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Insulin-like growth factor binding protein 2: gene expression microarrays and the hypothesis-generation paradigm.

A major goal of modern medicine is to identify key genes and their products that are altered in the diseased state and to elucidate the molecular mechanisms underlying disease development, progression, and resistance to therapy. This is a daunting task given the exceptionally high complexity of the human genome. The paradigm for research has historically been hypothesis-driven despite the fact that the hypotheses under scrutiny often rest on tenuous subjective grounds or are derived from and dependent on chance observation. The imminent deciphering of the complete human genome, coupled with recent advances in high-throughput bioanalytical technology, has made possible a new paradigm in which data-based hypothesis-generation is the initial step in the investigative process, followed by hypothesis-testing. Genomics technologies are the primary source of the new hypothesis-generating capabilities that are now empowering biomedical researchers. The synergistic interaction between contemporary genomics technologies and the hypothesis-generation paradigm is well-illustrated by the discovery and subsequent ongoing study of the role of insulin-like growth factor binding protein 2 (IGFBP2) in human glioma biology. Using gene expression microarray technology, the IGFBP2 gene was recently found to be highly and differentially overexpressed in the most advanced grade of human glioma, glioblastoma. Based on this discovery, subsequent functional studies were initiated that suggest that IGFBP2 overexpression may contribute to the invasive nature of glioblastoma, and that IGFBP2 may exert its function via a newly identified novel binding protein. The IGFBP2 story is but one example of the power and potential of the new molecular methodologies that are transforming modern diagnostic and investigative neuropathology.

Brain Neoplasms↗

Quantitative analysis of comparative genomic hybridization.

Comparative genomic hybridization (CGH) is a new molecular cytogenetic method for the detection of chromosomal imbalances. Following cohybridization of DNA prepared from a sample to be studied and control DNA to normal metaphase spreads, probes are detected via different fluorochromes. The ratio of the test and control fluorescence intensities along a chromosome reflects the relative copy number of segments of a chromosome in the test genome. Quantitative evaluation of CGH experiments is required for the determination of low copy changes, e.g., monosomy or trisomy, and for the definition of the breakpoints involved in unbalanced rearrangements. In this study, a program for quantitation of CGH preparations is presented. This program is based on the extraction of the fluorescence ratio profile along each chromosome, followed by averaging of individual profiles from several meta phase spreads. Objective parameters critical for quantitative evaluations were tested, and the criteria for selection of suitable CGH preparations are described. The granularity of the chromosome painting and the regional inhomogeneity of fluorescence intensities in metaphase spreads proved to be crucial parameters. The coefficient of variation of the ratio value for chromosomes in balanced state (CVBS) provides a general quality criterion for CGH experiments. Different cutoff levels (thresholds) of average fluorescence ratio values were compared for their specificity and sensitivity with regard to the detection of chromosomal imbalances.

Chromosome Banding↗

A new experimental approach for studying bacterial genomic island evolution identifies island genes with bacterial host-specific expression patterns.

BACKGROUND: Genomic islands are regions of bacterial genomes that have been acquired by horizontal transfer and often contain blocks of genes that function together for specific processes. Recently, it has become clear that the impact of genomic islands on the evolution of different bacterial species is significant and represents a major force in establishing bacterial genomic variation. However, the study of genomic island evolution has been mostly performed at the sequence level using computer software or hybridization analysis to compare different bacterial genomic sequences. We describe here a novel experimental approach to study the evolution of species-specific bacterial genomic islands that identifies island genes that have evolved in such a way that they are differentially-expressed depending on the bacterial host background into which they are transferred. RESULTS: We demonstrate this approach by using a "test" genomic island that we have cloned from the Salmonella typhimurium genome (island 4305) and transferred to a range of Gram negative bacterial hosts of differing evolutionary relationships to S. typhimurium. Systematic analysis of the expression of the island genes in the different hosts compared to proper controls allowed identification of genes with genera-specific expression patterns. The data from the analysis can be arranged in a matrix to give an expression "array" of the island genes in the different bacterial backgrounds. A conserved 19-bp DNA site was found upstream of at least two of the differentially-expressed island genes. To our knowledge, this is the first systematic analysis of horizontally-transferred genomic island gene expression in a broad range of Gram negative hosts. We also present evidence in this study that the IS200 element found in island 4305 in S. typhimurium strain LT2 was inserted after the island had already been acquired by the S. typhimurium lineage and that this element is likely not involved in the integration or excision of island 4305. CONCLUSION: The "clone-and-transfer" approach of evolutionary study identifies genes whose expression patterns indicate the existence of genera-specific regulatory mechanisms that influence the expression of horizontally-transferred DNA sections. The results provide key information that can be used to facilitate the identification of these regulatory mechanisms.

