The dynamics of cancer chromosomes and genomes

A key feature of cancer chromosomes and genomes is their high level of dynamics and the ability to constantly evolve. This unique characteristic forms the basis of genetic heterogeneity necessary for cancer formation, which presents major obstacles to current cancer diagnosis and treatment. It has been difficult to integrate such dynamics into traditional models of cancer progression. In this conceptual piece, we briefly discuss some of the recent exciting progress in the field of cancer genomics and genome research. In particular, a re-evaluation of the previously disregarded non-clonal chromosome aberrations (NCCAs) is reviewed, coupled with the progress of the detection of sub-chromosomal aberrations with array technologies. Clearly, the high level of genetic heterogeneity is directly caused by genome instability that is mediated by stochastic genomic changes, and genome variations defined by chromosome aberrations are the driving force of cancer progression. In addition to listing various types of non-recurrent chromosomal aberrations, we discuss the likely mechanism underlying cancer chromosome dynamics. Finally, we call for further examination of the features of dynamic genome diseases including cancer in the context of systems biology and the need to integrate this new knowledge into basic research and clinical applications. This genome centric concept will have a profound impact on the future of biological and medical research.     

piRNA抑制基因转座的分子机制

转座子是一类可以在染色体上或不同染色体间自由移动的DNA。在高等生物中,处于活跃状态的转座子多为通过RNA中间体进行转座的逆转录转座子。由于逆转录转座子在细胞基因组中占有很高的比例,它的频繁转座能引起细胞基因组结构和功能的改变,导致癌症等严重基因疾病的发生,因此宿主细胞在长期的进化中形成了多种自我保护机制用以控制逆转录转座子活性。属于非编码小RNA的piRNA以其独特的机制在转录及转录后水平控制逆转录转座子RNA中间体的产生,抑制了逆转录转座过程的发生。本文总结了近年来piRNA控制转座子转座相关分子机制的研究进展,以期为转座子及基因调控方面的研究工作提供一些参考。     

CRISPR/Cas9基因编辑在三维基因组研究中的应用

CRISPR/Cas9系统在基因编辑方面具有巨大优势,能够低成本、可编程、方便快捷地用于动物、植物以及微生物的基因组靶向编辑和功能改造。三维基因组学是近年来兴起的一门研究染色质高级结构动态调控及基因组生物学功能的交叉学科。在三维基因组研究中,通常采用对DNA片段进行基因编辑以模拟基因组结构性变异,标记特定DNA片段,进而研究调控元件对于基因调控、细胞分化、组织发生、器官形成、个体发育的影响,最终阐明三维基因组的组装调控机制和生物学功能。因此,CRISPR及其衍生技术为研究三维基因组提供了极好的遗传学工具。本文主要综述了CRISPR片段编辑及其衍生技术在三维基因组调控与功能研究中的应用,以期为后续研究工作提供理论参考以及新的研究思路。     

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.     

不同亚细胞结构中的长非编码RNA

长非编码RNA (long non-coding RNA,lncRNA)是长度大于200 nt的非编码RNA,最初被认为是不具有生物学功能的转录"垃圾".随着研究的深入,发现lncRNA参与了许多生物学调控过程,例如染色体沉默、染色质修饰、转录激活与干扰等.这些生物学调控过程与lncRNA的结构及时空特异性表达密切相关...     

Integrative Analysis of Genome, 3D Genome,and Transcriptome Alterations of Clinical Lung Cancer Samples

Genomic studies of cancer cell alterations, such as mutations, copy number variations (CNVs), and translocations, greatly promote our understanding of the genesis and development of cancers. However, the 3D genome architecture of cancers remains less studied due to the complexity of cancer genomes and technical difficulties. To explore the 3D genome structure in clinical lung cancer, we performed Hi-C experiments using paired normal and tumor cells harvested from patients with lung cancer, combining with RNA sequenceing analysis. We demonstrated the feasibility of studying 3D genome of clinical lung cancer samples with a small number of cells (1 × 10⁴), compared the genome architecture between clinical samples and cell lines of lung cancer, and identified conserved and changed spatial chromatin structures between normal and cancer samples. We also showed that Hi-C data can be used to infer CNVs and point mutations in cancer. By integrating those different types of cancer alterations, we showed significant associations between CNVs, 3D genome, and gene expression. We propose that 3D genome mediates the effects of cancer genomic alterations on gene expression through altering regulatory chromatin structures. Our study highlights the importance of analyzing 3D genomes of clinical cancer samples in addition to cancer cell lines and provides an integrative genomic analysis pipeline for future larger-scale studies in lung cancer and other cancers.     

