Biology subjects

Ramani, V.

Publications and source records attributed to Ramani, V..

31 records · Page 2Linked to original sources

bioRxiv2023

The single-molecule accessibility landscape of newly replicated mammalian chromatin

The higher-order structure of newly replicated (i.e. nascent) chromatin fibers remains poorly-resolved, limiting our understanding of how epigenomes are maintained across cell divisions. To address this, we present Replication-Aware Single-molecule Accessibility Mapping (RASAM), a long-read sequencing method that nondestructively measures genome-wide replication-status and protein-DNA interactions simultaneously on intact chromatin templates. We report that individual human and mouse nascent chromatin fibers are hyperaccessible compared to steady-state chromatin. This hyperaccessibility occurs at two, coupled length-scales: first, individual nucleosome core particles on nascent DNA exist as a mixture of partially-unwrapped nucleosomes and other subnucleosomal species; second, newly-replicated chromatin fibers are significantly enriched for irregularly-spaced nucleosomes on individual DNA molecules. Focusing on specific cis-regulatory elements (e.g. transcription factor binding sites; active transcription start sites [TSSs]), we discover unique modes by which nascent chromatin hyperaccessibility is resolved at the single-molecule level: at CCCTC-binding factor (CTCF) binding sites, CTCF and nascent nucleosomes compete for motifs on nascent chromatin fibers, resulting in quantitatively-reduced CTCF occupancy and motif accessibility post-replication; at active TSSs, high levels of steady-state chromatin accessibility are preserved, implying that nucleosome free regions (NFRs) are rapidly re-established behind the fork. Our study introduces a new paradigm for studying higher-order chromatin fiber organization behind the replication fork. More broadly, we uncover a unique organization of newly replicated chromatin that must be reset by active processes, providing a substrate for epigenetic reprogramming.

genomics↗

bioRxiv2022

Sensitive multimodal profiling of native DNA by transposase-mediated single-molecule sequencing

We present SMRT-Tag: a multiplexable, PCR-free approach for constructing low-input, single-molecule Pacific Biosciences (PacBio) sequencing libraries through Tn5 transposition. As proof-of-concept, we apply SMRT-Tag to resolve human genetic and epigenetic variation in gold-standard human reference samples. SMRT-Tag requires 1-5% as much input material as existing protocols (15,000 - 50,000 human cell equivalents) and enables highly-sensitive and simultaneous detection of single nucleotide variants, small insertions / deletions, and CpG methylation comparable to the current state-of-the-art. We further combine SMRT-Tag with in situ adenine methyltransferase footprinting of nuclei (SAMOSA-Tag) to facilitate joint analysis of nucleosome repeat length, CTCF occupancy, and CpG methylation on individual chromatin fibers in osteosarcoma cells. SMRT-Tag promises to enable basic and clinical research by offering scalable, sensitive, and multimodal single-molecule genomic and epigenomic analyses in rare cell populations.

genomics↗

bioRxiv2021

Single-fiber nucleosome density shapes the regulatory output of a mammalian chromatin remodeling enzyme

ATP-dependent chromatin remodelers regulate the DNA accessibility required of virtually all nuclear processes. Biochemical studies have provided insight into remodeler action at the nucleosome level, but how these findings translate to activity on chromatin fibers in vitro and in vivo remains poorly understood. Here, we present a massively multiplex single-molecule platform allowing high-resolution mapping of nucleosomes on fibers assembled on mammalian genomic sequences. We apply this method to distinguish between competing models for chromatin remodeling by the essential ISWI ATPase SNF2h: linker-length-dependent dynamic positioning versus fixed-linker-length static clamping. Our single-fiber data demonstrate that SNF2h operates as a density-dependent, length-sensing chromatin remodeler whose ability to decrease or increase DNA accessibility depends on single-fiber nucleosome density. In vivo, this activity manifests as different regulatory modes across epigenomic domains: at canonically-defined heterochromatin, SNF2h generates evenly-spaced nucleosome arrays of multiple nucleosome repeat lengths; at SNF2h-dependent accessible sites, SNF2h slides nucleosomes to increase accessibility of motifs for the essential transcription factor CTCF. Overall, our generalizable approach provides molecularly-precise views of the processes that shape nuclear physiology. Concurrently, our data illustrate how a mammalian chromatin remodeling enzyme can effectively sense nucleosome density to induce diametrically-opposed regulatory effects within the nucleus.

