Genomes for medicine

A comprehensive workflow of mass spectrometry-based untargeted metabolomics in cancer metabolic biomarker discovery using human plasma and urine

Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC-LC), reversed-phase liquid chromatography (RP-LC), and gas chromatography (GC). All three techniques are coupled to a mass spectrometer (MS) in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM) and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

Personalised medicine: a critique on the future of health care

In recent years we have seen the emergence of "personalised medicine." This development can be seen as the logical product of reductionism in medical science in which disease is increasingly understood in molecular terms. Personalised medicine has flourished as a consequence of the application of neoliberal principles to health care, whereby a commercial and social need for personalised medicine has been created. More specifically, personalised medicine benefits from the ongoing commercialisation of the body and of genetic knowledge, the idea that health is defined by genetics, and the emphasis the state places on individual citizens as being "responsible for" their own health. In this paper I critique the emergence of personalised medicine by examining the ways in which it has already impacted upon health and health care delivery.

DNA characterization by transverse electrical current in a nanochannel

We review an approach for the characterization of single-stranded DNA based on the statistical identification of single bases via transverse electronic transport while DNA translocates in a nanopore or nanochannel. We describe the theoretical methods used to demonstrate this method for experimentally realizable systems and discuss the different physical processes involved. Recent experimental reports have shown the validity of this approach, although further work is necessary to make this a practical fast sequencing tool.

Human cancer classification: a systems biology- based model integrating morphology, cancer stem cells, proteomics, and genomics

Human cancer classification is currently based on the idea of cell of origin, light and electron microscopic attributes of the cancer. What is not yet integrated into cancer classification are the functional attributes of these cancer cells. Recent innovative techniques in biology have provided a wealth of information on the genomic, transcriptomic and proteomic changes in cancer cells. The emergence of the concept of cancer stem cells needs to be included in a classification model to capture the known attributes of cancer stem cells and their potential contribution to treatment response, and metastases. The integrated model of cancer classification presented here incorporates all morphology, cancer stem cell contributions, genetic, and functional attributes of cancer. Integrated cancer classification models could eliminate the unclassifiable cancers as used in current classifications. Future cancer treatment may be advanced by using an integrated model of cancer classification.

The confluence of human genomics, environment, and determinants of health-related quality of life among African American hemodialysis patients

The intersection of human genome sequencing, environmental factors that lend to further understanding of the etiology of complex diseases, and components that constitute the health-related quality of life for African American hemodialysis patients are explored in this article. There are many renal diseases that have genetic components. Even though genetic polymorphisms and allelic variations can explain some of the etiology and disparities in disease susceptibility for African Americans, the role of the environment must also be considered. For African American hemodialysis patients, the environmental influences of religiosity and social support, along with genetic factors, affect their health-related quality of life. A study of 176 African American hemodialysis patients revealed that religiosity and social support had a significant impact on patient's health-related quality of life. Implications of the study mandate that social and behavioral researchers, who tend to focus on environmental issues, be given more freedom and latitude, along with genetic researchers, in designing and implementing studies involving genomic sequencing and the influence on health disparities among persons of African descent.

Newborn Screening and Genetic Testing

New screening techniques and diagnostic tests for genetic diseases available for newborn screening can provide information about many diseases long before they are clinically detected. However, this information creates complex questions and ethical dilemmas regarding which newborns should be tested, when testing should occur, availability and costs of tests, and how families should be counseled. There is no national policy regarding newborn screening, which leads to great variation among states' newborn screening programs. This article reviews newborn genetic testing and provides a blueprint for clinicians to improve practice by incorporating into their care knowledge of new developments in newborn testing and screening.

Individualized pain medicine

Since the first draft of the human genome was published 10 years ago, scientists have tried to develop new treatment strategies for various types of diseases based on individual genomes. It is called personalized (or individualized) medicine and is expected to increase efficacy and reduce adverse reactions of drugs. Much progress has been made with newly developed technologies, though individualized pain medicine is still far from realization. Efforts on the integrative genomic analyses along with understandings of interactions between other related factors such as environment will eventually translate complex genomic information into individualized pain medicine.

