High-throughput sequencing, also known as next-generation sequencing (NGS), has revolutionized genomic research. In recent years, NGS technology has steadily improved, with costs dropping and the number and range of sequencing applications increasing exponentially. Here, we examine the critical role of sequencing library quality and consider important challenges when preparing NGS libraries from DNA and RNA sources. Factors such as the quantity and physical characteristics of the RNA or DNA source material as well as the desired application (i.e., genome sequencing, targeted sequencing, RNA-seq, ChIP-seq, RIP-seq, and methylation) are addressed in the context of preparing high quality sequencing libraries. In addition, the current methods for preparing NGS libraries from single cells are also discussed.

BackgroundEarly application of second-generation sequencing technologies to transcript quantitation (RNA-seq) has hinted at a vast mammalian transcriptome, including transcripts from nearly all known genes, which might be fully measured only by ultradeep sequencing. Subsequent studies suggested that low-abundance transcripts might be the result of technical or biological noise rather than active transcripts; moreover, most RNA-seq experiments did not provide enough read depth to generate high-confidence estimates of gene expression for low-abundance transcripts. As a result, the community adopted several heuristics for RNA-seq analysis, most notably an arbitrary expression threshold of 0.3 - 1 FPKM for downstream analysis. However, advances in RNA-seq library preparation, sequencing technology, and informatic analysis have addressed many of the systemic sources of uncertainty and undermined the assumptions that drove the adoption of these heuristics. We provide an updated view of the accuracy and efficiency of RNA-seq experiments, using genomic data from large-scale studies like the ENCODE project to provide orthogonal information against which to validate our conclusions.ResultsWe show that a human cell’s transcriptome can be divided into active genes carrying out the work of the cell and other genes that are likely the by-products of biological or experimental noise. We use ENCODE data on chromatin state to show that ultralow-expression genes are predominantly associated with repressed chromatin; we provide a novel normalization metric, zFPKM, that identifies the threshold between active and background gene expression; and we show that this threshold is robust to experimental and analytical variations.ConclusionsThe zFPKM normalization method accurately separates the biologically relevant genes in a cell, which are associated with active promoters, from the ultralow-expression noisy genes that have repressed promoters. A read depth of twenty to thirty million mapped reads allows high-confidence quantitation of genes expressed at this threshold, providing important guidance for the design of RNA-seq studies of gene expression. Moreover, we offer an example for using extensive ENCODE chromatin state information to validate RNA-seq analysis pipelines.

Memory T cells are primed for rapid responses to antigen; however, the molecular mechanisms responsible for priming remain incompletely defined. CpG methylation in promoters is an epigenetic modification, which regulates gene transcription. Using targeted bisulfite sequencing, we examined methylation of 2100 genes (56,000 CpG) mapped by deep sequencing of T cell activation in human naïve and memory CD4 T cells. 466 CpGs (132 genes) displayed differential methylation between naïve and memory cells. 21 genes exhibited both differential methylation and gene expression before activation, linking promoter DNA methylation states to gene regulation; 6 of 21 genes encode proteins closely studied in T cells, while 15 genes represent novel targets for further study. 84 genes demonstrated differential methylation between memory and naïve cells that correlated to differential gene expression following activation, of which 39 exhibited reduced methylation in memory cells coupled with increased gene expression upon activation compared to naïve cells. These reveal a class of primed genes more rapidly expressed in memory compared to naïve cells and putatively regulated by DNA methylation. These findings define a DNA methylation signature unique to memory CD4 T cells that correlates with activation-induced gene expression.

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Cytosine methylation of DNA CpG dinucleotides in gene promoters is an epigenetic modification that regulates gene transcription. While many methods exist to interrogate methylation states, few current methods offer large-scale, targeted, single CpG resolution. We report an approach combining bisulfite treatment followed by microdroplet PCR with next-generation sequencing to assay the methylation state of 50 genes in the regions 1 kb upstream of and downstream from their transcription start sites. This method yielded 96% coverage of the targeted CpGs and demonstrated high correlation between CpG island (CGI) DNA methylation and transcriptional regulation. The method was scaled to interrogate the methylation status of 77,674 CpGs in the promoter regions of 2100 genes in primary CD4 T cells. The 2100 gene library yielded 97% coverage of all targeted CpGs and 99% of the target amplicons.

The epigenetic determinants driving the responses of CD4 T cells to antigen are currently an area of active research. Much has been done to characterize helper T cell subsets and their associated genome-wide epigenetic patterns. In contrast, little is known about the dynamics of histone modifications during CD4 T cell activation and the differential kinetics of these epigenetic marks between naïve and memory T cells. In this study we have detailed the dynamics of genome-wide promoter H3K4me2 and H3K4me3 over a time course during activation of human naïve and memory CD4 T cells. Our results demonstrate that changes to H3K4 methylation occur relatively late after activation (5 days) and reinforce activation-induced upregulation of gene expression, affecting multiple pathways important to T cell activation, differentiation, and function. The dynamics and mapped pathways of H3K4 methylation are distinctly different in memory cells, which have substantially more promoters marked by H3K4me3 alone, reinforcing their more differentiated state. Our study provides the first data examining genome-wide histone modification dynamics during CD4 T cell activation, providing insight into the cross talk between H3K4 methylation and gene expression, and underscoring the impact of these marks upon key pathways integral to CD4 T cell activation and function.

The changes to the epigenetic landscape in response to antigen during CD4 T cell activation have not been well characterized. While CD4 T cell subsets have been mapped globally for numerous epigenetic marks, little has been done to study their dynamics early after activation. We have studied changes to promoter H3K27me3 during activation of human naïve and memory CD4 T cells. Our results show that these changes occur relatively early (1 day) after activation of both naïve and memory cells, and that demethylation is the predominant change to H3K27me3 at this time point, reinforcing high expression of target genes. Additionally, inhibition of the H3K27 demethylase, JMJD3, in naïve CD4 T cells demonstrates how critically important molecules required for T cell differentiation, such as JAK2 and IL12RB2, are regulated by H3K27me3. Our results demonstrate that H3K27me3 is a dynamic and important epigenetic modification during CD4 T cell activation, and that JMJD3-driven H3K27 demethylation is critical for CD4 T cell function.

There are currently no published data documenting the presence of retroviruses in cetaceans, though the occurrences of cancers and immunodeficiency states suggest the potential. We examined tissues from adult killer whales and detected a novel gammaretrovirus by degenerate PCR. Reverse transcription-PCR also demonstrated tissue and serum expression of retroviral mRNA. The full-length sequence of the provirus was obtained by PCR, and a TaqMan-based copy number assay did not demonstrate evidence of productive infection. PCR on blood samples from 11 healthy captive killer whales and tissues from 3 free-ranging animals detected the proviral DNA in all tissues examined from all animals. A survey of multiple cetacean species by PCR for gag, pol, and env sequences showed homologs of this virus in the DNA of eight species of delphinids, pygmy and dwarf sperm whales, and harbor porpoises, but not in beluga or fin whales. Analysis of the bottlenose dolphin genome revealed two full-length proviral sequences with 97.4% and 96.9% nucleotide identity to the killer whale gammaretrovirus. The results of single-cell PCR on killer whale sperm and Southern blotting are also consistent with the conclusion that the provirus is endogenous. We suggest that this gammaretrovirus entered the delphinoid ancestor's genome before the divergence of modern dolphins or that an exogenous variant existed following divergence that was ultimately endogenized. However, the transcriptional activity demonstrated in tissues and the nearly intact viral genome suggest a more recent integration into the killer whale genome, favoring the latter hypothesis. The proposed name for this retrovirus is killer whale endogenous retrovirus.