Relevant bibliographies by topics / Isoform quantification

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Isoform quantification'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Isoform quantification"

1

Chabbert, Christophe D., Tanja Eberhart, Ilaria Guccini, Wilhelm Krek, and Werner J. Kovacs. "Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase (Khk)." F1000Research 7 (December 19, 2018): 1956. http://dx.doi.org/10.12688/f1000research.17082.1.

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Next generation sequencing protocols such as RNA-seq have made the genome wide characterization of the transcriptome a crucial part of many research projects in biology. Analyses of the resulting data provide key information on gene expression and in certain cases on exon or isoform usage. The emergence of transcript quantification software such as Salmon has enabled researchers to efficiently estimate isoform and gene expressions across the genome while tremendously reducing the necessary computational power. Although overall gene expression estimations were shown to be accurate, isoform expression quantifications appear to be a more challenging task. Low expression levels and uneven or insufficient coverage were reported as potential explanations for inconsistent estimates. Here, through the example of the ketohexokinase (Khk) gene in mouse, we demonstrate that the use of an incorrect gene annotation can also result in erroneous isoform quantification results. Manual correction of the input Khk gene model provided a much more accurate estimation of relative Khk isoform expression when compared to quantitative PCR (qPCR measurements). In particular, removal of an unexpressed retained intron and a proper adjustment of the 5’ and 3’ untranslated regions both had a strong impact on the correction of erroneous estimates. Finally, we observed a better concordance in isoform quantification between datasets and sequencing strategies when relying on the newly generated Khk annotations. These results highlight the importance of accurate gene models and annotations for correct isoform quantification and reassert the need for orthogonal methods of estimation of isoform expression to confirm important findings.
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Chabbert, Christophe D., Tanja Eberhart, Ilaria Guccini, Wilhelm Krek, and Werner J. Kovacs. "Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase (Khk)." F1000Research 7 (April 3, 2019): 1956. http://dx.doi.org/10.12688/f1000research.17082.2.

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Next generation sequencing protocols such as RNA-seq have made the genome-wide characterization of the transcriptome a crucial part of many research projects in biology. Analyses of the resulting data provide key information on gene expression and in certain cases on exon or isoform usage. The emergence of transcript quantification software such as Salmon has enabled researchers to efficiently estimate isoform and gene expressions across the genome while tremendously reducing the necessary computational power. Although overall gene expression estimations were shown to be accurate, isoform expression quantifications appear to be a more challenging task. Low expression levels and uneven or insufficient coverage were reported as potential explanations for inconsistent estimates. Here, through the example of the ketohexokinase (Khk) gene in mouse, we demonstrate that the use of an incorrect gene annotation can also result in erroneous isoform quantification results. Manual correction of the input Khk gene model provided a much more accurate estimation of relative Khk isoform expression when compared to quantitative PCR (qPCR measurements). In particular, removal of an unexpressed retained intron and a proper adjustment of the 5’ and 3’ untranslated regions both had a strong impact on the correction of erroneous estimates. Finally, we observed a better concordance in isoform quantification between datasets and sequencing strategies when relying on the newly generated Khk annotations. These results highlight the importance of accurate gene models and annotations for correct isoform quantification and reassert the need for orthogonal methods of estimation of isoform expression to confirm important findings.
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Sun, Jiao, Jae-Woong Chang, Teng Zhang, Jeongsik Yong, Rui Kuang, and Wei Zhang. "Platform-integrated mRNA isoform quantification." Bioinformatics 36, no. 8 (December 13, 2019): 2466–73. http://dx.doi.org/10.1093/bioinformatics/btz932.

