Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation

Advancements in copy number variation screening in herbivorous livestock genomes and their association with phenotypic traits

Copy number variations (CNVs) have garnered increasing attention within the realm of genetics due to their prevalence in human, animal, and plant genomes. These structural genetic variations have demonstrated associations with a broad spectrum of phenotypic diversity, economic traits, environmental adaptations, epidemics, and other essential aspects of both plants and animals. Furthermore, CNVs exhibit extensive sequence variability and encompass a wide array of genomes. The advancement and maturity of microarray and sequencing technologies have catalyzed a surge in research endeavors pertaining to CNVs. This is particularly prominent in the context of livestock breeding, where molecular markers have gained prominence as a valuable tool in comparison to traditional breeding methods. In light of these developments, a contemporary and comprehensive review of existing studies on CNVs becomes imperative. This review serves the purpose of providing a brief elucidation of the fundamental concepts underlying CNVs, their mutational mechanisms, and the diverse array of detection methods employed to identify these structural variations within genomes. Furthermore, it seeks to systematically analyze the recent advancements and findings within the field of CNV research, specifically within the genomes of herbivorous livestock species, including cattle, sheep, horses, and donkeys. The review also highlighted the role of CNVs in shaping various phenotypic traits including growth traits, reproductive traits, pigmentation and disease resistance etc., in herbivorous livestock. The main goal of this review is to furnish readers with an up-to-date compilation of knowledge regarding CNVs in herbivorous livestock genomes. By integrating the latest research findings and insights, it is anticipated that this review will not only offer pertinent information but also stimulate future investigations into the realm of CNVs in livestock. In doing so, it endeavors to contribute to the enhancement of breeding strategies, genomic selection, and the overall improvement of herbivorous livestock production and resistance to diseases.

Integrating whole-genome sequencing and transcriptomic findings in the diagnosis and management of Coffin-Siris syndrome

INTRODUCTION

Although the whole-exome sequencing (WES) approach has been widely used in clinic, many rare diseases with syndromic and nonsyndromic neurological manifestations remain undiagnosed. Coffin-Siris syndrome (CSS) is a rare autosomal dominant genetic disease characterized by neurodevelopmental delay. A suspected diagnosis can be made based on the typical CSS clinical features; however, molecular genetic testing is necessary for a confirmed diagnosis.

OBJECTIVES

Three CSS-like patients with negative results in the WES and chromosomal microarray analysis (CMA) were recruited in this study.

METHODS

We used whole-genome sequencing (WGS) technology to sequence the peripheral blood of the three families. To further explore the possible pathogenesis of CSS, we performed RNA-sequencing (RNA-seq).

RESULTS

WGS identified the three CSS patients were carrying de novo copy number variants of the ARID1B gene, which have not been reported before. RNA-seq identified 184 differentially expressed genes (DEGs), with 116 up-regulated and 68 down-regulated. Functional annotation of DEGs showed that two biological processes (immune response, chemokine activity) and two signaling pathways (cytokine-cytokine receptor interaction, chemokine activity) were highlighted. We speculated that ARID1B deficiency might trigger abnormal immune responses, which may be involved in the pathophysiologic mechanisms of CSS.

CONCLUSION

Our research provided further support for WGS application in CSS diagnosis and made an investigational approach for the underlying mechanisms of CSS.

CRISPR generation of CSF1R-G795A human microglia for robust microglia replacement in a chimeric mouse model

Chimeric mouse models have recently been developed to study human microglia in vivo. However, widespread engraftment of donor microglia within the adult brain has been challenging. Here, we present a protocol to introduce the G795A point mutation using CRISPR-Cas9 into the CSF1R locus of human pluripotent stem cells. We also describe an optimized microglial differentiation technique for transplantation into newborn or adult recipients. We then detail pharmacological paradigms to achieve widespread and near-complete engraftment of human microglia. For complete details on the use and execution of this protocol, please refer to Chadarevian et al. (2023).1.

Detection of Single-Nucleotide and Copy Number Defects Underlying Hyperphenylalaninemia by Next-Generation Sequencing

Hyperphenylalaninemia (HPA) is the most common inherited amino acid metabolism disorder characterized by serious clinical manifestations, including irreversible brain damage, intellectual deficiency and epilepsy. Due to its extensive genic and allelic heterogeneity, next-generation sequencing (NGS) technology may help to identify the molecular basis of this genetic disease. Herein, we describe the development and validation of a targeted NGS (tNGS) approach for the simultaneous detection of single-nucleotide changes and copy number variations (CNVs) in genes associated with HPA (PAH, GCH1, PTS, QDPR, PCBD1, DNAJC12) or useful for its differential diagnosis (SPR). Our tNGS approach offers the possibility to detail, with a high accuracy and in a single workflow, the combined effect of a broader spectrum of genomic variants in a comprehensive view, providing a significant step forward in the development of optimized patient care and management.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

The consequences of recurrent genetic and epigenetic variants in human pluripotent stem cells

It is well established that human pluripotent stem cells (hPSCs) can acquire genetic and epigenetic changes during culture in vitro. Given the increasing use of hPSCs in research and therapy and the vast expansion in the number of hPSC lines available for researchers, the International Society for Stem Cell Research has recognized the need to reassess quality control standards for ensuring the genetic integrity of hPSCs. Here, we summarize current knowledge of the nature of recurrent genetic and epigenetic variants in hPSC culture, the methods for their detection, and what is known concerning their effects on cell behavior in vitro or in vivo. We argue that the potential consequences of low-level contamination of cell therapy products with cells bearing oncogenic variants are essentially unknown at present. We highlight the key challenges facing the field with particular reference to safety assessment of hPSC-derived cellular therapeutics.

