Machine Learning Methods for Exploring Sequence Determinants of 3D Genome Organization

In higher eukaryotic cells, chromosomes are folded inside the nucleus. Recent advances in whole-genome mapping technologies have revealed the multiscale features of 3D genome organization that are intertwined with fundamental genome functions. However, DNA sequence determinants that modulate the formation of 3D genome organization remain poorly characterized. In the past few years, predicting 3D genome organization based on DNA sequence features has become an active area of research. Here, we review the recent progress in computational approaches to unraveling important sequence elements for 3D genome organization. In particular, we discuss the rapid development of machine learning-based methods that facilitate the connections between DNA sequence features and 3D genome architectures at different scales. While much progress has been made in developing predictive models for revealing important sequence features for 3D genome organization, new research is urgently needed to incorporate multi-omic data and enhance model interpretability, further advancing our understanding of gene regulation mechanisms through the lens of 3D genome organization.     

Whole Genome Sequencing Reveals a De Novo SHANK3 Mutation in Familial Autism Spectrum Disorder

IntroductionClinical genomics promise to be especially suitable for the study of etiologically heterogeneous conditions such as Autism Spectrum Disorder (ASD). Here we present three siblings with ASD where we evaluated the usefulness of Whole Genome Sequencing (WGS) for the diagnostic approach to ASD.MethodsWe identified a family segregating ASD in three siblings with an unidentified cause. We performed WGS in the three probands and used a state-of-the-art comprehensive bioinformatic analysis pipeline and prioritized the identified variants located in genes likely to be related to ASD. We validated the finding by Sanger sequencing in the probands and their parents.ResultsThree male siblings presented a syndrome characterized by severe intellectual disability, absence of language, autism spectrum symptoms and epilepsy with negative family history for mental retardation, language disorders, ASD or other psychiatric disorders. We found germline mosaicism for a heterozygous deletion of a cytosine in the exon 21 of the SHANK3 gene, resulting in a missense sequence of 5 codons followed by a premature stop codon ({"type":"entrez-nucleotide","attrs":{"text":"NM_033517","term_id":"380748962","term_text":"NM_033517"}}NM_033517:c.3259_3259delC, p.Ser1088Profs*6).ConclusionsWe reported an infrequent form of familial ASD where WGS proved useful in the clinic. We identified a mutation in SHANK3 that underscores its relevance in Autism Spectrum Disorder.     

Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data

Construction of chromosomes 3D models based on single cell Hi-C data constitute an important challenge. We present a reconstruction approach, DPDchrom, that incorporates basic knowledge whether the reconstructed conformation should be coil-like or globular and spring relaxation at contact sites. In contrast to previously published protocols, DPDchrom can naturally form globular conformation due to the presence of explicit solvent. Benchmarking of this and several other methods on artificial polymer models reveals similar reconstruction accuracy at high contact density and DPDchrom advantage at low contact density. To compare 3D structures insensitively to spatial orientation and scale, we propose the Modified Jaccard Index. We analyzed two sources of the contact dropout: contact radius change and random contact sampling. We found that the reconstruction accuracy exponentially depends on the number of contacts per genomic bin allowing to estimate the reconstruction accuracy in advance. We applied DPDchrom to model chromosome configurations based on single-cell Hi-C data of mouse oocytes and found that these configurations differ significantly from a random one, that is consistent with other studies.     

Global Spectrum of Copy Number Variations Reveals Genome Organizational Plasticity and Proposes New Migration Routes

Global spectrum of CNVs is required to catalog variations to provide a high-resolution on the dynamics of genome-organization and human migration. In this study, we performed genome-wide genotyping using high-resolution arrays and identified 44,109 CNVs from 1,715 genomes across 12 populations. The study unraveled the force of independent evolutionary dynamics on genome-organizational plasticity across populations. We demonstrated the use of CNV tool to study human migration and identified a second major settlement establishing new migration routes in addition to existing ones.     

