Hello.

My colleagues and I have developed a high-throughput sequencing method
that identifies polyadenylation sites in a quantitative and
strand-specific manner. We're about to submit a manuscript that
describes the method as well as a sizeable data set that we've generated
on an Illumina sequencer. We're making the data public now (i.e.,
depositing reads and alignments in GEO and SRA), and we'd like to know
if UCSC would be interested in making our alignment tracks public.

The data consists of a mixture of 22 tissues in human, mouse, rat, dog
and rhesus; they're mostly normal tissues, but the human samples include
brain and UHR MAQC samples, as well as a breast tumor and matched
normal. In each tissue, we sequenced several tens of millions of 76-bp
reads (details will follow pending interest).

An example is attached that shows wiggle tracks for a human gene; for
simplicity, only reads for the sense strand are shown. The first figure
is on a linear scale and shows that a single polyadenylation site
dominates across all tissues. The second figure is a close-up of the 3'
UTR on a log scale; it shows that multiple polyadenylation variants are
present in every tissue, and that the UCSC and Refseq transcripts
correspond to minor polyadenylation sites.

We developed a computational method to filter false positives arising
from internal poly-A tracts. We would suggest a super-track for each
tissue that shows four tracks, namely reads from the forward and reverse
strands in separate colors, and all reads vs. filtered reads in distinct
shades.

 <<human.agpat6.polyA.png>>  <<human.agpat6.polyA.zoom.log.png>> 

Thanks, and please let me know if you'd like me to provide additional
information.

Adnan Derti
Senior Research Scientist
Merck Research Laboratories
Boston, MA
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