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Abstract Motivation Accurate estimation of transcript isoform abundance is critical for downstream transcriptome analyses and can lead to precise molecular mechanisms for understanding complex human diseases, like cancer. Simplex mRNA Sequencing (RNA-Seq) based isoform quantification approaches are facing the challenges of inherent sampling bias and unidentifiable read origins. A large-scale experiment shows that the consistency between RNA-Seq and other mRNA quantification platforms is relatively low at the isoform level compared to the gene level. In this project, we developed a platform-integrated model for transcript quantification (IntMTQ) to improve the performance of RNA-Seq on isoform expression estimation. IntMTQ, which benefits from the mRNA expressions reported by the other platforms, provides more precise RNA-Seq-based isoform quantification and leads to more accurate molecular signatures for disease phenotype prediction. Results In the experiments to assess the quality of isoform expression estimated by IntMTQ, we designed three tasks for clustering and classification of 46 cancer cell lines with four different mRNA quantification platforms, including newly developed NanoString’s nCounter technology. The results demonstrate that the isoform expressions learned by IntMTQ consistently provide more and better molecular features for downstream analyses compared with five baseline algorithms which consider RNA-Seq data only. An independent RT-qPCR experiment on seven genes in twelve cancer cell lines showed that the IntMTQ improved overall transcript quantification. The platform-integrated algorithms could be applied to large-scale cancer studies, such as The Cancer Genome Atlas (TCGA), with both RNA-Seq and array-based platforms available. Availability and implementation Source code is available at: https://github.com/CompbioLabUcf/IntMTQ. Supplementary information Supplementary data are available at Bioinformatics online.
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Abendschein, D. R., H. L. Fontanet, and R. Nohara. "Optimized preservation of isoforms of creatine kinase MM isoenzyme in plasma specimens and their rapid quantification by semi-automated chromatofocusing." Clinical Chemistry 36, no. 5 (May 1, 1990): 723–27. http://dx.doi.org/10.1093/clinchem/36.5.723.

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Abstract We report a convenient chromatofocusing procedure for rapid and sensitive quantification of isoforms of the MM isoenzyme of creatine kinase (EC 2.7.3.2) in plasma and efficient methods for preserving isoform profiles during handling of specimens. The assay involves use of prepacked, re-usable Mono P chromatofocusing columns and a "Fast Protein Liquid Chromatograph" (FPLC) system with on-line detection of isoform enzymatic activity in column effluent. Profiles of isoforms are analyzed within 25 min with the use of a 1-mL column; the lower limit of sensitivity for CK activity is 5 mU, and recovery of each isoform is within 1% of the amount added to plasma. Collection of blood specimens in Vacutainer Tubes containing 28.5 mumol of EDTA (final concentration in plasma, 7 to 10 mmol/L) inhibited carboxypeptidase activity in plasma by 76%, sufficient to essentially abolish isoform conversion in vitro at room temperature. These methods should facilitate applications of isoform analysis for diagnosis of myocardial infarction and coronary artery recanalization.
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Baines, I. C., A. Corigliano-Murphy, and E. D. Korn. "Quantification and localization of phosphorylated myosin I isoforms in Acanthamoeba castellanii." Journal of Cell Biology 130, no. 3 (August 1, 1995): 591–603. http://dx.doi.org/10.1083/jcb.130.3.591.