DNA fragmentation-based combinatorial approaches to soluble protein expression Part I. Generating DNA fragment libraries

In addressing a new drug discovery target, the generation of tractable protein substrates for functional and structural analyses can represent a significant hurdle. Traditional approaches rely on protein expression trials of multiple variants in various systems, frequently with limited success. The increasing knowledge base derived from genomics and structural proteomics initiatives assists the bioinformatics-led design of these experiments. Nevertheless, for many eukaryotic polypeptides, particularly those with relatively few homologues, the generation of useful protein products can still be a major challenge. This review describes the basis of efforts to forge an alternative 'domain-hunting' paradigm, based upon combinatorial sampling of expression construct libraries derived by fragmentation of the encoding DNA template, namely the methods and considerations in generating fragment length DNA from target genes. An accompanying review focuses upon the expression screening of such combinatorial DNA libraries for the sampling of the corresponding set of protein fragments.

Increased single-nucleotide discrimination in allele-specific polymerase chain reactions through primer probes bearing nucleobase and 2'-deoxyribose modifications

The diagnosis of genetic dissimilarities between individuals is becoming increasingly important due to the discovery that these variations are related to complex phenotypes like the predisposition to certain diseases or compatibility with drugs. The most common among these sequence variations are single-nucleotide polymorphisms (SNPs). The availability of reliable and efficient methods for the interrogation of the respective genotypes is the basis for any progress along these lines. Many methods for the detection of nucleotide variations in genes exist, in which amplification of the target gene is required before analysis can take place. The allele-specific polymerase chain reaction (asPCR) combines target amplification and analysis in a single step. The principle of asPCR is based on the formation of matched or mismatched primer-target complexes. The most important parameter in asPCR is the discrimination of these matched or mismatched pairs. In recent publications we have shown that the reliability of SNP detection through asPCR is increased by employing chemically modified primer probes. In particular, primer probes that bear a polar 4'-C-methoxymethylene residue at the 3' end have superior properties in discriminating single-nucleotide variations by PCR. Here we describe the synthesis of several primer probes that bear nucleobase modifications in addition to the 4'-C-methoxymethylenated 2'-deoxyriboses. We studied the effects of these alterations on single-nucleotide discrimination in allele-specific PCR promoted by a DNA polymerase and completed these results with single-nucleotide-incorporation kinetic studies. Moreover, we investigated thermal denaturing of the primer-probe-template complexes and recorded circular dichroism (CD) spectra for inspecting the thermodynamic and photophysical duplex behaviour of the introduced modifications. In short, we found that primer probes bearing a 4'-C-methoxymethylene residue at the 2'-deoxyribose moiety in combination with a thiolated thymidine moiety have synergistic effects and display significantly increased discrimination properties in asPCR.

Clinical laboratory reports in molecular pathology

CONTEXT

Molecular pathology is a rapidly growing area of laboratory medicine in which DNA and RNA are analyzed. The recent introduction of array technology has added another layer of complexity involving massive parallel analysis of multiple genes, transcripts, or proteins.

OBJECTIVE

As molecular technologies are increasingly implemented in clinical settings, it is important to bring uniformity to the way that test results are reported.

DATA SOURCES

The College of American Pathologists Molecular Pathology Resource Committee members summarize elements that are already common to virtually all molecular pathology reports, as set forth in the College of American Pathologists checklists used in the laboratory accreditation process. Consensus recommendations are proposed to improve report format and content, and areas of controversy are discussed. Resources are cited that promote use of proper gene nomenclature and that describe methods for reporting mutations, translocations, microsatellite instability, and other genetic alterations related to inherited disease, cancer, identity testing, microbiology, and pharmacogenetics.

CONCLUSIONS

These resources and recommendations provide a framework for composing patient reports to convey molecular test results and their clinical significance to members of the health care team.

LightTyper platform for high-throughput clinical genotyping

DNA sequence variations due to single nucleotide changes or polymorphisms (SNPs) have demonstrated an association with certain diseases as causative agents or surrogate biomarkers. Identification and genotyping of SNPs requires reliable and robust technologies. Multiple genotyping platforms are available to detect SNPs. Although many of these platforms meet the requirements of the research environment, technologies have also emerged for high-throughput clinical genotyping as well. The LightTyper is one such platform, providing SNP identification by employing melting curve analysis of fluorescently labeled probes. The LightTyper has been used to identify SNPs associated with myocardial infarction, developing and validating assays for approximately 100 SNPs in 30 candidate genes. The LightTyper is also amenable to the use of assays already developed for the LightCycler, which is widely used in clinical laboratories. The initial experience presented here suggests the potential use of the LightTyper for high-throughput clinical genotyping.

