RNA-sequence analysis of human B-cells.

RNA-sequencing (RNA-seq) allows quantitative measurement of expression levels of genes and their transcripts. In this study, we sequenced complementary DNA fragments of cultured human B-cells and obtained 879 million 50-bp reads comprising 44 Gb of sequence. The results allowed us to study the gene expression profile of B-cells and to determine experimental parameters for sequencing-based expression studies. We identified 20,766 genes and 67,453 of their alternatively spliced transcripts. More than 90% of the genes with multiple exons are alternatively spliced; for most genes, one isoform is predominantly expressed. We found that while chromosomes differ in gene density, the percentage of transcribed genes in each chromosome is less variable. In addition, genes involved in related biological processes are expressed at more similar levels than genes with different functions. Besides characterizing gene expression, we also used the data to investigate the effect of sequencing depth on gene expression measurements. While 100 million reads are sufficient to detect most expressed genes and transcripts, about 500 million reads are needed to measure accurately their expression levels. We provide examples in which deep sequencing is needed to determine the relative abundance of genes and their isoforms. With data from 20 individuals and about 40 million sequence reads per sample, we uncovered only 21 alternatively spliced, multi-exon genes that are not in databases; this result suggests that at this sequence coverage, we can detect most of the known genes. Results from this project are available on the UCSC Genome Browser to allow readers to study the expression and structure of genes in human B-cells.

Feasibility of monitoring advanced melanoma patients using cell-free DNA from plasma.

To determine the feasibility of liquid biopsy for monitoring of patients with advanced melanoma, cell-free DNA was extracted from plasma for 25 Stage III/IV patients, most (84.0%) having received previous therapy. DNA concentrations ranged from 0.6 to 390.0 ng/ml (median = 7.8 ng/ml) and were positively correlated with tumor burden as measured by imaging (Spearman rho = 0.5435, p = .0363). Using ultra-deep sequencing for a 61-gene panel, one or more mutations were detected in 12 of 25 samples (48.0%), and this proportion did not vary significantly for patients on or off therapy at the time of blood draw (52.9% and 37.5% respectively; p = .673). Sixteen mutations were detected in eight different genes, with the most frequent mutations detected in BRAF, NRAS, and KIT. Allele fractions ranged from 1.1% to 63.2% (median = 29.1%). Among patients with tissue next-generation sequencing, nine of 11 plasma mutations were also detected in matched tissue, for a concordance of 81.8%.

A genome-wide association study identifies only two ancestry specific variants associated with spontaneous preterm birth.

Preterm birth (PTB), or the delivery prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. Although twin studies estimate that maternal genetic contributions account for approximately 30% of the incidence of PTB, and other studies reported fetal gene polymorphism association, to date no consistent associations have been identified. In this study, we performed the largest reported genome-wide association study analysis on 1,349 cases of PTB and 12,595 ancestry-matched controls from the focusing on genomic fetal signals. We tested over 2 million single nucleotide polymorphisms (SNPs) for associations with PTB across five subpopulations: African (AFR), the Americas (AMR), European, South Asian, and East Asian. We identified only two intergenic loci associated with PTB at a genome-wide level of significance: rs17591250 (P = 4.55E-09) on chromosome 1 in the AFR population and rs1979081 (P = 3.72E-08) on chromosome 8 in the AMR group. We have queried several existing replication cohorts and found no support of these associations. We conclude that the fetal genetic contribution to PTB is unlikely due to single common genetic variant, but could be explained by interactions of multiple common variants, or of rare variants affected by environmental influences, all not detectable using a GWAS alone.

Development and Validation of an Ultradeep Next-Generation Sequencing Assay for Testing of Plasma Cell-Free DNA from Patients with Advanced Cancer.

