Alistair N. Boettiger

Spatially resolved, highly multiplexed RNA profiling in single cells

Multiplexed RNA imaging in single cells The basis of cellular function is where and when proteins are expressed and in what quantities. Single-molecule fluorescence in situ hybridization (smFISH) experiments quantify the copy number and location of mRNA molecules; however, the numbers of RNA species that can be simultaneously measured by smFISH has been limited. Using combinatorial labeling with error-robust encoding schemes, Chen et al. simultaneously imaged 100 to 1000 RNA species in a single cell. Such large-scale detection allows regulatory interactions to be analyzed at the transcriptome scale. Science, this issue p. 10.1126/science.aaa6090 A single-molecule imaging method allows simultaneous measurement of 1000 RNA species in single cells. INTRODUCTION The copy number and intracellular localization of RNA are important regulators of gene expression. Measurement of these properties at the transcriptome scale in single cells will give answers to many questions related to gene expression and regulation. Single-molecule RNA imaging approaches, such as single-molecule fluorescence in situ hybridization (smFISH), are powerful tools for counting and mapping RNA; however, the number of RNA species that can be simultaneously imaged in individual cells has been limited. This makes it challenging to perform transcriptomic analysis of single cells in a spatially resolved manner. Here, we report multiplexed error-robust FISH (MERFISH), a single-molecule imaging method that allows thousands of RNA species to be imaged in single cells by using combinatorial FISH labeling with encoding schemes capable of detecting and/or correcting errors. RATIONALE We labeled each cellular RNA with a set of encoding probes, which contain targeting sequences that bind the RNA and readout sequences that bind fluorescently labeled readout probes. Each RNA species is encoded with a particular combination of readout sequences. We used successive rounds of hybridization and imaging, each with a different readout probe, to identify the readout sequences bound to each RNA and to decode the RNA. In principle, combinatorial labeling allows the number of detectable RNA species to grow exponentially with the number of imaging rounds, but the detection errors also increase exponentially. To combat such accumulating errors, we exploited error-robust encoding schemes used in digital electronics, such as the extended Hamming code, in the design of our encoding probes but modified these schemes in order to account for the error properties in FISH measurements. We assigned each RNA a binary word in our modified Hamming code and encoded the RNA with a combination of readout sequences according to this binary word. RESULTS We first imaged 140 RNA species in human fibroblast cells using MERFISH with 16 rounds of hybridization and a modified Hamming code capable of both error detection and correction. We obtained ~80% detection efficiency and observed excellent correlation of RNA copy numbers determined with MERFISH with both bulk RNA sequencing data and conventional smFISH measurements of individual genes. Next, we used an alternative MERFISH encoding scheme, which is capable of detecting but not correcting errors, to image 1001 RNA species in individual cells using only 14 rounds of hybridization. The observed RNA copy numbers again correlate well with bulk sequencing data. However, the detection efficiency is only one-third that of the error-correcting encoding scheme. We performed correlation analysis of the 104 to 106 pairs of measured genes and identified many covarying gene groups that share common regulatory elements. Such grouping allowed us to hypothesize potential functions of ~100 unannotated or partially annotated genes of unknown functions. We further analyzed correlations in the spatial distributions of different RNA species and identified groups of RNAs with different distribution patterns in the cell. DISCUSSION This highly multiplexed imaging approach enables analyses based on the variation and correlation of copy numbers and spatial distributions of a large number of RNA species within single cells. Such analyses should facilitate the delineation of regulatory networks and in situ identification of cell types. We envision that this approach will allow spatially resolved transcriptomes to be determined for single cells. MERFISH for transcriptome imaging. Numerous RNA species can be identified, counted, and localized in a single cell by using MERFISH, a single-molecule imaging approach that uses combinatorial labeling and sequential imaging with encoding schemes capable of detection and/or correction of errors. This highly multiplexed measurement of individual RNAs can be used to compute the gene expression profile and noise, covariation in expression among different genes, and spatial distribution of RNAs within single cells. Knowledge of the expression profile and spatial landscape of the transcriptome in individual cells is essential for understanding the rich repertoire of cellular behaviors. Here, we report multiplexed error-robust fluorescence in situ hybridization (MERFISH), a single-molecule imaging approach that allows the copy numbers and spatial localizations of thousands of RNA species to be determined in single cells. Using error-robust encoding schemes to combat single-molecule labeling and detection errors, we demonstrated the imaging of 100 to 1000 distinct RNA species in hundreds of individual cells. Correlation analysis of the ~104 to 106 pairs of genes allowed us to constrain gene regulatory networks, predict novel functions for many unannotated genes, and identify distinct spatial distribution patterns of RNAs that correlate with properties of the encoded proteins.

