Visualising three-dimensional genome organisation in two dimensions

Chromatin in 3D distinguishes dMes-4/NSD and Hypb/dSet2 in protecting genes from H3K27me3 silencing

Cell type-specific barcoding of genomes requires the establishment of hundreds of heterochromatin domains where heterochromatin-associated repressive complexes hinder chromatin accessibility thereby silencing genes. At heterochromatin-euchromatin borders, regulation of accessibility not only depends on the delimitation of heterochromatin but may also involve interplays with nearby genes and their transcriptional activity, or alternatively on histone modifiers, chromatin barrier insulators, and more global demarcation of chromosomes into 3D compartmentalized domains and topological-associating domain (TADs). Here, we show that depletion of H3K36 di- or tri-methyl histone methyltransferases dMes-4/NSD or Hypb/dSet2 induces reproducible increasing levels of H3K27me3 at heterochromatin borders including in nearby promoters, thereby repressing hundreds of genes. Furthermore, dMes-4/NSD influences genes demarcated by insulators and TAD borders, within chromatin hubs, unlike transcription-coupled action of Hypb/dSet2 that protects genes independently of TADs. Insulator mutants recapitulate the increase of H3K27me3 upon dMes-4/NSD depletion unlike Hypb/dSet2. Hi-C data demonstrate how dMes-4/NSD blocks propagation of long-range interactions onto active regions. Our data highlight distinct mechanisms protecting genes from H3K27me3 silencing, highlighting a direct influence of H3K36me on repressive TADs.

1Progress, applications, challenges and prospects of protein purification technology

Protein is one of the most important biological macromolecules in life, which plays a vital role in cell growth, development, movement, heredity, reproduction and other life activities. High quality isolation and purification is an essential step in the study of the structure and function of target proteins. Therefore, the development of protein purification technologies has great theoretical and practical significance in exploring the laws of life activities and guiding production practice. Up to now, there is no forthcoming method to extract any proteins from a complex system, and the field of protein purification still faces significant opportunities and challenges. Conventional protein purification generally includes three steps: pretreatment, rough fractionation, and fine fractionation. Each of the steps will significantly affect the purity, yield and the activity of target proteins. The present review focuses on the principle and process of protein purification, recent advances, and the applications of these technologies in the life and health industry as well as their far-reaching impact, so as to promote the research of protein structure and function, drug development and precision medicine, and bring new insights to researchers in related fields.

HiC1Dmetrics: framework to extract various one-dimensional features from chromosome structure data

Eukaryotic genomes are organized in a three-dimensional spatial structure. In this regard, the development of chromosome conformation capture methods has enabled studies of chromosome organization on a genomic scale. Hi-C, the high-throughput chromosome conformation capture method, can reveal a population-averaged, hierarchical chromatin structure. The typical Hi-C analysis uses a two-dimensional (2D) contact matrix that indicates contact frequencies between all possible genomic position pairs. Oftentimes, however, such a 2D matrix is not amenable to handling quantitative comparisons, visualizations and integrations across multiple datasets. Although several one-dimensional (1D) metrics have been proposed to depict structural information in Hi-C data, their effectiveness is still underappreciated. Here, we first review the currently available 1D metrics for individual Hi-C samples or two-sample comparisons and then discuss their validity and suitable analysis scenarios. We also propose several new 1D metrics to identify additional unique features of chromosome structures. We highlight that the 1D metrics are reproducible and robust for comparing and visualizing multiple Hi-C samples. Moreover, we show that 1D metrics can be easily combined with epigenome tracks to annotate chromatin states in greater details. We develop a new framework, called HiC1Dmetrics, to summarize all 1D metrics discussed in this study. HiC1Dmetrics is open-source (github.com/wangjk321/HiC1Dmetrics) and can be accessed from both command-line and web-based interfaces. Our tool constitutes a useful resource for the community of chromosome-organization researchers.

