<?xml version="1.0" encoding="UTF-8"?>
<STUDY_SET xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <STUDY center_name="GEO" alias="GSE24538" accession="SRP003781">
    <IDENTIFIERS>
      <PRIMARY_ID>SRP003781</PRIMARY_ID>
      <EXTERNAL_ID namespace="BioProject" label="primary">PRJNA132563</EXTERNAL_ID>
      <EXTERNAL_ID namespace="GEO">GSE24538</EXTERNAL_ID>
    </IDENTIFIERS>
    <DESCRIPTOR>
      <STUDY_TITLE>Ab initio identification of transcription start sites (TSSs) in the Rhesus macaque genome by histone modification and RNA-Seq</STUDY_TITLE>
      <STUDY_TYPE existing_study_type="Other"/>
      <STUDY_ABSTRACT>We addressed the lack of experimentally supported transcript annotations in the Rhesus macaque genome by ab initio identification of the transcription start sites (TSSs). We took advantage of histone H3 lysine 4 trimethylation (H3K4me3)''s ability to mark TSSs and the recently developed ChIP-Seq and RNA-Seq technology to survey the transcript structures in the macaque brain. We then integrated the two types of our newly generated data with genomic sequence features and extended a TSS prediction algorithm to ab initio predict and verify 16,833 of previously electronically annotated transcription start sites at 500 bp resolution and predicted ~10,000 new TSSs. Overall design: We took advantage of histone H3 lysine 4 trimethylation (H3K4me3)’s ability to mark transcription start sites (TSSs) and the recently developed ChIP-Seq and RNA-Seq technology to survey the transcript structures. By integrating the ChIP-seq, RNA-seq and small RNA-seq data (previously uploaded to GEO as GSM450615 by our collaborator) with genomic sequence features and extending and improving a state-of-the-art TSS prediction algorithm, we ab initio predicted and verified previously electronically annotated TSSs at a high resolution, and  predicted some novel TSSs.</STUDY_ABSTRACT>
      <CENTER_PROJECT_NAME>GSE24538</CENTER_PROJECT_NAME>
    </DESCRIPTOR>
    <STUDY_LINKS>
      <STUDY_LINK>
        <XREF_LINK>
          <DB>pubmed</DB>
          <ID>20952408</ID>
        </XREF_LINK>
      </STUDY_LINK>
    </STUDY_LINKS>
  </STUDY>
</STUDY_SET>
