Transcriptional analysis of b-cells post flu vaccination using rna sequencing

RNA-Seq (Nagalakshmi, et al., 2008; Mortazavi, et al., 2008), also known as Whole transcriptome sequencing investigates the RNA content from a sample through high throughput sequencing of cDNA. This exciting technology has important applications such as the improvement of existing genome annotations, discovery of novel genes and transcripts (Roberts, et al., 2011), revealing alternative splicing events and measuring the differential expression of genes across samples. This study examines the transcriptional responses of B-cells to the influenza vaccine using RNA-Seq. Five subjects received the flu vaccine. RNA was extracted at 11 different time points and sequenced using RNA-Seq. The RNA-Seq data was aligned to the reference genome using Tophat. The aligned reads were assembled into transcripts and the differential expression of the transcripts was measured across the samples using Cufflinks. The resultant data was analyzed by a downstream analysis algorithm to only select for novel genes that correlate with well-annotated genes known to be important in immunity. This analysis led to the selection of two novel genes that that are most likely to be of interest for further functional characterization

Expression profiling and in situ screening of circular RNAs in human tissues

Circular RNAs (circRNAs) were recently discovered as a class of widely expressed noncoding RNA and have been implicated in regulation of gene expression. However, the function of the majority of circRNAs remains unknown. Studies of circRNAs have been hampered by a lack of essential approaches for detection, quantification and visualization. We therefore developed a target-enrichment sequencing method suitable for screening of circRNAs and their linear counterparts in large number of samples. We also applied padlock probes and in situ sequencing to visualize and determine circRNA localization in human brain tissue at subcellular levels. We measured circRNA abundance across different human samples and tissues. Our results highlight the potential of this RNA class to act as a specific diagnostic marker in blood and serum, by detection of circRNAs from genes exclusively expressed in the brain. The powerful and scalable tools we present will enable studies of circRNA function and facilitate screening of circRNA as diagnostic biomarkers

Single-cell mutation analysis of clonal evolution in myeloid malignancies.

Myeloid malignancies, including acute myeloid leukaemia (AML), arise from the expansion of haematopoietic stem and progenitor cells that acquire somatic mutations. Bulk molecular profiling has suggested that mutations are acquired in a stepwise fashion: mutant genes with high variant allele frequencies appear early in leukaemogenesis, and mutations with lower variant allele frequencies are thought to be acquired later1-3. Although bulk sequencing can provide information about leukaemia biology and prognosis, it cannot distinguish which mutations occur in the same clone(s), accurately measure clonal complexity, or definitively elucidate the order of mutations. To delineate the clonal framework of myeloid malignancies, we performed single-cell mutational profiling on 146 samples from 123 patients. Here we show that AML is dominated by a small number of clones, which frequently harbour co-occurring mutations in epigenetic regulators. Conversely, mutations in signalling genes often occur more than once in distinct subclones, consistent with increasing clonal diversity. We mapped clonal trajectories for each sample and uncovered combinations of mutations that synergized to promote clonal expansion and dominance. Finally, we combined protein expression with mutational analysis to map somatic genotype and clonal architecture with immunophenotype. Our findings provide insights into the pathogenesis of myeloid transformation and how clonal complexity evolves with disease progression

Development and Validation of a Scalable Next-Generation Sequencing System for Assessing Relevant Somatic Variants in Solid Tumors

Next-generation sequencing (NGS) has enabled genome-wide personalized oncology efforts at centers and companies with the specialty expertise and infrastructure required to identify and prioritize actionable variants. Such approaches are not scalable, preventing widespread adoption. Likewise, most targeted NGS approaches fail to assess key relevant genomic alteration classes. To address these challenges, we predefined the catalog of relevant solid tumor somatic genome variants (gain-of-function or loss-of-function mutations, high-level copy number alterations, and gene fusions) through comprehensive bioinformatics analysis of >700,000 samples. To detect these variants, we developed the Oncomine Comprehensive Panel (OCP), an integrative NGS-based assay [compatible with 95% accuracy for KRAS, epidermal growth factor receptor, and BRAF mutation detection as well as for ALK and TMPRSS2:ERG gene fusions. Associating positive variants with potential targeted treatments demonstrated that 6% to 42% of profiled samples (depending on cancer type) harbored alterations beyond routine molecular testing that were associated with approved or guideline-referenced therapies. As a translational research tool, OCP identified adaptive CTNNB1 amplifications/mutations in treated prostate cancers. Through predefining somatic variants in solid tumors and compiling associated potential treatment strategies, OCP represents a simplified, broadly applicable targeted NGS system with the potential to advance precision oncology efforts