Next-generation tag sequencing for cancer gene expression profiling Export

@article{citeulike:5145344, abstract = {10.1101/gr.094482.109 We describe a new method, Tag-seq, which employs ultra high-throughput sequencing of 21 base pair cDNA tags for sensitive and cost-effective gene expression profiling. We compared Tag-seq data to LongSAGE data and observed improved representation of several classes of rare transcripts, including transcription factors, antisense transcripts, and intronic sequences, the latter possibly representing novel exons or genes. We observed increases in the diversity, abundance, and dynamic range of such rare transcripts and took advantage of the greater dynamic range of expression to identify, in cancers and normal libraries, altered expression ratios of alternative transcript isoforms. The strand-specific information of Tag-seq reads further allowed us to detect altered expression ratios of sense and antisense (S-AS) transcripts between cancer and normal libraries. S-AS transcripts were enriched in known cancer genes, while transcript isoforms were enriched in miRNA targeting sites. We found that transcript abundance had a stronger GC-bias in LongSAGE than Tag-seq, such that AT-rich tags were less abundant than GC-rich tags in LongSAGE. Tag-seq also performed better in gene discovery, identifying >98\% of genes detected by LongSAGE and profiling a distinct subset of the transcriptome characterized by AT-rich genes, which was expressed at levels below those detectable by LongSAGE. Overall, Tag-seq is sensitive to rare transcripts, has less sequence composition bias relative to LongSAGE, and allows differential expression analysis for a greater range of transcripts, including transcripts encoding important regulatory molecules.}, author = {Morrissy, A. Sorana and Morin, Ryan D. and Delaney, Allen and Zeng, Thomas and McDonald, Helen and Jones, Steven and Zhao, Yongjun and Hirst, Martin and Marra, Marco A.}, citeulike-article-id = {5145344}, citeulike-linkout-0 = {http://dx.doi.org/10.1101/gr.094482.109}, citeulike-linkout-1 = {http://genome.cshlp.org/content/early/2009/07/10/gr.094482.109.abstract}, citeulike-linkout-2 = {http://genome.cshlp.org/content/early/2009/07/10/gr.094482.109.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19541910}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19541910}, day = {10}, doi = {10.1101/gr.094482.109}, issn = {1088-9051}, journal = {Genome Research}, keywords = {expression, gene, illumina, profiling, solexa, tag}, month = {October}, number = {10}, pages = {1825--1835}, posted-at = {2009-10-08 14:18:17}, priority = {3}, title = {Next-generation tag sequencing for cancer gene expression profiling}, url = {http://dx.doi.org/10.1101/gr.094482.109}, volume = {19}, year = {2009} }

TY - JOUR ID - citeulike:5145344 L3 - citeulike-article-id:5145344 N2 - 10.1101/gr.094482.109 We describe a new method, Tag-seq, which employs ultra high-throughput sequencing of 21 base pair cDNA tags for sensitive and cost-effective gene expression profiling. We compared Tag-seq data to LongSAGE data and observed improved representation of several classes of rare transcripts, including transcription factors, antisense transcripts, and intronic sequences, the latter possibly representing novel exons or genes. We observed increases in the diversity, abundance, and dynamic range of such rare transcripts and took advantage of the greater dynamic range of expression to identify, in cancers and normal libraries, altered expression ratios of alternative transcript isoforms. The strand-specific information of Tag-seq reads further allowed us to detect altered expression ratios of sense and antisense (S-AS) transcripts between cancer and normal libraries. S-AS transcripts were enriched in known cancer genes, while transcript isoforms were enriched in miRNA targeting sites. We found that transcript abundance had a stronger GC-bias in LongSAGE than Tag-seq, such that AT-rich tags were less abundant than GC-rich tags in LongSAGE. Tag-seq also performed better in gene discovery, identifying >98% of genes detected by LongSAGE and profiling a distinct subset of the transcriptome characterized by AT-rich genes, which was expressed at levels below those detectable by LongSAGE. Overall, Tag-seq is sensitive to rare transcripts, has less sequence composition bias relative to LongSAGE, and allows differential expression analysis for a greater range of transcripts, including transcripts encoding important regulatory molecules. IS - 10 JF - Genome Research SN - 1088-9051 EP - 1835 TI - Next-generation tag sequencing for cancer gene expression profiling VL - 19 SP - 1825 KW - expression KW - gene KW - illumina KW - profiling KW - solexa KW - tag AU - Morrissy, Sorana AU - Morin, Ryan AU - Delaney, Allen AU - Zeng, Thomas AU - McDonald, Helen AU - Jones, Steven AU - Zhao, Yongjun AU - Hirst, Martin AU - Marra, Marco PY - 2009/10/10/ UR - http://dx.doi.org/10.1101/gr.094482.109 ER -