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CasKAS: direct profiling of genome-wide dCas9 and Cas9 specificity using ssDNA mapping.

Detecting and mitigating off-target activity is critical to the practical application of CRISPR-mediated genome and epigenome editing. While numerous methods have been developed to map Cas9 binding specificity genome-wide, they are generally time-consuming and/or expensive, and not applicable to catalytically dead CRISPR enzymes. We have developed CasKAS, a rapid, inexpensive, and facile assay for identifying off-target CRISPR enzyme binding and cleavage by chemically mapping the unwound single-stranded DNA structures formed upon binding of a sgRNA-loaded Cas9 protein. We demonstrate this method in both in vitro and in vivo contexts.

CRISPR-Cas Systems↗

Expressed genome molecular signatures of heart failure.

Traditional gene expression studies typically focus on one or a few genes of interest. An important limitation of single-gene studies is that they present a portrait of disease that is essentially static. However, disease is a dynamic process, driven by a combination of genetic, epigenetic and environmental factors. Recently, genomic technologies have permitted better characterization of the dynamic aspect of disease progression. Genome-wide expression profiles of cardiovascular diseases, heart failure in particular, using microarrays have been published and are providing new insights into this complex disease. Tissue biopsies required for traditional microarray studies, however, are often invasive and not readily available. By contrast, blood samples are relatively non-invasive and are readily available. In a number of recent studies, blood cells appear to be a viable substitute for tissue biopsy. Blood cells have the ability to mirror the body's tissues and organs in health and disease; thus, we hypothesize that blood cells can indicate at the molecular level the presence of disease. Here we review microarray gene expression profiling of blood RNA for a number of different diseases. Sieving through gene expression molecular signatures has identified groups of genes characteristic of each and has identified biomarkers associated with specific diseases.

Expressed Sequence Tags↗

Functional genomics approaches to understanding brain disorders.

The completed draft of the human genome sequence has facilitated a revolution in neuroscience research. This sequence information and the development of new technologies used to analyze gene expression on a genomic scale provides a new and powerful means to investigate brain disorders of unknown etiology and to isolate novel drug targets for these disorders. The term functional genomics broadly describes a set of technologies and strategies directed at the problem of determining the function of genes, and understanding how the genome works together to generate whole patterns of biological function. The most powerful of these functional genomics approaches, expression profiling or DNA microarrays, can be used to analyze the expression of thousands of genes simultaneously. The results to date from the application of DNA microarray methods to postmortem diseased human brain tissue, animal models and cell culture models of brain disorders provide an exciting glimpse into the future of this field.

Animals↗

Early embryonic death-associated changes in genome-wide gene expression profiles in the fetal placenta of the cow carrying somatic nuclear-derived cloned embryo.

Successful somatic nuclear transfer-derived cloning has been reported in cattle; however, the cloned embryo is highly susceptible to death around day 60 of gestation leading to early embryonic loss. The early embryonic death is postulated to possibly arise in part from an atypical placentation. We have performed cDNA macroarray analysis using 3,353 of the previously cataloged 4,165 genes, in order to characterize the early embryonic death-associated changes in genome-wide gene expression profiles in the fetal placenta of the cow carrying somatic nuclear transfer-derived cloned embryo. A more marked difference in the expression profiles was observed between the fetal placentas of the cows with the cloned immotile embryo (CD) and with the cloned motile embryo (CL) or artificial insemination-derived motile embryo (AI), as compared to between the CL and AI placentas, suggesting an aberration of the expression profile in the CD placenta among the three placentas. Further, 291 and 77 genes showed more than twofold elevation and less than 50% reduction, respectively, in either or both of two CD (CD1 and CD2) placentas in comparison with the CL placenta, but no differential expression between the CL and AI placentas. The expression patterns of six genes in the AI, CL, and CD placentas were confirmed in an experiment with an additional sample for each of the three placentas. Among the placental genes showing the early embryonic death-associated changes of expression in the cow with the cloned embryo, IGF2 (elevated gene), and HBA1, HBA2, SPTB, and SPTBN1 genes (reduced gene) are intriguing in that the changes of expression in these genes were observed in an additional sample of CD placenta as well as the CD1 and CD2 placentas, and in that overexpression (for IGF2) and dysfunction or deficiency (for HBA1, HBA2, SPTB, and SPTBN1) result in embryonic lethality.

Animals↗

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles.

UNLABELLED: Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html SUPPLEMENTARY INFORMATION: http://www.chip.org/~ge/gedihome.html

Algorithms↗

Genetic variability in MCF-7 sublines: evidence of rapid genomic and RNA expression profile modifications.