genomics↗

bioRxiv2020

MLX balances metabolism and stress to suppress apoptosis and maintain spermatogenesis

Male germ cell production is a metabolically-driven and apoptosis-prone process. Here we show that the glucose-sensing transcription factor MLX, and its binding partner MondoA, are both required for male fertility in the mouse, as well as survival of human tumor cells derived from the male germ line. Loss of Mlx results in altered metabolism as well as activation of multiple stress pathways and germ cell apoptosis in the testes. This is concomitant with dysregulation of the expression of male-specific germ cell transcripts and proteins, manifesting as oligoasthenoteratozoospermia (OAT). Our genomic and functional analyses identify loci directly bound by MLX involved in these processes, including metabolic targets, apoptotic effectors and obligate components of male-specific germ cell development. These in vivo and in vitro studies implicate MLX and other members of the proximal MYC network, such as MNT, in regulation of metabolism and differentiation, as well as in suppression of intrinsic and extrinsic death signaling pathways in both spermatogenesis and male germ cell tumors. Highlights- The MAX-like bHLHLZ protein MLX is required for male fertility, but not embryonic development. - MLX and its heterodimeric partner MondoA are each required for both male fertility and survival of male germ cell tumors. - Genomic analysis identifies direct MLX targets associated with metabolism, stress and male germ cell development. - Loss of MLX alters MYC network genome occupancy and transcriptional output.

developmental biology↗

bioRxiv2020

Single-cell landscape of nuclear configuration and gene expression during stem cell differentiation and X inactivation

Mammalian development is associated with extensive changes in gene expression, chromatin accessibility, and nuclear structure. Here, we follow such changes associated with mouse embryonic stem cell differentiation and X inactivation by integrating, for the first time, allele-specific data obtained by high-throughput single-cell RNA-seq, ATAC-seq, and Hi-C. In differentiated cells, contact decay profiles, which clearly distinguish the active and inactive X chromosomes, reveal loss of the inactive X-specific structure at mitosis followed by a rapid reappearance, suggesting a bookkeeping mechanism. In differentiating embryonic stem cells, changes in contact decay profiles are detected in parallel on both the X chromosomes and autosomes, suggesting profound simultaneous reorganization. The onset of the inactive X-specific structure in single cells is notably delayed relative to that of gene silencing, consistent with the idea that chromatin compaction is a late event of X inactivation. Novel computational approaches to effectively align single-cell gene expression, chromatin accessibility, and 3D chromosome structure reveal that long-range structural changes to chromosomes appear as discrete events, unlike progressive changes in gene expression and chromatin accessibility.

genomics↗

bioRxiv2020

Unsupervised manifold alignment for single-cell multi-omics data

Integrating single-cell measurements that capture different properties of the genome is vital to extending our understanding of genome biology. This task is challenging due to the lack of a shared axis across datasets obtained from different types of single-cell experiments. For most such datasets, we lack corresponding information among the cells (samples) and the measurements (features). In this scenario, unsupervised algorithms that are capable of aligning single-cell experiments are critical to learning an in silico co-assay that can help draw correspondences among the cells. Maximum mean discrepancy-based manifold alignment (MMD-MA) is such an unsupervised algorithm. Without requiring correspondence information, it can align single-cell datasets from different modalities in a common shared latent space, showing promising results on simulations and a small-scale single-cell experiment with 61 cells. However, it is essential to explore the applicability of this method to larger single-cell experiments with thousands of cells so that it can be of practical interest to the community. In this paper, we apply MMD-MA to two recent datasets that measure transcriptome and chromatin accessibility in ~2000 single cells. To scale the runtime of MMD-MA to a more substantial number of cells, we extend the original implementation to run on GPUs. We also introduce a method to automatically select one of the user-defined parameters, thus reducing the hyperparameter search space. We demonstrate that the proposed extensions allow MMD-MA to accurately align state-of-the-art single-cell experiments.

