A Postgenomic Perspective on Molecular Cytogenetics

Quantitative FISHing: Implications for Chromosomal Analysis

Quantifying signals substantially increases the efficiency of fluorescence in situ hybridization (FISH). Quantitative FISH analysis or QFISHing may be useful for differentiation between chromosome loss and chromosomal associations, detection of amplification of chromosomal loci, and/or quantification of chromosomal heteromorphisms (chromosomal DNAs). The latter is applicable to uncovering the parental origin of chromosomes, which is an important FISH application in genome research. In summary, one may acknowledge that QFISHing has a variety of applications in cancer chromosome research. Accordingly, a protocol for this technique is certainly required. Here, QFISHing protocol is described step-by-step.

The Importance of Monitoring Non-clonal Chromosome Aberrations (NCCAs) in Cancer Research

Cytogenetic analysis has traditionally focused on the clonal chromosome aberrations, or CCAs, and considered the large number of diverse non-clonal chromosome aberrations, or NCCAs, as insignificant noise. Our decade-long karyotype evolutionary studies have unexpectedly demonstrated otherwise. Not only the baseline of NCCAs is associated with fuzzy inheritance, but the frequencies of NCCAs can also be used to reliably measure genome or chromosome instability (CIN). According to the Genome Architecture Theory, CIN is the common driver of cancer evolution that can unify diverse molecular mechanisms, and genome chaos, including chromothripsis, chromoanagenesis, and polypoidal giant nuclear and micronuclear clusters, and various sizes of chromosome fragmentations, including extrachromosomal DNA, represent some extreme forms of NCCAs that play a key role in the macroevolutionary transition. In this chapter, the rationale, definition, brief history, and current status of NCCA research in cancer are discussed in the context of two-phased cancer evolution and karyotype-coded system information. Finally, after briefly describing various types of NCCAs, we call for more research on NCCAs in future cytogenetics.

The New Era of Cancer Cytogenetics and Cytogenomics

The promises of the cancer genome sequencing project, combined with various -omics technologies, have raised questions about the importance of cancer cytogenetic analyses. It is suggested that DNA sequencing provides high resolution, speed, and automation, potentially replacing cytogenetic testing. We disagree with this reductionist prediction. On the contrary, various sequencing projects have unexpectedly challenged gene theory and highlighted the importance of the genome or karyotype in organizing gene network interactions. Consequently, profiling the karyotype can be more meaningful than solely profiling gene mutations, especially in cancer where karyotype alterations mediate cellular macroevolution dominance. In this chapter, recent studies that illustrate the ultimate importance of karyotype in cancer genomics and evolution are briefly reviewed. In particular, the long-ignored non-clonal chromosome aberrations or NCCAs are linked to genome or chromosome instability, genome chaos is linked to genome reorganization under cellular crisis, and the two-phased cancer evolution reconciles the relationship between genome alteration-mediated punctuated macroevolution and gene mutation-mediated stepwise microevolution. By further synthesizing, the concept of karyotype coding is discussed in the context of information management. Altogether, we call for a new era of cancer cytogenetics and cytogenomics, where an array of technical frontiers can be explored further, which is crucial for both basic research and clinical implications in the cancer field.

Challenges and Opportunities for Clinical Cytogenetics in the 21st Century

The powerful utilities of current DNA sequencing technology question the value of developing clinical cytogenetics any further. By briefly reviewing the historical and current challenges of cytogenetics, the new conceptual and technological platform of the 21st century clinical cytogenetics is presented. Particularly, the genome architecture theory (GAT) has been used as a new framework to emphasize the importance of clinical cytogenetics in the genomic era, as karyotype dynamics play a central role in information-based genomics and genome-based macroevolution. Furthermore, many diseases can be linked to elevated levels of genomic variations within a given environment. With karyotype coding in mind, new opportunities for clinical cytogenetics are discussed to integrate genomics back into cytogenetics, as karyotypic context represents a new type of genomic information that organizes gene interactions. The proposed research frontiers include: 1. focusing on karyotypic heterogeneity (e.g., classifying non-clonal chromosome aberrations (NCCAs), studying mosaicism, heteromorphism, and nuclear architecture alteration-mediated diseases), 2. monitoring the process of somatic evolution by characterizing genome instability and illustrating the relationship between stress, karyotype dynamics, and diseases, and 3. developing methods to integrate genomic data and cytogenomics. We hope that these perspectives can trigger further discussion beyond traditional chromosomal analyses. Future clinical cytogenetics should profile chromosome instability-mediated somatic evolution, as well as the degree of non-clonal chromosomal aberrations that monitor the genomic system's stress response. Using this platform, many common and complex disease conditions, including the aging process, can be effectively and tangibly monitored for health benefits.