Longitudinal Measurement of Extracellular Matrix Rigidity in 3D Tumor Models Using Particle-tracking Microrheology

The mechanical microenvironment has been shown to act as a crucial regulator of tumor growth behavior and signaling, which is itself remodeled and modified as part of a set of complex, two-way mechanosensitive interactions. While the development of biologically-relevant 3D tumor models have facilitated mechanistic studies on the impact of matrix rheology on tumor growth, the inverse problem of mapping changes in the mechanical environment induced by tumors remains challenging. Here, we describe the implementation of particle-tracking microrheology (PTM) in conjunction with 3D models of pancreatic cancer as part of a robust and viable approach for longitudinally monitoring physical changes in the tumor microenvironment, in situ. The methodology described here integrates a system of preparing in vitro 3D models embedded in a model extracellular matrix (ECM) scaffold of Type I collagen with fluorescently labeled probes uniformly distributed for position- and time-dependent microrheology measurements throughout the specimen. In vitro tumors are plated and probed in parallel conditions using multiwell imaging plates. Drawing on established methods, videos of tracer probe movements are transformed via the Generalized Stokes Einstein Relation (GSER) to report the complex frequency-dependent viscoelastic shear modulus, G*(ω). Because this approach is imaging-based, mechanical characterization is also mapped onto large transmitted-light spatial fields to simultaneously report qualitative changes in 3D tumor size and phenotype. Representative results showing contrasting mechanical response in sub-regions associated with localized invasion-induced matrix degradation as well as system calibration, validation data are presented. Undesirable outcomes from common experimental errors and troubleshooting of these issues are also presented. The 96-well 3D culture plating format implemented in this protocol is conducive to correlation of microrheology measurements with therapeutic screening assays or molecular imaging to gain new insights into impact of treatments or biochemical stimuli on the mechanical microenvironment.     

The sequencing bias relaxed characteristics of Hi-C derived data and implications for chromatin 3D modeling

The 3D chromatin structure modeling by chromatin interactions derived from Hi-C experiments is significantly challenged by the intrinsic sequencing biases in these experiments. Conventional modeling methods only focus on the bias among different chromatin regions within the same experiment but neglect the bias arising from different experimental sequencing depth. We now show that the regional interaction bias is tightly coupled with the sequencing depth, and we further identify a chromatin structure parameter as the inherent characteristics of Hi-C derived data for chromatin regions. Then we present an approach for chromatin structure prediction capable of relaxing both kinds of sequencing biases by using this identified parameter. This method is validated by intra and inter cell-line comparisons among various chromatin regions for four human cell-lines (K562, GM12878, IMR90 and H1hESC), which shows that the openness of chromatin region is well correlated with chromatin function. This method has been executed by an automatic pipeline (AutoChrom3D) and thus can be conveniently used.     

Manifold Based Optimization for Single-Cell 3D Genome Reconstruction

The three-dimensional (3D) structure of the genome is important for orchestration of gene expression and cell differentiation. While mapping genomes in 3D has for a long time been elusive, recent adaptations of high-throughput sequencing to chromosome conformation capture (3C) techniques, allows for genome-wide structural characterization for the first time. However, reconstruction of "consensus" 3D genomes from 3C-based data is a challenging problem, since the data are aggregated over millions of cells. Recent single-cell adaptations to the 3C-technique, however, allow for non-aggregated structural assessment of genome structure, but data suffer from sparse and noisy interaction sampling. We present a manifold based optimization (MBO) approach for the reconstruction of 3D genome structure from chromosomal contact data. We show that MBO is able to reconstruct 3D structures based on the chromosomal contacts, imposing fewer structural violations than comparable methods. Additionally, MBO is suitable for efficient high-throughput reconstruction of large systems, such as entire genomes, allowing for comparative studies of genomic structure across cell-lines and different species.     

Impact of Dimensionality and Network Disruption on Microrheology of Cancer Cells in 3D Environments

Dimensionality is a fundamental component that can have profound implications on the characteristics of physical systems. In cell biology, however, the majority of studies on cell physical properties, from rheology to force generation to migration, have been performed on 2D substrates, and it is not clear how a more realistic 3D environment influences cell properties. Here, we develop an integrated approach and demonstrate the combination of mitochondria-tracking microrheology, microfluidics, and Brownian dynamics simulations to explore the impact of dimensionality on intracellular mechanics and on the effects of intracellular disruption. Additionally, we consider both passive thermal and active motor-driven processes within the cell and demonstrate through modeling how active internal fluctuations are modulated via dimensionality. Our results demonstrate that metastatic breast cancer cells (MDA-MB-231) exhibit more solid-like internal motions in 3D compared to 2D, and actin network disruption via Cytochalasin D has a more pronounced effect on internal cell fluctuations in 2D. Our computational results and modeling show that motor-induced active stress fluctuations are enhanced in 2D, leading to increased local intracellular particle fluctuations and apparent fluid-like behavior.     