Bacteria↗

Prenatal Phenotypic Features of Five Fetal Cases With RNU4ATAC-Associated Microcephalic Osteodysplastic Primordial Dwarfism Type I.

OBJECTIVE: To present the prenatal sonographic features, genomic findings, and pregnancy outcomes of fetuses with biallelic pathogenic RNU4ATAC variants linked to microcephalic osteodysplastic primordial dwarfism type I (MOPD1). METHODS: This retrospective case series includes five prenatal cases with MOPD1. Diagnoses were established by prenatal ultrasound and genetic testing. Genome sequencing (GS) or targeted exome sequencing (ES) detected the variants either prenatally or after termination of pregnancy (TOP). Clinical data including parental demographics, ultrasound findings, and pregnancy outcomes were collected. RESULTS: All fetuses presented with consistent anomalies on ultrasound including intrauterine growth restriction (IUGR), microcephaly, agenesis of the corpus callosum (ACC), intracranial cysts, lissencephaly, and micrognathia. IUGR was the earliest anomaly detected in all five cases. Prenatal ultrasound findings suggestive of skeletal dysplasia were identified in one case. All cases carried biallelic pathogenic RNU4ATAC variants associated with MOPD1. TOP was chosen in four cases. One fetus was delivered at 39 + 1 weeks with genetic diagnosis confirmed at 27 weeks. CONCLUSION: IUGR, microcephaly and ACC can be detected in fetuses with MOPD1 at around 18 weeks of gestation. Interestingly, skeletal dysplasia was not a consistent prenatal finding. Variants in the non-coding RNU4ATAC gene need to be detected by GS or targeted approaches beyond standard ES.

Humans↗

Multiplexed, targeted gene expression profiling and genetic analysis on electronic microarrays.

BACKGROUND: Electronic microarrays comprise independent microelectrode test sites that can be electronically biased positive or negative, or left neutral, to move and concentrate charged molecules such as DNA and RNA to one or more test sites. We developed a protocol for multiplexed gene expression profiling of mRNA targets that uses electronic field-facilitated hybridization on electronic microarrays. METHODS: A multiplexed, T7 RNA polymerase-mediated amplification method was used for expression profiling of target mRNAs from total cellular RNA; targets were detected by hybridization to sequence-specific capture oligonucleotides on electronic microarrays. Activation of individual test sites on the electronic microarray was used to target hybridization to designated subsets of sites and allow comparisons of target concentrations in different samples. We used multiplexed amplification and electronic field-facilitated hybridization to analyze expression of a model set of 10 target genes in the U937 cell line during lipopolysaccharide-mediated differentiation. Performance of multiple genetic analyses (single-nucleotide polymorphism detection, gene expression profiling, and splicing isoform detection) on a single electronic microarray was demonstrated using the ApoE and ApoER2 genes as a model system. RESULTS: Targets were detected after a 2-min hybridization reaction. With noncomplementary capture probes, no signal was detectable. Twofold changes in target concentration were detectable throughout the ( approximately 64-fold) range of concentrations tested. Levels of 10 targets were analyzed side by side across seven time points. By confining electronic activation to subsets of test sites, polymorphism detection, expression profiling, and splicing isoform analysis were performed on a single electronic microarray. CONCLUSIONS: Microelectronic array technology provides specific target detection and quantification with advantages over currently available methodologies for targeted gene expression profiling and combinatorial genomics testing.

