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In vitro identification and in silico utilization of interspecies sequence similarities using GeneChip? technology
Dmitry N Grigoryev, Shwu-Fan Ma, Brett A Simon, Rafael A Irizarry, Shui Q Ye, Joe GN Garcia
BMC Genomics , 2005, DOI: 10.1186/1471-2164-6-62
Abstract: Gene expression profiles of 40 canine samples were generated using the human HG-U133A GeneChip (U133A). Due to interspecies genetic differences, only 14 ± 2% of canine transcripts were detected by U133A probe sets whereas profiling of 40 human samples detected 49 ± 6% of human transcripts. However, when these probe sets were deconstructed into individual probes and examined performance of each probe, we found that 47% of human probes were able to find their targets in canine tissues and generate a detectable hybridization signal. Therefore, we restricted gene expression analysis to these probes and observed the 60% increase in the number of identified canine transcripts. These results were validated by comparison of transcripts identified by our restricted analysis of cross-species hybridization with transcripts identified by hybridization of total lung canine mRNA to new Affymetrix Canine GeneChip?.The experimental identification and restriction of gene expression analysis to probes with detectable hybridization signal drastically increases transcript detection of canine-human hybridization suggesting the possibility of broad utilization of cross-hybridizations of related species using GeneChip technology.Genome-wide analyses of multiple organisms in a variety of experimental biological systems are powerful tools employed in biomedical research. However, microarray platforms for numerous species, particularly large mammals, have yet to be fully developed. Large mammals, often preferred species for modeling of various pathophysiological conditions and environmental responses, demonstrate better concordance to humans with regard to toxicological effects compared to small animal models (rodents) [1,2]. Further, large animal models are indispensable in disease modeling that requires longer live span [3], in organ transplant research [4], and in studies where multiple samples are required to be collected [5]. For organ- and system-specific applications, such as the resp
On Hemangioblasts in Chicken  [PDF]
Wei Weng, Erike W. Sukowati, Guojun Sheng
PLOS ONE , 2007, DOI: 10.1371/journal.pone.0001228
Abstract: Hemangioblasts are bi-potential precursors for blood and endothelial cells (BCs and ECs). Existence of the hemangioblast in vivo by its strict definition, i.e. a clonal precursor giving rise to these two cell types after division, is still debated. Using a combination of mitotic figure analysis, cell labeling and long-term cell tracing, we show that, in chicken, cell division does not play a major role during the entire ventral mesoderm differentiation process after gastrulation. One eighth of cells do undergo at least one round of division, but mainly give rise to daughter cells contributing to the same lineage. Approximately 7% of the dividing cells that contribute to either the BC or EC lineage meet the criteria of true hemangioblasts, with one daughter cell becoming a BC and the other an EC. Our data suggest that hemangioblast-type generation of BC/EC occurs, but is not used as a major mechanism during early chicken development. It remains unclear, however, whether hemangioblast-like progenitor cells play a more prominent role in later development.
Intercenter reliability and validity of the rhesus macaque GeneChip
Fenghai Duan, Eliot R Spindel, Yu-Hua Li, Robert B Norgren
BMC Genomics , 2007, DOI: 10.1186/1471-2164-8-61
Abstract: The results indicate that center effects were minimal and the rhesus GeneChip appears highly reliable. To test the validity of the rhesus GeneChip, five of the most differentially expressed genes among tissues identified in the reliability experiments were chosen for analysis with Quantitative PCR. For all 5 genes, the qPCR and GeneChip results were in agreement with regard to differential expression between tissues. Significantly more probesets were called present when rhesus samples were hybridized with the rhesus GeneChip than when these same samples were hybridized with a human GeneChip.The rhesus GeneChip is both a reliable and a valid tool for examining gene expression and represents a significant improvement over the use of the human GeneChip for rhesus macaque gene expression studies.The non-human primate (NHP) research community has been intensely interested in obtaining whole-genome expression arrays for their work. The recent production of a rhesus macaque GeneChip (Affymetrix, Santa Clara, CA) now satisfies this need [1].Novel approaches were used to generate the DNA sequence information for the rhesus GeneChip. In 2005, when the rhesus macaque GeneChip was in the design stage, the percent of the total genes in the rhesus macaque genome covered by the ESTs was quite small. In addition, the rhesus macaque genome sequences were at an early stage of assembly and with limited redundancy. To overcome these limitations, we used a targeted PCR approach to acquire necessary sequences for the probes for over 5,000 genes [2]. All human last exons were identified and aligned with Probe Selection Region (PSR) sequences obtained from Affymetrix. Primers were designed that flanked the PSRs. These primers were used to amplify orthologous PSRs in rhesus macaques from rhesus genomic DNA. The PCR products were cloned, sequenced and deposited in GenBank. In an in silico version of our targeted PCR approach, sequences from an early draft of the Baylor Rhesus Genome assembly
