Single‐cell imaging of genome organization and dynamics

Probing the architecture, mechanism, and dynamics of genome folding is fundamental to our understanding of genome function in homeostasis and disease. Most chromosome conformation capture studies dissect the genome architecture with population‐ and time‐averaged snapshots and thus have limited capabilities to reveal 3D nuclear organization and dynamics at the single‐cell level. Here, we discuss emerging imaging techniques ranging from light microscopy to electron microscopy that enable investigation of genome folding and dynamics at high spatial and temporal resolution. Results from these studies complement genomic data, unveiling principles underlying the spatial arrangement of the genome and its potential functional links to diverse biological activities in the nucleus.     

Matching of array CGH and gene expression microarray features for the purpose of integrative genomic analyses

ABSTRACT: BACKGROUND: An increasing number of genomic studies interrogating more than one molecular level is published. Bioinformatics follows biological practice, and recent years have seen a surge in methodology for the integrative analysis of genomic data. Often such analyses require knowledge of which elements of one platform link to those of another. Although important, many integrative analyses do not or insufficiently detail the matching of the platforms. RESULTS: We describe, illustrate and discuss six matching procedures. They are implemented in the R-package sigaR (available from Bioconductor). The principles underlying the presented matching procedures are generic, and can be combined to form new matching approaches or be applied to the matching of other platforms. Illustration of the matching procedures on a variety of data sets reveals how the procedures differ in the use of the available data, and may even lead to different results for individual genes. CONCLUSIONS: Matching of data from multiple genomics platforms is an important preprocessing step for many integrative bioinformatic analysis, for which we present six generic procedures, both old and new. They have been implemented in the R-package sigaR, available from Bioconductor.     

Genomic resources for flatfish research and their applications

Flatfishes are a group of teleosts of high commercial and environmental interest, whose biology is still poorly understood. The recent rapid development of different 'omic' technologies is, however, enhancing the knowledge of the complex genetic control underlying different physiological processes of flatfishes. This review describes the different functional genomic approaches and resources currently available for flatfish research and summarizes different areas where microarray-based gene expression analysis has been applied. The increase in genome sequencing data has also allowed the construction of genetic linkage maps in different flatfish species; these maps are invaluable for investigating genome organization and identifying genetic traits of commercial interest. Despite the significant progress in this field, the genomic resources currently available for flatfish are still scarce. Further intensive research should be carried out to develop larger genomic sequence databases, high-density microarrays and, more detailed, complete linkage maps, using second-generation sequencing platforms. These tools will be crucial for further expanding the knowledge of flatfish physiology, and it is predicted that they will have important implications for wild fish population management, improved fish welfare and increased productivity in aquaculture.     

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies

Background  

Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies.     

Shaping the genome via lengthwise compaction,phase separation,and lamina adhesion

The link between genomic structure and biological function is yet to be consolidated, it is, however, clear that physical manipulation of the genome, driven by the activity of a variety of proteins, is a crucial step. To understand the consequences of the physical forces underlying genome organization, we build a coarse-grained polymer model of the genome, featuring three fundamentally distinct classes of interactions: lengthwise compaction, i.e., compaction of chromosomes along its contour, self-adhesion among epigenetically similar genomic segments, and adhesion of chromosome segments to the nuclear envelope or lamina. We postulate that these three types of interactions sufficiently represent the concerted action of the different proteins organizing the genome architecture and show that an interplay among these interactions can recapitulate the architectural variants observed across the tree of life. The model elucidates how an interplay of forces arising from the three classes of genomic interactions can drive drastic, yet predictable, changes in the global genome architecture, and makes testable predictions. We posit that precise control over these interactions in vivo is key to the regulation of genome architecture.     

The impact of next-generation sequencing on genomics

This article reviews basic concepts,general applications,and the potential impact of next-generation sequencing(NGS)technologies on genomics,with particular reference to currently available and possible future platforms and bioinformatics.NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed,thereby enabling previously unimaginable scientific achievements and novel biological applications.But,the massive data produced by NGS also presents a significant challenge for data storage,analyses,and management solutions.Advanced bioinformatic tools are essential for the successful application of NGS technology.As evidenced throughout this review,NGS technologies will have a striking impact on genomic research and the entire biological field.With its ability to tackle the unsolved challenges unconquered by previous genomic technologies,NGS is likely to unravel the complexity of the human genome in terms of genetic variations,some of which may be confined to susceptible loci for some common human conditions.The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.     

Arpeggio: harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories. Here, we present a signal processing approach that characterizes protein–chromatin interaction patterns at length scales of several kilobases. This allows us to efficiently compare numerous chromatin-immunoprecipitation sequencing (ChIP-seq) data sets consisting of many types of DNA-binding proteins collected from a variety of cells, conditions and organisms. Importantly, these interaction patterns broadly reflect the biological properties of the binding events. To generate these profiles, termed Arpeggio profiles, we applied harmonic deconvolution techniques to the autocorrelation profiles of the ChIP-seq signals. We used 806 publicly available ChIP-seq experiments and showed that Arpeggio profiles with similar spectral densities shared biological properties. Arpeggio profiles of ChIP-seq data sets revealed characteristics that are not easily detected by standard peak finders. They also allowed us to relate sequencing data sets from different genomes, experimental platforms and protocols. Arpeggio is freely available at http://sourceforge.net/p/arpeggio/wiki/Home/.     