Alternative Splicing↗

Functional analysis of HBV genomes from patients with fulminant hepatitis.

Two previous case reports suggest that hepatitis B virus (HBV) core promoter variants with a high replication competence contribute to the pathogenesis of fulminant hepatitis B (FHB). We recently found in HBV genomes from patients with FHB an accumulation of mutations within the core promoter region. Therefore, the aim of this study was to investigate the phenotype of these HBV variants. Replication competence and expression of hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) of viral genomes from seven patients with FHB and one patient with fulminant recurrent hepatitis after liver transplantation were analyzed by transfection experiments in human hepatoma cells. Compared with wild-type virus, the HBV variants from the seven patients with FHB produced similar or slightly lower levels of intracellular replicative intermediates and extracellular viral particles. In contrast, the HBV genomes from the patient with fulminant recurrent hepatitis synthesized and secreted significantly more HBV DNA. All genomes tested expressed similar or even higher levels of HBeAg compared with wild-type virus, except for those from four patients with a precore stop codon mutation in the respective dominant viral populations. The level of HBsAg produced by all variant genomes was similar or reduced compared with wild-type virus. These data indicate that in some cases HBV variants with enhanced replication competence and/or a defect in HBeAg expression may contribute to the development of FHB. However, neither phenotype is an essential prerequisite; thus, an additional role of other viral or host factors in the pathogenesis of FHB is suggested.

Base Sequence↗

CanVar-UK: A collaborative platform for germline interpretation in cancer susceptibility genes.

Germline variants in cancer susceptibility genes (CSGs) are typically inherited rather than arising de novo. Hence, wide cascade testing of families across geographies is common, meaning consistency in variant classification is particularly critical. Variant interpretation requires collation of variant-level data from diverse sources, as well as assembly of comprehensive clinical data, often necessitating sharing of information between genomic testing centers. Here, we describe CanVar-UK, a freely accessible web platform bespoke designed to support interpretation of germline CSG variants. CanVar-UK contains variant-level data for over 1.1 million single-nucleotide variants (SNVs), comprising all possible coding SNVs in 116 established CSGs. The data sources with which variants are annotated include in silico scores from 11 clinically relevant tools, population allele frequencies from gnomAD v4.1, case counts from multiple cohorts, including National Health Service (NHS) clinical laboratory testing, variant-level readouts from 47 selected functional and splicing datasets across 19 CSGs, genetic epidemiology studies, and live linkage to existing consensus classifications in the ClinVar database. The diagnostic discussion forum is only available to registered diagnostic scientist users. Through this, a variant-tagged email message can be dispatched in real time across the diagnostic forum community of >1,500 users, with all exchanges and classifications captured and stored in the platform. Already widely used by NHS diagnostic clinical scientists in the UK, CanVar-UK has a rapidly growing international diagnostic user base (>800 UK and >600 non-UK registered users). Survey of the NHS diagnostic user community illustrates the wide-ranging utility of CanVar-UK within their clinical workflows for interpretation of germline CSG variants.

Journal Article↗

Contributions of public health to genetics education for health care professionals.

With growing knowledge about the role of genetics in health, genetics education for health care professionals has taken on increasing importance. Many efforts are under way to develop new genetics curricula. Although such efforts are primarily the responsibility of health professional schools and professional societies, the public health system is an important stakeholder, and different sectors of public health have opportunities to enhance educational efforts. These include the development of authoritative information sources about the clinical utility of genetic susceptibility and pharmacogenetic tests, creation of networks that link professionals in underserved regions to educational materials and consultative backup, and sponsorship of forums for multidisciplinary discussion of controversial issues. Public health input can help to ensure an appropriate emphasis on health outcomes as new genomic tests and technologies come into use, thus helping to protect society from the social and medical costs of genetic tests with limited clinical value.

Genetic Predisposition to Disease↗

Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change.