Breed-Specific Hematological Phenotypes in the Dog: A Natural Resource for the Genetic Dissection of Hematological Parameters in a Mammalian Species  [PDF]
Jennifer Lawrence, Yu-Mei Ruby Chang, Balazs Szladovits, Lucy J. Davison, Oliver A. Garden
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0081288
Abstract: Remarkably little has been published on hematological phenotypes of the domestic dog, the most polymorphic species on the planet. Information on the signalment and complete blood cell count of all dogs with normal red and white blood cell parameters judged by existing reference intervals was extracted from a veterinary database. Normal hematological profiles were available for 6046 dogs, 5447 of which also had machine platelet concentrations within the reference interval. Seventy-five pure breeds plus a mixed breed control group were represented by 10 or more dogs. All measured parameters except mean corpuscular hemoglobin concentration (MCHC) varied with age. Concentrations of white blood cells (WBCs), neutrophils, monocytes, lymphocytes, eosinophils and platelets, but not red blood cell parameters, all varied with sex. Neutering status had an impact on hemoglobin concentration, mean corpuscular hemoglobin (MCH), MCHC, and concentrations of WBCs, neutrophils, monocytes, lymphocytes and platelets. Principal component analysis of hematological data revealed 37 pure breeds with distinctive phenotypes. Furthermore, all hematological parameters except MCHC showed significant differences between specific individual breeds and the mixed breed group. Twenty-nine breeds had distinctive phenotypes when assessed in this way, of which 19 had already been identified by principal component analysis. Tentative breed-specific reference intervals were generated for breeds with a distinctive phenotype identified by comparative analysis. This study represents the first large-scale analysis of hematological phenotypes in the dog and underlines the important potential of this species in the elucidation of genetic determinants of hematological traits, triangulating phenotype, breed and genetic predisposition.
Dissection of a QTL Hotspot on Mouse Distal Chromosome 1 that Modulates Neurobehavioral Phenotypes and Gene Expression  [PDF]
Khyobeni Mozhui,Daniel C. Ciobanu,Thomas Schikorski,Xusheng Wang,Lu Lu,Robert W. Williams
PLOS Genetics , 2008, DOI: 10.1371/journal.pgen.1000260
Abstract: A remarkably diverse set of traits maps to a region on mouse distal chromosome 1 (Chr 1) that corresponds to human Chr 1q21–q23. This region is highly enriched in quantitative trait loci (QTLs) that control neural and behavioral phenotypes, including motor behavior, escape latency, emotionality, seizure susceptibility (Szs1), and responses to ethanol, caffeine, pentobarbital, and haloperidol. This region also controls the expression of a remarkably large number of genes, including genes that are associated with some of the classical traits that map to distal Chr 1 (e.g., seizure susceptibility). Here, we ask whether this QTL-rich region on Chr 1 (Qrr1) consists of a single master locus or a mixture of linked, but functionally unrelated, QTLs. To answer this question and to evaluate candidate genes, we generated and analyzed several gene expression, haplotype, and sequence datasets. We exploited six complementary mouse crosses, and combed through 18 expression datasets to determine class membership of genes modulated by Qrr1. Qrr1 can be broadly divided into a proximal part (Qrr1p) and a distal part (Qrr1d), each associated with the expression of distinct subsets of genes. Qrr1d controls RNA metabolism and protein synthesis, including the expression of ~20 aminoacyl-tRNA synthetases. Qrr1d contains a tRNA cluster, and this is a functionally pertinent candidate for the tRNA synthetases. Rgs7 and Fmn2 are other strong candidates in Qrr1d. FMN2 protein has pronounced expression in neurons, including in the dendrites, and deletion of Fmn2 had a strong effect on the expression of few genes modulated by Qrr1d. Our analysis revealed a highly complex gene expression regulatory interval in Qrr1, composed of multiple loci modulating the expression of functionally cognate sets of genes.
