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Zeitschriftenartikel zum Thema „Gene Array“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 20. Februar 2023

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1

Zhang, Xiaoling, Marc E. Lenburg, and Avrum Spira. "Comparison of Nasal Epithelial Smoking-Induced Gene Expression on Affymetrix Exon 1.0 and Gene 1.0 ST Arrays." Scientific World Journal 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/951416.

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We have previously defined the impact of tobacco smoking on nasal epithelium gene expression using Affymetrix Exon 1.0 ST arrays. In this paper, we compared the performance of the Affymetrix GeneChip Human Gene 1.0 ST array with the Human Exon 1.0 ST array for detecting nasal smoking-related gene expression changes. RNA collected from the nasal epithelium of five current smokers and five never smokers was hybridized to both arrays. While the intersample correlation within each array platform was relatively higher in the Gene array than that in the Exon array, the majority of the genes most changed by smoking were tightly correlated between platforms. Although neither array dataset was powered to detect differentially expressed genes (DEGs) at a false discovery rate (FDR)<0.05, we identified more DEGs than expected by chance using the Gene ST array. These findings suggest that while both platforms show a high degree of correlation for detecting smoking-induced differential gene expression changes, the Gene ST array may be a more cost-effective platform in a clinical setting for gene-level genomewide expression profiling and an effective tool for exploring the host response to cigarette smoking and other inhaled toxins.

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2

Aschheim, Kathy. "Gene detection by array." Nature Biotechnology 18, no. 11 (November 2000): 1129. http://dx.doi.org/10.1038/81066.

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3

Thomas, E. V., K. H. Phillippy, B. Brahamsha, D. M. Haaland, J. A. Timlin, L. D. H. Elbourne, B. Palenik, and I. T. Paulsen. "Statistical Analysis of Microarray Data with Replicated Spots: A Case Study withSynechococcusWH8102." Comparative and Functional Genomics 2009 (2009): 1–11. http://dx.doi.org/10.1155/2009/950171.

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Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

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Gellert, Pascal, Mizue Teranishi, Katharina Jenniches, Piera De Gaspari, David John, Karsten grosse Kreymborg, Thomas Braun, and Shizuka Uchida. "Gene Array Analyzer: alternative usage of gene arrays to study alternative splicing events." Nucleic Acids Research 40, no. 6 (November 28, 2011): 2414–25. http://dx.doi.org/10.1093/nar/gkr1110.

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5

Walsh, James Bruce. "Persistence of Tandem Arrays: Implications for Satellite and Simple-Sequence DNAs." Genetics 115, no. 3 (March 1, 1987): 553–67. http://dx.doi.org/10.1093/genetics/115.3.553.

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ABSTRACT Recombination processes acting on tandem arrays are suggested here to have probable intrinsic biases, producing an expected net decrease in array size following each event, in contrast to previous models which assume no net change in array size. We examine the implications of this by modeling copy number dynamics in a tandem array under the joint interactions of sister-strand unequal crossing over (rate γ per generation per copy) and intrastrand recombination resulting in deletion (rate ∊ per generation per copy). Assuming no gene amplification or selection, the expected mean persistence time of an array starting with z excess copies (i.e., array size z + 1) is z(1 + γ/∊) recombinational events. Nontrivial equilibrium distributions of array sizes exist when gene amplification or certain forms of selection are considered. We characterize the equilibrium distribution for both a simple model of gene amplification and under the assumption that selection imposes a minimal array size, n. For the latter case, n + 1/03B1 is an upper bound for mean array size under fairly general conditions, where α(=2∊/γ) is the scaled deletion rate. Further, the distribution of excess copies over n is bounded above by a geometric distribution with parameter α/(1 + α). Tandem arrays are unlikely to be greatly expanded by unequal crossing over unless α &lt;&lt; 1, implying that other mechanisms, such as gene amplification, are likely important in the evolution of large arrays. Thus unequal crossing over, by itself, is likely insufficient to account for satellite DNA.

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6

Alkahtani, Mohammed, Yihua Hu, Zuyu Wu, Colin Sokol Kuka, Muflih S. Alhammad, and Chen Zhang. "Gene Evaluation Algorithm for Reconfiguration of Medium and Large Size Photovoltaic Arrays Exhibiting Non-Uniform Aging." Energies 13, no. 8 (April 14, 2020): 1921. http://dx.doi.org/10.3390/en13081921.

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Aging is known to exert various non-uniform effects on photovoltaic (PV) modules within a PV array that consequently can result in non-uniform operational parameters affecting the individual PV modules, leading to a variable power output of the overall PV array. This study presents an algorithm for optimising the configuration of a PV array within which different PV modules are subject to non-uniform aging processes. The PV array reconfiguration approach suggests maximising power generation across non-uniformly aged PV arrays by merely repositioning, rather than replacing, the PV modules, thereby keeping maintenance costs to a minimum. Such a reconfiguration strategy demands data input on the PV module electrical parameters so that optimal reconfiguration arrangements can be selected. The algorithm repetitively sorts the PV modules according to a hierarchical pattern to minimise the impact of module mismatch arising due to non-uniform aging of panels across the array. Computer modelling and analysis have been performed to assess the efficacy of the suggested approach for a variety of dimensions of randomly non-uniformly aged PV arrays (e.g., 5 × 5 and 7 × 20 PV arrays) using MATLAB. The results demonstrate that enhanced power output is possible from a non-uniformly aged PV array and that this can be applied to a PV array of any size.

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7

Mocellin, Simone, Maurizio Provenzano, Carlo Riccardo Rossi, Pierluigi Pilati, Donato Nitti, and Mario Lise. "DNA Array-Based Gene Profiling." Annals of Surgery 241, no. 1 (January 2005): 16–26. http://dx.doi.org/10.1097/01.sla.0000150157.83537.53.

