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.
Summary The goal of aging research is to extend healthy, active life. For decades, C. elegans daf-2 insulin/IGF-1 receptor mutants have served as a model for extended lifespan and youthfulness. However, a recent report suggested that their longevity is associated with an undesirable phenotype: a disproportionately long period of decrepitude at the end of life. In a human population, such an outcome would be a burden to society, bringing into question the relevance of daf-2 mutants as a model for life extension. However, here we report that, following an extended period of movement, daf-2 mutants survive longer in a decrepit state because of a beneficial trait: they are resistant to colonization of the digestive tract by dietary bacteria, a condition that leads to premature death in wild type and prevents their manifestation of decrepitude. If bacterial colonization is prevented, daf-2 mutants lead chronologically and proportionately healthier lives relative to wild type.
MicroRNAs (miRNA) are a class of small non-coding RNAs that constitute an essential and evolutionarily conserved mechanism for post-transcriptional gene regulation. Multiple miRNAs have been described to play key roles in T lymphocyte development, differentiation and function. In this review we highlight the current literature regarding the differential expression of miRNAs in various models of mouse and human T cell biology and emphasize mechanistic understandings of miRNA regulation of thymocyte development, T cell activation, and differentiation into effector and memory subsets. We describe the participation of miRNAs in complex regulatory circuits shaping T cell proteomes in a context-dependent manner. It is striking that some miRNAs regulate multiple processes, while others only appear in limited functional contexts. It is also evident that the expression and function of specific miRNAs can differ between mouse and human systems. Ultimately, it is not always correct to simplify the complex events of T cell biology into a model driven by only one or two master regulator miRNAs. In reality, T cell activation and differentiation involves the expression of multiple miRNAs with many mRNA targets and thus, the true extent of miRNA regulation of T cell biology is likely far more vast than currently appreciated.
Disruptions in the normal program of tissue repair can result in poor wound healing, which perturbs the integrity of barrier tissues such as the skin. Such defects in wound repair occur in transplant recipients treated with the immunosuppressant drug rapamycin (sirolimus). Intraepithelial lymphocytes, such as γδT cells in the skin, mediate tissue repair through the production of cytokines and growth factors. The capacity of skin-resident T cells to function during rapamycin treatment was analyzed in a mouse model of wound repair. Rapamycin treatment renders skin γδ T cells unable to proliferate, migrate and produce normal levels of growth factors. The observed impairment of skin γδ T cell function is directly related to the inhibitory action of rapamycin on mammalian target of rapamycin (mTOR). Skin γδ T cells treated with rapamycin are refractory to IL-2 stimulation and attempt to survive in the absence of cytokine and growth factor signaling by undergoing autophagy. Normal wound closure can be restored in rapamycin-treated mice by addition of the skin γδ T cell-produced factor, insulin-like growth factor-1. These studies not only reveal that mTOR is a master regulator of γδ T cell function but also provide a novel mechanism for the increased susceptibility to nonhealing wounds that occurs during rapamycin administration. This is an author-produced version of a manuscript accepted for publication in The Journal of Immunology (The JI). The American Association of Immunologists, Inc. (AAI), publisher of The JI, holds the copyright to this manuscript. This version of the manuscript has not yet been copyedited or subjected to editorial proofreading by The JI; hence, it may differ from the final version published in The JI (online and in print). AAI (The JI) is not liable for errors or omissions in this author-produced version of the manuscript or in any version derived from it by the U.S. National Institutes of Health or any other third party. The final, citable version of record can be found at www.jimmunol.org.
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