BACKGROUND: Both phenotypic and cytogenetic variability have been reported for clones of breast carcinoma cell lines but have not been comprehensively studied. Despite this, cell lines such as MCF-7 cells are extensively used as model systems. METHODS: In this work we documented, using CGH and RNA expression profiles, the genetic variability at the genomic and RNA expression levels of MCF-7 cells of different origins. Eight MCF-7 sublines collected from different sources were studied as well as 3 subclones isolated from one of the sublines by limit dilution. RESULTS: MCF-7 sublines showed important differences in copy number alteration (CNA) profiles. Overall numbers of events ranged from 28 to 41. Involved chromosomal regions varied greatly from a subline to another. A total of 62 chromosomal regions were affected by either gains or losses in the 11 sublines studied. We performed a phylogenetic analysis of CGH profiles using maximum parsimony in order to reconstruct the putative filiation of the 11 MCF-7 sublines. The phylogenetic tree obtained showed that the MCF-7 clade was characterized by a restricted set of 8 CNAs and that the most divergent subline occupied the position closest to the common ancestor. Expression profiles of 8 MCF-7 sublines were analyzed along with those of 19 unrelated breast cancer cell lines using home made cDNA arrays comprising 720 genes. Hierarchical clustering analysis of the expression data showed that 7/8 MCF-7 sublines were grouped forming a cluster while the remaining subline clustered with unrelated breast cancer cell lines. These data thus showed that MCF-7 sublines differed at both the genomic and phenotypic levels. CONCLUSIONS: The analysis of CGH profiles of the parent subline and its three subclones supported the heteroclonal nature of MCF-7 cells. This strongly suggested that the genetic plasticity of MCF-7 cells was related to their intrinsic capacity to generate clonal heterogeneity. We propose that MCF-7, and possibly the breast tumor it was derived from, evolved in a node like pattern, rather than according to a linear progression model. Due to their capacity to undergo rapid genetic changes MCF-7 cells could represent an interesting model for genetic evolution of breast tumors.

Breast Neoplasms↗

Sister grouping of chimpanzees and humans as revealed by genome-wide phylogenetic analysis of brain gene expression profiles.

Gene expression profiles from the anterior cingulate cortex (ACC) of human, chimpanzee, gorilla, and macaque samples provide clues about genetic regulatory changes in human and other catarrhine primate brains. The ACC, a cerebral neocortical region, has human-specific histological features. Physiologically, an individual's ACC displays increased activity during that individual's performance of cognitive tasks. Of approximately 45,000 probe sets on microarray chips representing transcripts of all or most human genes, approximately 16,000 were commonly detected in human ACC samples and comparable numbers, 14,000-15,000, in gorilla and chimpanzee ACC samples. Phylogenetic results obtained from gene expression profiles contradict the traditional expectation that the non-human African apes (i.e., chimpanzee and gorilla) should be more like each other than either should be like humans. Instead, the chimpanzee ACC profiles are more like the human than like the gorilla; these profiles demonstrate that chimpanzees are the sister group of humans. Moreover, for those unambiguous expression changes mapping to important biological processes and molecular functions that statistically are significantly represented in the data, the chimpanzee clade shows at least as much apparent regulatory evolution as does the human clade. Among important changes in the ancestry of both humans and chimpanzees, but to a greater extent in humans, are the up-regulated expression profiles of aerobic energy metabolism genes and neuronal function-related genes, suggesting that increased neuronal activity required increased supplies of energy.

Animals↗

Global transcriptional and physiological responses of Saccharomyces cerevisiae to ammonium, L-alanine, or L-glutamine limitation.

The yeast Saccharomyces cerevisiae encounters a range of nitrogen sources at various concentrations in its environment. The impact of these two parameters on transcription and metabolism was studied by growing S. cerevisiae in chemostat cultures with l-glutamine, l-alanine, or l-ammonium in limitation and by growing cells in an excess of ammonium. Cells grown in l-alanine-limited cultures had higher biomass yield per nitrogen mole (19%) than those from ammonium-limited cultures. Whole-genome transcript profiles were analyzed with a genome-scale metabolic model that suggested increased anabolic activity in l-alanine-limited cells. The changes in these cells were found to be focused around pyruvate, acetyl coenzyme A, glyoxylate, and alpha-ketoglutarate via increased levels of ALT1, DAL7, PYC1, GDH2, and ADH5 and decreased levels of GDH3, CIT2, and ACS1 transcripts. The transcript profiles were then clustered. Approximately 1,400 transcripts showed altered levels when amino acid-grown cells were compared to those from ammonium. Another 400 genes had low transcript levels when ammonium was in excess. Overrepresentation of the GATAAG element in their promoters suggests that nitrogen catabolite repression (NCR) may be responsible for this regulation. Ninety-one genes had transcript levels on both l-glutamine and ammonium that were decreased compared to those on l-alanine, independent of the concentration. The GATAAG element in these genes suggests two groups of NCR-responsive genes, those that respond to high levels of nitrogen and those that respond to levels below 30 muM. In conclusion, our results reveal that the nitrogen source has substantial influence on the transcriptome of yeasts and that transcriptional changes may be correlated to physiology via a metabolic model.