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8

O'Neill, Paul. "Gene array breakthrough for glioblastoma." Trends in Molecular Medicine 7, no. 9 (September 2001): 387. http://dx.doi.org/10.1016/s1471-4914(01)02145-1.

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9

AOKI, Hiroshi, Akiko KITAJIMA, and Hiroaki TAO. "Electrochemical Gene Sensor Arrays Prepared Using Non-contact Nanoliter Array Spotting of Gene Probes." Analytical Sciences 26, no. 3 (2010): 367–70. http://dx.doi.org/10.2116/analsci.26.367.

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10

Johnston, Mark. "Gene chips: Array of hope for understanding gene regulation." Current Biology 8, no. 5 (February 1998): R171—R174. http://dx.doi.org/10.1016/s0960-9822(98)70103-4.

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11

Müller, Stefanie, Robert Geffers, and Stephan Günther. "Analysis of gene expression in Lassa virus-infected HuH-7 cells." Journal of General Virology 88, no. 5 (May 1, 2007): 1568–75. http://dx.doi.org/10.1099/vir.0.82529-0.

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The pathogenesis of Lassa fever is poorly understood. As the liver is a major target organ of Lassa virus, gene expression in Lassa virus-infected HuH-7 cells, a differentiated human hepatoma cell line, was studied. Cellular mRNA levels were measured at the late phase of acute infection, when virtually all cells expressed large amounts of nucleoprotein, and virus RNA concentration had reached >108 copies (ml supernatant)−1. Two types of transcription array were used: cDNA-based macroarrays with a set of 3500 genes (Atlas Human 1.2 arrays; Clontech) and oligonucleotide-based microarrays covering 18 400 transcripts (Human Genome U133A array; Affymetrix). Data analysis was based on statistical frameworks controlling the false-discovery rate. Atlas array data were considered relevant if they could be verified by U133A array or real-time RT-PCR. According to these criteria, there was no evidence for true changes in gene expression. Considering the precision of the U133A array and the number of replicates tested, potential expression changes due to Lassa virus infection are probably smaller than twofold. To substantiate the array data, beta interferon (IFN-β) gene expression was studied longitudinally in Lassa virus-infected HuH-7 and FRhK-4 cells by using real-time RT-PCR. IFN-β mRNA levels increased only twofold upon Lassa virus infection, although there was no evidence that the virus inhibited poly(I : C)-induced IFN-β gene expression. In conclusion, Lassa virus interferes only minimally with gene expression in HuH-7 cells and poorly induces IFN-β gene transcription.

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12

Ghanekar, Ruchi, Vinodh Srinivasasainagendra, and Grier P. Page. "Cross-Chip Probe Matching Tool: A Web-Based Tool for Linking Microarray Probes within and across Plant Species." International Journal of Plant Genomics 2008 (October 21, 2008): 1–7. http://dx.doi.org/10.1155/2008/451327.

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The CCPMT is a free, web-based tool that allows plant investigators to rapidly determine if a given gene is present across various microarray platforms, which, of a list of genes, is present on array(s), and which gene a probe or probe set queries and vice versa, and to compare and contrast the gene contents of arrays. The CCPMT also maps a probe or probe sets to a gene or genes within and across species, and permits the mapping of the entire content from one array to another. By using the CCPMT, investigators will have a better understanding of the contents of arrays, a better ability to link data between experiments, ability to conduct meta-analysis and combine datasets, and an increased ability to conduct data mining projects.

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13

Liu, E. T. "Gene Array Technologies in Biological Investigations." Proceedings of the IEEE 93, no. 4 (April 2005): 737–49. http://dx.doi.org/10.1109/jproc.2005.844617.

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14

Higgins, John P. T. "Gene Array Studies in Renal Neoplasia." Scientific World JOURNAL 6 (2006): 502–11. http://dx.doi.org/10.1100/tsw.2006.109.

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Renal cell carcinoma (RCC) is comprised of several distinct histologic subtypes many of which have characteristic cytogenetic abnormalities. The molecular pathogenesis of some of these neoplasms is beginning to be elucidated. Yet renal cell carcinoma is often discovered at an advanced clinical stage and effective pharmacologic therapies for this disease remain to be discovered. For these reasons, renal cell carcinoma is ideally suited to the genome scale investigation made possible by DNA microarrays. A number of DNA array studies of renal cell carcinoma have been published. Renal cell carcinomas have also been studied by array based comparative genomic hybridization. The purpose of this review will be to summarize these studies, to compare the results of the different studies, and to suggest future areas of investigation with a particular emphasis on clinically relevant advances.

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15

Hu, Yuxin, Chang Han, Zhonglin Mou, and Jiayang Li. "Monitoring gene expression by cDNA array." Chinese Science Bulletin 44, no. 5 (March 1999): 441–44. http://dx.doi.org/10.1007/bf02977884.

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16

Shackel, Nicholas A., Mark D. Gorrell, and Geoffrey W. McCaughan. "Gene array analysis and the liver." Hepatology 36, no. 6 (December 2002): 1313–25. http://dx.doi.org/10.1002/hep.1840360603.

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17

Dorer, Douglas R., and Steven Henikoff. "Transgene Repeat Arrays Interact With Distant Heterochromatin and Cause Silencing in cis and trans." Genetics 147, no. 3 (November 1, 1997): 1181–90. http://dx.doi.org/10.1093/genetics/147.3.1181.