Genetic variation in placental insufficiency: What have we learned over time?

Genetic variation shapes placental development and function, which has long been known to impact fetal growth and pregnancy outcomes such as miscarriage or maternal pre-eclampsia. Early epidemiology studies provided evidence of a strong heritable component to these conditions with both maternal and fetal-placental genetic factors contributing. Subsequently, cytogenetic studies of the placenta and the advent of prenatal diagnosis to detect chromosomal abnormalities provided direct evidence of the importance of spontaneously arising genetic variation in the placenta, such as trisomy and uniparental disomy, drawing inferences that remain relevant to this day. Candidate gene approaches highlighted the role of genetic variation in genes influencing immune interactions at the maternal-fetal interface and angiogenic factors. More recently, the emergence of molecular techniques and in particular high-throughput technologies such as Single-Nucleotide Polymorphism (SNP) arrays, has facilitated the discovery of copy number variation and study of SNP associations with conditions related to placental insufficiency. This review integrates past and more recent knowledge to provide important insights into the role of placental function on fetal and perinatal health, as well as into the mechanisms leading to genetic variation during development.

Progress in Methods for Copy Number Variation Profiling

Copy number variations (CNVs) are the predominant class of structural genomic variations involved in the processes of evolutionary adaptation, genomic disorders, and disease progression. Compared with single-nucleotide variants, there have been challenges associated with the detection of CNVs owing to their diverse sizes. However, the field has seen significant progress in the past 20–30 years. This has been made possible due to the rapid development of molecular diagnostic methods which ensure a more detailed view of the genome structure, further complemented by recent advances in computational methods. Here, we review the major approaches that have been used to routinely detect CNVs, ranging from cytogenetics to the latest sequencing technologies, and then cover their specific features.

Somatic Hypomethylation of Pericentromeric SST1 Repeats and Tetraploidization in Human Colorectal Cancer Cells

Somatic DNA hypomethylation and aneuploidy are hallmarks of cancer, and there is evidence for a causal relationship between them in knockout mice but not in human cancer. The non-mobile pericentromeric repetitive elements SST1 are hypomethylated in about 17% of human colorectal cancers (CRC) with some 5-7% exhibiting strong age-independent demethylation. We studied the frequency of genome doubling, a common event in solid tumors linked to aneuploidy, in randomly selected single cell clones of near-diploid LS174T human CRC cells differing in their level of SST1 demethylation. Near-diploid LS174T cells underwent frequent genome-doubling events generating near-tetraploid clones with lower levels of SST1 methylation. In primary CRC, strong SST1 hypomethylation was significantly associated with global genomic hypomethylation and mutations in TP53. This work uncovers the association of the naturally occurring demethylation of the SST1 pericentromeric repeat with the onset of spontaneous tetraploidization in human CRC cells in culture and with TP53 mutations in primary CRCs. Altogether, our findings provide further support for an oncogenic pathway linking somatic hypomethylation and genetic copy number alterations in a subset of human CRC.

Radiation-Induced Chromosomal Breaks may be DNA Repair Fragile Sites with Larger-scale Correlations to Eight Double-Strand-Break Related Data Sets over the Human Genome

In this work, we compared the genomic distribution of common radiation-induced chromosomal breaks to eight different data sets covering the whole human genome. Sites with a high probability of chromatid breakage after exposure to low and high ionization density radiations were often located inside common and rare fragile sites, indicating that they may be a new and more local type of DNA repair-related fragility. Breaks in specific chromosome bands after acute exposure to oil and benzene also showed strong correlation with these sites and fragile sites. In addition, close correlation was found with cytologically detected chiasma and MLH1 immunofluorescence sites and with the HapMap recombination density distributions. Also, of interest, copy number changes occurred predominantly at radiation-induced breaks and fragile sites, at least for breast cancers with poor prognosis, and they decreased weakly but significantly in regions with increasing recombination and CpG density. An increased CpG density is linked to regions of high gene density to secure high-fidelity reproduction and survival. To minimize cancer induction, cancer-related genes are often located in regions of decreased recombination density and/or higher-than-average CpG density. It is compelling that all these data sets were influenced by the cells' handling of double-strand breaks and, more generally, DNA damage on its genome. In fact, the DNA repair genes systematically avoid regions with a high recombination density, as they need to be intact to accurately handle repairable DNA lesions.