BACKGROUND: Non-coding RNAs (ncRNAs) have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical screens. To advance biological knowledge, computational methods that can accurately detect ncRNAs in sequenced genomes are therefore desirable. The increasing number of genomic sequences provides a rich dataset for computational comparative sequence analysis and detection of novel ncRNAs. RESULTS: Here, Dynalign, a program for predicting secondary structures common to two RNA sequences on the basis of minimizing folding free energy change, is utilized as a computational ncRNA detection tool. The Dynalign-computed optimal total free energy change, which scores the structural alignment and the free energy change of folding into a common structure for two RNA sequences, is shown to be an effective measure for distinguishing ncRNA from randomized sequences. To make the classification as a ncRNA, the total free energy change of an input sequence pair can either be compared with the total free energy changes of a set of control sequence pairs, or be used in combination with sequence length and nucleotide frequencies as input to a classification support vector machine. The latter method is much faster, but slightly less sensitive at a given specificity. Additionally, the classification support vector machine method is shown to be sensitive and specific on genomic ncRNA screens of two different Escherichia coli and Salmonella typhi genome alignments, in which many ncRNAs are known. The Dynalign computational experiments are also compared with two other ncRNA detection programs, RNAz and QRNA. CONCLUSION: The Dynalign-based support vector machine method is more sensitive for known ncRNAs in the test genomic screens than RNAz and QRNA. Additionally, both Dynalign-based methods are more sensitive than RNAz and QRNA at low sequence pair identities. Dynalign can be used as a comparable or more accurate tool than RNAz or QRNA in genomic screens, especially for low-identity regions. Dynalign provides a method for discovering ncRNAs in sequenced genomes that other methods may not identify. Significant improvements in Dynalign runtime have also been achieved.

Algorithms↗

Translation of pharmacogenomics and pharmacogenetics: a regulatory perspective.

Pharmacogenomics and pharmacogenetics provide methodologies that can lead to DNA-based tests to improve drug selection, identify optimal dosing, maximize drug efficacy or minimize the risk of toxicity. Rapid advances in basic research have identified many opportunities for the development of 'personalized' treatments for individuals and/or subsets of patients defined by genetic and/or genomic tests. However, the integration of these tests into routine clinical practice remains a major multidisciplinary challenge, and even for well-established biomarkers there has been little progress. Here, we consider this challenge from a regulatory perspective, highlighting recent initiatives from the FDA that aim to facilitate the integration of pharmacogenetics and pharmacogenomics into drug development and clinical practice.

Drug Approval↗

Genomic and phenotypic characterization of Klebsiella pneumoniae phage KP Ø1: a novel lytic Slopekvirus targeting uropathogenic multidrug-resistant Klebsiella pneumoniae.

The rise of multidrug-resistant (MDR) uropathogenic gram-negative bacteria (GNB) necessitates the development of alternative therapeutic strategies. This study aimed to isolate, phenotypically characterize, and perform whole-genome sequencing of the bacteriophage demonstrating the broadest host range against MDR uropathogens. Fifty MDR GNB isolates were screened for lytic phages. The most promising candidate, Klebsiella pneumoniae phage KP Ø1, was characterized using plaque assay, Transmission Electron Microscopy (TEM), and pH/thermal stability testing. Genomic characterization was performed via whole-genome sequencing (WGS), with functional annotation and lifestyle prediction using PhaBOX and PhageScope software. Klebsiella pneumoniae was the most prevalent MDR uropathogen. Klebsiella pneumoniae phage KP Ø1 exhibited a 50% host range and high lytic titer (10⁸ PFU/mL). TEM revealed an icosahedral head and short contractile tail. Genomic characterization by WGS revealed that Klebsiella pneumoniae phage KP Ø1 possesses a 174,591 bp double-stranded deoxyribonucleic acid (dsDNA) genome containing 274 predicted open reading frames (ORFs). No lysogeny-related genes, toxins, or antibiotic resistance markers were detected, confirming its strictly lytic nature and supporting its potential as a candidate for phage therapy applications. The phage remained stable (10⁸ PFU/mL) across temperatures of - 20 °C to 50 °C; supporting its suitability for long-term biobanking and suggesting potential activity at physiological temperature, and across a pH range of 7-9. Klebsiella pneumoniae phage KP Ø1 is a novel, obligately lytic Slopekvirus whose genomic architecture, stability profile, and absence of lysogeny-associated, virulence, and antimicrobial resistance genes ( AMR) collectively support its candidacy for further preclinical evaluation as a phage therapy agent against uropathogenic MDR Klebsiella pneumoniae.