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The actin-activated Mg(2+)-ATPase activities of the three myosin I isoforms in Acanthamoeba castellanii are significantly expressed only after phosphorylation of a single site in the myosin I heavy chain. Synthetic phosphorylated and unphosphorylated peptides corresponding to the phosphorylation site sequences, which differ for the three myosin I isoforms, were used to raise isoform-specific antibodies that recognized only the phosphorylated myosin I or the total myosin I isoform (phosphorylated and unphosphorylated), respectively. With these antisera, the amounts of total and phosphorylated isoform were quantified, the phosphomyosin I isoforms localized, and the compartmental distribution of the phosphomyosin isoforms determined. Myosin IA, which was almost entirely in the actin-rich cortex, was 70-100% phosphorylated and particularly enriched under phagocytic cups. Myosins IB and IC were predominantly associated with plasma membranes and large vacuole membranes, where they were only 10-20% phosphorylated, whereas cytoplasmic myosins IB and IC, like cytoplasmic myosin IA, were mostly phosphorylated (60-100%). Moreover, phosphomyosin IB was concentrated in actively motile regions of the plasma membrane. More than 20-fold more phosphomyosin IC and 10-fold more F-actin were associated with the membranes of contracting contractile vacuoles (CV) than of filling CVs. As the total amount of CV-associated myosin IC remained constant, it must be phosphorylated at the start of CV contraction. These data extend previous proposals for the specific functions of myosin I isozymes in Acanthamoeba (Baines, I.C., H. Brzeska, and E.D. Korn. 1992. J. Cell Biol. 119: 1193-1203): phosphomyosin IA in phagocytosis, phosphomyosin IB in phagocytosis and pinocytosis, and phosphomyosin IC in contraction of the CV.
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Mahlapuu, Margit, Carina Johansson, Kerstin Lindgren, Göran Hjälm, Brian R. Barnes, Anna Krook, Juleen R. Zierath, Leif Andersson, and Stefan Marklund. "Expression profiling of the γ-subunit isoforms of AMP-activated protein kinase suggests a major role for γ3 in white skeletal muscle." American Journal of Physiology-Endocrinology and Metabolism 286, no. 2 (February 2004): E194—E200. http://dx.doi.org/10.1152/ajpendo.00147.2003.

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Expression patterns of the three isoforms of the regulatory γ-subunit of AMP-activated protein kinase (AMPK) were determined in various tissues from adult humans, mice, and rats, as well as in human primary muscle cells. Real-time PCR-based quantification of mRNA showed similar expression patterns in the three species and a good correlation with protein expression in mice and rats. The γ3-isoform appeared highly specific to skeletal muscle, whereas γ1 and γ2 showed broad tissue distributions. Moreover, the proportion of white, type IIb fibers in the mouse and rat muscle samples, as indicated by real-time PCR quantification of Atp1b2 mRNA, showed a strong positive correlation with the expression of γ3. In samples of white skeletal muscle, γ3 clearly appeared to be the most abundant γ-isoform. Differentiation of human primary muscle cells from myoblasts into multinucleated myotubes was accompanied by upregulation of γ3 mRNA expression, whereas levels of γ1 and γ2 remained largely unchanged. However, even in these cultured myotubes, γ2 was the most highly expressed isoform, indicating a considerable difference compared with adult skeletal muscle. Immunoblot analysis of mouse gastrocnemius and quadriceps muscle extracts precipitated with a γ3-specific antibody showed that γ3 was exclusively associated with the α2- and β2-subunit isoforms. The observation that the AMPKγ3 isoform is expressed primarily in white skeletal muscle, in which it is the predominant γ-isoform, strongly suggests that γ3 has a key role in this tissue.
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Yang, Sheng, Fang Shao, Weiwei Duan, Yang Zhao, and Feng Chen. "Variance component testing for identifying differentially expressed genes in RNA-seq data." PeerJ 5 (September 8, 2017): e3797. http://dx.doi.org/10.7717/peerj.3797.

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RNA sequencing (RNA-Seq) enables the measurement and comparison of gene expression with isoform-level quantification. Differences in the effect of each isoform may make traditional methods, which aggregate isoforms, ineffective. Here, we introduce a variance component-based test that can jointly test multiple isoforms of one gene to identify differentially expressed (DE) genes, especially those with isoforms that have differential effects. We model isoform-level expression data from RNA-Seq using a negative binomial distribution and consider the baseline abundance of isoforms and their effects as two random terms. Our approach tests the global null hypothesis of no difference in any of the isoforms. The null distribution of the derived score statistic is investigated using empirical and theoretical methods. The results of simulations suggest that the performance of the proposed set test is superior to that of traditional algorithms and almost reaches optimal power when the variance of covariates is large. This method is also applied to analyze real data. Our algorithm, as a supplement to traditional algorithms, is superior at selecting DE genes with sparse or opposite effects for isoforms.
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Mageean, Craig J., John R. Griffiths, Duncan L. Smith, Michael J. Clague, and Ian A. Prior. "Absolute Quantification of Endogenous Ras Isoform Abundance." PLOS ONE 10, no. 11 (November 11, 2015): e0142674. http://dx.doi.org/10.1371/journal.pone.0142674.