Increased single nucleotide discrimination in arrayed primer elongation by 4'C-modified primer probes

Herein we describe the beneficial impact of immobilized 4'C-modified primer probes on detecting single nucleotide variations in arrayed primer extension by a DNA polymerase.

Strategy Considerations in Genome Cohort Construction in Korea

Focusing on complex diseases of public health significance, strategic issues regarding the on-going Korean Genome Cohort were reviewed: target size and diseases, measurements, study design issues, and followup strategy of the cohort. Considering the epidemiologic characteristics of Korean population as well as strengths and drawbacks of current research environment, we tried to tailor the experience of other existing cohorts into proposals for this Korean study. Currently 100,000 individuals have been participating the new Genome Cohort in Korea. Target size of de novo collection is recommended to be set as between 300,000 to 500,000. This target size would allow acceptable power to detect genetic and environmental factors of moderate effect size and possible interactions between them. Family units and/or special subgroups are recommended to parallel main body of adult individuals to increase the overall efficiency of the study. Given that response rate to the conventional re-contact method may not be satisfactory, successful follow-up is the main key to the achievement of the Korean Genome Cohort. Access to the central database such as National Health Insurance data can provide enormous potential for near-complete case detection. Efforts to build consensus amongst scientists from broad fields and stakeholders are crucial to unleash the centralized database as well as to refine the commitment of this national project.

Sequencing the whole genome of infected human cells obtained from diseased patients--a proposed strategy for understanding and overcoming AIDS or other deadest virus-infected diseases

As the worry and pandemic about deadest virus such as AIDS and bird flu are intensified, eradical treatments for these virus-infected diseases are in high demand. However we currently know little about the virus involvement in human cells, which results poor therapeutic outcome. We propose that these viruses may penetrate into human genome in diseased cells that may finally result resistance to present applicable therapeutic options. Here proposes a strategy – sequence the whole genome (chromosomal as well as other genetic systems) of infected human cells obtained from diseased patients. This might help us to know greatly more about the consequences of virus infection and achieve biotherapy of specifically targeted in future.

Tuning single nucleotide discrimination in polymerase chain reactions (PCRs): synthesis of primer probes bearing polar 4'-C-modifications and their application in allele-specific PCR

There are many methods available for the detection of nucleotide variations in genetic material. Most of these methods are applied after amplification of the target genome sequence by the polymerase chain reaction (PCR). Many efforts are currently underway to develop techniques that can detect single nucleotide variations in genes either by means of, or without the need for, PCR. Allele-specific PCR (asPCR), which reports nucleotide variations based on either the presence or absence of a PCR-amplified DNA product, has the potential to combine target amplification and analysis in one single step. The principle of asPCR is based on the formation of matched or mismatched primer-target complexes by using allele-specific primer probes. PCR amplification by a DNA polymerase from matched 3'-primer termini proceeds, whereas a mismatch should obviate amplification. Given the recent advancements in real-time PCR, this technique should, in principle, allow single nucleotide variations to be detected online. However, this method is hampered by low selectivity, which necessitates tedious and costly manipulations. Recently, we reported that the selectivity of asPCR can be significantly increased through the employment of chemically modified primer probes. Here we report further significant advances in this area. We describe the synthesis of various primer probes that bear polar 4'-C-modified nucleotide residues at their 3' termini, and their evaluation in real-time asPCR. We found that primer probes bearing a 4'-C-methoxymethylene modification have superior properties in the discrimination of single nucleotide variations by PCR.

Genetic polymorphisms in monoamine neurotransmitter systems show only weak association with acute post-surgical pain in humans

Background

Candidate gene studies on the basis of biological hypotheses have been a practical approach to identify relevant genetic variation in complex traits. Based on previous reports and the roles in pain pathways, we have examined the effects of variations of loci in the genes of monoamine neurotransmitter systems including metabolizing enzymes, receptors and transporters on acute clinical pain responses in humans.