Alanine↗

Annotation of bacterial genomes using improved phylogenomic profiles.

MOTIVATION: Phylogenomic profiling is a large-scale comparative genomic method used to infer protein function from evolutionary information first described in a binary form by Pellegrini et al. (1999). Here, we propose improvements of this approach including the use of normalized Blastp bit scores, a normalization of the matrix of profiles to take into account the evolutionary distances between bacteria, the definition of a phylogenomic neighborhood based on continuous pairwise distances between genes and an original annotation procedure including the computation of a p-value for each functional assignment. RESULTS: The method presented here increases the number of Ecocyc enzymes identified as being evolutionarily related by about 25% with respect to the original binary form (absent/present) method. The fraction of 'false' positives is shown to be smaller than 20%. Based on their phylogenomic relationships, genes of unknown function can then be automatically related to annotated genes. Each gene annotation predicted is associated with a p-value, i.e. its probability to be obtained by chance. The validity of this method was extensively tested on a large set of genes of known function using the MultiFun database. We find that 50% of 3122 function attributions that can be made at a p-value level of 10(-11) correspond to the actual gene annotation. The method can be readily applied to any newly sequenced microbial genome. In contrast to earlier work on the same topic, our approach avoids the use of arbitrary cut-off values, and provides a reliability estimate of the functional predictions in form of p-values.

Algorithms↗

Predicting tissue-specific enhancers in the human genome.

Determining how transcriptional regulatory signals are encoded in vertebrate genomes is essential for understanding the origins of multicellular complexity; yet the genetic code of vertebrate gene regulation remains poorly understood. In an attempt to elucidate this code, we synergistically combined genome-wide gene-expression profiling, vertebrate genome comparisons, and transcription factor binding-site analysis to define sequence signatures characteristic of candidate tissue-specific enhancers in the human genome. We applied this strategy to microarray-based gene expression profiles from 79 human tissues and identified 7187 candidate enhancers that defined their flanking gene expression, the majority of which were located outside of known promoters. We cross-validated this method for its ability to de novo predict tissue-specific gene expression and confirmed its reliability in 57 of the 79 available human tissues, with an average precision in enhancer recognition ranging from 32% to 63% and a sensitivity of 47%. We used the sequence signatures identified by this approach to successfully assign tissue-specific predictions to approximately 328,000 human-mouse conserved noncoding elements in the human genome. By overlapping these genome-wide predictions with a data set of enhancers validated in vivo, in transgenic mice, we were able to confirm our results with a 28% sensitivity and 50% precision. These results indicate the power of combining complementary genomic data sets as an initial computational foray into a global view of tissue-specific gene regulation in vertebrates.

Animals↗

Microarray expression profiling: capturing a genome-wide portrait of the transcriptome.

The bacterial transcriptome is a dynamic entity that reflects the organism's immediate, ongoing and genome-wide response to its environment. Microarray expression profiling provides a comprehensive portrait of the transcriptional world enabling us to view the organism as a 'system' that is more than the sum of its parts. The vigilance of microorganisms to environmental change, the alacrity of the transcriptional response, the short half-life of bacterial mRNA and the genome-scale nature of the investigation collectively explain the power of this method. These same features pose the most significant experimental design and execution issues which, unless surmounted, predictably generate a distorted image of the transcriptome. Conversely, the expression profile of a properly conceived and conducted microarray experiment can be used for hypothesis testing: disclosure of the metabolic and biosynthetic pathways that underlie adaptation of the organism to chang-ing conditions of growth; the identification of co-ordinately regulated genes; the regulatory circuits and signal transduction systems that mediate the adaptive response; and temporal features of developmental programmes. The study of bacterial pathogenesis by microarray expression profiling poses special challenges and opportunities. Although the technical hurdles are many, obtaining expression profiles of an organism growing in tissue will probably reveal strategies for growth and survival in the host's microenvironment. Identifying these colonization strategies and their cognate expression patterns involves a 'deconstruction' process that combines bioinformatics analysis and in vitro DNA array experimentation.