An 82 bp tandem repeat family typical of 3' non-coding end of Gypsy/TAT LTR retrotransposons is conserved in Coffea spp. pericentromeres

Coffea spp. chromosomes are very small and accumulate a variety of repetitive DNA families around the centromeres. However, the proximal regions of Coffea chromosomes remain poorly understood, especially regarding the nature and organisation of the sequences. Taking advantage of the genome sequences of C. arabica (2n = 44), C. canephora, and C. eugenioides (C. arabica progenitors with 2n = 22) and good coverage genome sequencing of dozens of other wild Coffea spp., repetitive DNA sequences were identified, and the genomes were compared to decipher particularities of pericentromeric structures. The searches revealed a short tandem repeat (82 bp length) typical of Gypsy/TAT LTR retrotransposons, named Coffea_sat11. This repeat organises clusters with fragments of other transposable elements, comprising regions of non-coding RNA production. Cytogenomic analyses showed that Coffea_sat11 extends from the pericentromeres towards the middle of the chromosomal arms. This arrangement was observed in the allotetraploid C. arabica chromosomes, as well as in its progenitors. This study improves our understanding of the role of the Gypsy/TAT LTR retrotransposon lineage in the organisation of Coffea pericentromeres, as well as the conservation of Coffea_sat11 within the genus. The relationships between fragments of other transposable elements and the functional aspects of these sequences on the pericentromere chromatin were also evaluated. Highlights: A scattered short tandem repeat, typical of Gypsy/TAT LTR retrotransposons, associated with several fragments of other transposable elements, accumulates in the pericentromeres of Coffea chromosomes. This arrangement is preserved in all clades of the genus and appears to have a strong regulatory role in the organisation of chromatin around centromeres.

Large-scale comparative analysis of cytogenetic markers across Lepidoptera

Fluorescence in situ hybridization (FISH) allows identification of particular chromosomes and their rearrangements. Using FISH with signal enhancement via antibody amplification and enzymatically catalysed reporter deposition, we evaluated applicability of universal cytogenetic markers, namely 18S and 5S rDNA genes, U1 and U2 snRNA genes, and histone H3 genes, in the study of the karyotype evolution in moths and butterflies. Major rDNA underwent rather erratic evolution, which does not always reflect chromosomal changes. In contrast, the hybridization pattern of histone H3 genes was well conserved, reflecting the stable organisation of lepidopteran genomes. Unlike 5S rDNA and U1 and U2 snRNA genes which we failed to detect, except for 5S rDNA in a few representatives of early diverging lepidopteran lineages. To explain the negative FISH results, we used quantitative PCR and Southern hybridization to estimate the copy number and organization of the studied genes in selected species. The results suggested that their detection was hampered by long spacers between the genes and/or their scattered distribution. Our results question homology of 5S rDNA and U1 and U2 snRNA loci in comparative studies. We recommend the use of histone H3 in studies of karyotype evolution.

Systems Cytogenomics: Are We Ready Yet?

With the introduction of systems theory to genetics, numerous opportunities for genomic research have been identified. Consequences of DNA sequence variations are systematically evaluated using the network- or pathway-based analysis, a technological basis of systems biology or, more precisely, systems genomics. Despite comprehensive descriptions of advantages offered by systems genomic approaches, pathway-based analysis is uncommon in cytogenetic (cytogenomic) studies, i.e. genome analysis at the chromosomal level. Here, we would like to express our opinion that current cytogenomics benefits from the application of systems biology methodology. Accordingly, systems cytogenomics appears to be a biomedical area requiring more attention than it actually receives.

Genome chaos: Creating new genomic information essential for cancer macroevolution