Variational Inference for Coupled Hidden Markov Models Applied to the Joint Detection of Copy Number Variations

Hidden Markov models provide a natural statistical framework for the detection of the copy number variations (CNV) in genomics. In this context, we define a hidden Markov process that underlies all individuals jointly in order to detect and to classify genomics regions in different states (typically, deletion, normal or amplification). Structural variations from different individuals may be dependent. It is the case in agronomy where varietal selection program exists and species share a common phylogenetic past. We propose to take into account these dependencies inthe HMM model. When dealing with a large number of series, maximum likelihood inference (performed classically using the EM algorithm) becomes intractable. We thus propose an approximate inference algorithm based on a variational approach (VEM), implemented in the CHMM R package. A simulation study is performed to assess the performance of the proposed method and an application to the detection of structural variations in plant genomes is presented.

Chromosomal aberrations in renal cell carcinoma: An overview with implications for clinical practice

Chromosomal instability and aberrations are known in many cancers including renal cell carcinoma. Detailed understanding of these changes has led to an improved drug discovery and continued developments in other therapeutic options. Chromosomal aberrations have a potential to be used to monitor disease including prognostication. There has been a growing experience in cytogenetic techniques and gap between clinic and laboratory has narrowed significantly in the recent past. Nevertheless, more work on validation of these techniques, establishing threshold and interobserver agreement needs to be carried out for these diagnostic/prognostic tests before utilizing them in clinics as a part of “personalized medicine” care. The review presented here is a summary of common genetic disorders in renal cancer and some of acquired genetic changes which can be used as biomarkers. The review also describes basics of commonly used genetic techniques for wider clinical community involved in the management of renal cancer.

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

A Review of Copy Number Variants in Inherited Neuropathies

The rapid development in the last 10-15 years of microarray technologies, such as oligonucleotide array Comparative Genomic Hybridization (CGH) and Single Nucleotide Polymorphisms (SNP) genotyping array, has improved the identification of fine chromosomal structural variants, ranging in length from kilobases (kb) to megabases (Mb), as an important cause of genetic differences among healthy individuals and also as disease-susceptibility and/or disease-causing factors. Structural genomic variations due to unbalanced chromosomal rearrangements are known as Copy-Number Variants (CNVs) and these include variably sized deletions, duplications, triplications and translocations. CNVs can significantly contribute to human diseases and rearrangements in several dosage-sensitive genes have been identified as an important causative mechanism in the molecular aetiology of Charcot-Marie-Tooth (CMT) disease and of several CMT-related disorders, a group of inherited neuropathies with a broad range of clinical phenotypes, inheritance patterns and causative genes. Duplications or deletions of the dosage-sensitive gene PMP22 mapped to chromosome 17p12 represent the most frequent causes of CMT type 1A and Hereditary Neuropathy with liability to Pressure Palsies (HNPP), respectively. Additionally, CNVs have been identified in patients with other CMT types (e.g., CMT1X, CMT1B, CMT4D) and different hereditary poly- (e.g., giant axonal neuropathy) and focal- (e.g., hereditary neuralgic amyotrophy) neuropathies, supporting the notion of hereditary peripheral nerve diseases as possible genomic disorders and making crucial the identification of fine chromosomal rearrangements in the molecular assessment of such patients. Notably, the application of advanced computational tools in the analysis of Next-Generation Sequencing (NGS) data has emerged in recent years as a powerful technique for identifying a genome-wide scale complex structural variants (e.g., as the ones resulted from balanced rearrangements) and also smaller pathogenic (intragenic) CNVs that often remain beyond the detection limit of most conventional genomic microarray analyses; in the context of inherited neuropathies where more than 70 disease-causing genes have been identified to date, NGS and particularly Whole-Genome Sequencing (WGS) hold the potential to reduce the number of genomic assays required per patient to reach a diagnosis, analyzing with a single test all the Single Nucleotide Variants (SNVs) and CNVs in the genes possibly implicated in this heterogeneous group of disorders.

The nuclear factor-kappa B pathway and response to treatment in breast cancer

The nuclear factor-kappa B (NF-κB) pathway is known to contribute to critical signaling in cancer biology, including breast cancer, through promotion of proliferation, angiogenesis, metastasis, tumor progression, inflammation and cell survival. In this review, in vivo and in vitro studies of the NF-κB pathway in breast cancer are discussed, focusing on DNA damage and the epithelial-mesenchymal transition associated with breast cancer stem cell properties. The relationships between NF-κB signaling and conventional cancer treatments in terms of response to chemo- and radiotherapy will also be discussed. Then contribution and involvement of immune system in the NF-κB pathway will be covered. Furthermore, the future perspective of NF-κB targeting as an innovative strategy to overcome refractory breast cancer, including recent updates on out-receptor activator of NF-κB (RANKing), will be covered.

