Ageing is characterised by cellular senescence, leading to imbalanced tissue maintenance, cell death and compromised organ function. This is first observed in the thymus, the primary lymphoid organ that generates and selects T cells. However, the molecular and cellular mechanisms underpinning these ageing processes remain unclear. Here, we show that mouse ageing leads to less efficient T cell selection, decreased self-antigen representation and increased T cell receptor repertoire diversity. Using a combination of single-cell RNA-seq and lineage-tracing, we find that progenitor cells are the principal targets of ageing, whereas the function of individual mature thymic epithelial cells is compromised only modestly. Specifically, an early-life precursor cell population, retained in the mouse cortex postnatally, is virtually extinguished at puberty. Concomitantly, a medullary precursor cell quiesces, thereby impairing maintenance of the medullary epithelium. Thus, ageing disrupts thymic progenitor differentiation and impairs the core immunological functions of the thymus.

To induce central T‐cell tolerance, medullary thymic epithelial cells (mTEC) collectively express most protein‐coding genes, thereby presenting an extensive library of tissue‐restricted antigens (TRAs). To resolve mTEC diversity and whether promiscuous gene expression (PGE) is stochastic or coordinated, we sequenced transcriptomes of 6,894 single mTEC, enriching for 1,795 rare cells expressing either of two TRAs, TSPAN8 or GP2. Transcriptional heterogeneity allowed partitioning of mTEC into 15 reproducible subpopulations representing distinct maturational trajectories, stages and subtypes, including novel mTEC subsets, such as chemokine‐expressing and ciliated TEC, which warrant further characterisation. Unexpectedly, 50 modules of genes were robustly defined each showing patterns of co‐expression within individual cells, which were mainly not explicable by chromosomal location, biological pathway or tissue specificity. Further, TSPAN8+ and GP2+ mTEC were randomly dispersed within thymic medullary islands. Consequently, these data support observations that PGE exhibits ordered co‐expression, although mechanisms underlying this instruction remain biologically indeterminate. Ordered co‐expression and random spatial distribution of a diverse range of TRAs likely enhance their presentation and encounter with passing thymocytes, while maintaining mTEC identity.

Persistent infections with hepatitis B virus (HBV) or hepatitis C virus (HCV) account for the majority of cases of hepatic cirrhosis and hepatocellular carcinoma (HCC) worldwide. Small, non-coding RNAs play important roles in virus-host interactions. We used high throughput sequencing to conduct an unbiased profiling of small (14-40 nts) RNAs in liver from Japanese subjects with advanced hepatitis B or C and hepatocellular carcinoma (HCC). Small RNAs derived from tRNAs, specifically 30–35 nucleotide-long 5′ tRNA-halves (5′ tRHs), were abundant in non-malignant liver and significantly increased in humans and chimpanzees with chronic viral hepatitis. 5′ tRH abundance exceeded microRNA abundance in most infected non-cancerous tissues. In contrast, in matched cancer tissue, 5′ tRH abundance was reduced, and relative abundance of individual 5′ tRHs was altered. In hepatitis B-associated HCC, 5′ tRH abundance correlated with expression of the tRNA-cleaving ribonuclease, angiogenin. These results demonstrate that tRHs are the most abundant small RNAs in chronically infected liver and that their abundance is altered in liver cancer.

Next-generation deep sequencing of small RNAs has unveiled the complexity of the microRNA (miRNA) transcriptome, which is in large part due to the diversity of miRNA sequence variants (“isomiRs”). Changes to a miRNA’s seed sequence (nucleotides 2–8), including shifted start positions, can redirect targeting to a dramatically different set of RNAs and alter biological function. We performed deep sequencing of small RNA from mouse insulinoma (MIN6) cells (widely used as a surrogate for the study of pancreatic beta cells) and developed a bioinformatic analysis pipeline to profile isomiR diversity. Additionally, we applied the pipeline to recently published small RNA-seq data from primary human beta cells and whole islets and compared the miRNA profiles with that of MIN6. We found that: (1) the miRNA expression profile in MIN6 cells is highly correlated with those of primary human beta cells and whole islets; (2) miRNA loci can generate multiple highly expressed isomiRs with different 5′-start positions (5′-isomiRs); (3) isomiRs with shifted start positions (5′-shifted isomiRs) are highly expressed, and can be as abundant as their unshifted counterparts (5′-reference miRNAs). Finally, we identified 10 beta cell miRNA families as candidate regulatory hubs in a type 2 diabetes (T2D) gene network. The most significant candidate hub was miR-29, which we demonstrated regulates the mRNA levels of several genes critical to beta cell function and implicated in T2D. Three of the candidate miRNA hubs were novel 5′-shifted isomiRs: miR-375+1, miR-375-1 and miR-183-5p+1. We showed by in silico target prediction and in vitro transfection studies that both miR-375+1 and miR-375-1 are likely to target an overlapping, but distinct suite of beta cell genes compared to canonical miR-375. In summary, this study characterizes the isomiR profile in beta cells for the first time, and also highlights the potential functional relevance of 5′-shifted isomiRs to T2D.