bioinformatics↗

bioRxiv2020

Massively multiplex single-molecule oligonucleosome footprinting

Our understanding of the beads-on-a-string arrangement of nucleosomes has been built largely on high-resolution sequence-agnostic imaging methods and sequence-resolved bulk biochemical techniques. To bridge the divide between these approaches, we present the single-molecule adenine methylated oligonucleosome sequencing assay (SAMOSA). SAMOSA is a high-throughput single-molecule sequencing method that combines adenine methyltransferase footprinting and single-molecule real-time DNA sequencing to natively and nondestructively measure nucleosome positions on individual chromatin fibres. SAMOSA data allows unbiased classification of single-molecular states of nucleosome occupancy on individual chromatin fibres. We leverage this to estimate nucleosome regularity and spacing on single chromatin fibres genome-wide, at predicted transcription factor binding motifs, and across both active and silent human epigenomic domains. Our analyses suggest that chromatin is comprised of a diverse array of both regular and irregular single-molecular oligonucleosome patterns that differ subtly in their relative abundance across epigenomic domains. This irregularity is particularly striking in constitutive heterochromatin, which has typically been viewed as a conformationally static entity. Our proof-of-concept study provides a powerful new methodology for studying nucleosome organization at a previously intractable resolution, and offers up new avenues for modeling and visualizing higher-order chromatin structure. 1-sentence summaryHigh-throughput single-molecule real-time footprinting of chromatin arrays reveals heterogeneous patterns of oligonucleosome occupancy.

genomics↗

bioRxiv2019

Sci-Hi-C: a single-cell Hi-C method for mapping 3D genome organization in large number of single cells

The highly dynamic nature of chromosome conformation and three-dimensional (3D) genome organization leads to cell-to-cell variability in chromatin interactions within a cell population, even if the cells of the population appear to be functionally homogeneous. Hence, although Hi-C is a powerful tool for mapping 3D genome organization, this heterogeneity of chromosome higher order structure among individual cells limits the interpretive power of population based bulk Hi-C assays. Moreover, single-cell studies have the potential to enable the identification and characterization of rare cell populations or cell subtypes in a heterogeneous population. However, it may require surveying relatively large numbers of single cells to achieve statistically meaningful observations in single-cell studies. By applying combinatorial cellular indexing to chromosome conformation capture, we developed single-cell combinatorial indexed Hi-C (sci-Hi-C), a high throughput method that enables mapping chromatin interactomes in large number of single cells. We demonstrated the use of sci-Hi-C data to separate cells by karytoypic and cell-cycle state differences and to identify cellular variability in mammalian chromosomal conformation. Here, we provide a detailed description of method design and step-by-step working protocols for sci-Hi-C.

genomics↗

bioRxiv2019

Capturing cell type-specific chromatin structural patterns by applying topic modeling to single-cell Hi-C data

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate twelve different single-cell combinatorial indexed Hi-C (sciHi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 25,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sciHi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.

genomics↗

bioRxiv2018

Real-time detection of circulating tumor cells in living animals using functionalized large gold nanorods

Optical coherence tomography (OCT) with significant speckle reduction can be used with highly-scattering contrast agents for noninvasive, contrast-enhanced imaging of living tissue at the cellular scale. The advantages of reduced speckle noise and improved targeted contrast can be harnessed to track objects as small as 2 m in vivo, with the potential for cell tracking and counting in living subjects. Here we demonstrate the use of Large Gold Nanorods (LGNRs) as contrast agents for detecting individual micron-sized polystyrene beads and single myeloma cells in blood circulation using speckle modulating-OCT (SM-OCT). This is the first time that OCT has been used to image at the individual cell scale in vivo. This technical capability presents an exciting opportunity for the dynamic detection and quantification of tumor cells circulating in living subjects.

