Detection and measurement of alternative splicing using splicing-sensitive microarrays

Srinivasan, Karpagam; Shiue, Lily; Hayes, Justin D.; Centers, Ross; Fitzwater, Sean; Loewen, Rebecca; Edmondson, Lillian R.; Bryant, Jessica M.; Smith, M Ichael J.; Rommelfanger, Claire; Welch, Valerie; Clark, Tyson A.; Sugnet, Charles W.; Howe, Kenneth J.; Mandel-Gutfreund, Yael; Ares, Manuel

doi:10.1016/j.ymeth.2005.09.007

Cited by 91 publications

(104 citation statements)

References 25 publications

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“…We next calculated the SI by dividing NI DM1 by NI control . 20 We also calculated t-test P-values of SIs between three controls and three patients.…”

Section: Resultsmentioning

confidence: 99%

Four parameters increase the sensitivity and specificity of the exon array analysis and disclose 25 novel aberrantly spliced exons in myotonic dystrophy

et al. 2012

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Myotonic dystrophy type 1 (DM1) is an RNA gain-of-function disorder in which abnormally expanded CTG repeats of DMPK sequestrate a splicing trans-factor MBNL1 and upregulate another splicing trans-factor CUGBP1. To identify a diverse array of aberrantly spliced genes, we performed the exon array analysis of DM1 muscles. We analyzed 72 exons by RT-PCR and found that 27 were aberrantly spliced, whereas 45 were not. Among these, 25 were novel and especially splicing aberrations of LDB3 exon 4 and TTN exon 45 were unique to DM1. Retrospective analysis revealed that four parameters efficiently detect aberrantly spliced exons: (i) the signal intensity is high; (ii) the ratio of probe sets with reliable signal intensities (that is, detection above background P-value ¼ 0.000) is high within a gene; (iii) the splice index (SI) is high; and (iv) SI is deviated from SIs of the other exons that can be estimated by calculating the deviation value (DV). Application of the four parameters gave rise to a sensitivity of 77.8% and a specificity of 95.6% in our data set. We propose that calculation of DV, which is unique to our analysis, is of particular importance in analyzing the exon array data. INTRODUCTIONAlternative splicing regulates developmental stage-specific and tissuespecific gene expressions and markedly expands the proteome diversity with a limited number of genes. High-throughput sequencing of total mRNAs expressed in cells has revealed that 98% or more of multiexon genes are alternatively spliced, 1 with an average of seven alternative splicing per multiexon gene. 2 Alternative splicing is achieved by exonic/intronic splicing enhancers/silencers (ESE, ISE, ESS, ISS) in combination with spatial and temporal expression of trans-acting splicing factors, such as serine/arginine-rich (SR) proteins and heterogeneous nuclear ribonucleoproteins. 3,4 Aberrations of alternative splicing are mediated by either mutations disrupting splicing cis-elements or dysregulation of splicing trans-factors. 5,6 Myotonic dystrophy is an autosomal dominant multisystem disorder affecting the skeletal muscles, eye, heart, endocrine system and central nervous system. The clinical symptoms include muscle weakness and wasting, myotonia, cataract, insulin resistance, hypogonadism, cardiac conduction defects, frontal balding and intellectual

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“…We next calculated the SI by dividing NI DM1 by NI control . 20 We also calculated t-test P-values of SIs between three controls and three patients.…”

Section: Resultsmentioning

confidence: 99%

Four parameters increase the sensitivity and specificity of the exon array analysis and disclose 25 novel aberrantly spliced exons in myotonic dystrophy

et al. 2012

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“…Johnson et al, 2003;Srinivasan et al, 2005;Shai et al, 2006) to quantify AS across many genes and to determine how AS is connected to other forms of variation in gene expression, as well as to allelic variation, signaling pathways and environmental variables. The basic idea is that each AS gene must have a number of array probes that hybridize to constitutive exons only, AS exons only and/or junctions between exons.…”

Section: Jh Mardenmentioning

confidence: 99%

Quantitative and evolutionary biology of alternative splicing: how changing the mix of alternative transcripts affects phenotypic plasticity and reaction norms

Marden

2006

Heredity

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Alternative splicing (AS) of pre-messenger RNA is a common phenomenon that creates different transcripts from a single gene, and these alternative transcripts affect phenotypes. The majority of AS research has examined tissue and developmental specificity of expression of particular AS transcripts, how this specificity affects cell function, and how aberrant AS is related to disease. Few studies have examined quantitative between-individual variation in AS within a cell or tissue type, or in relation to phenotypes, but the results are compelling: quantitative variation in AS affects plastic traits such as stress, anxiety, fear, egg production, muscle performance, energetics and plant growth. Genomic analyses of AS are also at a nascent stage, but have revealed a number of significant evolutionary patterns. Growing knowledge of upstream genes and kinases that regulate AS provides the as-yet little explored potential to examine how these genes and pathways respond to environmental and genotype variables. Research in this area can provide glimpses of a labyrinth of genetic architectures that have rarely been considered in evolutionary and organismal biology, or in quantitative genetics. The scarcity of contribution to knowledge about AS from these fields is illustrated by the fact that heritability of quantitative variation in AS has not yet been determined for any gene in any organism. New research tactics that incorporate quantitative analyses of AS will allow organismal and evolutionary biologists to attain a fuller mechanistic understanding of many of the traits they study, and may lead to more rapid discovery of functionally important polymorphisms.

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“…Another feature analyzed by array technology is SNPs and genotyping of large gene sets [278,279]. Splice variant detection is enabled by splicing-sensitive microarrays [280].…”

Section: Discussionmentioning

confidence: 99%

Transforming omics data into context: Bioinformatics on genomics and proteomics raw data

et al. 2006

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Differential gene expression analysis and proteomics have exerted significant impact on the elucidation of concerted cellular processes, as simultaneous measurement of hundreds to thousands of individual objects on the level of RNA and protein ensembles became technically feasible. The availability of such data sets has promised a profound understanding of phenomena on an aggregate level, expressed as the phenotypic response (observables) of cells, e.g., in the presence of drugs, or characterization of cells and tissue displaying distinct patho-physiological states. However, the step of transforming these data into context, i.e., linking distinct expression or abundance patterns with phenotypic observables -and furthermore enabling a sound biological interpretation on the level of reaction networks and concerted pathways, is still a major shortcoming. This finding is certainly based on the enormous complexity embedded in cellular reaction networks, but a variety of computational approaches have been developed over the last few years to overcome these issues. This review provides an overview on computational procedures for analysis of genomic and proteomic data introducing a sequential analysis workflow: Explorative statistics for deriving a first, from the purely statistical viewpoint, relevant candidate gene/protein list, followed by co-regulation and network analysis to biologically expand this core list toward functional networks and pathways. The review on these procedures is complemented by example applications tailored at identification of disease-associated proteins. Optimization of computational procedures involved, in conjunction with the continuous increase in additional biological data, clearly has the potential of boosting our understanding of processes on a cell-wide level.

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Detection and measurement of alternative splicing using splicing-sensitive microarrays

Cited by 91 publications

References 25 publications

Four parameters increase the sensitivity and specificity of the exon array analysis and disclose 25 novel aberrantly spliced exons in myotonic dystrophy

Four parameters increase the sensitivity and specificity of the exon array analysis and disclose 25 novel aberrantly spliced exons in myotonic dystrophy

Quantitative and evolutionary biology of alternative splicing: how changing the mix of alternative transcripts affects phenotypic plasticity and reaction norms

Transforming omics data into context: Bioinformatics on genomics and proteomics raw data

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