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Tandem repeats of Drosophila transgenes can cause heterochromatic variegation for transgene expression in a copy-number and orientation-dependent manner. Here, we demonstrate different ways in which these transgene repeat arrays interact with other sequences at a distance, displaying properties identical to those of a naturally occurring block of interstitial heterochromatin. Arrays consisting of tandemly repeated white transgenes are strongly affected by proximity to constitutive heterochromatin. Moving an array closer to heterochromatin enhanced variegation, and enhancement was reverted by recombination of the array onto a normal sequence chromosome. Rearrangements that lack the array enhanced variegation of white on a homologue bearing the array. Therefore, silencing of white genes within a repeat array depends on its distance from heterochromatin of the same chromosome or of its paired homologue. In addition, white transgene arrays cause variegation of a nearby gene in cis, a hallmark of classical position-effect variegation. Such spreading of heterochromatic silencing correlates with array size. Finally, white transgene arrays cause pairing-dependent silencing of a non-variegating white insertion at the homologous position.

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18

Santamaría-Gómez, Javier, Miguel Ángel Rubio, Rocío López-Igual, Ana B. Romero-Losada, Fernando M. Delgado-Chaves, Roque Bru-Martínez, Francisco J. Romero-Campero, et al. "Role of a cryptic tRNA gene operon in survival under translational stress." Nucleic Acids Research 49, no. 15 (August 11, 2021): 8757–76. http://dx.doi.org/10.1093/nar/gkab661.

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Abstract As compared to eukaryotes, bacteria have a reduced tRNA gene set encoding between 30 and 220 tRNAs. Although in most bacterial phyla tRNA genes are dispersed in the genome, many species from distinct phyla also show genes forming arrays. Here, we show that two types of arrays with distinct evolutionary origins exist. This work focuses on long tRNA gene arrays (L-arrays) that encompass up to 43 genes, which disseminate by horizontal gene transfer and contribute supernumerary tRNA genes to the host. Although in the few cases previously studied these arrays were reported to be poorly transcribed, here we show that the L-array of the model cyanobacterium Anabaena sp. PCC 7120, encoding 23 functional tRNAs, is largely induced upon impairment of the translation machinery. The cellular response to this challenge involves a global reprogramming of the transcriptome in two phases. tRNAs encoded in the array are induced in the second phase of the response, directly contributing to cell survival. Results presented here show that in some bacteria the tRNA gene set may be partitioned between a housekeeping subset, which constantly sustains translation, and an inducible subset that is generally silent but can provide functionality under particular conditions.

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19

Gestal, Alicia M., H. W. Stokes, Sally R. Partridge, and Ruth M. Hall. "Recombination between the dfrA12-orfF-aadA2 Cassette Array and an aadA1 Gene Cassette Creates a Hybrid Cassette, aadA8b." Antimicrobial Agents and Chemotherapy 49, no. 11 (November 2005): 4771–74. http://dx.doi.org/10.1128/aac.49.11.4771-4774.2005.

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ABSTRACT Homologous recombination between closely related gene cassettes, such as aadA1 and aadA2, which are 89% identical, can create hybrid cassettes and hybrids of existing cassette arrays. A new cassette array, dfrA12-orfF-aadA8b, which was created by such a recombination event occurring within the aadA2 cassette in the dfrA12-orfF-aadA2 array, has been identified.

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20

Saito, I., R. Groves, E. Giulotto, M. Rolfe, and G. R. Stark. "Evolution and stability of chromosomal DNA coamplified with the CAD gene." Molecular and Cellular Biology 9, no. 6 (June 1989): 2445–52. http://dx.doi.org/10.1128/mcb.9.6.2445-2452.1989.

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We have compared clones of Syrian hamster cells selected for the first amplification of the CAD gene with clones selected for further amplification. The large domain amplified initially was not reamplified as an intact unit. Instead, subregions were reamplified preferentially, and parts of the initial array were often lost. These events reduced the average amount of coamplified DNA accompanying each copy of the selected gene. The degree of amplification was small in the first step (about three extra copies of CAD per cell), but second-step amplifications to a high copy number (up to 60 extra copies per cell) occurred frequently. After several separate steps of amplification, highly condensed arrays that brought many CAD genes close together were formed. In striking contrast to the stability of these highly amplified arrays, the low-copy chromosomal arrays formed early were quite unstable and were often lost completely within 1 or 2 months of growth without selection. The results suggest that different mechanisms may be involved in the first step of amplification and in the later evolution of an already amplified array.

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21

Saito, I., R. Groves, E. Giulotto, M. Rolfe, and G. R. Stark. "Evolution and stability of chromosomal DNA coamplified with the CAD gene." Molecular and Cellular Biology 9, no. 6 (June 1989): 2445–52. http://dx.doi.org/10.1128/mcb.9.6.2445.

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We have compared clones of Syrian hamster cells selected for the first amplification of the CAD gene with clones selected for further amplification. The large domain amplified initially was not reamplified as an intact unit. Instead, subregions were reamplified preferentially, and parts of the initial array were often lost. These events reduced the average amount of coamplified DNA accompanying each copy of the selected gene. The degree of amplification was small in the first step (about three extra copies of CAD per cell), but second-step amplifications to a high copy number (up to 60 extra copies per cell) occurred frequently. After several separate steps of amplification, highly condensed arrays that brought many CAD genes close together were formed. In striking contrast to the stability of these highly amplified arrays, the low-copy chromosomal arrays formed early were quite unstable and were often lost completely within 1 or 2 months of growth without selection. The results suggest that different mechanisms may be involved in the first step of amplification and in the later evolution of an already amplified array.

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22

Natarajan, Shobhana, Cindy Groff-Vindman, and Michael J. McEachern. "Factors Influencing the Recombinational Expansion and Spread of Telomeric Tandem Arrays in Kluyveromyces lactis." Eukaryotic Cell 2, no. 5 (October 2003): 1115–27. http://dx.doi.org/10.1128/ec.2.5.1115-1127.2003.

