Most human pre-mRNAs are spliced into linear molecules that retain the exon order defined by the genomic sequence. By deep sequencing of RNA from a variety of normal and malignant human cells, we found RNA transcripts from many human genes in which the exons were arranged in a non-canonical order. Statistical estimates and biochemical assays provided strong evidence that a substantial fraction of the spliced transcripts from hundreds of genes are circular RNAs. Our results suggest that a non-canonical mode of RNA splicing, resulting in a circular RNA isoform, is a general feature of the gene expression program in human cells.

The field of single-cell genomics is advancing rapidly and is generating many new insights into complex biological systems, ranging from the diversity of microbial ecosystems to the genomics of human cancer. In this Review, we provide an overview of the current state of the field of single-cell genome sequencing. First, we focus on the technical challenges of making measurements that start from a single molecule of DNA, and then explore how some of these recent methodological advancements have enabled the discovery of unexpected new biology. Areas highlighted include the application of single-cell genomics to interrogate microbial dark matter and to evaluate the pathogenic roles of genetic mosaicism in multicellular organisms, with a focus on cancer. We then attempt to predict advances we expect to see in the next few years.

SUMMARY Analysis of molecular aberrations across multiple cancer types, known as pan-cancer analysis, identifies commonalities and differences in key biological processes dysregulated in cancer cells from diverse lineages. Pan-cancer analyses have been performed for adult1–4 but not pediatric cancers, which commonly occur in developing mesodermic rather than adult epithelial tissues5. Here we present a pan-cancer study of somatic alterations, including single nucleotide variants (SNVs), small insertion/deletions (indels), structural variations (SVs), copy number alterations (CNAs), gene fusions and internal tandem duplications (ITDs), in 1,699 pediatric leukemia and solid tumours across six histotypes, with whole-genome (WGS), whole-exome (WES) and transcriptome (RNA-seq) sequencing data processed under a uniform analytical framework (Online Methods and Extended Data Fig. 1). We report 142 driver genes in pediatric cancers, of which only 45% matched those found in adult pan-cancer studies and CNAs and SVs constituted the majority (62%) of events. Eleven genome-wide mutational signatures were identified, including one attributed to ultraviolet-light exposure in eight aneuploid leukemias. Transcription of the mutant allele was detectable for 34% of protein-coding mutations, and 20% exhibited allele-specific expression. These data provide a comprehensive genomic architecture for pediatric cancers and emphasize the need for pediatric cancer-specific development of precision therapies.

Medulloblastoma is a malignant childhood cerebellar tumour comprised of distinct molecular subgroups. Whereas genomic characteristics of these subgroups are well defined, the extent to which cellular diversity underlies their divergent biology and clinical behaviour remains largely unexplored. We used single-cell transcriptomics to investigate intra-and inter-tumoural heterogeneity in twenty-five medulloblastomas spanning all molecular subgroups. WNT, SHH, and Group 3 tumours comprised subgroup-specific undifferentiated and differentiated neuronallike malignant populations, whereas Group 4 tumours were exclusively comprised of differentiated neuronal-like neoplastic cells. SHH tumours closely resembled granule neurons of varying differentiation states that correlated with patient age. Group 3 and Group 4 tumours exhibited a developmental trajectory from primitive progenitor-like to more mature neuronal-like cells, whose relative proportions distinguished these subgroups. Cross-species transcriptomics defined distinct glutamatergic populations as putative cells-of-origin for SHH and Group 4 subtypes. Collectively, these data provide novel insights into the cellular and developmental states underlying subtypespecific medulloblastoma biology. Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Many cancers have substantial genomic heterogeneity within a given tumor, and to fully understand that diversity requires the ability to perform single cell analysis. We performed targeted sequencing of a panel of single nucleotide variants (SNVs), deletions, and IgH sequences in 1,479 single tumor cells from six acute lymphoblastic leukemia (ALL) patients. By accurately segregating groups of cooccurring mutations into distinct clonal populations, we identified codominant clones in the majority of patients. Evaluation of intraclonal mutation patterns identified clone-specific punctuated cytosine mutagenesis events, showed that most structural variants are acquired before SNVs, determined that KRAS mutations occur late in disease development but are not sufficient for clonal dominance, and identified clones within the same patient that are arrested at varied stages in B-cell development. Taken together, these data order the sequence of genetic events that underlie childhood ALL and provide a framework for understanding the development of the disease at single-cell resolution.single-cell genomics | acute lymphoblastic leukemia | intratumor heterogeneity | clonal evolution | cytosine mutagenesis A more comprehensive understanding of how malignancies develop could facilitate the rational development of novel anticancer treatment and prevention strategies. Large projects that aim to comprehensively characterize somatic mutations in cancer samples have cataloged many of the recurrent genomic lesions in a wide variety of tumors (1). However, these studies do not measure the correlated cooccurrence of genomic lesions between different cells, which is required for understanding the clonal structure of a tumor as well as for rigorously determining temporal ordering of mutation acquisition. Other studies have provided some temporal resolution of mutation segregation patterns from diagnosis to disease recurrence, allowing for post hoc inference of intratumor clonal heterogeneity at diagnosis (2-5). However, approaches that rely on mutant allele frequencies to determine clonal structure require multiple samples from the same patient and are unable to resolve clones with mutations present at similar frequencies, which is a prerequisite to unambiguously determine the clonal structure and delineate the evolution of the disease (3-5). In principle, single cell genomics provides the most rigorous method to determine the clonal heterogeneity of tumors; as discussed below, there have been recent advances in this approach, but technical limitations have until now prevented it from fully addressing the questions of interest.Studies of pediatric acute lymphoblastic leukemias (ALL) have provided a limited ordering of the genetic events that underlie childhood leukemogenesis by studying prediagnostic samples. For example, ETV6 -RUNX1 translocations, which occur in about a third of patients under 10 y of age, have been shown to occur in utero by tracking the translocation back to neonatal blood spots (6, 7). In addition, a recent report ...