Delineating the longitudinal tumor evolution using organoid models

Cancer is an evolutionary process fueled by genetic or epigenetic alterations in the genome. Understanding the evolutionary dynamics that are operative at different stages of tumor progression might inform effective strategies in early detection, diagnosis, and treatment of cancer. However, our understanding on the dynamics of tumor evolution through time is very limited since it is usually impossible to sample patient tumors repeatedly. The recent advances in in vitro 3D organoid culture technologies have opened new avenues for the development of more realistic human cancer models that mimic many in vivo biological characteristics in human tumors. Here, we review recent progresses and challenges in cancer genomic evolution studies and advantages of using tumor organoids to study cancer evolution. We propose to establish an experimental evolution model based on continuous passages of patient-derived organoids and longitudinal sampling to study clonal dynamics and evolutionary patterns over time. Development and integration of population genetic theories and computational models into time-course genomic data in tumor organoids will help to pinpoint the key cellular mechanisms underlying cancer evolutionary dynamics, thus providing novel insights on therapeutic strategies for highly dynamic and heterogeneous tumors.     

Microarray expression profiling resources for plant genomics

Large volumes of genomic data have been generated for several plant species over the past decade, including structural sequence data and functional annotation at the genome level. Various technologies such as expressed sequence tags (ESTs), massively parallel signature sequencing (MPSS) and microarrays have been used to study gene expression and to provide functional data for many genes simultaneously. This review focuses on recent advances in the application of microarrays in plant genomic research and in gene expression databases available for plants. Large sets of Arabidopsis microarray data are publicly available. Recently developed array platforms are currently being used to generate genome-wide expression profiles for several crop species. Coupled to these platforms are public databases that provide access to these large-scale expression data, which can be used to aid the functional discovery of gene function.     

The ups and downs of genome size evolution in polyploid species of Nicotiana (Solanaceae)

BACKGROUND: In studies looking at individual polyploid species, the most common patterns of genomic change are that either genome size in the polyploid is additive (i.e. the sum of parental genome donors) or there is evidence of genome downsizing. Reports showing an increase in genome size are rare. In a large-scale analysis of 3008 species, genome downsizing was shown to be a widespread biological response to polyploidy. Polyploidy in the genus Nicotiana (Solanaceae) is common with approx. 40 % of the approx. 75 species being allotetraploid. Recent advances in understanding phylogenetic relationships of Nicotiana species and dating polyploid formation enable a temporal dimension to be added to the analysis of genome size evolution in these polyploids. METHODS: Genome sizes were measured in 18 species of Nicotiana (nine diploids and nine polyploids) ranging in age from <200,000 years to approx. 4.5 Myr old, to determine the direction and extent of genome size change following polyploidy. These data were combined with data from genomic in situ hybridization and increasing amounts of information on sequence composition in Nicotiana to provide insights into the molecular basis of genome size changes. KEY RESULTS AND CONCLUSIONS: By comparing the expected genome size of the polyploid (based on summing the genome size of species identified as either a parent or most closely related to the diploid progenitors) with the observed genome size, four polyploids showed genome downsizing and five showed increases. There was no discernable pattern in the direction of genome size change with age of polyploids, although with increasing age the amount of genome size change increased. In older polyploids (approx. 4.5 million years old) the increase in genome size was associated with loss of detectable genomic in situ hybridization signal, whereas some hybridization signal was still detected in species exhibiting genome downsizing. The possible significance of these results is discussed.     

Chromosome‐level de novo genome assembly of Sarcophaga peregrina provides insights into the evolutionary adaptation of flesh flies

Sarcophaga peregrina is considered to be of great ecological, medical and forensic significance, and has unusual biological characteristics such as an ovoviviparous reproductive pattern and adaptation to feed on carrion. The availability of a high‐quality genome will help to further reveal the mechanisms underlying these charcateristics. Here we present a de novo‐assembled genome at chromosome scale for S. peregrina. The final assembled genome was 560.31 Mb with contig N50 of 3.84 Mb. Hi‐C scaffolding reliably anchored six pseudochromosomes, accounting for 97.76% of the assembled genome. Moreover, 45.70% of repeat elements were identified in the genome. A total of 14,476 protein‐coding genes were functionally annotated, accounting for 92.14% of all predicted genes. Phylogenetic analysis indicated that S. peregrina and S. bullata diverged ~ 7.14 million years ago. Comparative genomic analysis revealed expanded and positively selected genes related to biological features that aid in clarifying its ovoviviparous reproduction and carrion‐feeding adaptations, such as lipid metabolism, olfactory receptor activity, antioxidant enzymes, proteolysis and serine‐type endopeptidase activity. Protein‐coding genes associated with ovoviparity, such as yolk proteins, transferrin and acid sphingomyelinase, were identified. This study provides a valuable genomic resource for S. peregrina, and sheds insight into further revealing the underlying molecular mechanisms of adaptive evolution.     