Klebsiella pneumoniae↗

A genetic signature can predict prognosis and response to therapy in breast cancer: Oncotype DX.

We now recognize that not all breast cancers are the same. Different characteristics in gene expression profiles result in differential clinical behavior. With the use of gene microarrays, different subtypes of breast cancer have been characterized. These subtypes include the basal, the ERBB2+, and the luminal A, B and C subtypes. The importance of these different subtypes lies in the fact that they differ in clinical outcome, with the basal and ERBB2+ subtypes having the worst prognosis and the luminal A group having the best prognosis. However, identification of these subtypes is still not clinically used. Other strategies for evaluating tumors in a clinical setting have been developed using smaller sets of genes. One such strategy is the 21-gene assay (Oncotype DX), which is currently in commercial use in the USA. One advantage of this test is the use of paraffin-embedded blocks instead of previous methods, which required fresh frozen tissue. Oncotype DX has been shown to predict 10-year distant recurrence in patients with estrogen receptor-positive, axillary lymph node-negative breast cancer. This genomic assay has also been shown to predict chemotherapy and endocrine therapy response. Large, prospective, randomized clinical trials are currently underway using this genomic test. Other similar tests are also finding their way in clinical practice. A 70-gene assay, which has been developed by a group in The Netherlands, is currently being used as a tool to assign treatment in women with early stage breast cancer. In the near future, clinical decisions will most likely be dictated by the genetic characteristics of the tumor, with the clinical characteristics becoming less important. Tailoring our treatment based on individual tumor characteristics will help us develop better therapeutic strategies and save many of our patients from receiving unnecessary toxic therapy.

Biomarkers, Tumor↗

A microsatellite-based genetic linkage map of the waterflea, Daphnia pulex: On the prospect of crustacean genomics.

We describe the first genetic linkage map for Daphnia pulex using 185 microsatellite markers, including 115 new markers reported in this study. Our approach was to study the segregation of polymorphisms in 129 F2 progeny of one F1 hybrid obtained by crossing two genetically divergent lineages of Daphnia isolated from two Oregon populations. The map spanned 1206 Kosambi cM and had an average intermarker distance of 7 cM. Linkage groups ranged in size from 7 to 185 cM and contained 4 to 27 markers. The map revealed 12 linkage groups corresponding to the expected number of chromosomes and covers approximately 87% of the genome. Tests for random segregation of alleles at individual loci revealed that 21% of the markers showed significant transmission ratio distortion (primarily homozygote deficiency) likely due to markers being linked to deleterious recessive alleles. This map will become the anchor for the physical map of the Daphnia genome and will serve as a starting point for mapping single and quantitative trait loci affecting ecologically important phenotypes. By mapping 342 tentative orthologous gene pairs (Daphnia/Drosophila) into the Daphnia linkage map, we facilitate future comparative projects.

Animals↗

Standardizing tests of mouse behavior: reasons, recommendations, and reality.

As more investigators with widely varying backgrounds enter the field of mouse behavioral genetics, there is a growing need to standardize some of the more popular tests because differences between laboratories in the details of behavioral testing and the pretesting environment can contribute to failures to replicate results of genetic experiments. It is argued here that we have sufficient knowledge to warrant a wise choice of a short list of standard strains and even details of apparatus and protocols for several kinds of behavioral tests. Equating the laboratory environment does not appear to be feasible. Instead, we need to learn what kinds of behavioral tests yield the most stable results in different labs and what kinds are most sensitive to the ubiquitous variations among test sites. Methods for making an informed choice of sample size for evaluating interactions between the laboratory environment and genotype are available and should be utilized in standardization trials. New resources for convenient sharing of data will greatly aid in collaborative and comparative studies involving several sites. Like the sequencing of an entire genome, test standardization is something that needs to be done only once if it is done properly, and the work will then benefit the field of behavioral and neural genetics for many years.