Purpose: Tumor-derived cell-free DNA (cfDNA) in plasma can be used for molecular testing and provide an attractive alternative to tumor tissue. Commonly used PCR-based technologies can test for limited number of alterations at the time. Therefore, novel ultrasensitive technologies capable of testing for a broad spectrum of molecular alterations are needed to further personalized cancer therapy.Experimental Design: We developed a highly sensitive ultradeep next-generation sequencing (NGS) assay using reagents from TruSeqNano library preparation and NexteraRapid Capture target enrichment kits to generate plasma cfDNA sequencing libraries for mutational analysis in 61 cancer-related genes using common bioinformatics tools. The results were retrospectively compared with molecular testing of archival primary or metastatic tumor tissue obtained at different points of clinical care.Results: In a study of 55 patients with advanced cancer, the ultradeep NGS assay detected 82% (complete detection) to 87% (complete and partial detection) of the aberrations identified in discordantly collected corresponding archival tumor tissue. Patients with a low variant allele frequency (VAF) of mutant cfDNA survived longer than those with a high VAF did (P = 0.018). In patients undergoing systemic therapy, radiological response was positively associated with changes in cfDNA VAF (P = 0.02), and compared with unchanged/increased mutant cfDNA VAF, decreased cfDNA VAF was associated with longer time to treatment failure (TTF; P = 0.03).Conclusions: Ultradeep NGS assay has good sensitivity compared with conventional clinical mutation testing of archival specimens. A high VAF in mutant cfDNA corresponded with shorter survival. Changes in VAF of mutated cfDNA were associated with TTF. Clin Cancer Res; 23(18); 5648-56. ©2017 AACR.

Detection theory in identification of RNA-DNA sequence differences using RNA-sequencing.

Advances in sequencing technology have allowed for detailed analyses of the transcriptome at single-nucleotide resolution, facilitating the study of RNA editing or sequence differences between RNA and DNA genome-wide. In humans, two types of post-transcriptional RNA editing processes are known to occur: A-to-I deamination by ADAR and C-to-U deamination by APOBEC1. In addition to these sequence differences, researchers have reported the existence of all 12 types of RNA-DNA sequence differences (RDDs); however, the validity of these claims is debated, as many studies claim that technical artifacts account for the majority of these non-canonical sequence differences. In this study, we used a detection theory approach to evaluate the performance of RNA-Sequencing (RNA-Seq) and associated aligners in accurately identifying RNA-DNA sequence differences. By generating simulated RNA-Seq datasets containing RDDs, we assessed the effect of alignment artifacts and sequencing error on the sensitivity and false discovery rate of RDD detection. Overall, we found that even in the presence of sequencing errors, false negative and false discovery rates of RDD detection can be contained below 10% with relatively lenient thresholds. We also assessed the ability of various filters to target false positive RDDs and found them to be effective in discriminating between true and false positives. Lastly, we used the optimal thresholds we identified from our simulated analyses to identify RDDs in a human lymphoblastoid cell line. We found approximately 6,000 RDDs, the majority of which are A-to-G edits and likely to be mediated by ADAR. Moreover, we found the majority of non A-to-G RDDs to be associated with poorer alignments and conclude from these results that the evidence for widespread non-canonical RDDs in humans is weak. Overall, we found RNA-Seq to be a powerful technique for surveying RDDs genome-wide when coupled with the appropriate thresholds and filters.

Widespread RNA and DNA sequence differences in the human transcriptome.

The transmission of information from DNA to RNA is a critical process. We compared RNA sequences from human B cells of 27 individuals to the corresponding DNA sequences from the same individuals and uncovered more than 10,000 exonic sites where the RNA sequences do not match that of the DNA. All 12 possible categories of discordances were observed. These differences were nonrandom as many sites were found in multiple individuals and in different cell types, including primary skin cells and brain tissues. Using mass spectrometry, we detected peptides that are translated from the discordant RNA sequences and thus do not correspond exactly to the DNA sequences. These widespread RNA-DNA differences in the human transcriptome provide a yet unexplored aspect of genome variation.