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ABSTRACT We have previously shown that DNA circles containing telomeric repeats and a marker gene can promote the recombinational elongation of telomeres in Kluyveromyces lactis by a mechanism proposed to involve rolling-circle DNA synthesis. Wild-type cells acquire a long tandem array at a single telomere, while telomerase deletion (ter1-Δ) cells, acquire an array and also spread it to multiple telomeres. In this study, we further examine the factors that affect the formation and spread of telomeric tandem arrays. We show that a telomerase+ strain with short telomeres and high levels of subtelomeric gene conversion can efficiently form and spread arrays, while a telomere fusion mutant is not efficient at either process. This indicates that an elevated level of gene conversion near telomeres is required for spreading but that growth senescence and a tendency to elongate telomeres in the absence of exogenously added circles are not. Surprisingly, telomeric repeats are frequently deleted from a transforming URA3-telomere circle at or prior to the time of array formation by a mechanism dependent upon the presence of subtelomeric DNA in the circle. We further show that in a ter1-Δ strain, long tandem arrays can arise from telomeres initially containing a single-copy insert of the URA3-telomere sequence. However, the reduced rate of array formation in such strains suggests that single-copy inserts are not typical intermediates in arrays formed from URA3-telomere circles. Using heteroduplex circles, we have demonstrated that either strand of a URA3-telomere circle can be utilized to form telomeric tandem arrays. Consistent with this, we demonstrate that 100-nucleotide single-stranded telomeric circles of either strand can promote recombinational telomere elongation.

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23

Kowtharapu, Bhavani S., Jyoti Damaraju, Nitesh Kumar Singh, Josefin Ziebart, Rainer Bader, Dirk Koczan, and Oliver Stachs. "Analysis of the Differential Gene and Protein Expression Profiles of Corneal Epithelial Cells Stimulated with Alternating Current Electric Fields." Genes 12, no. 2 (February 20, 2021): 299. http://dx.doi.org/10.3390/genes12020299.

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In cells, intrinsic endogenous direct current (DC) electric fields (EFs) serve as morphogenetic cues and are necessary for several important cellular responses including activation of multiple signaling pathways, cell migration, tissue regeneration and wound healing. Endogenous DC EFs, generated spontaneously following injury in physiological conditions, directly correlate with wound healing rate, and different cell types respond to these EFs via directional orientation and migration. Application of external DC EFs results in electrode polarity and is known to activate intracellular signaling events in specific direction. In contrast, alternating current (AC) EFs are known to induce continuous bidirectional flow of charged particles without electrode polarity and also minimize electrode corrosion. In this context, the present study is designed to study effects of AC EFs on corneal epithelial cell gene and protein expression profiles in vitro. We performed gene and antibody arrays, analyzed the data to study specific influence of AC EFs, and report that AC EFs has no deleterious effect on epithelial cell function. Gene Ontology results, following gene and protein array data analysis, showed that AC EFs influence similar biological processes that are predominantly responsive to organic substance, chemical, or external stimuli. Both arrays activate cytokine–cytokine receptor interaction, MAPK and IL-17 signaling pathways. Further, in comparison to the gene array data, the protein array data show enrichment of diverse activated signaling pathways through several interconnecting networks.

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24

Kim, Yeonjung, Neil McLaughlin, Kim Lindstrom, Toshio Tsukiyama, and David J. Clark. "Activation of Saccharomyces cerevisiae HIS3 Results in Gcn4p-Dependent, SWI/SNF-Dependent Mobilization of Nucleosomes over the EntireGene." Molecular and Cellular Biology 26, no. 22 (September 18, 2006): 8607–22. http://dx.doi.org/10.1128/mcb.00678-06.

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ABSTRACT The effects of transcriptional activation on the chromatin structure of the Saccharomyces cerevisiae HIS3 gene were addressed by mapping the precise positions of nucleosomes in uninduced and induced chromatin. In the absence of the Gcn4p activator, the HIS3 gene is organized into a predominant nucleosomal array. In wild-type chromatin, this array is disrupted, and several alternative overlapping nucleosomal arrays are formed. The disruption of the predominant array also requires the SWI/SNF remodeling machine, indicating that the SWI/SNF complex plays an important role in nucleosome mobilization over the entire HIS3 gene. The Isw1 remodeling complex plays a more subtle role in determining nucleosome positions on HIS3, favoring positions different from those preferred by the SWI/SNF complex. Both the SWI/SNF and Isw1 complexes are constitutively present in HIS3 chromatin, although Isw1 tends to be excluded from the HIS3 promoter. Despite the apparent disorder of HIS3 chromatin generated by the formation of multiple nucleosomal arrays, nucleosome density profiles indicate that some long-range order is always present. We propose that Gcn4p stimulates nucleosome mobilization over the entire HIS3 gene by the SWI/SNF complex. We suggest that the net effect of interplay among remodeling machines at HIS3 is to create a highly dynamic chromatin structure.

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25

Lee, Jae K. "Analysis Issues for Gene Expression Array Data." Clinical Chemistry 47, no. 8 (August 1, 2001): 1350–52. http://dx.doi.org/10.1093/clinchem/47.8.1350.

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26

Leonard, P., T. Sharp, S. Henderson, D. Hewitt, J. Pringle, A. Sandison, A. Goodship, J. Whelan, and C. Boshoff. "Gene expression array profile of human osteosarcoma." British Journal of Cancer 89, no. 12 (December 2003): 2284–88. http://dx.doi.org/10.1038/sj.bjc.6601389.

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27

Nitta, Kouichi, and Jun Tanida. "Gene Network Inference Using Optical Array Logic." Optical Review 10, no. 2 (March 2003): 82–88. http://dx.doi.org/10.1007/s10043-003-0082-z.