Single-cell RNA sequencing (scRNA-seq) has opened new avenues for the characterization of heterogeneity in a large variety of cellular systems. As this is a relatively new technique, the field is fast evolving. Here, we discuss general considerations in experimental design and the two most popular approaches, plate-based Smart-Seq2 and microdroplet-based scRNA-seq at the example of 10x Chromium. We discuss advantages and disadvantages of both methods and point out major factors to consider in designing successful experiments.

Recent advances in sequencing technology have helped unveil the unexpected complexity and diversity of small RNAs. A critical step in small RNA library preparation for sequencing is the ligation of adapter sequences to both the 5′ and 3′ ends of small RNAs. Studies have shown that adapter ligation introduces a significant but widely unappreciated bias in the results of high-throughput small RNA sequencing. We show that due to this bias the two widely used Illumina library preparation protocols produce strikingly different microRNA (miRNA) expression profiles in the same batch of cells. There are 102 highly expressed miRNAs that are >5-fold differentially detected and some miRNAs, such as miR-24-3p, are over 30-fold differentially detected. While some level of bias in library preparation is not surprising, the apparent massive differential bias between these two widely used adapter sets is not well appreciated. In an attempt to mitigate this bias, the new Bioo Scientific NEXTflex V2 protocol utilizes a pool of adapters with random nucleotides at the ligation boundary. We show that this protocol is able to detect robustly several miRNAs that evade capture by the Illumina-based methods. While these analyses do not indicate a definitive gold standard for small RNA library preparation, the results of the NEXTflex protocol do correlate best with RT-qPCR. As increasingly more laboratories seek to study small RNAs, researchers should be aware of the extent to which the results may differ with different protocols, and should make an informed decision about the protocol that best fits their study.

Summary Maintenance of genomic integrity is critical during neurodevelopment, particularly in rapidly dividing cerebellar granule neuronal precursors that experience constitutive replication-associated DNA damage. As Dicer was recently recognized to have an unexpected function in the DNA damage response, we examined whether Dicer was important for preserving genomic integrity in the developing brain. We report that deletion of Dicer in the developing mouse cerebellum resulted in the accumulation of DNA damage leading to cerebellar progenitor degeneration, which was rescued with p53 deficiency; deletion of DGCR8 also resulted in similar DNA damage and cerebellar degeneration. Dicer deficiency also resulted in DNA damage and death in other rapidly dividing cells including embryonic stem cells and the malignant cerebellar progenitors in a mouse model of medulloblastoma. Together, these results identify an essential function of Dicer in resolving the spontaneous DNA damage that occurs during the rapid proliferation of developmental progenitors and malignant cells.

Estrogen receptor α (ERα) is an important biomarker of breast cancer severity and a common therapeutic target. In response to estrogen, ERα stimulates a dynamic transcriptional program including both coding and noncoding RNAs. We generate a fine-scale map of expression dynamics by performing a temporal profiling of both messenger RNAs (mRNAs) and microRNAs (miRNAs) in MCF-7 cells (an ER+ model cell line for breast cancer) in response to estrogen stimulation. We identified three primary expression trends-transient, induced, and repressed-that were each enriched for genes with distinct cellular functions. Integrative analysis of mRNA and miRNA temporal expression profiles identified miR-503 as the strongest candidate master regulator of the estrogen response, in part through suppression of ZNF217-an oncogene that is frequently amplified in cancer. We confirmed experimentally that miR-503 directly targets ZNF217 and that overexpression of miR-503 suppresses MCF-7 cell proliferation. Moreover, the levels of ZNF217 and miR-503 are associated with opposite outcomes in breast cancer patient cohorts, with high expression of ZNF217 associated with poor survival and high expression of miR-503 associated with improved survival. Overall, these data indicate that miR-503 acts as a potent estrogen-induced candidate tumor suppressor miRNA that opposes cellular proliferation and has promise as a novel therapeutic for breast cancer. More generally, our work provides a systemslevel framework for identifying functional interactions that shape the temporal dynamics of gene expression.