RNA-Seq is increasingly used for the diagnosis of patients, targeting of therapies and for single cell transcriptomics. These applications require cost effective, fast and reliable ways of capturing and analyzing gene expression data. Here we compared Lexogen’s QuantSeq which captures only the 3′ end of RNA transcripts and Illumina’s TruSeq, using both Tophat2 and Salmon for gene quantification. We also compared these results to microarray. This analysis was performed on peripheral blood mononuclear cells stimulated with Poly (I:C), a viral mimic that induces innate antiviral responses. This provides a well-established model to determine if RNA-Seq and QuantSeq identify the same biological signatures. Gene expression levels in QuantSeq and RNA-Seq were strongly correlated (Spearman’s rho ~0.8), Salmon and Tophat2 (Spearman’s rho > 0.9). There was high consistency in protein coding genes, non-concordant genes had a high proportion of shorter, non-coding features. RNA-Seq identified more differentially expressed genes than QuantSeq, both methods outperformed microarray. The same key biological signals emerged in each of these approaches. We conclude that QuantSeq, coupled with a fast quantification method such as Salmon, should provide a viable alternative to traditional RNA-Seq in many applications and may be of particular value in the study of the 3′UTR region of mRNA.

A subset of human follicular helper T cells (TFH) cells expresses CD57 for which no distinct function has been identified. We show that CD57+ TFH cells are universally PD-1^hi, but compared to their CD57− PD-1^hicounterparts, express little IL-21 or IL-10 among others. Instead, CD57 expression on TFH cells marks cytotoxicity transcriptional signatures that translate into only a weak cytotoxic phenotype. Similarly, circulating PD-1+ CD57+ CD4+ T cells make less cytokine than their CD57− PD-1+ counterparts, but have a prominent cytotoxic phenotype. By analysis of responses to STAT3-dependent cytokines and cells from patients with gain- or loss-of-functionSTAT3mutations, we show that CD4+ T cell cytotoxicity is STAT3-dependent. TFH formation also requires STAT3, but paradoxically, once formed, PD-1^hicells become unresponsive to STAT3. These findings suggest that changes in blood and germinal center cytotoxicity might be affected by changes in STAT3 signaling, or modulation of PD-1 by therapy.

RNA-Seq is now widely used as a research tool. Choices must be made whether to use paired-end (PE) or single-end (SE) sequencing, and whether to use strand-specific or non-specific (NS) library preparation kits. To date there has been no analysis of the effect of these choices on identifying differentially expressed genes (DEGs) between controls and treated samples and on downstream functional analysis. We undertook four mammalian transcriptomics experiments to compare the effect of SE and PE protocols on read mapping, feature counting, identification of DEGs and functional analysis. For three of these experiments we also compared a non-stranded (NS) and a strand-specific approach to mapping the paired-end data. SE mapping resulted in a reduced number of reads mapped to features, in all four experiments, and lower read count per gene. Up to 4.3% of genes in the SE data and up to 12.3% of genes in the NS data had read counts which were significantly different compared to the PE data. Comparison of DEGs showed the presence of false positives (average 5%, using voom) and false negatives (average 5%, using voom) using the SE reads. These increased further, by one or two percentage points, with the NS data. Gene ontology functional enrichment (GO) of the DEGs arising from SE or NS approaches, revealed striking differences in the top 20 GO terms, with as little as 40% concordance with PE results. Caution is therefore advised in the interpretation of such results. By comparison, there was overall consistency in gene set enrichment analysis results. A strand-specific protocol should be used in library preparation to generate the most reliable and accurate profile of expression. Ideally PE reads are also recommended particularly for transcriptome assembly. Whilst SE reads produce a DEG list with around 5% of false positives and false negatives, this method can substantially reduce sequencing cost and this saving could be used to increase the number of biological replicates thereby increasing the power of the experiment. As SE reads, when used in association with gene set enrichment, can generate accurate biological results, this may be a desirable trade-off.