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28

Maier, Elmar, Sebastian Meier-Ewert, David Bancroft, and Hans Lehrach. "Automated array technologies for gene expression profiling." Drug Discovery Today 2, no. 8 (August 1997): 315–24. http://dx.doi.org/10.1016/s1359-6446(97)01054-4.

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29

Pena, Maria, Xiaofang Wu, Mary Rose, Roberta Lima, and Jennifer Peters-Hall. "Glandular gene array profiling in pediatric rhinosinusitis." Otolaryngology - Head and Neck Surgery 141, no. 3 (September 2009): P98. http://dx.doi.org/10.1016/j.otohns.2009.06.304.

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30

Mehla, Rajeev, and Velpandi Ayyavoo. "Gene Array Studies in HIV-1 Infection." Current HIV/AIDS Reports 9, no. 1 (December 20, 2011): 34–43. http://dx.doi.org/10.1007/s11904-011-0100-x.

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31

Leone, Paola E., Brian A. Walker, David Gonzalez, Matthew Jenner, Fiona M. Ross, Cheng Li, Faith E. Davies, and Gareth J. Morgan. "Status of Chromosome 13 in Multiple Myeloma: Integrated Approach Using SNP Mapping Array and Gene Expression Array." Blood 106, no. 11 (November 16, 2005): 1563. http://dx.doi.org/10.1182/blood.v106.11.1563.1563.

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Abstract Deletions on chromosome 13 are thought to be one of the most important prognostic features in Multiple Myeloma (MM). The biology underlying this is, however, uncertain. Chromosome 13 abnormalities have been evaluated conventionally by FISH using probes for 13q14, covering the retinoblastoma gene (RB1) region. Typically, for recurrent regions of loss of heterozygosity (LOH) it is possible to map a minimally deleted region within which an important gene may be located. This should be the case with 13q−, or alternatively there may be linkage with another genetic lesion, which could be contributing to the poor prognosis. Following the implementation of high-density single-nucleotide polymorphism (SNP) array, it is now possible to genotype the whole human genome with a mapping resolution of less than 50 Kb. Thus, the SNP array approach offers an opportunity to analyze both copy number abnormalities and LOH simultaneously. The aim of this study was to determine the numerical alterations, LOH and changes in the gene expression profile of the chromosome 13 in MM, and its possible association with other genetic events. For this purpose, we analyzed 17 patients included on the Myeloma IX trial with deletion of 13q14 compared with 22 samples without deletion, using Affymetrix 50K SNP arrays and Affymetrix U133 Plus 2 expression array. IGH translocations and 13q deletion were determined by FISH. dChipSNP and WGSA programs were used to analyze the data. With respect to 13q14, there was 100% correlation between FISH and SNP array results. 16 out of 17 cases with deletion of the RB1 gene by FISH analysis showed loss of 13q arm by SNP array, demonstrating that loss of the whole chromosome 13 is responsible for 13q deletions found in MM in &gt;90% of cases, with only one case showing a defined region of deletion of chromosome 13 (13q14.11–13q21.2). Using gene expression arrays we could not define a specific pattern characteristic of expression loss in genes at 13q. Lower RB1 expression levels were not only restricted to cases with del(13). However, samples containing IGH translocations (t(11;14) and t(4;14)) without del(13) showed up to 4 times more RB1 expression, suggesting that MM evolution in cases containing IGH translocations is independent of RB1 expression. Interestingly, the hyperdiploid cases with and without del(13) expressed similar level of RB1. We also investigated whether other key cell cycle regulatory genes were associated with del(13); in particular, 4 cases showed 9p21 LOH by SNP array and no different gene expression levels, which suggest that LOH does not seem to be a mechanism of lost of expression of CDKN2A, CDKN2B and p14/ARF. We could not find any significant correlation with del(13) and expression of cell cycle regulatory genes, apart from 8/17 samples with del(13) that had low expression of p53 gene, including 6 t(4;14) cases and 2 t(11;14) cases. Also, 2 cases without monosomy 13 (1 with t(4;14) and 1 with t(11;14)), showed low p53 expression levels. However, SNP array data did not show any deletion at 17p in 38 cases, with the exception of a case with monosomy 13 and t(11;14) in which SNP array data showed loss at 17pter-17q21.2 and FISH detected p53 deletion. Further investigation between the association of p53 and del(13) are ongoing and maybe useful in defining the biology of this poor subgroup of patients.

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Comelli, Elena M., Margarida Amado, Steven R. Head, and James C. Paulson. "Custom microarray for glycobiologists: considerations for glycosyltransferase gene expression profiling." Biochemical Society Symposia 69 (October 1, 2002): 135–42. http://dx.doi.org/10.1042/bss0690135.

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The development of microarray technology offers the unprecedented possibility of studying the expression of thousands of genes in one experiment. Its exploitation in the glycobiology field will eventually allow the parallel investigation of the expression of many glycosyltransferases, which will ultimately lead to an understanding of the regulation of glycoconjugate synthesis. While numerous gene arrays are available on the market, e.g. the Affymetrix GeneChip® arrays, glycosyltransferases are not adequately represented, which makes comprehensive surveys of their gene expression difficult. This chapter describes the main issues related to the establishment of a custom glycogenes array.

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Mackin, Robert D., Ruth A. Frey, Carmina Gutierrez, Ashley A. Farre, Shoji Kawamura, Diana M. Mitchell, and Deborah L. Stenkamp. "Endocrine regulation of multichromatic color vision." Proceedings of the National Academy of Sciences 116, no. 34 (August 5, 2019): 16882–91. http://dx.doi.org/10.1073/pnas.1904783116.