Microrheology and ROCK signaling of human endothelial cells embedded in a 3D matrix

Cell function is profoundly affected by the geometry of the extracellular environment confining the cell. Whether and how cells plated on a two-dimensional matrix or embedded in a three-dimensional (3D) matrix mechanically sense the dimensionality of their environment is mostly unknown, partly because individual cells in an extended matrix are inaccessible to conventional cell-mechanics probes. Here we develop a functional assay based on multiple particle tracking microrheology coupled with ballistic injection of nanoparticles to measure the local intracellular micromechanical properties of individual cells embedded inside a matrix. With our novel assay, we probe the mechanical properties of the cytoplasm of individual human umbilical vein endothelial cells (HUVECs) embedded in a 3D peptide hydrogel in the presence or absence of vascular endothelial growth factor (VEGF). We found that VEGF treatment, which enhances endothelial migration, increases the compliance and reduces the elasticity of the cytoplasm of HUVECs in a matrix. This VEGF-induced softening response of the cytoplasm is abrogated by specific Rho-kinase (ROCK) inhibition. These results establish combined particle-tracking microrheology and ballistic injection as the first method able to probe the micromechanical properties and mechanical response to agonists and/or drug treatments of individual cells inside a matrix. These results suggest that ROCK plays an essential role in the regulation of the intracellular mechanical response to VEGF of endothelial cells in a 3D matrix.     

GITAR: An Open Source Tool for Analysis and Visualization of Hi-C Data

Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources (GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains (TADs). GITAR is composed of two main modules: (1) HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and (2) processed data library, a large collection of human and mouse datasets processed using HiCtool. HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.     

Freeze substitution Hi-C,a convenient and cost-effective method for capturing the natural 3D chromatin conformation from frozen samples

Chromatin interactions functionally affect genome architecture and gene regulation, but to date, only fresh samples must be used in High-through chromosome conformation capture(Hi-C) to keep natural chromatin conformation intact. This requirement has impeded the advancement of 3 D genome research by limiting sample collection and storage options for researchers and severely limiting the number of samples that can be processed in a short time. Here, we develop a freeze substitution Hi-C(FS-Hi-C) technique that overcomes the need for fresh samples. FS-Hi-C can be used with samples stored in liquid nitrogen(LN2):the water in a vitreous form in the sample cells is replaced with ethanol via automated freeze substitution.After confirming that the FS step preserves the natural chromosome conformation during sample thawing,we tested the performance of FS-Hi-C with Drosophila melanogaster and Gossypium hirsutum. Beyond allowing the use of frozen samples and confirming that FS-Hi-C delivers robust data for generating contact heat maps and delineating A/B compartments and topologically associating domains, we found that FS-HiC outperforms the in situ Hi-C in terms of library quality, reproducibility, and valid interactions. Thus, FS-HiC will probably extend the application of 3 D genome structure analysis to the vast number of experimental contexts in biological and medical research for which Hi-C methods have been unfeasible to date.     

qc3C: Reference-free quality control for Hi-C sequencing data

Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of chromatin, scaffolding of large genome assemblies and more recently the accurate resolution of metagenome-assembled genomes (MAGs). Despite continued refinements, however, preparing a Hi-C library remains a complex laboratory protocol. To avoid costly failures and maximise the odds of successful outcomes, diligent quality management is recommended. Current wet-lab methods provide only a crude assay of Hi-C library quality, while key post-sequencing quality indicators used have—thus far—relied upon reference-based read-mapping. When a reference is accessible, this reliance introduces a concern for quality, where an incomplete or inexact reference skews the resulting quality indicators. We propose a new, reference-free approach that infers the total fraction of read-pairs that are a product of proximity ligation. This quantification of Hi-C library quality requires only a modest amount of sequencing data and is independent of other application-specific criteria. The algorithm builds upon the observation that proximity ligation events are likely to create k-mers that would not naturally occur in the sample. Our software tool (qc3C) is to our knowledge the first to implement a reference-free Hi-C QC tool, and also provides reference-based QC, enabling Hi-C to be more easily applied to non-model organisms and environmental samples. We characterise the accuracy of the new algorithm on simulated and real datasets and compare it to reference-based methods.