The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.

A n A ly s i s RNA-seq experiments generate reads derived not only from mature RNA transcripts but also from pre-mRNA. Here we present a computational approach called exon-intron split analysis (EISA) that measures changes in mature RNA and pre-mRNA reads across different experimental conditions to quantify transcriptional and post-transcriptional regulation of gene expression. We apply EISA to 17 diverse data sets to show that most intronic reads arise from nuclear RNA and changes in intronic read counts accurately predict changes in transcriptional activity. Furthermore, changes in posttranscriptional regulation can be predicted from differences between exonic and intronic changes. EISA reveals both transcriptional and post-transcriptional contributions to expression changes, increasing the amount of information that can be gained from RNA-seq data sets.Cellular RNAs are regulated at multiple stages, including transcription, RNA maturation and degradation. Several analytic methods have been developed to measure these processes on a transcriptomewide scale. For example, global run-on sequencing (GRO-seq) 1 uses incorporation of a nucleotide analog to enrich for nascent RNA. In Nascent-seq 2,3 , newly transcribed RNAs are isolated by purification of their complex with proteins and the DNA template. Cellular fractionation techniques 4 have also been adapted to measure nascent transcripts, which are enriched in the nucleus. mRNA half-lives have been determined, for example, by blockage of transcription followed by transcriptional profiling 5 . RNA sequencing, the most widely used method for transcriptome analysis, has been applied in numerous studies to determine steady-state mRNA levels 6,7 and alternative splicing events 8 and to identify previously unknown transcripts and noncoding RNAs 9-11 . In general, these protocols aim to enrich for mature mRNA by selection of polyadenylated RNA or by depletion of ribosomal RNA.Many computational methods (reviewed in refs. 12,13) have been developed for the analysis of RNA-seq data, to enable spliced alignment 14,15 , transcript assembly 16,17 , transcript quantification 14,18 and differential expression analysis [19][20][21] . Although RNA-seq mostly generates reads that map to exons, it also captures less abundant intronic sequences 6 . However, their interpretation has remained controversial. Some have suggested that they originate from DNA contamination and can thus be used as a quality metric for RNA-seq data 22 (see also RNA-seq guidelines of the Roadmap Epigenomics Consortium, http://www.roadmapepigenomics.org/), whereas others have hypothesized that they stem from unknown exons or intronic enhancers 6,7 . In a study based on exon arrays, probes mapping to introns were used to investigate pre-mRNA dynamics 23 . Three recent studies based on RNA-seq provided evidence that intronic reads might correlate with transcriptional activity. In two of these, the read coverage along introns was related to nascent transcription in combination with co-transcriptional splicing e...

Embryonic development is a crucial period in the life of a multicellular organism, during which limited sets of embryonic progenitors produce all cells in the adult body. Determining which fate these progenitors acquire in adult tissues requires the simultaneous measurement of clonal history and cell identity at single-cell resolution, which has been a major challenge. Clonal history has traditionally been investigated by microscopically tracking cells during development, monitoring the heritable expression of genetically encoded fluorescent proteins and, more recently, using next-generation sequencing technologies that exploit somatic mutations, microsatellite instability, transposon tagging, viral barcoding, CRISPR-Cas9 genome editing and Cre-loxP recombination. Single-cell transcriptomics provides a powerful platform for unbiased cell-type classification. Here we present ScarTrace, a single-cell sequencing strategy that enables the simultaneous quantification of clonal history and cell type for thousands of cells obtained from different organs of the adult zebrafish. Using ScarTrace, we show that a small set of multipotent embryonic progenitors generate all haematopoietic cells in the kidney marrow, and that many progenitors produce specific cell types in the eyes and brain. In addition, we study when embryonic progenitors commit to the left or right eye. ScarTrace reveals that epidermal and mesenchymal cells in the caudal fin arise from the same progenitors, and that osteoblast-restricted precursors can produce mesenchymal cells during regeneration. Furthermore, we identify resident immune cells in the fin with a distinct clonal origin from other blood cell types. We envision that similar approaches will have major applications in other experimental systems, in which the matching of embryonic clonal origin to adult cell type will ultimately allow reconstruction of how the adult body is built from a single cell.