In-Vitro Differentiation Of Human Embryonic Stem Cells Into Hemangioblasts
F Ganji,S Abruon,H Baharvand,M Ebrahimi
Tehran University Medical Journal , 2012,
Abstract: Background: Human embryonic stem cells (hESCs) are capable of self-renewal and large-scale expansion. They also have the capacity to differentiate into a variety of cell types including liver, cardiac and neuron cells. However, it is not yet clear whether hESCs can differentiate to hemangioblasts under in-vitro conditions. Hemangioblasts are bipotential progenitors that can generate hematopoietic lineages and endothelial cells. The aim of this study was to identify the potential of human Royan H5 embryonic stem cells in differentiating into hemangioblast cells. Methods: HESCs were cultured at suspension system in DMEM/F12 supplemented with bFGF. 7-day old cells differentiated into blast cells under defined condition consisting of hematopoietic cytokines including BMP4, VEGF, etc. Blast cell markers kinase insert domain receptor (KDR), CD31, and CD34 were evaluated by flow cytometry and blast gene expressions (TAL-1, Runx-1 and CD34) were detected by qRT-PCR. Clonogenic assays were performed in semisolid medium by colony forming unit-assays. Results: The hESCs (Royan H5) had the capacity of differentiating into hemangioblast cells. We could detect colonies that expressed 79%±12.5 KDR+, 5.6%±2.8 CD31+-CD34+ and 6%±2.12 KDR+-CD31+ on day 8 in the hESCs. Up-regulation of TAL-1, Runx-1 and CD34 occurred during hemangioblast commitment (P≤0.05 and P≤0.01, respectively). Moreover, hemangioblast cells generated mixed-type and endothelial-like colonies in semi-solid media. Conclusion: Our results showed that hESCs (Royan H5) were able to differentiate into hemangioblasts under in-vitro conditions. The hemangioblasts had the potential to generate two non-adherent (Mixed-type) and adherent (endothelial-like) cell populations.
GCOD - GeneChip Oncology Database
Fenglong Liu, Joseph A White, Corina Antonescu, Daniel Gusenleitner, John Quackenbush
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-46
Abstract: To address this issue we have collected published human cancer gene expression datasets generated on the Affymetrix GeneChip platform, and carefully annotated those studies with a focus on providing accurate sample annotation. To facilitate comparison between datasets, we implemented a consistent data normalization and transformation protocol and then applied stringent quality control procedures to flag low-quality assays.The resulting resource, the GeneChip Oncology Database, is available through a publicly accessible website that provides several query options and analytical tools through an intuitive interface.Although gene expression microarrays have been widely used to study human disease, by far the most extensive application has been to the analysis of human cancers. Despite the large number of array experiments deposited in public databases such as GEO [1] and ArrayExpress [2], our ability to perform meta-analyses of these data to discover cross-cutting patterns has been hampered by both the heterogeneous nature of the data and the lack of consistent annotation of the experimental samples. Although there have been some attempts to organize these data in resources such as Oncomine [3] and Genevestigator [4], both focus on analyses of subsets of the data and neither fully addresses the problem of integration across studies.To overcome these limitations, we developed GCOD, the GeneChip Oncology Database, a freely-available web-accessible resource focused on gene expression profiles in cancer collected on the Affymetrix GeneChip platform. Relative to other resources, GCOD has three distinguishing features that we believe greatly enhance its overall utility. First, since GCOD focuses on expression data derived from a single platform and on studies where raw data are available, all datasets in GCOD are uniformly processed and properly scaled such that levels of gene expression in multiple samples across studies are comparable. Second, quality control protocols hav
Functional dissection of the ash2 and ash1 transcriptomes provides insights into the transcriptional basis of wing phenotypes and reveals conserved protein interactions
Sergi Beltran, Mireia Angulo, Miguel Pignatelli, Florenci Serras, Montserrat Corominas
Genome Biology , 2007, DOI: 10.1186/gb-2007-8-4-r67
Abstract: The analysis of wing imaginal disc transcriptomes from ash2 and ash1 mutants showed that they are highly similar. Functional annotation of regulated genes using Gene Ontology allowed identification of severely affected groups of genes that could be correlated to the wing phenotypes observed. Comparison of the differentially expressed genes with those from other genome-wide analyses revealed similarities between ASH2 and Sin3A, suggesting a putative functional relationship. Coimmunoprecipitation studies and immunolocalization on polytene chromosomes demonstrated that ASH2 and Sin3A interact with HCF (host-cell factor). The results of nucleosome western blots and clonal analysis indicated that ASH2 is necessary for trimethylation of the Lys4 on histone 3 (H3K4).The similarity between the transcriptomes of ash2 and ash1 mutants supports a model in which the two genes act together to maintain stable states of transcription. Like in humans, both ASH2 and Sin3A bind HCF. Finally, the