Bacteria↗

Application of genome-wide gene expression profiling by high-density DNA arrays to the treatment and study of inflammatory bowel disease.

Identification of factors involved in the initiation, amplification, and perpetuation of the chronic immune response and the identification of markers for the characterization of patient subgroups remain critical objectives for ongoing research in inflammatory bowel disease (IBD). The Human Genome Project and the development of the expressed sequence tag (EST) clone collection and database have made possible a new revolution in gene expression analysis. Instead of measuring one or a few genes, parallel DNA microarrays are capable of simultaneously measuring expression of thousands of genes, providing a glimpse into the logic and functional grouping of gene programs encoded by our genome. Applied to clinical specimens from affected and normal individuals, this methodology has the potential to provide a new level of information about disease pathogenesis not previously possible. Two dominant platforms for the construction of high-density microarrays have emerged: cDNA arrays and GeneChips. The first involves robotic spotting of DNA molecules, often derived from EST clone collections, onto a suitable solid phase matrix such as a glass slide. The second involves direct in situ synthesis of sets of gene-specific oligonucleotides on a silicon wafer by an eloquent derivative of the photolithography process. Both cDNA and oligonucleotide arrays are interrogated by hybridization with a fluorescent-labeled cDNA or cRNA representation of the original tissue mRNA. This enables measurement of the expression levels for thousands of mucosal genes in a single experiment. These technologies have recently become less expensive and more widely accessible to all researchers. This review details the principles and methods behind DNA array technology, data analysis and mining, and potential application to research and treatment of IBD.

Gene Expression Profiling↗

Identification of molecular markers and signaling pathway in endometrial cancer in Hong Kong Chinese women by genome-wide gene expression profiling.

Endometrial cancer is the third most common gynecologic malignancy and the ninth most common malignancy for females overall in Hong Kong. Approximately 80% or more of these cancers are endometrioid endometrial adenocarcinomas. The aim of this study was to reveal genes contributing to the development of endometrioid endometrial cancer, which may impact diagnosis, prognosis and treatment of the disease. Whole-genome gene expression analysis was completed for a set of 55 microdissected sporadic endometrioid endometrial adenocarcinomas and 29 microdissected normal endometrium specimens using the Affymetrix Human U133 Plus 2.0 oligonucleotide microarray. Selected genes of interest were validated by quantitative real-time-polymerase chain reaction (qRT-PCR). Pathway analysis was performed to reveal gene interactions involved in endometrial tumorigenesis. Unsupervised hierarchical clustering displayed a distinct separation between the endometrioid adenocarcinomas and normal endometrium samples. Supervised analysis identified 117 highly differentially regulated genes (>or=4.0-fold change), which distinguished the endometrial cancer specimens from normal endometrium. Twelve novel genes including DKK4, ZIC1, KIF1A, SAA2, LOC16378, ALPP2, CCL20, CXCL5, BST2, OLFM1, KLRC1 and MBC45780 were deregulated in the endometrial cancer, and further validated in an independent set of 56 cancer and 29 normal samples using qRT-PCR. In addition, 10 genes were differentially regulated in late-stage cancer, as compared to early-stage disease, and may be involved in tumor progression. Pathway analysis of the expression data from this tumor revealed an interconnected network consisting of 21 aberrantly regulated genes involved in angiogenesis, cell proliferation and chromosomal instability. The results of this study highlight the molecular features of endometrioid endometrial cancer and provide insight into the events underlying the development and progression of endometrioid endometrial cancer.

Endometrial Neoplasms↗

Genomic organization and transcript profiling of the bovine toll-like receptor gene cluster TLR6-TLR1-TLR10.

Toll-like receptors (TLRs) are a family of recognition receptors playing a crucial role in the innate immune system. Different combinations of TLRs are thought to be crucial for effective immune response, thus insight into the organization and expression of TLRs is important for understanding disease resistance. Mastitis is the most frequent and costly disease in dairy production, and the innate immune system is considered to be important in the first line defence against this disease. In the present paper we have characterized the genomic organization of TLR6-TLR1-TLR10 in a approximately 50 kb region of bovine chromosome 6, including 5'-untranslated exons not previously described. A method for gene expression analysis was developed and used for transcription profiling of the three paralogous genes in different bovine tissues. The expression analysis showed similar expression profiles for TLR1 and TLR6, which indicate a co-regulation of these two genes in cattle. TLR10 had a different expression profile, pointing toward a stronger functional diversification compared to TLR1 and TLR6. The differences in expression are in accordance with the evolutionary history of this gene cluster, where TLR10 diverged from the common ancestral gene before the duplication event that created TLR1 and TLR6.

