RNA-Seq mapping and detection of gene fusions with a suffix array algorithm.

High-throughput RNA sequencing enables quantification of transcripts (both known and novel), exon/exon junctions and fusions of exons from different genes. Discovery of gene fusions-particularly those expressed with low abundance- is a challenge with short- and medium-length sequencing reads. To address this challenge, we implemented an RNA-Seq mapping pipeline within the LifeScope software. We introduced new features including filter and junction mapping, annotation-aided pairing rescue and accurate mapping quality values. We combined this pipeline with a Suffix Array Spliced Read (SASR) aligner to detect chimeric transcripts. Performing paired-end RNA-Seq of the breast cancer cell line MCF-7 using the SOLiD system, we called 40 gene fusions among over 120,000 splicing junctions. We validated 36 of these 40 fusions with TaqMan assays, of which 25 were expressed in MCF-7 but not the Human Brain Reference. An intra-chromosomal gene fusion involving the estrogen receptor alpha gene ESR1, and another involving the RPS6KB1 (Ribosomal protein S6 kinase beta-1) were recurrently expressed in a number of breast tumor cell lines and a clinical tumor sample.

mRNA-Seq whole-transcriptome analysis of a single cell.

Next-generation sequencing technology is a powerful tool for transcriptome analysis. However, under certain conditions, only a small amount of material is available, which requires more sensitive techniques that can preferably be used at the single-cell level. Here we describe a single-cell digital gene expression profiling assay. Using our mRNA-Seq assay with only a single mouse blastomere, we detected the expression of 75% (5,270) more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads. Moreover, 8-19% of the genes with multiple known transcript isoforms expressed at least two isoforms in the same blastomere or oocyte, which unambiguously demonstrated the complexity of the transcript variants at whole-genome scale in individual cells. Finally, for Dicer1(-/-) and Ago2(-/-) (Eif2c2(-/-)) oocytes, we found that 1,696 and 1,553 genes, respectively, were abnormally upregulated compared to wild-type controls, with 619 genes in common.

Highly-multiplexed barcode sequencing: an efficient method for parallel analysis of pooled samples.

Next-generation sequencing has proven an extremely effective technology for molecular counting applications where the number of sequence reads provides a digital readout for RNA-seq, ChIP-seq, Tn-seq and other applications. The extremely large number of sequence reads that can be obtained per run permits the analysis of increasingly complex samples. For lower complexity samples, however, a point of diminishing returns is reached when the number of counts per sequence results in oversampling with no increase in data quality. A solution to making next-generation sequencing as efficient and affordable as possible involves assaying multiple samples in a single run. Here, we report the successful 96-plexing of complex pools of DNA barcoded yeast mutants and show that such 'Bar-seq' assessment of these samples is comparable with data provided by barcode microarrays, the current benchmark for this application. The cost reduction and increased throughput permitted by highly multiplexed sequencing will greatly expand the scope of chemogenomics assays and, equally importantly, the approach is suitable for other sequence counting applications that could benefit from massive parallelization.

Assessing gene expression variation in normal human tissues using GeneTag, a novel, global, sensitive profiling method.

GeneTag is a novel expression profiling method that allows the visualization, quantification and identification of expressed genes-whether known or novel-in any species, tissue or cell type, independent of knowledge of the underlying sequence. Here we describe the application of this method to determine variation of gene expression in individual human liver samples and the identification of tissue-specific genes by comparing expression patterns across several human organs. Expression data are stored in a database for future reference and data analysis relies on proprietary software, which allows complex comparisons to be performed. Differentially expressed genes are quickly identified through a link to a sequence database. The results from our study underscore the importance of knowledge of individual variation of gene expression for the design and interpretation of transcript profiling experiments in the context of any biological question.

mRNA-sequencing whole transcriptome analysis of a single cell on the SOLiD system.

We have developed a sequencing-based gene expression profiling assay at single-cell resolution by combining a modified single-cell whole transcriptome amplification method with the next generation sequencing technique, the SOLiD system. Using this assay, we have shown that blastomeres in a four-cell stage embryo have similar gene expression, which is compatible with the fact that they have similar developmental potential. We proved that compared with cDNA microarray technique, our single-cell cDNA SOLiD sequencing assay can detect expression of thousands of more genes. Moreover, for the genes detected by microarray and SOLiD sequencing, our assay detected new transcript variants for a large proportion of them, which confirms unambiguously at single-cell resolution that the transcriptome complexity is higher than expected traditionally. Finally, by using our assay to Dicer knockout (KO) and Ago2 KO oocytes, we showed that a significant amount of transposons were up-regulated abnormally in Dicer/Ago2 KO mature oocytes compared with wild-type controls.