Multiple enhancers ensure precision of gap gene-expression patterns in the Drosophila embryo

Segmentation of the Drosophila embryo begins with the establishment of spatially restricted gap gene-expression patterns in response to broad gradients of maternal transcription factors, such as Bicoid. Numerous studies have documented the fidelity of these expression patterns, even when embryos are subjected to genetic or environmental stress, but the underlying mechanisms for this transcriptional precision are uncertain. Here we present evidence that every gap gene contains multiple enhancers with overlapping activities to produce authentic patterns of gene expression. For example, a recently identified hunchback (hb) enhancer (located 5-kb upstream of the classic enhancer) ensures repression at the anterior pole. The combination of intronic and 5′ knirps (kni) enhancers produces a faithful expression pattern, even though the intronic enhancer alone directs an abnormally broad expression pattern. We present different models for “enhancer synergy,” whereby two enhancers with overlapping activities produce authentic patterns of gene expression.

Synchronous and Stochastic Patterns of Gene Activation in the Drosophila Embryo

Stalled Development? Most developmental control genes that pattern the Drosophila embryo appear to have stalled RNA polymerase II (Pol II) bound to them prior to their activation. Classical studies on the Drosophila heat shock genes have shown that stalled Pol II renders these genes “poised” for rapid induction by stress. Boettiger and Levine (p. 471) now provide evidence for another potential function of stalled Pol II: Stalled genes exhibit synchronous patterns of gene activation in the early Drosophila embryo so that most or all cells in an embryonic tissue display nascent transcripts at the onset of expression. This synchrony might promote transcriptional precision during development. Synchronous activation of genes with stalled RNA polymerase improves transcriptional coordination. Drosophila embryogenesis is characterized by rapid transitions in gene activity, whereby crudely distributed gradients of regulatory proteins give way to precise on/off patterns of gene expression. To explore the underlying mechanisms, a partially automated, quantitative in situ hybridization method was used to visualize expression profiles of 14 developmental control genes in hundreds of embryos. These studies revealed two distinct patterns of gene activation: synchronous and stochastic. Synchronous genes display essentially uniform expression of nascent transcripts in all cells of an embryonic tissue, whereas stochastic genes display erratic patterns of de novo activation. RNA polymerase II is “pre-loaded” (stalled) in the promoter regions of synchronous genes, but not stochastic genes. Transcriptional synchrony might ensure the orderly deployment of the complex gene regulatory networks that control embryogenesis.

Single-molecule super-resolution imaging of chromosomes and in situ haplotype visualization using Oligopaint FISH probes

Fluorescence in situ hybridization (FISH) is a powerful single-cell technique for studying nuclear structure and organization. Here we report two advances in FISH-based imaging. We first describe the in situ visualization of single-copy regions of the genome using two single-molecule super-resolution methodologies. We then introduce a robust and reliable system that harnesses single-nucleotide polymorphisms (SNPs) to visually distinguish the maternal and paternal homologous chromosomes in mammalian and insect systems. Both of these new technologies are enabled by renewable, bioinformatically designed, oligonucleotide-based Oligopaint probes, which we augment with a strategy that uses secondary oligonucleotides (oligos) to produce and enhance fluorescent signals. These advances should substantially expand the capability to query parent-of-origin-specific chromosome positioning and gene expression on a cell-by-cell basis.

Nuclear Trapping Shapes the Terminal Gradient in the Drosophila Embryo

Patterning of the terminal regions of the Drosophila embryo relies on the gradient of phosphorylated ERK/MAPK (dpERK), which is controlled by the localized activation of the Torso receptor tyrosine kinase [1-4]. This model is supported by a large amount of data, but the gradient itself has never been quantified. We present the first measurements of the dpERK gradient and establish a new intracellular layer of its regulation. Based on the quantitative analysis of the spatial pattern of dpERK in mutants with different levels of Torso as well as the dynamics of the wild-type dpERK pattern, we propose that the terminal-patterning gradient is controlled by a cascade of diffusion-trapping modules. A ligand-trapping mechanism establishes a sharply localized pattern of the Torso receptor occupancy on the surface of the embryo. Inside the syncytial embryo, nuclei play the role of traps that localize diffusible dpERK. We argue that the length scale of the terminal-patterning gradient is determined mainly by the intracellular module.