Application of a New Probabilistic Model for Mining Implicit Associated Cancer Genes from OMIM and Medline

An important issue in current medical science research is to find the genes that are strongly related to an inherited disease. A particular focus is placed on cancer-gene relations, since some types of cancers are inherited. As bio-medical databases have grown speedily in recent years, an informatics approach to predict such relations from currently available databases should be developed. Our objective is to find implicit associated cancer-genes from biomedical databases including the literature database. Co-occurrence of biological entities has been shown to be a popular and efficient technique in biomedical text mining. We have applied a new probabilistic model, called mixture aspect model (MAM) [ 48 ], to combine different types of co-occurrences of genes and cancer derived from Medline and OMIM (Online Mendelian Inheritance in Man). We trained the probability parameters of MAM using a learning method based on an EM (Expectation and Maximization) algorithm. We examined the performance of MAM by predicting associated cancer gene pairs. Through cross-validation, prediction accuracy was shown to be improved by adding gene-gene co-occurrences from Medline to cancer-gene co-occurrences in OMIM. Further experiments showed that MAM found new cancer-gene relations which are unknown in the literature. Supplementary information can be found at http://www.bic.kyotou.ac.jp/pathway/zhusf/CancerInformatics/Supplemental2006.html

Gel-seq: whole-genome and transcriptome sequencing by simultaneous low-input DNA and RNA library preparation using semi-permeable hydrogel barriers

The advent of next generation sequencing has fundamentally changed genomics research. Unfortunately, standard protocols for sequencing the genome and the transcriptome are incompatible. This forces researchers to choose between examining either the DNA or the RNA for a particular sample. Here we describe a new device and method, collectively dubbed Gel-seq, that enables researchers to simultaneously sequence both DNA and RNA from the same sample. This technology makes it possible to directly examine the ways that changes in the genome impact the transcriptome in as few as 100 cells. The heart of the Gel-seq protocol is the physical separation of DNA from RNA. This separation is achieved electrophoretically using a newly designed device that contains several different polyacrylamide membranes. Here we report on the development and validation of this device. We present both the manufacturing protocol for the device and the biological protocol for preparing genetic libraries. Using cell lines with uniform expression (PC3 and Hela), we show that the libraries generated with Gel-seq are similar to those developed using standard methods for either RNA or DNA. Furthermore, we demonstrate the power of Gel-seq by generating a matched genome and transcriptome library from a sample of 100 cells collected from a mouse liver tumor.

A Novel Graph-based Algorithm to Infer Recurrent Copy Number Variations in Cancer

Many cancers have been linked to copy number variations (CNVs) in the genomic DNA. Although there are existing methods to analyze CNVs from individual samples, cancer-causing genes are more frequently discovered in regions where CNVs are common among tumor samples, also known as recurrent CNVs. Integrating multiple samples and locating recurrent CNV regions remain a challenge, both computationally and conceptually. We propose a new graph-based algorithm for identifying recurrent CNVs using the maximal clique detection technique. The algorithm has an optimal solution, which means all maximal cliques can be identified, and guarantees that the identified CNV regions are the most frequent and that the minimal regions have been delineated among tumor samples. The algorithm has successfully been applied to analyze a large cohort of breast cancer samples and identified some breast cancer-associated genes and pathways.

Molecular Karyotyping: Array CGH Quality Criteria for Constitutional Genetic Diagnosis

Array CGH (comparative genomic hybridization) enables the identification of chromosomal copy number changes. The availability of clone sets covering the human genome opens the possibility for the widespread use of array CGH for both research and diagnostic purposes. In this manuscript we report on the parameters that were critical for successful implementation of the technology, assess quality criteria, and discuss the potential benefits and pitfalls of the technology for improved pre- and postnatal constitutional genetic diagnosis. We propose to name the genome-wide array CGH “molecular karyotyping,” in analogy with conventional karyotyping that uses staining methods to visualize chromosomes.

Random monoallelic expression of autosomal genes: stochastic transcription and allele-level regulation

Random monoallelic expression (RME) of genes represents a striking example of how stochastic molecular processes can result in cellular heterogeneity. Recent transcriptome-wide studies have revealed both mitotically stable and cell-to-cell dynamic forms of autosomal RME, with the latter presumably resulting from burst-like stochastic transcription. Here, we discuss the distinguishing features of these two forms of RME and revisit literature on their nature, pervasiveness and regulation. Finally, we explore how RME may contribute to phenotypic variation, including the incomplete penetrance and variable expressivity often seen in genetic disease.

ENVE: a novel computational framework characterizes copy-number mutational landscapes in colorectal cancers from African American patients

Reliable detection of somatic copy-number alterations (sCNAs) in tumors using whole-exome sequencing (WES) remains challenging owing to technical (inherent noise) and sample-associated variability in WES data. We present a novel computational framework, ENVE, which models inherent noise in any WES dataset, enabling robust detection of sCNAs across WES platforms. ENVE achieved high concordance with orthogonal sCNA assessments across two colorectal cancer (CRC) WES datasets, and consistently outperformed a best-in-class algorithm, Control-FREEC. We subsequently used ENVE to characterize global sCNA landscapes in African American CRCs, identifying genomic aberrations potentially associated with CRC pathogenesis in this population. ENVE is downloadable at https://github.com/ENVE-Tools/ENVE.

Hybrid algorithms for multiple change-point detection in biological sequences

Array comparative genomic hybridization (aCGH) is one of the techniques that can be used to detect copy number variations in DNA sequences in high resolution. It has been identified that abrupt changes in the human genome play a vital role in the progression and development of many complex diseases. In this study we propose two distinct hybrid algorithms that combine efficient sequential change-point detection procedures (the Shiryaev-Roberts procedure and the cumulative sum control chart (CUSUM) procedure) with the Cross-Entropy method, which is an evolutionary stochastic optimization technique to estimate both the number of change-points and their corresponding locations in aCGH data. The proposed hybrid algorithms are applied to both artificially generated data and real aCGH experimental data to illustrate their usefulness. Our results show that the proposed methodologies are effective in detecting multiple change-points in biological sequences of continuous measurements.