During gastrulation, embryonic cells become specified into distinct germ layers. In mouse, this continues throughout somitogenesis from a population of bipotent stem cells called neuromesodermal progenitors (NMps). However, the degree of self-renewal associated with NMps in the fast-developing zebrafish embryo is unclear. Using a genetic clone-tracing method, we labelled early embryonic progenitors and found a strong clonal similarity between spinal cord and mesoderm tissues. We followed individual cell lineages using light-sheet imaging, revealing a common neuromesodermal lineage contribution to a subset of spinal cord tissue across the anterior-posterior body axis. An initial population subdivides at mid-gastrula stages and is directly allocated to neural and mesodermal compartments during gastrulation. A second population in the tailbud undergoes delayed allocation to contribute to the neural and mesodermal compartment only at late somitogenesis. Cell tracking and retrospective cell fate assignment at late somitogenesis stages reveal these cells to be a collection of mono-fated progenitors. Our results suggest that NMps are a conserved population of bipotential progenitors, the lineage of which varies in a species-specific manner due to vastly different rates of differentiation and growth.

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3 equal contribution 4 correspondence: janphilipp.junker@mdc-berlin.de (J.P.J.), a.vanoudenaarden@hubrecht.eu (A.v.O.) A key goal of developmental biology is to understand how a single cell transforms into a full-grown organism consisting of many cells. Although impressive progress has been made in lineage tracing using imaging approaches, analysis of vertebrate lineage trees has mostly been limited to relatively small subsets of cells. Here we present scartrace, a strategy for massively parallel whole-organism lineage tracing based on Cas9 induced genetic scars in the zebrafish.The timing of each cell division and the fate of the progeny define the lineage of an organism. Analysis of the lineage history of cell populations can reveal the developmental origin and the clonality of cell populations 1 . Genetically encoded fluorescent proteins are widely used as lineage markers 2,3 , but due to limited spectral resolution this approach has mostly been restricted to tracking the lineage of a relatively small subset of cells. Recent progress in live imaging has allowed for following many individual cells over time in optically transparent samples such as early fly and zebrafish embryos 4,5 . Nevertheless, direct observation of all cell divisions is generally only possible at the earliest developmental stages. RNA sequencing has emerged as a powerful method for systematic expression profiling of single cells and for computational inference of differentiation dynamics 6-8 . However, our ability to harness the enormous multiplexing capacity of high-throughput sequencing for lineage tracing has so far been lagging behind, despite pioneering studies in the hematopoietic system based on viral barcoding 9,10 or transposon

"Supranormal" cardiac function in athletes is due to better endothelial and arterial function, related to lower oxidative stress, with optimized ventriculo-arterial coupling; athlete's heart is purely a physiological phenomenon, associated with "supranormal" cardiac function, and there are no markers of myocardial fibrosis.

The aim of this work was to assess the reproducibility of ultrasound parameters of vascular function, since these measurements are currently recommended by the guidelines for the evaluation of the cardiovascular risk. Twenty subjects (51 ± 17 years, 11 men) had vascular ultrasound (Aloka Prosound α10) performed by two observers, at the level of the right common carotid artery for assessment of intima-media thickness (IMT), "wall tracking", and "wave-intensity analysis", and at the level of the right brachial artery for the assessment of flow-mediated dilation (FMD). Wave intensity is a hemodynamic index, evaluating ventriculo-arterial interaction and can be measured in real time by a double-beam ultrasound technique through simultaneous recording of carotid arterial blood flow velocity and diameter. Carotido-femoral pulse wave velocity (PWV) was determined using the Complior method. Intra- and inter-observer reproducibility was assessed during a first session, when three consecutive acquisitions were made (first observer → second observer → first observer); repeatability was evaluated 1 week later (second observer). The most reproducible and repeatable parameters were PWV (intraobserver ±3.3%, interobserver ±2.6%, repeatability ±5.6%) and IMT (±3.7, ±4.3, ±4.9%, respectively). Intraobserver reproducibility for arterial stiffness and ventriculo-arterial coupling parameters was the highest for the beta index (±3.8%), and the lowest for the second systolic peak (±22.4%). Interobserver reproducibility and repeatability varied between very good for the wave speed (±5.5 and ±4.3%), and unsatisfactory for the negative area (±31.8 and ±38.6%). FMD had good reproducibility (intraobserver ±11.6%, interobserver ±8%, repeatability ±7%), whereas augmentation index had only satisfactory results (±17.8, ±8.4, ±23.8%, respectively). Only some parameters of vascular function have good reproducibility and repeatability, better or similar to other ultrasound methods and, therefore, these are ready to be used in routine clinical practice.