5’-TCACGCAA as a binding sequence for Hms1p, a transcription factor that positively regulates pseudohyphal growth and previously had no known motif. The general strategy outlined here presents a straightforward approach to discovery of transcription factor activities and mapping targets that could be adapted to any organism with transgenic technology.

Supplementary Data:

• Sequence data
  • ORF list [xls]
  • Promoter sequences [fasta]

• S. cerevisiae chromosome features
  • Sorted table from SGD [tab]
  • README file with description of columns [txt]

• Array Design
  • Array (spot map) [xls]

• Microarray data
  • Overexpression mutant normalized log ratios [xls]
  • Deletion mutant normalized log ratios [xls]
  • README for microarray data notation [txt] (NEW)

• Experiments passing quality control measures
  • List of experiments [xls]

• Combined Z-scores for all 106 experiments
  • Z-scores [xls]

• Z-scores for an additional 23 TFs without slow growth phenotype
  • Z-scores [txt, xls]

• Gene ontology functional enrichment
  • Scores [txt].

    The absolute value of each element in the table is the -log (base 10) of the WMW P-value for enrichment of the GO annotation (row) in either the up- or down-regulated genes for a given mutant (column). The sign of the elements indicates whether the term was enriched in the up-regulated (positive) or down-regulated (negative) genes. Zero elements indicates GO annotation/gene pairs whose WMW P-value had an FDR > 0.05 after correcting for testing against multiple GO categories.

• Gene ontology annotations
  • GO biological process annotations [txt, zip]

• Motifs (known and as predicted by RankMotif)
  • Description of the RankMotif algorithm [doc] (NEW)
  • Motifs for upregulated ORFs from overexpressed TF mutants [txt]
  • Motifs for downregulated ORFs from overexpressed TF mutants [txt]
  • Motifs for upregulated ORFs from deletion TF mutants [txt]
  • Motifs for downregulated ORFs from deletion TF mutants [txt]

• P-value calculations for motif matches
  • Description of the algorithm [doc]
  • Matlab function [M-file]