reduction of H3K4 trimethylation in ash2 mutants is the first evidence in Drosophila regarding the molecular function of this trxG gene.During early development, transcription factors and signalling molecules initiate a cascade of developmental decisions that culminates in lineage restriction, cell determination and cell differentiation. However, commitment to a particular cell fate in the early embryo must be maintained throughout development, even after the factors that specified the cell fate are no longer present. The trithorax group (trxG) and Polycomb group (PcG) proteins are positive and negative regulators, respectively, that are involved in maintaining heritable patterns of transcription during development and differentiation (recently reviewed in [1-3]). Although the way in which trxG and PcG proteins recognize their target genes is not fully understood, Polycomb and trithorax response elements (generally termed PREs) are known to play an important role in this process, since they r
Washing scaling of GeneChip microarray expression
Hans Binder, Knut Krohn, Conrad J Burden
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-291
Abstract: We conducted experiments on GeneChip microarrays with altered protocols for washing, scanning and staining to study the probe-level intensity changes as a function of the number of washing cycles. For calibration and analysis of the intensity data we make use of the 'hook' method which allows intensity contributions due to non-specific and specific hybridization of perfect match (PM) and mismatch (MM) probes to be disentangled in a sequence specific manner. On average, washing according to the standard protocol removes about 90% of the non-specific background and about 30-50% and less than 10% of the specific targets from the MM and PM, respectively. Analysis of the washing kinetics shows that the signal-to-noise ratio doubles roughly every ten stringent washing cycles. Washing can be characterized by time-dependent rate constants which reflect the heterogeneous character of target binding to microarray probes. We propose an empirical washing function which estimates the survival of probe bound targets. It depends on the intensity contribution due to specific and non-specific hybridization per probe which can be estimated for each probe using existing methods. The washing function allows probe intensities to be calibrated for the effect of washing. On a relative scale, proper calibration for washing markedly increases expression measures, especially in the limit of small and large values.Washing is among the factors which potentially distort expression measures. The proposed first-order correction method allows direct implementation in existing calibration algorithms for microarray data. We provide an experimental 'washing data set' which might be used by the community for developing amendments of the washing correction.Gene expression profiling using microarrays has become a standard technique for the large scale estimation of transcript abundance [1]. The method is based on the hybridization of RNA prepared from samples of interest with gene-specific oligonucleoti
Assessing affymetrix GeneChip microarray quality
Matthew N McCall, Peter N Murakami, Margus Lukk, Wolfgang Huber, Rafael A Irizarry
BMC Bioinformatics , 2011, DOI: 10.1186/1471-2105-12-137
Abstract: We begin by providing a precise definition of microarray quality and reviewing existing Affymetrix GeneChip quality metrics in light of this definition. We show that the best-performing metrics require multiple arrays to be assessed simultaneously. While such multi-array quality metrics are adequate for bench science, as microarrays begin to be used in clinical settings, single-array quality metrics will be indispensable. To this end, we define a single-array version of one of the best multi-array quality metrics and show that this metric performs as well as the best multi-array metrics. We then use this new quality metric to assess the quality of microarry data available via the Gene Expression Omnibus (GEO) using more than 22,000 Affymetrix HGU133a and HGU133plus2 arrays from 809 studies.We find that approximately 10 percent of these publicly available arrays are of poor quality. Moreover, the quality of microarray measurements varies greatly from hybridization to hybridization, study to study, and lab to lab, with some experiments producing unusable data. Many of the concepts described here are applicable to other high-throughput technologies.Microarray technology has become a widely used tool in the biological sciences. Over the past decade, the number of users has grown exponentially, and with the number of applications and secondary data analyses rapidly increasing, we expect this rate to continue. Various initiatives such as the External RNA Control Consortium (ERCC) [1] and the MicroArray Quality Control (MAQC) projects [2,3] have explored ways to provide standards for the technology. For microarrays to become generally accepted as a reliable technology, statistical methods for assessing quality will be an indispensable component; however, there remains a lack of consensus in both defining and measuring microarray quality.Defining quality in the context of a microarray experiment is not an easy task. The American Society for Quality (ASQ) defines quality as
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