Many genes are differentially expressed in the cortex of people with schizophrenia, implicating factors that control transcription more generally. Hormone nuclear receptors dimerize to coordinate context-dependent changes in gene expression. We hypothesized that members of two families of nuclear receptors (NR4As), and retinoid receptors (RARs and RXRs), are altered in the dorsal lateral prefrontal cortex (DLPFC) of people with schizophrenia. We used next generation sequencing and then qPCR analysis to test for changes in mRNA levels for transcripts encoding nuclear receptors: orphan nuclear receptors (3 in the NR4A, 3 in the RAR, 3 in the RXR families and KLF4) in total RNA extracted from the DLPFC from people with schizophrenia compared to controls (n = 74). We also correlated mRNA levels with demographic factors and with estimates of antipsychotic drug exposure (schizophrenia group only). We tested for correlations between levels of transcription factor family members and levels of genes putatively regulated by these transcription factors. We found significantly down regulated expression of NR4A1 (Nurr 77) and KLF4 mRNAs in people with schizophrenia compared to controls, by both NGS and qPCR (p = or <0.01). We also detected decreases in NR4A2 (Nurr1) and RXRB mRNAs by using qPCR in the larger cohort (p<0.05 and p<0.01, respectively). We detected decreased expression of RARG and NR4A2 mRNAs in females with schizophrenia (p<0.05). The mRNA levels of NR4A1, NR4A2 and NR4A3 were all negative correlated with lifetime estimates of antipsychotic exposure. These novel findings, which may be influenced by antipsychotic drug exposure, implicate the orphan and retinoid nuclear receptors in the cortical pathology found in schizophrenia. Genes down stream of these receptors can be dysregulated as well, but the direction of change is not immediately predictable based on the putative transcription factor changes.

Yes-associated protein (YAP) is a mechanosensor protein and a downstream effector of the Hippo kinase pathway, which controls organ growth, cell proliferation, survival, maintenance and regeneration. Unphosphorylated YAP translocates to the nucleus where it acts as a cofactor of primarily the TEAD transcription factors to activate target gene transcription and cell proliferation. Perturbed YAP activation results in tumorigenesis. The pathways downstream of activated YAP that drive cell proliferation remain relatively unexplored. In this study, we employed YAP2-5SA-∆C transgenic mice, which overexpress a mildly activated YAP mutant protein in basal keratinocytes leading to increased proliferation of the epidermal stem/progenitor cell populations. We performed massively-parallel sequencing of skin biopsy mRNA (RNA-Seq) and found dysregulation of 1491 genes in YAP2-5SA-∆C skin, including many with roles in cell activation and proliferation. Furthermore, we found that 150 of these dysregulated genes harbored YAP/TEAD binding motifs in the 3′ UTR, suggesting that these may be direct YAP/TEAD target genes in the control of epidermal regeneration. Further validation and functional characterization assays identified Plau and Tgfbr3 as prime candidate genes that may be activated by epidermal YAP activity in the mouse skin in vivo to promote keratinocyte proliferation. This study provides novel insights into the mechanisms regulated by YAP that control tissue homeostasis, and in particular in conditions where YAP is aberrantly activated such as in neoplastic and regenerative skin disease.

A significant gap in the knowledge of zinc homeostasis exists for breast cancer cells. In this study, we investigated the transcriptomic response of the luminal breast cancer cells (MCF-7) to the exposure of extracellular zinc using next-generation RNA sequencing (RNA-seq). The dataset was collected for three time points (T₀, T₃₀ and T₁₂₀) in the time course of zinc treatment, which revealed the dramatic increase, up to 869-fold, of the gene expression for metallothioneins (MT1B, MT1F, MT1X and MT2A) and the zinc exporter ZnT1 (SLC30A1) at T₃₀, continuingly through to T₁₂₀. The similar dynamic expression pattern was found for the autophagy-related gene (VMP1) and numerous genes for zinc finger proteins (e.g. RNF165, ZNF365, ZBTB2, SNAI1, ZNF442, ZNF547, ZNF563 and ZNF296). These findings point to the all-hands-on-deck strategy adopted by the cancer cells for maintaining zinc homeostasis. The stress responsive genes encoding heat shock proteins (HSPA1A, HSPA1B, HSPA1L, HSPA4L, HSPA6, HSPA8, HSPH1, HSP90AA1 and HSP90AB1) and the MTF-1 biomarker genes (AKR1C2, CLU, ATF3, GDF15, HMOX1, MAP1A, MAFG, SESN2 and UBC) were also differentially up-regulated at T₁₂₀, suggesting a role of heat shock proteins and the MTF-1 related stress proteins in dealing with zinc exposure. It is for the first time that the gene encoding Polo-like kinase 2 (PLK2) was found to be involved in zinc-related response. The top differentially expressed genes were validated by qRT-PCR and further extended to the basal type breast cancer cells (MDA-MB-231). It was found that the expression level of SLC30A1 in MDA-MB-231 was higher than MCF-7 in response to zinc exposure. Taken together, the findings contribute to our knowledge and understanding of zinc homeostasis in breast cancer cells.