Related Experiment Videos
Targeting a complex transcriptome: the construction of the mouse full-length cDNA encyclopedia.
Piero Carninci1, Kazunori Waki, Toshiyuki Shiraki
1Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center (GSC), RIKEN Yokohama Institute, Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
Genome Research
|June 24, 2003
Summary
Researchers created the most extensive mouse full-length complementary DNA (cDNA) encyclopedia, revealing novel insights into the complex transcriptome. This comprehensive resource significantly advances our understanding of gene expression and regulation in mammals.
Area of Science:
- Transcriptomics
- Molecular Biology
- Genomics
Background:
- The mouse transcriptome is complex and incompletely understood.
- Previous efforts have not provided a comprehensive view of full-length complementary DNAs (cDNAs).
Purpose of the Study:
- To construct the most extensive mouse full-length cDNA encyclopedia.
- To provide an unprecedented view of a complex transcriptome.
- To identify novel transcriptional units and regulatory elements.
Main Methods:
- Preparation and sequencing of 246 cDNA libraries.
- Enrichment of full-length cDNAs using Cap-Trapper technology.
- Aggressive subtraction/normalization of cDNAs.
- Clustering of 3'-end and 5'-end reads.
- Annotation using FANTOM-2 database.
Main Results:
- Generated over 1.4 million 3'-end sequences and 547,000 5'-end reads.
- Clustered cDNAs into 70,000 transcriptional units (TUs), representing the highest transcriptome coverage to date.
- Defined Tentative Equivalent Coverage (TEC) estimated to be equivalent to over 12 million standard ESTs.
- Identified potential promoters for 8,637 known genes and nearly 63,000 transcriptional starting points.
- Estimated that at least half of singletons represent real messenger RNAs (mRNAs).
Conclusions:
- The mouse full-length cDNA encyclopedia offers the most extensive view of a complex transcriptome to date.
- High coverage explains discrepancies with genome annotation gene counts and highlights the importance of non-protein-coding RNAs.
- Transcriptome discovery is ongoing, with significant potential for further findings.