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      Partitioning Transcript Variation in Drosophila: Abundance, Isoforms, and Alleles

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          Abstract

          Multilevel analysis of transcription is facilitated by a new array design that includes modules for assessment of differential expression, isoform usage, and allelic imbalance in Drosophila. The ∼2.5 million feature chip incorporates a large number of controls, and it contains 18,769 3′ expression probe sets and 61,919 exon probe sets with probe sequences from Drosophila melanogaster and 60,118 SNP probe sets focused on Drosophila simulans. An experiment in D. simulans identified genes differentially expressed between males and females (34% in the 3′ expression module; 32% in the exon module). These proportions are consistent with previous reports, and there was good agreement (κ = 0.63) between the modules. Alternative isoform usage between the sexes was identified for 164 genes. The SNP module was verified with resequencing data. Concordance between resequencing and the chip design was greater than 99%. The design also proved apt in separating alleles based upon hybridization intensity. Concordance between the highest hybridization signals and the expected alleles in the genotype was greater than 96%. Intriguingly, allelic imbalance was detected for 37% of 6579 probe sets examined that contained heterozygous SNP loci. The large number of probes and multiple probe sets per gene in the 3′ expression and exon modules allows the array to be used in D. melanogaster and in closely related species. The SNP module can be used for allele specific expression and genotyping of D. simulans.

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

            A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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              Systematic variation in gene expression patterns in human cancer cell lines.

              We used cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institute's screen for anti-cancer drugs. Classification of the cell lines based solely on the observed patterns of gene expression revealed a correspondence to the ostensible origins of the tumours from which the cell lines were derived. The consistent relationship between the gene expression patterns and the tissue of origin allowed us to recognize outliers whose previous classification appeared incorrect. Specific features of the gene expression patterns appeared to be related to physiological properties of the cell lines, such as their doubling time in culture, drug metabolism or the interferon response. Comparison of gene expression patterns in the cell lines to those observed in normal breast tissue or in breast tumour specimens revealed features of the expression patterns in the tumours that had recognizable counterparts in specific cell lines, reflecting the tumour, stromal and inflammatory components of the tumour tissue. These results provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.
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                Author and article information

                Contributors
                Role: Communicating editor
                Journal
                G3 (Bethesda)
                ggg
                ggg
                ggg
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                1 November 2011
                November 2011
                : 1
                : 6
                : 427-436
                Affiliations
                [* ]Genetics Institute, University of Florida, Gainesville, FL 32610-3610
                []Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL 32610-0266
                []Department of Zoology, University of Florida, Gainesville, FL, 32611-8525
                [§ ]Department of Statistics, University of Florida, Gainesville, FL 32611-8545
                [** ]Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089-2910
                Author notes

                Supporting information is available online at http://www.g3journal.org/lookup/suppl/doi:10.1534/g3.111.000596/-/DC1

                Arrays have been submitted to the GEO database at NCBI as the custom platform GPL11273 and series GSE31750. Sequencing data have been submitted to the SRA database at NCBI as SRP005952.

                [1 ]Corresponding author: 2033 Mowry Road, Cancer/Genetics Research Complex, University of Florida, Gainesville, FL 32610-3610. E-mail: mcintyre@ 123456ufl.edu
                Article
                GGG_000596
                10.1534/g3.111.000596
                3276160
                22384353
                219ece5b-c28d-4cbc-b6a6-675f2801b67e
                Copyright © 2011 Yang et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 June 2011
                : 11 September 2011
                Categories
                Investigation
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                Genetics
                snp chip
                Genetics
                snp chip

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