Results

Variations in the catecholamine metabolizing enzyme genes (MAOA and COMT) showed significant associations with the maximum post-operative pain rating while the serotonin transporter gene (SLC6A4) showed association with the onset time of post-operative pain. Analgesic onset time after medication was significantly associated with the norepinephrine transporter gene (SLC6A2). However, the association between COMT genetic variation and pain sensitivity in our study differ from previous studies with small sample sizes, population stratification and pain phenotype derived from combining different types of pain stimuli. Correcting for multiple comparisons did not sustain these genetic associations between monoamine neurotransmitter systems and pain sensitivity even in this large and homogeneous sample.

Conclusion

These results suggest that the previously reported associations between genetic polymorphisms in the monoamine neurotransmitter systems and the interindividual variability in pain responses cannot be replicated in a clinically relevant pain phenotype.

microRNAs exhibit high frequency genomic alterations in human cancer

MicroRNAs (miRNAs) are endogenous noncoding RNAs, which negatively regulate gene expression. To determine genomewide miRNA DNA copy number abnormalities in cancer, 283 known human miRNA genes were analyzed by high-resolution array-based comparative genomic hybridization in 227 human ovarian cancer, breast cancer, and melanoma specimens. A high proportion of genomic loci containing miRNA genes exhibited DNA copy number alterations in ovarian cancer (37.1%), breast cancer (72.8%), and melanoma (85.9%), where copy number alterations observed in >15% tumors were considered significant for each miRNA gene. We identified 41 miRNA genes with gene copy number changes that were shared among the three cancer types (26 with gains and 15 with losses) as well as miRNA genes with copy number changes that were unique to each tumor type. Importantly, we show that miRNA copy changes correlate with miRNA expression. Finally, we identified high frequency copy number abnormalities of Dicer1, Argonaute2, and other miRNA-associated genes in breast and ovarian cancer as well as melanoma. These findings support the notion that copy number alterations of miRNAs and their regulatory genes are highly prevalent in cancer and may account partly for the frequent miRNA gene deregulation reported in several tumor types.

Genetic profiling of newborns: ethical and social issues

Identifying genetic factors that could reliably predict health risks for individuals has the potential to bring great health benefits, both for the individuals concerned and for health-care providers. Genetic profiling at birth would allow a person's genome to be analysed at an early stage, and the data electronically stored for future use. However, although this might seem like an attractive proposition, it carries with it serious ethical and social concerns that would need to be addressed if the genetic profiling of newborns were ever to be considered on a population-wide basis.

Genomic medicine: genetic variation and its impact on the future of health care

Advances in genome technology and other fruits of the Human Genome Project are playing a growing role in the delivery of health care. With the development of new technologies and opportunities for large-scale analysis of the genome, transcriptome, proteome and metabolome, the genome sciences are poised to have a profound impact on clinical medicine. Cancer prognostics will be among the first major test cases for a genomic medicine paradigm, given that all cancer is caused by genomic instability, and microarrays allow assessment of patients' entire expressed genomes. Analysis of breast cancer patients' expression patterns can already be highly correlated with recurrence risks. By integrating clinical data with gene expression profiles, imaging, metabolomic profiles and proteomic data, the prospect for developing truly individualized care becomes ever more real. Notwithstanding these promises, daunting challenges remain for genomic medicine. Success will require planning robust prospective trials, analysing health care economic and outcome data, assuaging insurance and privacy concerns, developing health delivery models that are commercially viable and scaling up to meet the needs of the whole population.

Genetic epidemiology of diabetes

Conventional genetic analysis focuses on the genes that account for specific phenotypes, while traditional epidemiology is more concerned with the environmental causes and risk factors related to traits. Genetic epidemiology is an alliance of the 2 fields that focuses on both genetics, including allelic variants in different populations, and environment, in order to explain exactly how genes convey effects in different environmental contexts and to arrive at a more complete comprehension of the etiology of complex traits. In this review, we discuss the epidemiology of diabetes and the current understanding of the genetic bases of obesity and diabetes and provide suggestions for accelerated accumulation of clinically useful genetic information.

DNA sequencing by indexer walking

BACKGROUND

There is a need for DNA sequencing methods that are faster, more accurate, and less expensive than existing techniques. Here we present a new method for DNA analysis by means of indexer walking.