Cancer research has traditionally focused on the characterization of individual molecular mechanisms that can contribute to cancer. Due to the multiple levels of genomic and non-genomic heterogeneity, however, overwhelming molecular mechanisms have been identified, most with low clinical predictability. It is thus necessary to search for new concepts to unify these diverse mechanisms and develop better strategies to understand and treat cancer. In recent years, two-phased cancer evolution (comprised of the genome reorganization-mediated punctuated phase and gene mutation-mediated stepwise phase), initially described by tracing karyotype evolution, was confirmed by the Cancer Genome Project. In particular, genome chaos, the process of rapid and massive genome reorganization, has been commonly detected in various cancers-especially during key phase transitions, including cellular transformation, metastasis, and drug resistance-suggesting the importance of genome-level changes in cancer evolution. In this Perspective, genome chaos is used as a discussion point to illustrate new genome-mediated somatic evolutionary frameworks. By rephrasing cancer as a new system emergent from normal tissue, we present the multiple levels (or scales) of genomic and non-genomic information. Of these levels, evolutionary studies at the chromosomal level are determined to be of ultimate importance, since altered genomes change the karyotype coding and karyotype change is the key event for punctuated cellular macroevolution. Using this lens, we differentiate and analyze developmental processes and cancer evolution, as well as compare the informational relationship between genome chaos and its various subtypes in the context of macroevolution under crisis. Furthermore, the process of deterministic genome chaos is discussed to interpret apparently random events (including stressors, chromosomal variation subtypes, surviving cells with new karyotypes, and emergent stable cellular populations) as nonrandom patterns, which supports the new cancer evolutionary model that unifies genome and gene contributions during different phases of cancer evolution. Finally, the new perspective of using cancer as a model for organismal evolution is briefly addressed, emphasizing the Genome Theory as a new and necessary conceptual framework for future research and its practical implications, not only in cancer but evolutionary biology as a whole.

About three-fourths of mouse proteins unexpectedly appear at a low position of SDS-PAGE, often as additional isoforms, questioning whether all protein isoforms have been eliminated in gene-knockout cells or organisms

Most genes in evolutionarily complex genomes are expressed to multiple protein isoforms, but there is not yet any simple high-throughput approach to identify these isoforms. Using an oversimplified top-down LC-MS/MS strategy, we detected, around the 26-kD position of SDS-PAGE, proteins produced from 782 genes in a Cdk4-/- mouse embryonic fibroblast cell line. Interestingly, only 213 (27.24%, about one-fourth) of these 782 genes have their proteins with a theoretical molecular mass (TMM) 10% smaller or larger than 26 kD, that is, between 23 and 29 kD, the range set as allowed variation in SDS-PAGE. These 213 proteins are considered as the wild type (WT). The remaining three-fourths includes proteins from 66 (9.44%) genes with a TMM smaller than 23 kD and proteins from 503 (64.32%, nearly two-thirds) genes with a TMM larger than 29 kD; these proteins are categorized into a larger-group or a smaller-group, respectively, for their appearance at a higher or lower position of SDS-PAGE. For instance, at this 26-kD position we detected proteins from the Rps27a, Snrpf, Hist1h4a, and Rps25 genes whose proteins' TMM is 8.6, 9.7, 11.4, and 13.7 kD, respectively, and detected proteins from the Plelc1 and Prkdc genes, whose largest isoform is 533.9 and 471.1 kD, respectively. We extrapolate that many of those proteins migrating unexpectedly in SDS-PAGE may be isoforms besides the WT protein. Moreover, we also detected a Cdk4 protein in this Cdk4-/- cell line, thus wondering whether some of other gene-knockout cells or organisms show similar incompleteness of the knockout.

Laundering CNV data for candidate process prioritization in brain disorders

Background

Prioritization of genomic data has become a useful tool for uncovering the phenotypic effect of genetic variations (e.g. copy number variations or CNV) and disease mechanisms. Due to the complexity, brain disorders represent a major focus of genomic research aimed at revealing pathologic significance of genomic changes leading to brain dysfunction. Here, we propose a “CNV data laundering” algorithm based on filtering and prioritizing of genomic pathways retrieved from available databases for uncovering altered molecular pathways in brain disorders. The algorithm comprises seven consecutive steps of processing individual CNV data sets. First, the data are compared to in-house and web databases to discriminate recurrent non-pathogenic variants. Second, the CNV pool is confined to the genes predominantly expressed in the brain. Third, intergenic interactions are used for filtering causative CNV. Fourth, a network of interconnected elements specific for an individual genome variation set is created. Fifth, ontologic data (pathways/functions) are attributed to clusters of network elements. Sixth, the pathways are prioritized according to the significance of elements affected by CNV. Seventh, prioritized pathways are clustered according to the ontologies.

Results

The algorithm was applied to 191 CNV data sets obtained from children with brain disorders (intellectual disability and autism spectrum disorders) by SNP array molecular karyotyping. “CNV data laundering” has identified 13 pathway clusters (39 processes/475 genes) implicated in the phenotypic manifestations.

Conclusions

Elucidating altered molecular pathways in brain disorders, the algorithm may be used for uncovering disease mechanisms and genotype-phenotype correlations. These opportunities are strongly required for developing therapeutic strategies in devastating neuropsychiatric diseases.