A decade of structural variants: description, history and methods to detect structural variation

In the past decade, the view on genomic structural variation (SV) has been changed completely. SVs, previously considered rare events, are now recognized as the largest source of interindividual genetic variation affecting more bases than single nucleotide polymorphisms, variable number of tandem repeats and other small genetic variants. They have also been shown to play a role in phenotypic variation and in disease. In this review, the authors will provide an introduction to SV; a short historical perspective on the research of this source of genomic variation; a description of the types of structural variants, and on how they may have arisen; and an overview on methods of detecting structural variants, focusing on the analysis of high-throughput sequencing data.

Protein Microarrays with Novel Microfluidic Methods: Current Advances

Microfluidic-based micromosaic technology has allowed the pattering of recognition elements in restricted micrometer scale areas with high precision. This controlled patterning enabled the development of highly multiplexed arrays multiple analyte detection. This arraying technology was first introduced in the beginning of 2001 and holds tremendous potential to revolutionize microarray development and analyte detection. Later, several microfluidic methods were developed for microarray application. In this review we discuss these novel methods and approaches which leverage the property of microfluidic technologies to significantly improve various physical aspects of microarray technology, such as enhanced imprinting homogeneity, stability of the immobilized biomolecules, decreasing assay times, and reduction of the costs and of the bulky instrumentation.

MLL3 is a haploinsufficient 7q tumor suppressor in acute myeloid leukemia

Recurring deletions of chromosome 7 and 7q [-7/del(7q)] occur in myelodysplastic syndromes and acute myeloid leukemia (AML) and are associated with poor prognosis. However, the identity of functionally relevant tumor suppressors on 7q remains unclear. Using RNAi and CRISPR/Cas9 approaches, we show that an ∼50% reduction in gene dosage of the mixed lineage leukemia 3 (MLL3) gene, located on 7q36.1, cooperates with other events occurring in -7/del(7q) AMLs to promote leukemogenesis. Mll3 suppression impairs the differentiation of HSPC. Interestingly, Mll3-suppressed leukemias, like human -7/del(7q) AMLs, are refractory to conventional chemotherapy but sensitive to the BET inhibitor JQ1. Thus, our mouse model functionally validates MLL3 as a haploinsufficient 7q tumor suppressor and suggests a therapeutic option for this aggressive disease.

Effect of high-LET Fe-ion beam irradiation on mutation induction in Arabidopsis thaliana

Heavy-ion beams are powerful mutagens. They cause a broad spectrum of mutation phenotypes with high efficiency even at low irradiation doses and short irradiation times. These mutagenic effects are due to dense ionisation in a localised region along the ion particle path. Linear energy transfer (LET; keV·μm(-1)), which represents the degree of locally deposited energy, is an important parameter in heavy-ion mutagenesis. For high LET radiation above 290 keV∙μm(-1), however, neither the mutation frequency nor the molecular nature of the mutations has been fully characterised. In this study, we investigated the effect of Fe-ion beams with an LET of 640 keV∙μm(-1) on both the mutation frequency and the molecular nature of the mutations. Screening of well-characterised mutants (hy and gl) revealed that the mutation frequency was lower than any other ion species with low LET. We investigated the resulting mutations in the 4 identified mutants. Three mutants were examined by employing PCR-based methods, one of which had 2-bp deletion, another had 178 bp of tandemly duplication, and other one had complicated chromosomal rearrangements with variable deletions in size at breakpoints. We also detected large deletions in the other mutant by using array comparative genomic hybridisation. From the results of the analysis of the breakpoints and junctions of the detected deletions, it was revealed that the mutants harboured chromosomal rearrangements in their genomes. These results indicate that Fe-ion irradiation tends to cause complex mutations with low efficiency. We conclude that Fe-ion irradiation could be useful for inducing chromosomal rearrangements or large deletions.

Bayesian hierarchical structured variable selection methods with application to MIP studies in breast cancer

The analysis of alterations that may occur in nature when segments of chromosomes are copied (known as copy number alterations) has been a focus of research to identify genetic markers of cancer. One high-throughput technique recently adopted is the use of molecular inversion probes (MIPs) to measure probe copy number changes. The resulting data consist of high-dimensional copy number profiles that can be used to ascertain probe-specific copy number alterations in correlative studies with patient outcomes to guide risk stratification and future treatment. We propose a novel Bayesian variable selection method, the hierarchical structured variable selection (HSVS) method, which accounts for the natural gene and probe-within-gene architecture to identify important genes and probes associated with clinically relevant outcomes. We propose the HSVS model for grouped variable selection, where simultaneous selection of both groups and within-group variables is of interest. The HSVS model utilizes a discrete mixture prior distribution for group selection and group-specific Bayesian lasso hierarchies for variable selection within groups. We provide methods for accounting for serial correlations within groups that incorporate Bayesian fused lasso methods for within-group selection. Through simulations we establish that our method results in lower model errors than other methods when a natural grouping structure exists. We apply our method to an MIP study of breast cancer and show that it identifies genes and probes that are significantly associated with clinically relevant subtypes of breast cancer.

