Using long-read CAGE sequencing to profile cryptic-promoter-derived transcripts and their contribution to the immunopeptidome.

Recent studies have shown that the noncoding genome can produce unannotated proteins as antigens that induce immune response. One major source of this activity is the aberrant epigenetic reactivation of transposable elements (TEs). In tumors, TEs often provide cryptic or alternate promoters, which can generate transcripts that encode tumor-specific unannotated proteins. Thus, TE-derived transcripts (TE transcripts) have the potential to produce tumor-specific, but recurrent, antigens shared among many tumors. Identification of TE-derived tumor antigens holds the promise to improve cancer immunotherapy approaches; however, current genomics and computational tools are not optimized for their detection. Here we combined CAGE technology with full-length long-read transcriptome sequencing (long-read CAGE, or LRCAGE) and developed a suite of computational tools to significantly improve immunopeptidome detection by incorporating TE and other tumor transcripts into the proteome database. By applying our methods to human lung cancer cell line H1299 data, we show that long-read technology significantly improves mapping of promoters with low mappability scores and that LRCAGE guarantees accurate construction of uncharacterized 5' transcript structure. Augmenting a reference proteome database with newly characterized transcripts enabled us to detect noncanonical antigens from HLA-pulldown LC-MS/MS data. Lastly, we show that epigenetic treatment increased the number of noncanonical antigens, particularly those encoded by TE transcripts, which might expand the pool of targetable antigens for cancers with low mutational burden.

Epigenomic analysis reveals prevalent contribution of transposable elements to cis-regulatory elements, tissue-specific expression, and alternative promoters in zebrafish.

Transposable elements (TEs) encode regulatory elements that impact gene expression in multiple species, yet a comprehensive analysis of zebrafish TEs in the context of gene regulation is lacking. Here, we systematically investigate the epigenomic and transcriptomic landscape of TEs across 11 adult zebrafish tissues using multidimensional sequencing data. We find that TEs contribute substantially to a diverse array of regulatory elements in the zebrafish genome and that 37% of TEs are positioned in active regulatory states in adult zebrafish tissues. We identify TE subfamilies enriched in highly specific regulatory elements among different tissues. We use transcript assembly to discover TE-derived transcriptional units expressed across tissues. Finally, we show that novel TE-derived promoters can initiate tissue-specific transcription of alternate gene isoforms. This work provides a comprehensive profile of TE activity across normal zebrafish tissues, shedding light on mechanisms underlying the regulation of gene expression in this widely used model organism.

Vecuum: identification and filtration of false somatic variants caused by recombinant vector contamination.

MOTIVATION: Advances in sequencing technologies have remarkably lowered the detection limit of somatic variants to a low frequency. However, calling mutations at this range is still confounded by many factors including environmental contamination. Vector contamination is a continuously occurring issue and is especially problematic since vector inserts are hardly distinguishable from the sample sequences. Such inserts, which may harbor polymorphisms and engineered functional mutations, can result in calling false variants at corresponding sites. Numerous vector-screening methods have been developed, but none could handle contamination from inserts because they are focusing on vector backbone sequences alone. RESULTS: We developed a novel method-Vecuum-that identifies vector-originated reads and resultant false variants. Since vector inserts are generally constructed from intron-less cDNAs, Vecuum identifies vector-originated reads by inspecting the clipping patterns at exon junctions. False variant calls are further detected based on the biased distribution of mutant alleles to vector-originated reads. Tests on simulated and spike-in experimental data validated that Vecuum could detect 93% of vector contaminants and could remove up to 87% of variant-like false calls with 100% precision. Application to public sequence datasets demonstrated the utility of Vecuum in detecting false variants resulting from various types of external contamination. AVAILABILITY AND IMPLEMENTATION: Java-based implementation of the method is available at http://vecuum.sourceforge.net/ CONTACT: swkim@yuhs.acSupplementary information: Supplementary data are available at Bioinformatics online.

Pan-cancer analysis identifies tumor-specific antigens derived from transposable elements.

Cryptic promoters within transposable elements (TEs) can be transcriptionally reactivated in tumors to create new TE-chimeric transcripts, which can produce immunogenic antigens. We performed a comprehensive screen for these TE exaptation events in 33 TCGA tumor types, 30 GTEx adult tissues and 675 cancer cell lines, and identified 1,068 TE-exapted candidates with the potential to generate shared tumor-specific TE-chimeric antigens (TS-TEAs). Whole-lysate and HLA-pulldown mass spectrometry data confirmed that TS-TEAs are presented on the surface of cancer cells. In addition, we highlight tumor-specific membrane proteins transcribed from TE promoters that constitute aberrant epitopes on the extracellular surface of cancer cells. Altogether, we showcase the high pan-cancer prevalence of TS-TEAs and atypical membrane proteins that could potentially be therapeutically exploited and targeted.

The use of technical replication for detection of low-level somatic mutations in next-generation sequencing.

Accurate genome-wide detection of somatic mutations with low variant allele frequency (VAF, <1%) has proven difficult, for which generalized, scalable methods are lacking. Herein, we describe a new computational method, called RePlow, that we developed to detect low-VAF somatic mutations based on simple, library-level replicates for next-generation sequencing on any platform. Through joint analysis of replicates, RePlow is able to remove prevailing background errors in next-generation sequencing analysis, facilitating remarkable improvement in the detection accuracy for low-VAF somatic mutations (up to ~99% reduction in false positives). The method is validated in independent cancer panel and brain tissue sequencing data. Our study suggests a new paradigm with which to exploit an overwhelming abundance of sequencing data for accurate variant detection.