TSS assembly pipeline for Zm_EPDnew_001
This document provides a technical description of the transcription
start site assembly pipeline that was used to generate EPDnew
version 001 for Z. mays
Oct 2013 B73 RefGen_v3/zm3
Mejía-Guerra et al., 2015
Assembly pipeline overview
Description of procedures and intermediate data files
1. Download annotated TSS
Data was downloaded from
Transcrips have been filtered according to the following rules:
- Transcripts of protein coding genes only
- Transcript lies on full chromosomes
- Transcripts have a non-empty description field
Gene names were taken from the field "Gene stable ID". Since the
EPD format doesn't allow gene names longer than 18 characters,
we checked whether the names repsected this limitation.
A total number of 35171 promoters were selected.
2. Gramene TSS collection
The Gramene TSS collection is stored as a tab-deliminated text file
conforming to the SGA format under the name:
The six field contain the following kinds of information:
- NCBI/RefSeq chromosome id
- strand ("+" or "-")
- gene stable ID
Note that the second and forth fields are invariant.
3. Import CAGE data
Data was imported from GEO as SRA file format. Raw sequence files were
mapped to zm3 genome using Bowtie. The resulting BAM files were
converted to SGA file format using ChIP-Convert
5. mRNA 5' tags peak calling
For each individual sample (8), peak calling for the merged file has been
carried out using ChIP-Peak
on-line tool with the following parameters:
- Window width = 200
- Vicinity range = 200
- Peak refine = Y
- Count cutoff = 9999999
- Threshold = 5
6. TSS validation and shifting
Each sample in the collection (mRNA peaks and Gramene TSS) was then
separately processed in a pipeline aiming at validating transcription
start sites with mRNA peaks. A Gramene TSS was experimentally confirmed
if an mRNA peak lied in a window of 500 bp around it. The validated
TSS was then shifted to the nearest base with the higher tag
7. UCSC not-validated TSS
The total number (summing up all samples) of non experimentally validated TSS was around 15000.
8. Promoter collection for each sample
Each sample in the dataset was used to generate a separate
promoter collection. Potentially, the same transcript could be
validated by multiple samples and it could have different start
sites in different samples. To avoid redundancy, the individual
collections were used as input for an additional step in the
analysis (Assembly pipeline part B).
9. Merging collections and second TSS selection
The 8 promoter collections were merged into a unique file and
further analysed. Transcript
validated by multiple samples could potentially have the TSS set
on a broader region and not to single position. To avoid such
inconsistency, for each transcript we selected the position that
was validated by the larger number of samples as the true TSS.
Different TSSs that belong to the same gene were classified according
to their global expression level. The primary TSSs of a gene (marked with an '_1' at the end of the ID) have always the highest expression level followed by all the other in decreasing order of expression (marked as '_2', '_3', etc.).
Transcription Start Sites that mapped closed to other TSS that
belonged to the same gene (500 bp window) were merged into a
unique promoter following the same rule: the promoter that was
validated by the higher number of samples was kept.
10. Final EPDnew collection
The 17000 experimentally validated promoter were stored in the
EPDnew database that can be downloaded from our ftp
site. Scientist are wellcome to use our other tools ChIP-Seq
correlation analysis) and SSA
(for motifs analysis
around promoters) to analyse EPDnew database.