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Vertebrate color vision requires spectrally selective opsin-based pigments, expressed in distinct cone photoreceptor populations. In primates and in fish, spectrally divergent opsin genes may reside in head-to-tail tandem arrays. Mechanisms underlying differential expression from such arrays have not been fully elucidated. Regulation of human red (LWS) vs. green (MWS) opsins is considered a stochastic event, whereby upstream enhancers associate randomly with promoters of the proximal or distal gene, and one of these associations becomes permanent. We demonstrate that, distinct from this stochastic model, the endocrine signal thyroid hormone (TH) regulates differential expression of the orthologous zebrafish lws1/lws2 array, and of the tandemly quadruplicated rh2-1/rh2-2/rh2-3/rh2-4 array. TH treatment caused dramatic, dose-dependent increases in abundance of lws1, the proximal member of the lws array, and reduced lws2. Fluorescent lws reporters permitted direct visualization of individual cones switching expression from lws2 to lws1. Athyroidism increased lws2 and reduced lws1, except within a small ventral domain of lws1 that was likely sustained by retinoic acid signaling. Changes in lws abundance and distribution in athyroid zebrafish were rescued by TH, demonstrating plasticity of cone phenotype in response to this signal. TH manipulations also regulated the rh2 array, with athyroidism reducing abundance of distal members. Interestingly, the opsins encoded by the proximal lws gene and distal rh2 genes are sensitive to longer wavelengths than other members of their respective arrays; therefore, endogenous TH acts upon each opsin array to shift overall spectral sensitivity toward longer wavelengths, underlying coordinated changes in visual system function during development and growth.

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Edgar, R. "Gene Expression Omnibus: NCBI gene expression and hybridization array data repository." Nucleic Acids Research 30, no. 1 (January 1, 2002): 207–10. http://dx.doi.org/10.1093/nar/30.1.207.

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Li, Jiexun, Hua Su, Hsinchun Chen, and Bernard W. Futscher. "Optimal Search-Based Gene Subset Selection for Gene Array Cancer Classification." IEEE Transactions on Information Technology in Biomedicine 11, no. 4 (July 2007): 398–405. http://dx.doi.org/10.1109/titb.2007.892693.

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Oshikawa, Maiko, Naoyuki Sugano, Ryo Ishigaki, and Koichi Ito. "Gene expression in the developing rat mandible: a gene array study." Archives of Oral Biology 49, no. 4 (April 2004): 325–29. http://dx.doi.org/10.1016/j.archoralbio.2003.09.008.

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Kellogg, E. A., and R. Appels. "Intraspecific and interspecific variation in 5S RNA genes are decoupled in diploid wheat relatives." Genetics 140, no. 1 (May 1, 1995): 325–43. http://dx.doi.org/10.1093/genetics/140.1.325.

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Abstract 5S RNAs form part of the ribosome in most organisms. In some, e.g., prokaryotes and some fungi, the genes are part of the ribosomal operon, but in most eukaryotes they are in tandem arrays of hundreds to thousands of copies separate from the main ribosomal array. 5S RNA genes can be aligned across kingdoms. We were therefore surprised to find that, for 28 diploid species of the wheat tribe (Triticeae), nucleotide diversity within an array is up to 6.2% in the genes, not significantly different from that of the nontranscribed spacers. Rates of concerted evolution must therefore be insufficient to homogenize the entire array. Between species, there are significantly fewer fixed differences in the gene than would be expected, given the high within-species variation. In contrast, the amount of variation between species in the spacer is the same as or greater than that within individuals. This leads to a paradox. High variation within an individual suggests that there is little selection on any particular gene within an array. But conservation of the gene across species implies that polymorphisms are periodically eliminated at a rate approximately equal to or greater than that of speciation. Levels of intraspecific polymorphism and interspecific divergence are thus decoupled. This implies that selective mechanisms exist to eliminate mutations in the gene without also affecting the spacer.

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Rosolowski, M., H. Berger, C. Schwaenen, S. Wessendorf, M. Loeffler, D. Hasenclever, and M. Kreuz. "Development and Implementation of an Analysis Tool for Array-based Comparative Genomic Hybridization." Methods of Information in Medicine 46, no. 05 (2007): 608–13. http://dx.doi.org/10.1160/me9064.

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Summary Objectives: Array-comparative genomic hybridization (aCGH) is a high-throughput method to detect and map copy number aberrations in the genome. Multi-step analysis of high-dimensional data requires an integrated suite of bioinformatic tools. In this paperwe detail an analysis pipeline for array CGH data. Methods: We developed an analysis tool for array CGH data which supports single and multi-chip analyses as well as combined analyses with paired mRNA gene expression data. The functions supporting relevant steps of analysis were implemented using the open source software R and combined as package aCGHPipeline. Analysis methods were illustrated using 189 CGH arrays of aggressive B-cell lymphomas. Results: The package covers data input, quality control, normalization, segmentation and classification. For multi-chip analysis aCGHPipeline offers an algorithm for automatic delineation of recurrent regions. This task was performed manuallyup to now. The package also supports combined analysis with mRNA gene expression data. Outputs consist of HTML documents to facilitate communication with clinical partners. Conclusions: The R package aCGHPipeline supports basic tasks of single and multi-chip analysis of array CGH data.

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DEEB, SAMIR S. "Molecular genetics of color-vision deficiencies." Visual Neuroscience 21, no. 3 (May 2004): 191–96. http://dx.doi.org/10.1017/s0952523804213244.