Evolution of prenatal genetics: from point mutation testing to chromosomal microarray analysis

Molecular genetic testing involves DNA analysis using various methods for the purpose of diagnosing genetic disorders. In the prenatal DNA diagnostic setting, fetal DNA is usually tested for a specific single-gene disorder for which the fetal risk is 25% or more. In contrast, cytogenetic testing is often used to detect fetal chromosomal abnormalities in cases that involve a wider range of indications. Classic cytogenetic and DNA-based testing methods provide a range of aberrations detected with different levels of genomic resolution. More recently developed molecular cytogenetic methods provide powerful tools to bridge the technical divide between these related areas. One such hybrid method is microarray-based comparative genomic hybridization. Chromosomal microarray analysis has been applied to clinical testing for unbalanced gains or losses of genomic regions associated with genetic disorders. This technology is poised to have a substantial impact on clinical genetics, including prenatal genetic testing.

Recurrent genomic alterations in sequential progressive leukoplakia and oral cancer: drivers of oral tumorigenesis?

A significant proportion (up to 62%) of oral squamous cell carcinomas (OSCCs) may arise from oral potential malignant lesions (OPMLs), such as leukoplakia. Patient outcomes may thus be improved through detection of lesions at a risk for malignant transformation, by identifying and categorizing genetic changes in sequential, progressive OPMLs. We conducted array comparative genomic hybridization analysis of 25 sequential, progressive OPMLs and same-site OSCCs from five patients. Recurrent DNA copy number gains were identified on 1p in 20/25 cases (80%) with minimal, high-level amplification regions on 1p35 and 1p36. Other regions of gains were frequently observed: 11q13.4 (68%), 9q34.13 (64%), 21q22.3 (60%), 6p21 and 6q25 (56%) and 10q24, 19q13.2, 22q12, 5q31.2, 7p13, 10q24 and 14q22 (48%). DNA losses were observed in >20% of samples and mainly detected on 5q31.2 (35%), 16p13.2 (30%), 9q33.1 and 9q33.29 (25%) and 17q11.2, 3p26.2, 18q21.1, 4q34.1 and 8p23.2 (20%). Such copy number alterations (CNAs) were mapped in all grades of dysplasia that progressed, and their corresponding OSCCs, in 70% of patients, indicating that these CNAs may be associated with disease progression. Amplified genes mapping within recurrent CNAs (KHDRBS1, PARP1, RAB1A, HBEGF, PAIP2, BTBD7) were selected for validation, by quantitative real-time PCR, in an independent set of 32 progressive leukoplakia, 32 OSSCs and 21 non-progressive leukoplakia samples. Amplification of BTBD7, KHDRBS1, PARP1 and RAB1A was exclusively detected in progressive leukoplakia and corresponding OSCC. BTBD7, KHDRBS1, PARP1 and RAB1A may be associated with OSCC progression. Protein–protein interaction networks were created to identify possible pathways associated with OSCC progression.

Stability-based comparison of class discovery methods for DNA copy number profiles

MOTIVATION

Array-CGH can be used to determine DNA copy number, imbalances in which are a fundamental factor in the genesis and progression of tumors. The discovery of classes with similar patterns of array-CGH profiles therefore adds to our understanding of cancer and the treatment of patients. Various input data representations for array-CGH, dissimilarity measures between tumor samples and clustering algorithms may be used for this purpose. The choice between procedures is often difficult. An evaluation procedure is therefore required to select the best class discovery method (combination of one input data representation, one dissimilarity measure and one clustering algorithm) for array-CGH. Robustness of the resulting classes is a common requirement, but no stability-based comparison of class discovery methods for array-CGH profiles has ever been reported.

RESULTS

We applied several class discovery methods and evaluated the stability of their solutions, with a modified version of Bertoni's [Formula: see text]-based test [1]. Our version relaxes the assumption of independency required by original Bertoni's [Formula: see text]-based test. We conclude that Minimal Regions of alteration (a concept introduced by [2]) for input data representation, sim [3] or agree [4] for dissimilarity measure and the use of average group distance in the clustering algorithm produce the most robust classes of array-CGH profiles.

AVAILABILITY

The software is available from http://bioinfo.curie.fr/projects/cgh-clustering. It has also been partly integrated into "Visualization and analysis of array-CGH"(VAMP)[5]. The data sets used are publicly available from ACTuDB [6].