METHODS

For DNA sequencing by indexer walking, we ligated double-stranded synthetic oligonucleotides (indexers) to DNA fragments that were produced by type IIS restriction endonucleases, which generate nonidentical 4-nucleotide 5' overhangs. The subsequent amplification (30 thermal cycles) of indexed DNA provided a template for automated DNA sequencing with fluorescent dideoxy terminators. The data gathered in the first sequencing reaction permitted further movement into the unknown nucleotide sequence by digestion of analyzed DNA with selected type IIS restriction endonuclease followed by ligation of the next indexer. A library of presynthesized indexers consisting of 256 oligonucleotides was used for bidirectional analysis of DNA molecules and provided universal primers for sequencing.

RESULTS

The proposed protocol was successfully applied to sequencing of cryptic plasmids isolated from pathogenic strains of Escherichia coli. The overall error rate for base-calling was 0.5%, with a mean read length of 550 nucleotides. Approximately 1000 nucleotides of high-quality sequence could be obtained per day from a single clone.

CONCLUSIONS

Indexer walking can be used as a low-cost procedure for nucleotide sequence determination of DNA molecules, such as natural plasmids, cDNA clones, and longer DNA fragments. It can also serve as an alternative method for gap filling at the final stage of genome sequencing projects.

The search for genenotype/phenotype associations and the phenome scan

All the approaches to the search for genotype/phenotype associations have their share of problems. Comparing the genome scan and candidate gene approaches, the former makes fewer assumptions at the genetic level or about mechanism but has greater statistical difficulties while the latter partially solves the statistical problem but makes more assumptions at both genetic and mechanistic levels. Among current difficulties is a lack of information about the nature of gene variant/phenotype associations: the frequency with which different classes of gene or sequence are involved; the type of genetic variation most commonly involved; the appropriate genetic models to apply to analysis. The overarching problem is that of multiple testing, one solution to which is to integrate genetic information to create a smaller number of compound variables. At the other end of the scale, decisions about the level of complexity at which to pitch the identification of phenotypes also affect the multiple testing problem: whether to pitch them at the level of disease outcomes, or at any of the multiple levels of intermediate phenotypes or traits. The third issue is how best to deal with gene/gene or gene/environment interactions, or whether to ignore them. Only as more genotype/phenotype associations emerge, by whatever means, will the numbers of results allow these questions to be answered. We describe here a new approach to genotype/phenotype association studies, the phenome scan, in which dense phenotypic information in human cohorts is scanned for associations with individual genetic variants. We believe that this approach can generate data that will be useful in answering generic questions about genotype/phenotype associations as well as in discovering novel ones.

Pharmacogenomics and the drug discovery pipeline: when should it be implemented?

One of the key factors in developing improved medicines lies in understanding the molecular basis of the complex diseases we treat. Investigation of genetic associations with disease utilizing advances in linkage disequilibrium-based whole genome association strategies will provide novel targets for therapy and define relevant pathways contributing to disease pathogenesis. Genetic studies in conjunction with gene expression, proteomic, and metabonomic analyses provide a powerful tool to identify molecular subtypes of disease. Using these molecular data, pharmacogenomics has the potential to impact on the drug discovery and development process at many stages of the pipeline, contributing to both target identification and increased confidence in the therapeutic rationale. This is exemplified by the identified association of 5-lipoxygenase-activating protein (ALOX5AP/FLAP) with increased risk of myocardial infarction, and of the chemokine receptor 5 (CCR5) with HIV infection and therapy. Pharmacogenomics has already been used in oncology to demonstrate that molecular data facilitates assessment of disease heterogeneity, and thus identification of molecular markers of response to drugs such as imatinib mesylate (Gleevec) and trastuzumab (Herceptin). Knowledge of genetic variation in a target allows early assessment of the clinical significance of polymorphism through the appropriate design of preclinical studies and use of relevant animal models. A focussed pharmacogenomic strategy at the preclinical phase of drug development will produce data to inform the pharmacogenomic plan for exploratory and full development of compounds. Opportunities post-approval show the value of large well-characterized data sets for a systematic assessment of the contribution of genetic determinants to adverse drug reactions and efficacy. The availability of genomic samples in large phase IV trials also provides a valuable resource for further understanding the molecular basis of disease heterogeneity, providing data that feeds back into the drug discovery process in target identification and validation for the next generation of improved medicines.