Large-scale reconstruction of 3D structures of human chromosomes from chromosomal contact data

Chromosomes are not positioned randomly within a nucleus, but instead, they adopt preferred spatial conformations to facilitate necessary long-range gene–gene interactions and regulations. Thus, obtaining the 3D shape of chromosomes of a genome is critical for understanding how the genome folds, functions and how its genes interact and are regulated. Here, we describe a method to reconstruct preferred 3D structures of individual chromosomes of the human genome from chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. A novel parameterized objective function was designed for modeling chromosome structures, which was optimized by a gradient descent method to generate chromosomal structural models that could satisfy as many intra-chromosomal contacts as possible. We applied the objective function and the corresponding optimization method to two Hi-C chromosomal data sets of both a healthy and a cancerous human B-cell to construct 3D models of individual chromosomes at resolutions of 1 MB and 200 KB, respectively. The parameters used with the method were calibrated according to an independent fluorescence in situ hybridization experimental data. The structural models generated by our method could satisfy a high percentage of contacts (pairs of loci in interaction) and non-contacts (pairs of loci not in interaction) and were compatible with the known two-compartment organization of human chromatin structures. Furthermore, structural models generated at different resolutions and from randomly permuted data sets were consistent.     

Advances in technologies for 3D genomics research

The spatial structure of the orderly organized chromatin in the nucleus has important roles in maintaining normal cell function and in regulation of gene expression, and the high-throughput Hi-C and Ch IA-PET methods have been widely used in various biological studies for determining potential spatial genome structures and their functions. However, there are still great difficulties and challenges in three-dimensional(3D) genomics research. More efficient, economical, and unbiased approaches to studying 3D genomics need to be developed for more widespread and easier applications. Here, we review the most recent studies on new 3D genomics research technologies, such as improvements of the traditional Hi-C and Ch IA-PET methods, new approaches based on non-proximal-ligation strategies, and imaging-based methods improved in recent years. Especially, we review the CRISPR-based methods for functional validations in 3D genomics, which could be the forthcoming directions. We hope this review can show some insights into the potential improvements for future 3D genomics.     

微小RNA分析技术研究进展

微小RNA（miRNA）是一类起重要调控作用的非编码小分子RNA。准确分析组织或细胞中miRNA的表达水平是研究其生物学功能的基础。近年,研究者开发出多种方法检测不同生理、病理过程中miRNA的差异表达,发现miRNA的异常表达与癌症等多种疾病密切相关。目前,miRNA已逐渐成为重要的疾病诊断生物标志物乃至治疗靶点。miRNA的分析技术贯穿miRNA的研究和药物研发过程,并起到关键作用。我们针对miRNA的不同研究阶段所采用的定性和定量分析方法,着重阐述了用于初始miRNA研究的克隆测序类技术、分析miRNA表达谱的高通量芯片技术、研究具体目标miRNA及其前体表达的qPCR和改良Northern印迹技术,以及将修饰后miRNA作为药物的药代动力学评价技术。     