The variome concept: focus on CNVariome

Background

Variome may be used for designating complex system of interplay between genomic variations specific for an individual or a disease. Despite the recognized complexity of genomic basis for phenotypic traits and diseases, studies of genetic causes of a disease are usually dedicated to the identification of single causative genomic changes (mutations). When such an artificially simplified model is employed, genomic basis of phenotypic outcomes remains elusive in the overwhelming majority of human diseases. Moreover, it is repeatedly demonstrated that multiple genomic changes within an individual genome are likely to underlie the phenome. Probably the best example of cumulative effect of variome on the phenotype is CNV (copy number variation) burden. Accordingly, we have proposed a variome concept based on CNV studies providing the evidence for the existence of a CNVariome (the set of CNV affecting an individual genome), a target for genomic analyses useful for unraveling genetic mechanisms of diseases and phenotypic traits.

Conclusion

Variome (CNVariome) concept suggests that a genomic milieu is determined by the whole set of genomic variations (CNV) within an individual genome. The genomic milieu is likely to result from interplay between these variations. Furthermore, such kind of variome may be either individual or disease-specific. Additionally, such variome may be pathway-specific. The latter is able to affect molecular/cellular pathways of genome stability maintenance leading to occurrence of genomic/chromosome instability and/or somatic mosaicism resulting in somatic variome. This variome type seems to be important for unraveling disease mechanisms, as well. Finally, it appears that bioinformatic analysis of both individual and somatic variomes in the context of diseases- and pathway-specific variomes is the most promising way to determine genomic basis of the phenome and to unravel disease mechanisms for the management and treatment of currently incurable diseases.

Ontogenetic and Pathogenetic Views on Somatic Chromosomal Mosaicism

Intercellular karyotypic variability has been a focus of genetic research for more than 50 years. It has been repeatedly shown that chromosome heterogeneity manifesting as chromosomal mosaicism is associated with a variety of human diseases. Due to the ability of changing dynamically throughout the ontogeny, chromosomal mosaicism may mediate genome/chromosome instability and intercellular diversity in health and disease in a bottleneck fashion. However, the ubiquity of negligibly small populations of cells with abnormal karyotypes results in difficulties of the interpretation and detection, which may be nonetheless solved by post-genomic cytogenomic technologies. In the post-genomic era, it has become possible to uncover molecular and cellular pathways to genome/chromosome instability (chromosomal mosaicism or heterogeneity) using advanced whole-genome scanning technologies and bioinformatic tools. Furthermore, the opportunities to determine the effect of chromosomal abnormalities on the cellular phenotype seem to be useful for uncovering the intrinsic consequences of chromosomal mosaicism. Accordingly, a post-genomic review of chromosomal mosaicism in the ontogenetic and pathogenetic contexts appears to be required. Here, we review chromosomal mosaicism in its widest sense and discuss further directions of cyto(post)genomic research dedicated to chromosomal heterogeneity.

Pathway-based classification of genetic diseases

Background

In medical genetics, diseases are classified according to the nature (hypothetical nature) of the underlying genetic defect. The classification is “gene-centric” and “factor-centric”; a disease may be, thereby, designated as monogenic, oligogenic or polygenic/multifactorial. Chromosomal diseases/syndromes and abnormalities are generally considered apart from these designations due to distinctly different formation mechanisms and simultaneous encompassing from several to several hundreds of co-localized genes. These definitions are ubiquitously used and are perfectly suitable for human genetics issues in historical and academic perspective. However, recent achievements in systems biology have offered a possibility to explore the consequences of a genetic defect from genomic variations to molecular/cellular pathway alterations unique to a disease. Since pathogenetic mechanisms (pathways) are more influential on our understating of disease presentation and progression than genetic defects per se, a need for a disease classification reflecting both genetic causes and molecular/cellular mechanisms appears to exist. Here, we propose an extension to the common disease classification based on the underlying genetic defects, which focuses on disease-specific molecular pathways.

Conclusion

The basic idea of our classification is to propose pathways as parameters for designating a genetic disease. To proceed, we have followed the tradition of using ancient Greek words and prefixes to create the terms for the pathway-based classification of genetic diseases. We have chosen the word “griphos” (γρῖφος), which simultaneously means “net” and “puzzle”, accurately symbolizing the term “pathway” currently used in molecular biology and medicine. Thus, diseases may be classified as monogryphic (single pathway is altered to result in a phenotype), digryphic (two pathways are altered to result in a phenotype), etc.; additionally, diseases may be designated as oligogryphic (several pathways are altered to result in a phenotype), polygryphic (numerous pathways or cascades of pathways are altered to result in a phenotype) and homeogryphic in cases of comorbid diseases resulted from shared pathway alterations. We suppose that classifying illness this way using both “gene-centric” and “pathway-centric” concepts is able to revolutionize current views on genetic diseases.