Evidence That Inconsistent Gene Prediction Can Mislead Analysis of Dinoflagellate Genomes

Comparative algal genomics often relies on predicted genes from de novo assembled genomes. However, the artifacts introduced by different gene-prediction approaches, and their impact on comparative genomic analysis remain poorly understood. Here, using available genome data from six dinoflagellate species in the Symbiodiniaceae, we identified methodological biases in the published genes that were predicted using different approaches and putative contaminant sequences in the published genome assemblies. We developed and applied a comprehensive customized workflow to predict genes from these genomes. The observed variation among predicted genes resulting from our workflow agreed with current understanding of phylogenetic relationships among these taxa, whereas the variation among the previously published genes was largely biased by the distinct approaches used in each instance. Importantly, these biases affect the inference of homologous gene families and synteny among genomes, thus impacting biological interpretation of these data. Our results demonstrate that a consistent gene-prediction approach is critical for comparative analysis of dinoflagellate genomes.     

A unified framework for inferring the multi-scale organization of chromatin domains from Hi-C

Chromosomes are giant chain molecules organized into an ensemble of three-dimensional structures characterized with its genomic state and the corresponding biological functions. Despite the strong cell-to-cell heterogeneity, the cell-type specific pattern demonstrated in high-throughput chromosome conformation capture (Hi-C) data hints at a valuable link between structure and function, which makes inference of chromatin domains (CDs) from the pattern of Hi-C a central problem in genome research. Here we present a unified method for analyzing Hi-C data to determine spatial organization of CDs over multiple genomic scales. By applying statistical physics-based clustering analysis to a polymer physics model of the chromosome, our method identifies the CDs that best represent the global pattern of correlation manifested in Hi-C. The multi-scale intra-chromosomal structures compared across different cell types uncover the principles underlying the multi-scale organization of chromatin chain: (i) Sub-TADs, TADs, and meta-TADs constitute a robust hierarchical structure. (ii) The assemblies of compartments and TAD-based domains are governed by different organizational principles. (iii) Sub-TADs are the common building blocks of chromosome architecture. Our physically principled interpretation and analysis of Hi-C not only offer an accurate and quantitative view of multi-scale chromatin organization but also help decipher its connections with genome function.     

From microscopes to microarrays: dissecting recurrent chromosomal rearrangements

Submicroscopic chromosomal rearrangements that lead to copy-number changes have been shown to underlie distinctive and recognizable clinical phenotypes. The sensitivity to detect copy-number variation has escalated with the advent of array comparative genomic hybridization (CGH), including BAC and oligonucleotide-based platforms. Coupled with improved assemblies and annotation of genome sequence data, these technologies are facilitating the identification of new syndromes that are associated with submicroscopic genomic changes. Their characterization reveals the role of genome architecture in the aetiology of many clinical disorders. We review a group of genomic disorders that are mediated by segmental duplications, emphasizing the impact that high-throughput detection methods and the availability of the human genome sequence have had on their dissection and diagnosis.     

Integrated nanoliter systems

Microfluidic chip platforms for manipulating liquid volumes in the nanoliter range are slowly inching their way into mainstream genomic and proteomic research. The principal challenge faced by these technologies is the need for high-throughput processing of increasingly smaller volumes, with ever higher degrees of parallelization. Significant advances have been made over the past few years in addressing these needs through electrokinetic manipulation, vesicle encapsulation and mechanical valve approaches. These strategies allow levels of integration density and platform complexity that promise to make them into serious alternatives to current robotic systems.     

InterStoreDB:A Generic Integration Resource for Genetic and Genomic Data

Associating phenotypic traits and quantitative trait loci (QTL) to causative regions of the underlying genome is a key goal in agricultural research.InterStoreDB is a suite of integrated databases designed to assist in this process.The individual databases are species independent and generic in design,providing access to curated datasets relating to plant populations,phenotypic traits,genetic maps,marker loci and QTL,with links to functional gene annotation and genomic sequence data.Each component database provides access to associated metadata,including data provenance and parameters used in analyses,thus providing users with information to evaluate the relative worth of any associations identified.The databases include CropStoreDB,for management of population,genetic map,QTL and trait measurement data,SeqStoreDB for sequence-related data and AlignStoreDB,which stores sequence alignment information,and allows navigation between genetic and genomic datasets.Genetic maps are visualized and compared using the CMAP tool,and functional annotation from sequenced genomes is provided via an EnsEMBL-based genome browser.This framework facilitates navigation of the multiple biological domains involved in genetics and genomics research in a transparent manner within a single portal.We demonstrate the value of InterStoreDB as a tool for Brassica research.InterStoreDB is available from:http://www.interstoredb.org