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The normal X-chromosome-linked color-vision gene array is composed of a single long-wave-sensitive (L-) pigment gene followed by one or more middle-wave-sensitive (M-) pigment genes. The expression of these genes to form L- or M-cones is controlled by the proximal promoter and by the locus control region. The high degree of homology between the L- and M-pigment genes predisposed them to unequal recombination, leading to gene deletion or the formation of L/M hybrid genes that explain the majority of the common red–green color-vision deficiencies. Hybrid genes encode a variety of L-like or M-like pigments. Analysis of the gene order in arrays of normal and deutan subjects indicates that only the two most proximal genes of the array contribute to the color-vision phenotype. This is supported by the observation that only the first two genes of the array are expressed in the human retina. The severity of the color-vision defect is roughly related to the difference in absorption maxima (λmax) between the photopigments encoded by the first two genes of the array. A single amino acid polymorphism (Ser180Ala) in the L pigment accounts for the subtle difference in normal color vision and influences the severity of red–green color-vision deficiency.Blue-cone monochromacy is a rare disorder that involves absence of L- and M-cone function. It is caused either by deletion of a critical region that regulates expression of the L/M gene array, or by mutations that inactivate the L- and M-pigment genes. Total color blindness is another rare disease that involves complete absence of all cone function. A number of mutants in the genes encoding the cone-specific α- and β-subunits of the cGMP-gated cation channel as well as in the α-subunit of transducin have been implicated in this disorder.

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Sun, Fang-Lin, Matthew H. Cuaycong, and Sarah C. R. Elgin. "Long-Range Nucleosome Ordering Is Associated with Gene Silencing in Drosophila melanogaster Pericentric Heterochromatin." Molecular and Cellular Biology 21, no. 8 (April 15, 2001): 2867–79. http://dx.doi.org/10.1128/mcb.21.8.2867-2879.2001.

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ABSTRACT We have used line HS-2 of Drosophila melanogaster, carrying a silenced transgene in the pericentric heterochromatin, to investigate in detail the chromatin structure imposed by this environment. Digestion of the chromatin with micrococcal nuclease (MNase) shows a nucleosome array with extensive long-range order, indicating regular spacing, and with well-defined MNase cleavage fragments, indicating a smaller MNase target in the linker region. The repeating unit is ca. 10 bp larger than that observed for bulkDrosophila chromatin. The silenced transgene shows both a loss of DNase I-hypersensitive sites and decreased sensitivity to DNase I digestion within an array of nucleosomes lacking such sites; within such an array, sensitivity to digestion by MNase is unchanged. The ordered nucleosome array extends across the regulatory region of the transgene, a shift that could explain the loss of transgene expression in heterochromatin. Highly regular nucleosome arrays are observed over several endogenous heterochromatic sequences, indicating that this is a general feature of heterochromatin. However, genes normally active within heterochromatin (rolled and light) do not show this pattern, suggesting that the altered chromatin structure observed is associated with regions that are silent, rather than being a property of the domain as a whole. The results indicate that long-range nucleosomal ordering is linked with the heterochromatic packaging that imposes gene silencing.

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Cronin, Maureen, Krishna Ghosh, Frank Sistare, John Quackenbush, Vincent Vilker, and Catherine O’Connell. "Universal RNA Reference Materials for Gene Expression." Clinical Chemistry 50, no. 8 (August 1, 2004): 1464–71. http://dx.doi.org/10.1373/clinchem.2004.035675.

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Abstract A workshop entitled “Metrology and Standards Needs for Gene Expression Technologies: Universal RNA Standards” was held in March 2003 to define the requirements for standardizing RNA-based molecular assays, specifically microarray and quantitative reverse-transcriptase-PCR technologies. NIST sponsored the workshop, and participants represented government, industry, academia, and clinic. Workshop participants concluded that as a first step, two RNA reference materials could be defined that would help in standardization of gene-expression technologies: an Assay Process Reference Material, and a Universal Array Hybridization Reference Material. The specific characteristics of these two standardized materials were broadly outlined. The Assay Process Material was proposed to be a pool of 96 expressed human sequences of defined composition, cloned in a defined vector and pooled in prescribed ways. The Universal Array Hybridization Material was defined as a pool of 12 “alien” synthetic sequences not expressed in any known genome to be used to control for variability in array hybridization methods. Work is underway at NIST and among members of the gene expression array community to further define these materials and make them available.

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Hiratsuka, K., Y. Kamino, T. Nagata, Y. Takahashi, S. Asai, K. Ishikawa, and Y. Abiko. "Microarray Analysis of Gene Expression Changes in Aging in Mouse Submandibular Gland." Journal of Dental Research 81, no. 10 (October 2002): 679–82. http://dx.doi.org/10.1177/154405910208101005.

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Little is known about the effect of salivary gland function during aging based on gene expression. Recently emerged DNA array technology provides a sensitive, quantitative, rapid approach to the monitoring of the global pattern of gene expression. In this study, we used high-density oligonucleotide arrays to monitor the changes of gene expression levels in the submandibular gland (SMG) by comparing adult mice with elderly adult mice. Of the 1328 genes screened, 160 genes (12.0%) showed more than two-fold changes; 154 (96.3%) of these genes, associated with transcription regulation, transport, signal transduction, and enzymes in the elderly mice, exhibited decreased expression levels. The remaining 6 genes (3.7%) in the elderly mice showed increased expression levels. In mouse SMG, analysis of these data suggests that aging may lead the gene expression to decrease than increase. Thus, DNA array technology can be a powerful tool for the identification of age-associated candidate genes for further analysis in aging.

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Wu, Zhong, Martin Schlumpberger, Sameen Raza, Jiaye Yu, John DiCarlo, Yexun Wang, and Vikram Devgan. "Pathway Signature PCR Array: a novel method for studying inflammatory responses (173.11)." Journal of Immunology 188, no. 1_Supplement (May 1, 2012): 173.11. http://dx.doi.org/10.4049/jimmunol.188.supp.173.11.