Comparative 3D Genome Structure Analysis of the Fission and the Budding Yeast

We studied the 3D structural organization of the fission yeast genome, which emerges from the tethering of heterochromatic regions in otherwise randomly configured chromosomes represented as flexible polymer chains in an nuclear environment. This model is sufficient to explain in a statistical manner many experimentally determined distinctive features of the fission yeast genome, including chromatin interaction patterns from Hi-C experiments and the co-locations of functionally related and co-expressed genes, such as genes expressed by Pol-III. Our findings demonstrate that some previously described structure-function correlations can be explained as a consequence of random chromatin collisions driven by a few geometric constraints (mainly due to centromere-SPB and telomere-NE tethering) combined with the specific gene locations in the chromosome sequence. We also performed a comparative analysis between the fission and budding yeast genome structures, for which we previously detected a similar organizing principle. However, due to the different chromosome sizes and numbers, substantial differences are observed in the 3D structural genome organization between the two species, most notably in the nuclear locations of orthologous genes, and the extent of nuclear territories for genes and chromosomes. However, despite those differences, remarkably, functional similarities are maintained, which is evident when comparing spatial clustering of functionally related genes in both yeasts. Functionally related genes show a similar spatial clustering behavior in both yeasts, even though their nuclear locations are largely different between the yeast species.     

Proteins without 3D structure: definition, detection and beyond

MOTIVATION: Predictions, and experiments to a lesser extent, following the decoding of the human genome showed that a significant fraction of gene products do not have well-defined 3D structures. While the presence of structured domains traditionally suggested function, it was not clear what the absence of structure implied. These and many other findings initiated the extensive theoretical and experimental research into these types of proteins, commonly known as intrinsically disordered proteins (IDPs). Crucial to understanding IDPs is the evaluation of structural predictors based on different principles and trained on various datasets, which is currently the subject of active research. The view is emerging that structural disorder can be considered as a separate structural category and not simply as absence of secondary and/or tertiary structure. IDPs perform essential functions and their improper functioning is responsible for human diseases such as neurodegenerative disorders.     

A Scalable Computational Approach for Simulating Complexes of Multiple Chromosomes

Significant efforts have been recently made to obtain the three-dimensional (3D) structure of the genome with the goal of understanding how structures may affect gene regulation and expression. Chromosome conformational capture techniques such as Hi-C, have been key in uncovering the quantitative information needed to determine chromatin organization. Complementing these experimental tools, co-polymers theoretical methods are necessary to determine the ensemble of three-dimensional structures associated to the experimental data provided by Hi-C maps. Going beyond just structural information, these theoretical advances also start to provide an understanding of the underlying mechanisms governing genome assembly and function. Recent theoretical work, however, has been focused on single chromosome structures, missing the fact that, in the full nucleus, interactions between chromosomes play a central role in their organization. To overcome this limitation, MiChroM (Minimal Chromatin Model) has been modified to become capable of performing these multi-chromosome simulations. It has been upgraded into a fast and scalable software version, which is able to perform chromosome simulations using GPUs via OpenMM Python API, called Open-MiChroM. To validate the efficiency of this new version, analyses for GM12878 individual autosomes were performed and compared to earlier studies. This validation was followed by multi-chain simulations including the four largest human chromosomes (C1-C4). These simulations demonstrated the full power of this new approach. Comparison to Hi-C data shows that these multiple chromosome interactions are essential for a more accurate agreement with experimental results. Without any changes to the original MiChroM potential, it is now possible to predict experimentally observed inter-chromosome contacts. This scalability of Open-MiChroM allow for more audacious investigations, looking at interactions of multiple chains as well as moving towards higher resolution chromosomes models.     

非编码DNA序列的功能及其鉴定

非编码DNA序列是指基因组中不编码蛋白质的DNA序列。这些序列可以结合调节因子、转录为功能性RNA、单独或协同地调节生理活动和病理过程。文章围绕基因表达调控作用, 总结了近几年非编码DNA序列的研究成果, 对其结构、功能和可能的作用机制进行了初步阐述, 介绍了目前鉴定非编码DNA序列中功能元件的计算方法和实验技术, 并对非编码DNA未来的研究进行了展望。     

长链非编码RNA的功能与疾病治疗的潜力

人类基因组转录本长度>200 nt（核苷酸）、不编码蛋白质的RNA分子为长链非编码RNA（long non-coding RNA,lncRNA)。lncRNA可在多个层面调节基因表达,其功能失调与包括肿瘤在内的很多人类疾病密切相关。本文概述lncRNA的种类、功能与疾病的关系,讨论基于lncRNA基因编辑、干细胞修饰及其与miRNA、蛋白质相互作用等的治疗潜能。