Atherosclerosis-susceptible and atherosclerosis-resistant pigeon aortic cells express different genes in vivo

Spontaneous atherosclerosis in the White Carneau (WC-As) pigeon is inherited as a single gene disorder, and its progression closely mirrors the human disease. Representational difference analysis and microarray were used to identify genes that were differentially expressed between the susceptible WC-As and resistant Show Racer (SR-Ar) aortic tissue. The RNA extracted from 1-d-old squab aortas was used to make cDNA for each experiment. Fifty-six unique genes were found using representational difference analysis, with 25 exclusively expressed in the WC-As, 15 exclusive to the SR-Ar, and 16 nonexclusive genes having copy number variation between breeds. Caveolin and β-actin were expressed in the WC-As, whereas the proteasome maturation protein and the transcription complex CCR4-NOT were exclusive to the SR-Ar. Microarray analysis revealed 48 genes with differential expression. Vascular endothelial growth factor and p53 binding protein were among the 17 genes upregulated in the WC-As. Thirty-one genes were upregulated in the SR-Ar including the transforming growth factor-β signaling factor SMAD2 and heat shock protein 90. Genes representing several biochemical pathways were distinctly different between breeds. The most striking divergences were in cytoskeletal remodeling, proteasome activity, cellular respiration, and immune response. Actin cytoskeletal remodeling appears to be one of the first differences between susceptible and resistant breeds, lending support to the smooth muscle cell phenotypic reversion hypothesis of human atherogenesis.

Integration of cancer genomics with treatment selection: from the genome to predictive biomarkers

The field of cancer genomics is rapidly advancing as new technology provides detailed genetic and epigenetic profiling of human cancers. The amount of new data available describing the genetic make-up of tumors is paralleled by rapid advances in drug discovery and molecular therapy currently under investigation to treat these diseases. This review summarizes the challenges and approaches associated with the integration of genomic data into the development of new biomarkers in the management of cancer.

Loss of DOK2 induces carboplatin resistance in ovarian cancer via suppression of apoptosis

OBJECTIVE

Ovarian cancers are highly heterogeneous and while chemotherapy is the preferred treatment many patients are intrinsically resistant or quickly develop resistance. Furthermore, all tumors that recur ultimately become resistant. Recent evidence suggests that epigenetic deregulation may be a key factor in the onset and maintenance of chemoresistance. We set out to identify epigenetically silenced genes that affect chemoresistance.

METHODS

The epigenomes of a total of 45 ovarian samples were analyzed to identify epigenetically altered genes that segregate with platinum response, and further filtered with expression data to identify genes that were suppressed. A tissue culture carboplatin resistance screen was utilized to functionally validate this set of candidate platinum resistance genes.

RESULTS

Our screen correctly identified 19 genes that when suppressed altered the chemoresistance of the cells in culture. Of the genes identified in the screen we further characterized one gene, docking protein 2 (DOK2), an adapter protein downstream of tyrosine kinase, to determine if we could elucidate the mechanism by which it increased resistance. The loss of DOK2 decreased the level of apoptosis in response to carboplatin. Furthermore, in cells with reduced DOK2, the level of anoikis was decreased.

CONCLUSIONS

We have developed a screening methodology that analyzes the epigenome and informatically identifies candidate genes followed by in vitro culture screening of the candidate genes. To validate our screening methodology we further characterized one candidate gene, DOK2, and showed that loss of DOK2 induces chemotherapy resistance by decreasing the level of apoptosis in response to treatment.

The use of cytogenetic microarrays in myelodysplastic syndrome characterization

Various microarray platforms, including BAC, oligonucleotide, and SNP arrays, have been shown to -provide clinically useful diagnostic and prognostic information for patients with myelodysplastic syndromes (MDS). Clinically useful arrays are designed with specific purposes in mind and with attention to genomic content and probe density. All array types have been shown to detect genomic copy gains and losses, with SNP arrays having the added advantage of detecting copy neutral loss of heterozygosity (CNLOH). The finding of CNLOH has led to the identification of certain disease genes implicated in the initiation or progression of myeloid diseases. In addition, SNP karyotyping alone, or in conjunction with routine cytogenetics, can affect the outcome prediction and improve prognostic stratification of patients with MDS. Patients who were reclassified after array testing as having adverse-risk chromosomal findings correlated with poor survival. Results of over 25 published studies support the use of arrays in MDS testing. Because few balanced translocations are found in MDS, this disease is particularly amenable to microarray testing, and studies have shown better disease classification, identification of cryptic changes, and prognostication in this heterogeneous group of disorders. Novel genomic alterations identified by array testing may lead to better targeted therapies for treating patients with MDS.

Integrative prediction of gene function and platinum-free survival from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to discover genes critical to the development, progression, and therapeutic resistance of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatics analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We identify changes in DNA methylation and expression specifically for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic gene function from integrative analysis of three modalities: copy number variation, DNA methylation, and gene expression. Our method (1) calculates the extent of genomic and epigenetic alterations of defined tumor suppressor and oncogenic features for the functional prediction of significant ovarian cancer gene candidates and (2) identifies the functional activity or inactivity of known tumor suppressors and oncogenes in ovarian cancer. We applied our protocol on 42 primary serous ovarian cancer samples using MOMA-ROMA representational array assays. Additionally, we provide the basis for incorporating epigenetic profiles of ovarian tumors for the purposes of platinum-free survival prediction in the context of TCGA data.

