PolyA-Seq Track Settings
 
Poly(A)-sequencing from Merck Research Laboratories   (All mRNA and EST tracks)

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 Brain  Reverse  Signal  Poly(A)-tail sequencing of Brain from Merck (Rev strand)   Schema 
 
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 Liver  Forward  Signal  Poly(A)-tail sequencing of Liver from Merck (Fwd strand)   Schema 
 
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 MAQC Brain 1  Reverse  Signal  Poly(A)-tail sequencing of MAQC Brain (replicate 1) from Merck (Rev strand)   Schema 
 
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 MAQC Brain 1  Forward  Signal  Poly(A)-tail sequencing of MAQC Brain (replicate 1) from Merck (Fwd strand)   Schema 
 
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 MAQC Brain 2  Reverse  Signal  Poly(A)-tail sequencing of MAQC Brain (replicate 2) from Merck (Rev strand)   Schema 
 
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 MAQC Brain 2  Forward  Signal  Poly(A)-tail sequencing of MAQC Brain (replicate 2) from Merck (Fwd strand)   Schema 
 
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 MAQC UHR 1  Reverse  Signal  Poly(A)-tail sequencing of MAQC UHR (replicate 1) from Merck (Rev strand)   Schema 
 
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 MAQC UHR 1  Forward  Signal  Poly(A)-tail sequencing of MAQC UHR (replicate 1) from Merck (Fwd strand)   Schema 
 
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 MAQC UHR 2  Reverse  Signal  Poly(A)-tail sequencing of MAQC UHR (replicate 2) from Merck (Rev strand)   Schema 
 
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 MAQC UHR 2  Forward  Signal  Poly(A)-tail sequencing of MAQC UHR (replicate 2) from Merck (Fwd strand)   Schema 
 
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 Muscle  Reverse  Signal  Poly(A)-tail sequencing of Muscle from Merck (Rev strand)   Schema 
 
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 Muscle  Forward  Signal  Poly(A)-tail sequencing of Muscle from Merck (Fwd strand)   Schema 
 
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 Testis  Reverse  Signal  Poly(A)-tail sequencing of Testis from Merck (Rev strand)   Schema 
 
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 Testis  Forward  Signal  Poly(A)-tail sequencing of Testis from Merck (Fwd strand)   Schema 
    

Description

This track displays the location of RNA polyadenylation (polyA) sites based on high-throughput RNA sequencing using the PolyA-seq protocol.

PolyA-Seq data is strand-specific, therefore two tracks are provided for each tissue. PolyA site positions correspond to a single base, namely the ends of read alignments immediately upstream of the polyadenylation site. The data provided in this track consists of filtered polyA sites (see Methods). When multiple sites occurred within a 30-bp window on the same strand, the sum of the reads was attributed to the site with the most reads. Units are in reads per million (RPM) aligned. To obtain read counts, multiply RPM values by the total number of filtered reads for the corresponding experiment:

Sample Filtered reads
MAQC Universal Human Reference 1 5057048
MAQC Universal Human Reference 2 5030985
MAQC Brain 1 4086039
MAQC Brain 2 3921040
Brain 2980439
Kidney 4626843
Liver 5626271
Muscle 4920121
Testis 5098780

Display Conventions and Configuration

These tracks may be configured in a variety of ways to highlight different aspects of the displayed data. The graphical configuration options are shown at the top of the track description page. For more information, see Configuring graph-based tracks.

In the full and pack display modes, forward-strand tracks are shown in red and reverse-strand tracks are shown in black. In the squish and dense display modes, intensity is represented in grayscale (the darker the shading, the higher the intensity). To show only selected subtracks, uncheck the boxes next to the tracks that you wish to hide.

Methods

A detailed explanation of the experimental methods is provided at NCBI's Gene Expression Omnibus under accession GSE30198. Briefly, PolyA+ RNA was reverse-transcribed using a T(10)VN primer and strand-specific universal adapters, amplified, and sequenced on an Illumina GAIIx sequencer. Reads were reverse-complemented, aligned to the corresponding reference genome and splice junctions, and retained only if they aligned uniquely. 3' ends of alignments were considered polyA sites. Sites were then filtered using downstream base frequency matrices for true- and false-positive sites determined from a modified experiment based on a T(10) primer (i.e., excluding the 3' VN). When multiple filtered sites occurred within a 30-nt window on the same strand, read counts were summed and attributed to the most abundant peak. For each tissue, read counts were then divided by the total number of reads, in millions, from all filtered sites.

Credits

These data were generated at Merck Research Laboratories and submitted by Adnan Derti and Tomas Babak.

Data Release Policy

No restrictions.