Understanding the spatial organization of gene expression with single nucleotide resolution requires localizing the sequences of expressed RNA transcripts within a cell in situ. Here we describe fluorescent in situ RNA sequencing (FISSEQ), in which stably cross-linked cDNA amplicons are sequenced within a biological sample. Using 30-base reads from 8,742 genes in situ, we examined RNA expression and localization in human primary fibroblasts using a simulated wound healing assay. FISSEQ is compatible with tissue sections and whole mount embryos, and reduces the limitations of optical resolution and noisy signals on single molecule detection. Our platform enables massively parallel detection of genetic elements, including gene transcripts and molecular barcodes, and can be used to investigate cellular phenotype, gene regulation, and environment in situ.

We developed Tethered Conformation Capture (TCC), a method for genome-wide mapping of chromatin interactions. By implementing solid-phase ligation, TCC substantially enhanced the signal-to-noise ratio and thus, enabled a detailed analysis of inter-chromosomal interactions. We identified a group of regions in each chromosome that predominantly mediate inter-chromosomal interactions. These regions are marked by high transcriptional activity, suggesting that their interactions are mediated by transcription factories. Each of these regions interacts with numerous other such regions throughout the genome in an indiscriminate fashion, partly driven by the accessibility of the partners. Therefore, it is likely that a different combination of interactions is present in different cells. Accommodating this variability, we developed a computational method to translate the TCC data into physical chromatin contacts in a population of three-dimensional genome structures. Statistical analysis of the resulting population demonstrates that the indiscriminate properties of inter-chromosomal interactions is consistent with the well-known architectural features of the human genome.

RNA sequencing measures the quantitative change in gene expression over the whole transcriptome, but it lacks spatial context. On the other hand, in situ hybridization provides the location of gene expression, but only for a small number of genes. Here we detail a protocol for genome-wide profiling of gene expression in situ in fixed cells and tissues, in which RNA is converted into cross-linked cDNA amplicons and sequenced manually on a confocal microscope. Unlike traditional RNA-seq our method enriches for context-specific transcripts over house-keeping and/or structural RNA, and it preserves the tissue architecture for RNA localization studies. Our protocol is written for researchers experienced in cell microscopy with minimal computing skills. Library construction and sequencing can be completed within 14 d, with image analysis requiring an additional 2 d.

In vivo barcoding using nuclease-induced mutations is a powerful approach for recording biological information, including developmental lineages; however, its application in mammalian systems has been limited. We present in vivo barcoding in the mouse with multiple homing guide RNAs that each generate hundreds of mutant alleles and combine to produce an exponential diversity of barcodes. Activation upon conception and continued mutagenesis through gestation resulted in developmentally barcoded mice wherein information is recorded in lineage-specific mutations. We used these recordings for reliable post hoc reconstruction of the earliest lineages and investigation of axis development in the brain. Our results provide an enabling and versatile platform for in vivo barcoding and lineage tracing in a mammalian model system.

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm the presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization. (14), and single-cell (15) and in situ Hi-C (16)], close chromatin contacts can now be identified at increasing resolution, providing new insight into genome organization. These methods measure the relative frequencies of chromosome interactions averaged over a large population of cells. However, individual 3D genome structures can vary dramatically from cell to cell even within an isogenic sample, especially with respect to long-range interactions (15,17,18). This structural variability poses a great challenge to the interpretation of ensemble-averaged Hi-C data (14,(19)(20)(21)(22)(23) and prevents the direct detection of cooperative interactions co-occurring in the same cell. This problem is particularly evident for long-range (cis) and interchromosomal (trans) interactions, which are generally observed at relatively low frequencies and are therefore present only in a small subset of individual cells at any given time (3,11,15). Despite their low frequencies, long-range and interchromosome interaction patterns are not random noise. In fact, these interactions are more informative than short-range interactions in determining the global genome architectures in cells and are often functionally relevant-interactions between transcriptionally active regions are often interchromosomal in nature (14). Owing to their variable nature, long-range and trans interactions can be part of alternative, structurally different conformations, which makes their interpretation in form of consensus structures impossible. However, inferring which of the long-range interactions co-occur in the same cell from ensemble Hi-C data remains a major challenge.These challenges cannot be easily overcome even by the new single-cell Hi-C techno...

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power–bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices.

We present here an approach for engineering evolving DNA barcodes in living cells. The methodology entails using a homing guide RNA (hgRNA) scaffold that directs the Cas9-hgRNA complex to target the DNA locus of the hgRNA itself. We show that this homing CRISPR-Cas9 system acts as an expressed genetic barcode that diversifies its sequence and that the rate of diversification can be controlled in cultured cells. We further evaluate these barcodes in cell populations and show the barcode RNAs can be assayed as single molecules in situ . This integrated approach will have wide ranging applications, such as in deep lineage tracing, cellular barcoding, molecular recording, dissecting cancer biology, and connectome mapping.

Robust SNP genotyping technologies and data analysis programs have encouraged researchers in recent years to use SNPs for linkage studies. Platforms used to date have been 10 K chip arrays, but the possible value of interrogating SNPs at higher densities has been considered. Here, we present a genome-wide linkage analysis by means of a 500 K SNP platform. The analysis was done on a large pedigree affected with Parkinsonian-pyramidal syndrome (PPS), and the results showed linkage to chromosome 22. Sequencing of candidate genes revealed a disease-associated homozygous variation (R378G) in FBXO7. FBXO7 codes for a member of the F-box family of proteins, all of which may have a role in the ubiquitin-proteosome protein-degradation pathway. This pathway has been implicated in various neurodegenerative diseases, and identification of FBXO7 as the causative gene of PPS is expected to shed new light on its role. The performance of the array was assessed and systematic analysis of effects of SNP density reduction was performed with the real experimental data. Our results suggest that linkage in our pedigree may have been missed had we used chips containing less than 100,000 SNPs across the genome.