Major chromosomal breakpoint intervals in breast cancer co-localize with differentially methylated regions

Solid tumors exhibit chromosomal rearrangements resulting in gain or loss of multiple chromosomal loci (copy number variation, or CNV), and translocations that occasionally result in the creation of novel chimeric genes. In the case of breast cancer, although most individual tumors each have unique CNV landscape, the breakpoints, as measured over large datasets, appear to be non-randomly distributed in the genome. Breakpoints show a significant regional concentration at genomic loci spanning perhaps several megabases. The proximal cause of these breakpoint concentrations is a subject of speculation, but is, as yet, largely unknown. To shed light on this issue, we have performed a bio-statistical analysis on our previously published data for a set of 119 breast tumors and normal controls (Wiedswang et al., 2003), where each sample has both high-resolution CNV and methylation data. The method examined the distribution of closeness of breakpoint regions with differentially methylated regions (DMR), coupled with additional genomic parameters, such as repeat elements and designated "fragile sites" in the reference genome. Through this analysis, we have identified a set of 93 regional loci called breakpoint enriched DMR (BEDMRs) characterized by altered DNA methylation in cancer compared to normal cells that are associated with frequent breakpoint concentrations within a distance of 1 Mb. BEDMR loci are further associated with local hypomethylation (66%), concentrations of the Alu SINE repeats within 3 Mb (35% of the cases), and tend to occur near a number of cancer related genes such as the protocadherins, AKT1, DUB3, GAB2. Furthermore, BEDMRs seem to deregulate members of the histone gene family and chromatin remodeling factors, e.g., JMJD1B, which might affect the chromatin structure and disrupt coordinate signaling and repair. From this analysis we propose that preference for chromosomal breakpoints is related to genome structure coupled with alterations in DNA methylation and hence, chromatin structure, associated with tumorigenesis.

Structural and genic characterization of stable genomic regions in breast cancer: relevance to chemotherapy

BACKGROUND

Cancer genomes accumulate frequent and diverse chromosomal abnormalities as well as gene mutations but must maintain the ability to survive in vivo. We hypothesize that genetic selection acts to maintain tumour survival by preserving copy number of specific genes and genomic regions. Genomic regions and genes that remain unaltered in copy number and expression, respectively, may be essential for maintaining tumour survival.

METHODS

We analyzed copy number data of 243 previously reported breast tumours and computationally derived stable copy number regions. To identify genes in stable copy number regions with nominal changes in expression, datasets for tumour and normal samples were compared. Results were replicated by analysis of a series of independent copy number, expression and genomic sequencing studies. A subset of stable regions, including stable paralogous regions, were confirmed by quantitative PCR and fluorescence in situ hybridization (FISH) in 5 breast cancer cell lines. We deduced a comprehensive set of dually stable genes (i.e. maintaining nominal copy number and expression) which were categorized according to pathway and ontology assignments. The stability of genes encoding therapeutic drug targets was also assessed.

RESULTS AND CONCLUSION

Tumour genome analysis revealed 766 unstable (amplified and/or deleted) and 812 stable contiguous genomic regions. Replication analysis of an independent set of 171 breast tumours confirmed copy number stability of 1.3 Gb of the genome. We found that 5804 of these genes were dually stable. The composition of this gene set remained essentially unchanged (<2% reduction) after accounting for commonly mutated breast cancer genes found by sequencing and differential expression. The stable breast cancer genome is enriched for cellular metabolism, regulation of gene expression, DNA packaging (chromatin and nucleosome assembly), and regulation of apoptosis functions. Stable genes participating in multiple essential pathways were consistently found to be targets of chemotherapies. Preservation of stable, essential genes may be related to the effectiveness of certain chemotherapeutic agents that act on multiple gene products in this set.

Copy number variation in the genomes of domestic animals

Copy number variation (CNV) might be one of the main contributors to phenotypic diversity and evolutionary adaptation in animals and plants, employing a wide variety of mechanisms, such as gene dosage and transcript structure alterations, to modulate organismal plasticity. In the past 4 years, considerable advances have been made in the characterization of the genomic architecture of CNV in domestic species. First, low-resolution CNV maps were produced for cattle, goat, sheep, pig, dog, chicken, duck and turkey, showing that these structural polymorphisms comprise a significant part of these genomes. Furthermore, CNVs have been associated with several pigmentation (white coat in horse, pig and sheep) and morphological (late feathering and pea comb in chicken) traits, as well as with susceptibility to a wide array of diseases and developmental disorders, for example osteopetrosis, anhidrotic ectodermal dysplasia, copper toxicosis, intersexuality, cone degeneration, periodic fever and dermoid sinus, among others. In the future, development of high-resolution tools for CNV detection and typing combined with the implementation of databases integrating CNV, QTL and gene expression data will be essential to identify and measure the impact of this source of structural variation on the many phenotypes that are relevant to animal breeders and veterinary practitioners.

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.

Comparative genomic hybridization to detect variation in the copy number of large DNA segments

Array comparative genomic hybridization (CGH) is an excellent tool to scan the genome for copy number variations (CNVs) when used conscientiously. This article is intended to provide an understanding of the basic principles of array CGH and the different options available to the user to design their array CGH experiments. Specifically, the six subsections discuss the different array platforms available, test and reference DNA preparation, reference DNA choice, the basics of hybridization, data processing, and our current understanding of CNVs in the human genome.