5' Untranslated Regions↗

Genome-wide gene expression profiling of testicular carcinoma in situ progression into overt tumours.

The carcinoma in situ (CIS) cell is the common precursor of nearly all testicular germ cell tumours (TGCT). In a previous study, we examined the gene expression profile of CIS cells and found many features common to embryonic stem cells indicating that initiation of neoplastic transformation into CIS occurs early during foetal life. Progression into an overt tumour, however, typically first happens after puberty, where CIS cells transform into either a seminoma (SEM) or a nonseminoma (N-SEM). Here, we have compared the genome-wide gene expression of CIS cells to that of testicular SEM and a sample containing a mixture of N-SEM components, and analyse the data together with the previously published data on CIS. Genes showing expression in the SEM or N-SEM were selected, in order to identify gene expression markers associated with the progression of CIS cells. The identified markers were verified by reverse transcriptase-polymerase chain reaction and in situ hybridisation in a range of different TGCT samples. Verification showed some interpatient variation, but combined analysis of a range of the identified markers may discriminate TGCT samples as SEMs or N-SEMs. Of particular interest, we found that both DNMT3B (DNA (cytosine-5-)-methyltransferase 3 beta) and DNMT3L (DNA (cytosine-5-)-methyltransferase 3 like) were overexpressed in the N-SEMs, indicating the epigenetic differences between N-SEMs and classical SEM.

Carcinoma in Situ↗

Metabolite profiling as a functional genomics tool.

Plants accumulate a very large number of small molecules (phytochemicals) with important functions in the ecology of plants and in the protection against biotic and abiotic stress conditions. Little is known on how phytochemical biosynthetic pathways are regulated, which is a key step to successfully engineering plant metabolism. Plant natural products are usually not essential, and genetic analyses often fail to identify phenotypes associated with the absence of these compounds. We have investigated the use of metabolite profiling of plant cells in culture to establish the function of transcription factors suspected to control plant metabolic pathways.

Cell Culture Techniques↗

Limited tissue fixation times and whole genomic amplification do not impact array CGH profiles.

BACKGROUND: Array comparative genomic hybridisation (CGH) is a powerful method for the genetic analysis of lesional and normal tissues to identify genomic imbalances associated with malignancies. However, the use of this technique with DNA extracted from archival formalin fixed, paraffin embedded (FFPE) tissue specimens, the most widely available resource for retrospective studies, is subject to quantitative and qualitative limitations. In this report, the suitability and integrity of the DNA extracted from FFPE MCF7 breast cancer cells fixed for different periods of time for array CGH applications were examined. RESULTS: Using our established cDNA microarray protocol in conjunction with whole genome amplification methods, the genetic profiles of freshly harvested MCF7 cells and their matched FFPE counterparts were analysed. Congruent profiles between FFPE MCF7 cells and their fresh counterpart and between amplified and non-amplified FFPE MCF7 cells were observed. Our results demonstrate that formalin fixation of <20 hours has no significant adverse effect on the integrity of DNA for array CGH studies. CONCLUSIONS: Our findings attest to the fidelity of our array CGH methods to effectively examine material recovered from FFPE tissue specimens for microarray applications. This in turn has great potential to identify novel diagnostic and prognostic markers for human disease.

Breast Neoplasms↗

Genome-wide gene expression profiling of human mast cells stimulated by IgE or FcepsilonRI-aggregation reveals a complex network of genes involved in inflammatory responses.

BACKGROUND: Mast cells are well established effectors of IgE-triggered allergic reactions and immune responses to parasitic infections. Recent studies indicate that mast cells may play roles in adaptive and innate immunity, suggesting an innovative view of the regulation of immune responses. Here, we profiled the transcriptome of human mast cells sensitized with IgE alone, or stimulated by FcepsilonRI aggregation. RESULTS: Our data show that among 8,793 genes examined, 559 genes are differentially regulated in stimulated mast cells when compared with resting/unstimulated mast cells. The major functional categories of upregulated genes include cytokines, chemokines, and other genes involved in innate and adaptive immune-responses. We observed the increased expression of over 63 gene-transcripts following IgE-sensitization alone. Our data was validated using Real-Time-PCR; ELISA and western blot. We confirmed that IgE alone does not trigger mast cell-immediate responses, such as calcium signals, degranulation or protein-phosphorylation. CONCLUSION: This report represents a substantial advance in our understanding of the genome wide effects triggered by "passive sensitization" or active stimulation of human mast cells, supporting mast cells' potential involvement in a wide range of inflammatory responses.

Gene Expression Profiling↗