Neurogenetics II: complex disorders

The genetic analysis of common neurological disorders will be a difficult and protracted endeavour. Genetics is only one of many disciplines that will be required but it has already thrown considerable light on the aetiology of several major neurological disorders through the analysis of rare inherited subgroups. The identification of individual susceptibility genes with variants of smaller effect will be more difficult but there is no sharp demarcation between large and small genetic effects, so that many new and important insights will emerge using existing and new technologies. The availability of improved neuroimaging, better animal models of disease and new genetic tools, such as high-throughput gene chips, expression microarrays and proteomics, are extending the range of traditional genetic mapping tools. Finally, an understanding of the genetic and epigenetic mechanisms that restrain the differentiation and integration of human neural stem cells into mature neuronal networks could have a major impact on clinical practice. These approaches will be illustrated in the context of Alzheimer disease, Parkinson disease and synucleinopathies, tauopathies, amyotrophic lateral sclerosis and stroke.

Systems biology: new approaches to old environmental health problems

The environment plays a pivotal role as a human health determinant and presence of hazardous pollutants in the environment is often implicated in human disease. That pollutants cause human diseases however is often controversial because data connecting exposure to environmental hazards and human diseases are not well defined, except for some cancers and syndromes such as asthma. Understanding the complex nature of human-environment interactions and the role they play in determining the state of human health is one of the more compelling problems in public health. We are becoming more aware that the reductionist approach promulgated by current methods has not, and will not yield answers to the broad questions of population health risk analysis. If substantive applications of environment-gene interactions are to be made, it is important to move to a systems level approach, to take advantage of epidemiology and molecular genomic advances. Systems biology is the integration of genomics, transcriptomics, proteomics, and metabolomics together with computer technology approaches to elucidate environmentally caused disease in humans. We discuss the applications of environmental systems biology as a route to solution of environmental health problems.

Social science and a post-genomic future: alternative readings of genomic agency

This paper explores competing discourses that envision different socio-technical landscapes opened up by the completion of the map of the human genome in 2003. It examines the ways in which the map, and it organising principle and very rationale--the gene as the sole or prime agent through which to understand the body and its disordering (as disease)--has been interpreted in quite distinct ways. It suggests how the sequences of a genomic map have post-genomic con-sequences that depend on a social rather than simply biological reading of genomic agency. Various accounts of the map and genetic agency or [sic] described, within science, science policy and social science, especially across science and technology studies (STS). The paper concludes with a comparative summary of these positions and asks whether a deconstructive reading of genomic agency by STS analysts might be the basis for a critical re-constructive engagement with post-genomic policy discourse that avoids the over-determination of agency one often finds in the latter.

Breast cancer: integrating the patient with her genome

Increasingly, gene expression data are becoming the currency of the realm in assessing disease prognosis. This has been especially evident in cancer, particularly those malignancies for which tumor samples are fairly accessible and understanding prognostic factors has clear implications for treatment decisions. Recently, Pittman et al. demonstrated substantially increased accuracy of personalized disease outcome prediction in breast cancer by integrating gene-expression profile data with traditional clinical risk factors in a set of 158 breast cancer patients.

Megabase deletions of gene deserts result in viable mice

The functional importance of the roughly 98% of mammalian genomes not corresponding to protein coding sequences remains largely undetermined. Here we show that some large-scale deletions of the non-coding DNA referred to as gene deserts can be well tolerated by an organism. We deleted two large non-coding intervals, 1,511 kilobases and 845 kilobases in length, from the mouse genome. Viable mice homozygous for the deletions were generated and were indistinguishable from wild-type littermates with regard to morphology, reproductive fitness, growth, longevity and a variety of parameters assaying general homeostasis. Further detailed analysis of the expression of multiple genes bracketing the deletions revealed only minor expression differences in homozygous deletion and wild-type mice. Together, the two deleted segments harbour 1,243 non-coding sequences conserved between humans and rodents (more than 100 base pairs, 70% identity). Some of the deleted sequences might encode for functions unidentified in our screen; nonetheless, these studies further support the existence of potentially 'disposable DNA' in the genomes of mammals.