Web supplement to
"A Unified Model for Yeast Transcript Definition"

Identifying genes in the genomic context is central to a cell's ability to interpret the genome. Yet, in general, the signals used to define eukaryotic genes are poorly described. Here, we derived simple classifiers that identify where transcription will initiate and terminate using nucleic acid sequence features detectable by the yeast cell, which we integrate into a Unified Model (UM) that models transcription as a whole. The cis-elements that denote where transcription initiates function primarily through nucleosome depletion, and, using a synthetic promoter system, we show that most of these elements are sufficient to initiate transcription in vivo. Hrp1 binding sites are the major characteristic of terminators; these binding sites are often clustered in terminator regions, and can terminate transcription bidirectionally. The UM predicts global transcript structure by modeling the entire process of transcription using a hidden Markov model whose emissions are the outputs of the initiation and termination classifiers. We validated the novel predictions of the UM with available RNA-Seq data, and test it further by directly comparing the transcript structure predicted by the model to the transcription generated by the cell for synthetic DNA segments of random design. We show that the UM identifies transcription start sites more accurately than the initiation classifier alone, indicating that the relative arrangement of promoter and terminator elements influences their function. Our model presents a concrete description of how the cell defines transcript units, explains the existence of non-genic transcripts, and provides insight into genome evolution.

• Supplementary methods PDF describing supplementary methods
• Supplementary figures PDF containing the supplementary figures and figure legends
• Supplementary tables 2 and 3 Excel file containing the entire feature set originally included in the initiation and termination classifiers.

• Files required for calculating features, including the PFMs and di/trinucleotide based features.
• Positive and negative examples for the classifiers.
• Transcript State Map used for training the UM.
• UM Parameters, including the transition probabilities, observation means and variances, and the boxcox transformation lambdas (for turning classifier scores normal).
• Software used to generate the classifiers and UM, as well as the classifiers themselves and the UM parameters. This software is provided AS IS with no warrantee provided whatsoever. Feel free to use it as long as you acknowledge its source.

• All data pertaining to the combinatorial promoter library with the exception of the HiSeq read data below. This includes promoter sequences, contents, expression levels, FACS data, and initiation classifier scores.

Note the following sequencing files are very large, so please only download them off peak hours.

• README file describing the sequencing files.
• Barcode map describing the tags and what fluorescence bin they correspond to.
• Mapping library to which the reads were mapped using bowtie.
• First read.
• Second read - barcode.
• Third read.

• All data, including Agilent array layout, raw data, normalized data, genome browser tracks, and the design log for the 3kb pieces.

May 2008 Genome Version

• All classifiers, including initiation termination.
• All UM tracks. Chr1-8 only.
• Predicted transcripts across chr1-8.
• Novel transcripts that don't correspond to known features across chr1-8.

20110203 R64 Genome Version

These are the same tracks as those available in the genome browser.

• All classifiers, including initiation and termination.
• All UM tracks for Chr1-8 only.