Animals↗

The meiotic behavior of some single-cistron mutants in the zeste-white region of the Drosophila melanogaster X chromosome.

There are two dosage sensitive sites in the zeste-white region of the Drosophila melanogaster X chromosome that affect meiotic chromosome behavior. Single-cistron mutants at essential and female fertility loci in the two segments have been tested for meiotic effects similar to those of deficiencies. None of the mutants have detectable meiotic effects. A de novo search for meiotic mutants in the region has not uncovered any, but the results suggest that a deficiency for the zeste-white region would be useful for detecting meiotic mutants elsewhere in the genome. Tests for interactions between the deficiency and known meiotic mutants support this. Though tentative, these results suggest that non-essential regions need not be devoid of function.

Animals↗

Reliability of transmembrane predictions in whole-genome data.

Transmembrane prediction methods are generally benchmarked on a set of proteins with experimentally verified topology. We have investigated if the accuracy measured on such datasets can be expected in an unbiased genomic analysis, or if there is a bias towards 'easily predictable' proteins in the benchmark datasets. As a measurement of accuracy, the concordance of the results from five different prediction methods was used (TMHMM, PHD, HMMTOP, MEMSAT, and TOPPRED). The benchmark dataset showed significantly higher levels (up to five times) of agreement between different methods than in 10 tested genomes. We have also analyzed which programs are most prone to make mispredictions by measuring the frequency of one-out-of-five disagreeing predictions.

Algorithms↗

Examining gaps in institutional policies for clinical genomic data sharing: A cross-jurisdictional study.

The sharing of data generated by clinical genetic and genomic testing without explicit consent is important for timely diagnosis and treatment. While many jurisdictions permit the sharing of identifiable data for direct clinical care, institutional policies vary in how clearly they specify key elements, including when sharing is permitted, what data are covered, and what safeguards apply. Greater clarity around these elements may support responsible data sharing while balancing timely care with transparency and appropriate protections. We conducted a mixed-methods content analysis of data-sharing and privacy policies from 33 clinical genomic institutions across 17 countries and regions. Using a predefined analytical framework, we assessed how policies document key governance elements relevant to sharing without explicit consent. Two independent reviewers extracted information about clinical contexts, data types, justifications, and protections. Although 70% of institutions described circumstances permitting data sharing without explicit consent, most policies did not clearly define the scope or governance of such sharing. Policies also rarely distinguished clinical from research or secondary use and inconsistently specified privacy and security safeguards. While sharing was commonly justified for clinical care (78.3%) or testing services (43.5%), data recipient roles and onward-sharing expectations were often left undefined. This uneven documentation could make it difficult for clinical teams and institutional decision-makers to identify and justify decisions about what is permitted and under what conditions. A guidance framework specifying core governance elements and corresponding protections could help institutions communicate their governance choices more clearly and support comparable baseline practices for responsible data sharing.

Information Dissemination↗

End-sequence profiling: sequence-based analysis of aberrant genomes.

Genome rearrangements are important in evolution, cancer, and other diseases. Precise mapping of the rearrangements is essential for identification of the involved genes, and many techniques have been developed for this purpose. We show here that end-sequence profiling (ESP) is particularly well suited to this purpose. ESP is accomplished by constructing a bacterial artificial chromosome (BAC) library from a test genome, measuring BAC end sequences, and mapping end-sequence pairs onto the normal genome sequence. Plots of BAC end-sequences density identify copy number abnormalities at high resolution. BACs spanning structural aberrations have end pairs that map abnormally far apart on the normal genome sequence. These pairs can then be sequenced to determine the involved genes and breakpoint sequences. ESP analysis of the breast cancer cell line MCF-7 demonstrated its utility for analysis of complex genomes. End sequencing of approximately 8,000 clones (0.37-fold haploid genome clonal coverage) produced a comprehensive genome copy number map of the MCF-7 genome at better than 300-kb resolution and identified 381 genome breakpoints, a subset of which was verified by fluorescence in situ hybridization mapping and sequencing.

Animals↗