FISH Going Meso-Scale: A Microscopic Search for Chromatin Domains

The intimate relationships between genome structure and function direct efforts toward deciphering three-dimensional chromatin organization within the interphase nuclei at different genomic length scales. For decades, major insights into chromatin structure at the level of large-scale euchromatin and heterochromatin compartments, chromosome territories, and subchromosomal regions resulted from the evolution of light microscopy and fluorescence in situ hybridization. Studies of nanoscale nucleosomal chromatin organization benefited from a variety of electron microscopy techniques. Recent breakthroughs in the investigation of mesoscale chromatin structures have emerged from chromatin conformation capture methods (C-methods). Chromatin has been found to form hierarchical domains with high frequency of local interactions from loop domains to topologically associating domains and compartments. During the last decade, advances in super-resolution light microscopy made these levels of chromatin folding amenable for microscopic examination. Here we are reviewing recent developments in FISH-based approaches for detection, quantitative measurements, and validation of contact chromatin domains deduced from C-based data. We specifically focus on the design and application of Oligopaint probes, which marked the latest progress in the imaging of chromatin domains. Vivid examples of chromatin domain FISH-visualization by means of conventional, super-resolution light and electron microscopy in different model organisms are provided.

Productive visualization of high-throughput sequencing data using the SeqCode open portable platform

Large-scale sequencing techniques to chart genomes are entirely consolidated. Stable computational methods to perform primary tasks such as quality control, read mapping, peak calling, and counting are likewise available. However, there is a lack of uniform standards for graphical data mining, which is also of central importance. To fill this gap, we developed SeqCode, an open suite of applications that analyzes sequencing data in an elegant but efficient manner. Our software is a portable resource written in ANSI C that can be expected to work for almost all genomes in any computational configuration. Furthermore, we offer a user-friendly front-end web server that integrates SeqCode functions with other graphical analysis tools. Our analysis and visualization toolkit represents a significant improvement in terms of performance and usability as compare to other existing programs. Thus, SeqCode has the potential to become a key multipurpose instrument for high-throughput professional analysis; further, it provides an extremely useful open educational platform for the world-wide scientific community. SeqCode website is hosted at http://ldicrocelab.crg.eu, and the source code is freely distributed at https://github.com/eblancoga/seqcode.

Protein Purification Technologies

Protein Biotechnology is an exciting and fast- growing area of research, with numerous industrial applications. The growing demand for developing efficient and rapid protein purification methods is driving research and growth in this area. Advances and progress in the techniques and methods of protein purification have been such that one can reasonably expect that any protein of a given order of stability may be purified to currently acceptable standards of homogeneity. However, protein manufacturing cost remains extremely high, with downstream processing constituting a substantial proportion of the overall cost. Understanding of the methods and optimization of the experimental conditions have become critical to the manufacturing industry in order to minimize production costs while satisfying the quality as well as all regulatory requirements. New purification processes exploiting specific, effective and robust methods and chromatographic materials are expected to guide the future of the protein purification market.

FAN-C: a feature-rich framework for the analysis and visualisation of chromosome conformation capture data

Chromosome conformation capture data, particularly from high-throughput approaches such as Hi-C, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data ( https://github.com/vaquerizaslab/fanc ). Due to its compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.

SpectralTAD: an R package for defining a hierarchy of topologically associated domains using spectral clustering

BACKGROUND

The three-dimensional (3D) structure of the genome plays a crucial role in gene expression regulation. Chromatin conformation capture technologies (Hi-C) have revealed that the genome is organized in a hierarchy of topologically associated domains (TADs), sub-TADs, and chromatin loops. Identifying such hierarchical structures is a critical step in understanding genome regulation. Existing tools for TAD calling are frequently sensitive to biases in Hi-C data, depend on tunable parameters, and are computationally inefficient.

METHODS

To address these challenges, we developed a novel sliding window-based spectral clustering framework that uses gaps between consecutive eigenvectors for TAD boundary identification.

RESULTS

Our method, implemented in an R package, SpectralTAD, detects hierarchical, biologically relevant TADs, has automatic parameter selection, is robust to sequencing depth, resolution, and sparsity of Hi-C data. SpectralTAD outperforms four state-of-the-art TAD callers in simulated and experimental settings. We demonstrate that TAD boundaries shared among multiple levels of the TAD hierarchy were more enriched in classical boundary marks and more conserved across cell lines and tissues. In contrast, boundaries of TADs that cannot be split into sub-TADs showed less enrichment and conservation, suggesting their more dynamic role in genome regulation.

CONCLUSION

SpectralTAD is available on Bioconductor, http://bioconductor.org/packages/SpectralTAD/ .