Understanding aneuploidy in cancer through the lens of system inheritance, fuzzy inheritance and emergence of new genome systems

BACKGROUND

In the past 15 years, impressive progress has been made to understand the molecular mechanism behind aneuploidy, largely due to the effort of using various -omics approaches to study model systems (e.g. yeast and mouse models) and patient samples, as well as the new realization that chromosome alteration-mediated genome instability plays the key role in cancer. As the molecular characterization of the causes and effects of aneuploidy progresses, the search for the general mechanism of how aneuploidy contributes to cancer becomes increasingly challenging: since aneuploidy can be linked to diverse molecular pathways (in regards to both cause and effect), the chances of it being cancerous is highly context-dependent, making it more difficult to study than individual molecular mechanisms. When so many genomic and environmental factors can be linked to aneuploidy, and most of them not commonly shared among patients, the practical value of characterizing additional genetic/epigenetic factors contributing to aneuploidy decreases.

RESULTS

Based on the fact that cancer typically represents a complex adaptive system, where there is no linear relationship between lower-level agents (such as each individual gene mutation) and emergent properties (such as cancer phenotypes), we call for a new strategy based on the evolutionary mechanism of aneuploidy in cancer, rather than continuous analysis of various individual molecular mechanisms. To illustrate our viewpoint, we have briefly reviewed both the progress and challenges in this field, suggesting the incorporation of an evolutionary-based mechanism to unify diverse molecular mechanisms. To further clarify this rationale, we will discuss some key concepts of the genome theory of cancer evolution, including system inheritance, fuzzy inheritance, and cancer as a newly emergent cellular system.

CONCLUSION

Illustrating how aneuploidy impacts system inheritance, fuzzy inheritance and the emergence of new systems is of great importance. Such synthesis encourages efforts to apply the principles/approaches of complex adaptive systems to ultimately understand aneuploidy in cancer.

Experimental Induction of Genome Chaos

Genome chaos, or karyotype chaos, represents a powerful survival strategy for somatic cells under high levels of stress/selection. Since the genome context, not the gene content, encodes the genomic blueprint of the cell, stress-induced rapid and massive reorganization of genome topology functions as a very important mechanism for genome (karyotype) evolution. In recent years, the phenomenon of genome chaos has been confirmed by various sequencing efforts, and many different terms have been coined to describe different subtypes of the chaotic genome including "chromothripsis," "chromoplexy," and "structural mutations." To advance this exciting field, we need an effective experimental system to induce and characterize the karyotype reorganization process. In this chapter, an experimental protocol to induce chaotic genomes is described, following a brief discussion of the mechanism and implication of genome chaos in cancer evolution.

Why it is crucial to analyze non clonal chromosome aberrations or NCCAs?

Current cytogenetics has largely focused its efforts on the identification of recurrent karyotypic alterations, also known as clonal chromosomal aberrations (CCAs). The rationale of doing so seems simple: recurrent genetic changes are relevant for diseases or specific physiological conditions, while non clonal chromosome aberrations (NCCAs) are insignificant genetic background or noise. However, in reality, the vast majority of chromosomal alterations are NCCAs, and it is challenging to identify commonly shared CCAs in most solid tumors. Furthermore, the karyotype, rather than genes, represents the system inheritance, or blueprint, and each NCCA represents an altered genome system. These realizations underscore the importance of the re-evaluation of NCCAs in cytogenetic analyses. In this concept article, we briefly review the definition of NCCAs, some historical misconceptions about them, and why NCCAs are not insignificant "noise," but rather a highly significant feature of the cellular population for providing genome heterogeneity and complexity, representing one important form of fuzzy inheritance. The frequencies of NCCAs also represent an index to measure both internally- and environmentally-induced genome instability. Additionally, the NCCA/CCA cycle is associated with macro- and micro-cellular evolution. Lastly, elevated NCCAs are observed in many disease/illness conditions. Considering all of these factors, we call for the immediate action of studying and reporting NCCAs. Specifically, effort is needed to characterize and compare different types of NCCAs, to define their baseline in various tissues, to develop methods to access mitotic cells, to re-examine/interpret the NCCAs data, and to develop an NCCA database.