Chromatin topology is coupled to Polycomb group protein subnuclear organization

The genomes of metazoa are organized at multiple scales. Many proteins that regulate genome architecture, including Polycomb group (PcG) proteins, form subnuclear structures. Deciphering mechanistic links between protein organization and chromatin architecture requires precise description and mechanistic perturbations of both. Using super-resolution microscopy, here we show that PcG proteins are organized into hundreds of nanoscale protein clusters. We manipulated PcG clusters by disrupting the polymerization activity of the sterile alpha motif (SAM) of the PcG protein Polyhomeotic (Ph) or by increasing Ph levels. Ph with mutant SAM disrupts clustering of endogenous PcG complexes and chromatin interactions while elevating Ph level increases cluster number and chromatin interactions. These effects can be captured by molecular simulations based on a previously described chromatin polymer model. Both perturbations also alter gene expression. Organization of PcG proteins into small, abundant clusters on chromatin through Ph SAM polymerization activity may shape genome architecture through chromatin interactions.

The neural origins of shell structure and pattern in aquatic mollusks.

We present a model to explain how the neurosecretory system of aquatic mollusks generates their diversity of shell structures and pigmentation patterns. The anatomical and physiological basis of this model sets it apart from other models used to explain shape and pattern. The model reproduces most known shell shapes and patterns and accurately predicts how the pattern alters in response to environmental disruption and subsequent repair. Finally, we connect the model to a larger class of neural models.

Inferring ecological and behavioral drivers of African elephant movement using a linear filtering approach

Understanding the environmental factors influencing animal movements is fundamental to theoretical and applied research in the field of movement ecology. Studies relating fine-scale movement paths to spatiotemporally structured landscape data, such as vegetation productivity or human activity, are particularly lacking despite the obvious importance of such information to understanding drivers of animal movement. In part, this may be because few approaches provide the sophistication to characterize the complexity of movement behavior and relate it to diverse, varying environmental stimuli. We overcame this hurdle by applying, for the first time to an ecological question, a finite impulse-response signal-filtering approach to identify human and natural environmental drivers of movements of 13 free-ranging African elephants (Loxodonta africana) from distinct social groups collected over seven years. A minimum mean-square error (MMSE) estimation criterion allowed comparison of the predictive power of landscape and ecological model inputs. We showed that a filter combining vegetation dynamics, human and physical landscape features, and previous movement outperformed simpler filter structures, indicating the importance of both dynamic and static landscape features, as well as habit, on movement decisions taken by elephants. Elephant responses to vegetation productivity indices were not uniform in time or space, indicating that elephant foraging strategies are more complex than simply gravitation toward areas of high productivity. Predictions were most frequently inaccurate outside protected area boundaries near human settlements, suggesting that human activity disrupts typical elephant movement behavior. Successful management strategies at the human-elephant interface, therefore, are likely to be context specific and dynamic. Signal processing provides a promising approach for elucidating environmental factors that drive animal movements over large time and spatial scales.

Spatial organization shapes the turnover of a bacterial transcriptome

Spatial organization of the transcriptome has emerged as a powerful means for regulating the post-transcriptional fate of RNA in eukaryotes; however, whether prokaryotes use RNA spatial organization as a mechanism for post-transcriptional regulation remains unclear. Here we used super-resolution microscopy to image the E. coli transcriptome and observed a genome-wide spatial organization of RNA: mRNAs encoding inner-membrane proteins are enriched at the membrane, whereas mRNAs encoding outer-membrane, cytoplasmic and periplasmic proteins are distributed throughout the cytoplasm. Membrane enrichment is caused by co-translational insertion of signal peptides recognized by the signal-recognition particle. Time-resolved RNA-sequencing revealed that degradation rates of inner-membrane-protein mRNAs are on average greater that those of the other mRNAs and that this selective destabilization of inner-membrane-protein mRNAs is abolished by dissociating the RNA degradosome from the membrane. Together, these results demonstrate that the bacterial transcriptome is spatially organized and suggest that this organization shapes the post-transcriptional dynamics of mRNAs. DOI: http://dx.doi.org/10.7554/eLife.13065.001

Rapid Transcription Fosters Coordinate snail Expression in the Drosophila Embryo

Transcription is commonly held to be a highly stochastic process, resulting in considerable heterogeneity of gene expression among the different cells in a population. Here, we employ quantitative in situ hybridization methods coupled with high-resolution imaging assays to measure the expression of snail, a developmental patterning gene necessary for coordinating the invagination of the mesoderm during gastrulation of the Drosophila embryo. Our measurements of steady-state mRNAs suggest that there is very little variation in snail expression across the different cells that make up the mesoderm and that synthesis approaches the kinetic limits of Pol II processivity. We propose that rapid transcription kinetics and negative autoregulation are responsible for the remarkable homogeneity of snail expression and the coordination of mesoderm invagination.