bioengineering↗

bioRxiv2017

Dynamic reorganization of nuclear architecture during human cardiogenesis

While chromosomal architecture varies among cell types, little is known about how this organization is established or its role in development. We integrated Hi-C, RNA-seq and ATAC-seq during cardiac differentiation from human pluripotent stem cells to generate a comprehensive profile of chromosomal architecture. We identified active and repressive domains that are dynamic during cardiogenesis and recapitulate in vivo cardiomyocytes. During differentiation, heterochromatic regions condense in cis. In contrast, many cardiac-specific genes, such as TTN (titin), decompact and transition to an active compartment coincident with upregulation. Moreover, we identify a network of genes, including TTN, that share the heart-specific splicing factor, RBM20, and become associated in trans during differentiation, suggesting the existence of a 3D nuclear splicing factory. Our results demonstrate both the dynamic nature in nuclear architecture and provide insights into how developmental genes are coordinately regulated.\n\nOne Sentence SummaryThe three-dimensional structure of the human genome is dynamically regulated both globally and locally during cardiogenesis.

genomics↗

bioRxiv2017

Orientation-dependent Dxz4 contacts shape the 3D structure of the inactive X chromosome

The mammalian inactive X chromosome (Xi) condenses into a bipartite structure with two superdomains of frequent long-range contacts separated by a boundary or hinge region. Using in situ DNase Hi-C in mouse cells with deletions or inversions within the hinge we show that the conserved repeat locus Dxz4 alone is sufficient to maintain the bipartite structure and that Dxz4 orientation controls the distribution of long-range contacts on the Xi. Frequent long-range contacts between Dxz4 and the telomeric superdomain are either lost after its deletion or shifted to the centromeric superdomain after its inversion. This massive reversal in contact distribution is consistent with the reversal of CTCF motif orientation at Dxz4. De-condensation of the Xi after Dxz4 deletion is associated with partial restoration of TADs normally attenuated on the Xi. There is also an increase in chromatin accessibility and CTCF binding on the Xi after Dxz4 deletion or inversion, but few changes in gene expression, in accordance with multiple epigenetic mechanisms ensuring X silencing. We propose that Dxz4 represents a structural platform for frequent long-range contacts with multiple loci in a direction dictated by the orientation of a bank of CTCF motifs at Dxz4, which may work as a ratchet to form the distinctive bipartite structure of the condensed Xi.

molecular biology↗

bioRxiv2017

Comprehensive single cell transcriptional profiling of a multicellular organism by combinatorial indexing

Conventional methods for profiling the molecular content of biological samples fail to resolve heterogeneity that is present at the level of single cells. In the past few years, single cell RNA sequencing has emerged as a powerful strategy for overcoming this challenge. However, its adoption has been limited by a paucity of methods that are at once simple to implement and cost effective to scale massively. Here, we describe a combinatorial indexing strategy to profile the transcriptomes of large numbers of single cells or single nuclei without requiring the physical isolation of each cell (Single cell Combinatorial Indexing RNA-seq or sci-RNA-seq). We show that sci-RNA-seq can be used to efficiently profile the transcriptomes of tens-of-thousands of single cells per experiment, and demonstrate that we can stratify cell types from these data. Key advantages of sci-RNA-seq over contemporary alternatives such as droplet-based single cell RNA-seq include sublinear cost scaling, a reliance on widely available reagents and equipment, the ability to concurrently process many samples within a single workflow, compatibility with methanol fixation of cells, cell capture based on DNA content rather than cell size, and the flexibility to profile either cells or nuclei. As a demonstration of sci-RNA-seq, we profile the transcriptomes of 42,035 single cells from C. elegans at the L2 stage, effectively 50-fold \"shotgun cellular coverage\" of the somatic cell composition of this organism at this stage. We identify 27 distinct cell types, including rare cell types such as the two distal tip cells of the developing gonad, estimate consensus expression profiles and define cell-type specific and selective genes. Given that C. elegans is the only organism with a fully mapped cellular lineage, these data represent a rich resource for future methods aimed at defining cell types and states. They will advance our understanding of developmental biology, and constitute a major step towards a comprehensive, single-cell molecular atlas of a whole animal.

genomics↗