Gene identification signature (GIS) analysis for transcriptome characterization and genome annotation

Abstract

We have developed a DNA tag sequencing and mapping strategy called gene identification signature (GIS) analysis, in which 5' and 3' signatures of full-length cDNAs are accurately extracted into paired-end ditags (PETs) that are concatenated for efficient sequencing and mapped to genome sequences to demarcate the transcription boundaries of every gene. GIS analysis is potentially 30-fold more efficient than standard cDNA sequencing approaches for transcriptome characterization. We demonstrated this approach with 116,252 PET sequences derived from mouse embryonic stem cells. Initial analysis of this dataset identified hundreds of previously uncharacterized transcripts, including alternative transcripts of known genes. We also uncovered several intergenically spliced and unusual fusion transcripts, one of which was confirmed as a trans-splicing event and was differentially expressed. The concept of paired-end ditagging described here for transcriptome analysis can also be applied to whole-genome analysis of cis-regulatory and other DNA elements and represents an important technological advance for genome annotation.

Genomic analysis of human microRNA transcripts

“…GIS analysis covalently links the 5Ј and 3Ј signatures of each full-length transcript into a paired-end ditag (PET) (38). Ditags provide unique identifiers for transcript 5Ј and 3Ј ends and are useful in defining their boundaries (38,39).…”

“…Ditags provide unique identifiers for transcript 5Ј and 3Ј ends and are useful in defining their boundaries (38,39). The prediction of TSS sites/CpG islands can be supported by mapping the 5Ј end of ditags or 5Ј CAGE tags in the upstream region.…”

The use of high-throughput sequencing methods for plant microRNA research

“…One of the highly efficient approaches is RNA-PET-seq. [24][25][26][27] RNA-PET-seq is a paired-end tag sequencing method for full-length mRNA analysis based on the HTS platform. Different from RNA-seq that treating the randomly sheared shortgun RNA fragments as sequencing libraries, RNA-PET-seq enables us to simultaneously capture the 5 0 and the 3 0 ends of the full-length transcripts on a transcriptome-wide scale (Fig.…”

“…In addition to its ability to quantify the transcription levels of the genes, the most important use of RNA-PET is to demarcate the boundaries of the transcription units. [24][25][26][27] Since the RNA-PET sequencing libraries are prepared from poly(A)-tailed transcripts, the pri-miRNAs could be included for PET sequencing. Thus, a combinatorial use of the PET tags and the RNA-seq reads could be a high-throughput strategy enabling us to delineate the transcriptional regions of the miRNA genes, and to quantify the abundances of the pri-miRNAs.…”

Inference of Isoforms from Short Sequence Reads

“…A large amount of work has been devoted to transcriptomics, which includes the international projects EST (Boguski et al, 1994;Boguski, 1995), FANTOM (The FANTOM Consortium, 2005), and ENCODE (The ENCODE Project Consortium, 2007;Weinstock, 2007). Many technologies have been introduced in recent years, including array-based experimental methods such as tiling arrays (Bertone et al, 2004), exon arrays (Kwan et al, 2008), and exon-junction arrays ( Johnson et al, 2003;Kapranov et al, 2007); and tag-based approaches such as MPSS (Brenner et al, 2000;Reinartz et al, 2002), SAGE (Velculescu et al, 1995;Harbers and Carninci, 2005), CAGE (Shiraki et al, 2003;Kodzius et al, 2005), PMAGE (Kim et al, 2007), and GIS (Ng et al, 2005). However, due to various constraints intrinsic to these technologies, the speed of advance in transcriptomics is far from being satisfactory, especially on eukaryotic species because of widespread alternative splicing events.…”