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Abstract Signaling pathways play central roles in cellular physiology, and assessing the state of pathways helps clarify molecular mechanisms of disease and inflammatory responses. Gene expression signatures of pathway activation status enable reliable measurement of pathway activity. Our group developed Pathway Signature PCR Arrays to analyze gene expression and determine pathway activity within a single real-time PCR experiment. This study identified a set of genes that provide a gene signature for evaluating IL6/STAT3 pathway activity. A set of 88 signature genes were derived from microarray profiling on HepG2 and MCF10A cells treated with IL-6 protein and STAT3-specific siRNA. Genes were selected on the basis of statistically significant expression changes in response to IL-6 and reversion of altered expression upon treatment with STAT3 siRNA. These 88 IL-6/STAT3 response genes were further verified by real-time PCR, using a panel of 14 different cell lines stimulated with IL-6 or inhibited with STAT3 siRNA. Using a mathematical classifier method, a subset of genes was identified as a gene expression signature for assessing IL-6/STAT3 pathway activity. These signature genes, along with IL-6 pathway-related genes identified by literature mining, constitute the IL-6 Pathway Signature PCR Array. This array provides a useful tool for studying regulation of pathway activity via gene expression changes during inflammatory responses. Array is for molecular biology applications only.

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Wong, Lee-Jun C., David Dimmock, Michael T. Geraghty, Richard Quan, Uta Lichter-Konecki, Jing Wang, Ellen K. Brundage, Fernando Scaglia, and A. Craig Chinault. "Utility of Oligonucleotide Array–Based Comparative Genomic Hybridization for Detection of Target Gene Deletions." Clinical Chemistry 54, no. 7 (July 1, 2008): 1141–48. http://dx.doi.org/10.1373/clinchem.2008.103721.

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Abstract Background: Direct DNA sequencing is the primary clinical technique for identifying mutations in human disease, but sequencing often does not detect intragenic or whole-gene deletions. Oligonucleotide array–based comparative genomic hybridization (CGH) is currently in clinical use to detect major changes in chromosomal copy number. Methods: A custom oligonucleotide-based microarray was constructed to provide high-density coverage of an initial set of 130 nuclear genes involved in the pathogenesis of metabolic and mitochondrial disorders. Standard array CGH procedures were used to test patient DNA samples for regions of copy number change. Sequencing of regions of predicted breakpoints in genomic DNA and PCR analysis were used to confirm oligonucleotide array CGH data. Results: Oligonucleotide array CGH identified intragenic exonic deletions in 2 cases: a heterozygous single-exon deletion of 4.5 kb in the SLC25A13 gene [solute carrier family 25, member 13 (citrin)] in an individual with citrin deficiency and a homozygous 10.5-kb deletion of exons 13–17 in the ABCB11 gene [PFIC2, ATP-binding cassette, sub-family B (MDR/TAP), member 11] in a patient with progressive familial intrahepatic cholestasis. In 2 females with OTC deficiency, we also found 2 large heterozygous deletions of approximately 7.4 Mb and 9 Mb on the short arm of the X chromosome extending from sequences telomeric to the DMD gene [dystrophin (muscular dystrophy, Duchenne and Becker types)] to sequences within or centromeric to the OTC gene (ornithine carbamoyltransferase). Conclusions: These examples illustrate the successful use of custom oligonucleotide arrays to detect either whole-gene deletions or intragenic exonic deletions. This technology may be particularly useful as a complementary diagnostic test in the context of a recessive disease when only one mutant allele is found by sequencing.

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Liu, Hong, Asher Zilberstein, Pascal Pannier, Frederic Fleche, Christopher Arendt, Christoph Lengauer, and Chang S. Hahn. "Evaluating Translocation Gene Fusions by SNP Array Data." Cancer Informatics 11 (December 21, 2011): CIN.S8026. http://dx.doi.org/10.4137/cin.s8026.

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Somatic cell genetic alterations are a hallmark of tumor development and progression. Although various technologies have been developed and utilized to identify genetic aberrations, identifying genetic translocations at the chromosomal level is still a challenging task. High density SNP microarrays are useful to measure DNA copy number variation (CNV) across the genome. Utilizing SNP array data of cancer cell lines and patient samples, we evaluated the CNV and copy number breakpoints for several known fusion genes implicated in tumorigenesis. This analysis demonstrated the potential utility of SNP array data for the prediction of genetic aberrations via translocations based on identifying copy number breakpoints within the target genes. Genome-wide analysis was also performed to identify genes harboring copy number breakpoints across 820 cancer cell lines. Candidate oncogenes were identified that are linked to potential translocations in specific cancer cell lines.

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Etchebarne, B., W. Nobis, M. Allen, and M. Van de Haar. "Design of a bovine metabolism oligonucleotide gene array." Journal of Animal and Feed Sciences 13, Suppl. 1 (August 30, 2004): 385–88. http://dx.doi.org/10.22358/jafs/73943/2004.

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Geschwind, Daniel H. "Sharing gene expression data: an array of options." Nature Reviews Neuroscience 2, no. 6 (June 2001): 435–38. http://dx.doi.org/10.1038/35077576.

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Mocellin, Simone, Ena Wang, Monica Panelli, Pierluigi Pilati, and Francesco M. Marincola. "DNA Array-Based Gene Profiling in Tumor Immunology." Clinical Cancer Research 10, no. 14 (July 15, 2004): 4597–606. http://dx.doi.org/10.1158/1078-0432.ccr-04-0327.

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Dozmorov, I., and M. Centola. "An associative analysis of gene expression array data." Bioinformatics 19, no. 2 (January 22, 2003): 204–11. http://dx.doi.org/10.1093/bioinformatics/19.2.204.

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Han, Eun-Soo, and Susan G. Hilsenbeck. "Array-based gene expression profiling to study aging." Mechanisms of Ageing and Development 122, no. 10 (July 2001): 999–1018. http://dx.doi.org/10.1016/s0047-6374(01)00215-9.

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