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RACE-Seq: Extension of human lncRNA transcripts by RACE coupled with long read high-throughput sequencing

Welcome to the companion website of Lagarde, Uszczynska-Ratajczak et al., Nature Communications 2016.

Summary

Long noncoding RNAs (lncRNAs) constitute a large, yet mostly uncharacterized fraction of the mammalian transcriptome. Such characterization requires a comprehensive, high-quality annotation of their gene structure and boundaries, which is currently lacking. Here, we describe RACE-Seq, an experimental workflow designed to address this based on RACE (Rapid Amplification of cDNA ends) and long-read RNA sequencing. We apply RACE-Seq to 398 human lncRNA genes in seven tissues, leading to the discovery of 2,556 on-target, novel transcripts. 60% of the targeted loci are extended in either 5' or 3', often reaching genomic hallmarks of gene boundaries. Analysis of the novel transcripts suggests that lncRNAs are as long, have as many exons and undergo as much alternative splicing as protein-coding genes, contrary to current assumptions. Overall, we show that RACE-Seq is an effective tool to annotate an organism’s deep transcriptome, and compares favorably to other targeted sequencing techniques.

Supplementary Data Access

lncRNA transcript targets and RACE primers

Detailed information about GENCODE v7 targets as well as the RACE primers used in this study can be found in the Supplementary Data of the article.

Raw sequencing data

All FASTQ files generated in this experiment are downloadable from the European Nucleotide Archive (accession: ERP012249).

Track Hub

Track Hubs allow convenient, in-context visualization of custom sets of tracks in genome browsers. We have registered a Track Hub Registry entry, with links loading the RACE-Seq track hub directly into the UCSC Genome Browser and Ensembl.
 
  The RACE-Seq track hub is based on genome assembly GRCh37 (a.k.a. hg19) and includes the following RACE-Seq tracks/datasets:

• GENCODE v7 test cases (i.e. pre-RACE-Seq lncRNA targets):
  
• Targeted lncRNA transcripts (BED, hg19)
  
• Post-RACE-Seq manually curated transcript models:
• All transcript models (BED, hg19)
• 5'RACE models only (BED, hg19)
• 3'RACE models only (BED, hg19)
  
• 5' and 3' RACE primers
• 454 RACE-Seq read alignments (GMAP BAM files)

RACE-Seq transcript model support by tissue

For each assayed tissue, we provide a list of detected RACE-Seq transcript models: Brain, Heart, Kidney, Liver, Lung, Spleen, Testis.

Transcription Start Sites (RACE-Seq and Capture-Seq)

  Collapsed, non-redundant sets of TSSs (in BED format) are linked below. "Raw" TSSs were clustered using the "bedtools merge -nms -n -s -d 50" command.

• RACE-Seq: All, novel, CAGE-supported

• CaptureSeq: All, novel, CAGE-supported

Contact

Questions, requests and comments about this study should be addressed to:

• Julien Lagarde (CRG, Barcelona, Spain): julien.lagarde AT crg.cat
  
• Barbara Uszczynska-Ratajczak (CRG, Barcelona, Spain): barbara.uszczynska AT crg.cat
  
• Jen Harrow (Sanger Institute, Hinxton, UK): harrow.jen AT gmail.com
  
• Roderic Guigó (CRG, Barcelona, Spain): roderic.guigo AT crg.cat