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Hohenegger, M. A., L. Fineder, F. Kronenberg, A. Lingenhel, A. Gruber, G. Utermann, and H. Dieplinger. "Apolipoprotein(α) isoform-independent quantification of lipoprotein(α)." Atherosclerosis 144 (May 1999): 109. http://dx.doi.org/10.1016/s0021-9150(99)80422-5.

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Hiller, David, and Wing Hung Wong. "Simultaneous Isoform Discovery and Quantification from RNA-Seq." Statistics in Biosciences 5, no. 1 (June 14, 2012): 100–118. http://dx.doi.org/10.1007/s12561-012-9069-2.

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Dissertations / Theses on the topic "Isoform quantification"

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Huang, Yuanhua. "Structured Bayesian methods for splicing analysis in RNA-seq data." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31328.

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In most eukaryotes, alternative splicing is an important regulatory mechanism of gene expression that results in a single gene coding for multiple protein isoforms, thus largely increases the diversity of the proteome. RNA-seq is widely used for genome-wide splicing isoform quantification, and several effective and powerful methods have been developed for splicing analysis with RNA-seq data. However, it remains problematic for genes with low coverages or large number of isoforms. These difficulties may in principle be ameliorated by exploiting correlations encoded in the structured data sources. This thesis contributes to developments of Bayesian methods for splicing analysis by leveraging additional information in multiple datasets with structured prior distributions. First, we developed DICEseq, the first isoform quantification method tailored to time-series RNA-seq experiments. DICEseq explicitly models the correlations between experiments at different time points to aid the quantification of isoforms across experiments. Numerical experiments on both simulated and real datasets show that DICEseq yields more accurate results than state-of-the-art methods, an advantage that can become considerable at low coverage levels. Furthermore, DICEseq permits to quantify the trade-off between temporal sampling of RNA and depth of sequencing, frequently an important choice when planning experiments. Second, we developed BRIE (Bayesian Regression for Isoform Estimation), a Bayesian hierarchical model which resolves the difficulties in splicing analysis in single-cell RNA-seq (scRNA-seq) data by learning an informative prior distribution from sequence features. This method combines the quantification and imputation for splicing analysis via a Bayesian way, which is particularly useful in scRNA-seq data due to its extreme low coverages and high technical noises. We validated BRIE on several scRNA-seq data sets, showing that BRIE yields reproducible estimates of exon inclusion ratios in single cells. Third, we provided an effective tool by using Bayes factor to sensitively detect differential splicing between different single cells. When applying BRIE to a few real datasets, we found interesting heterogeneity patterns in splicing events across cell population, for example alternative exons in DNMT3B. In summary, this thesis proposes structured Bayesian methods to integrate multiple datasets to improve splicing analysis and study its biological functions.
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Johnson, Kristen. "Software for Estimation of Human Transcriptome Isoform Expression Using RNA-Seq Data." ScholarWorks@UNO, 2012. http://scholarworks.uno.edu/td/1448.

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The goal of this thesis research was to develop software to be used with RNA-Seq data for transcriptome quantification that was capable of handling multireads and quantifying isoforms on a more global level. Current software available for these purposes uses various forms of parameter alteration in order to work with multireads. Many still analyze isoforms per gene or per researcher determined clusters as well. By doing so, the effects of multireads are diminished or possibly wrongly represented. To address this issue, two programs, GWIE and ChromIE, were developed based on a simple iterative EM-like algorithm with no parameter manipulation. These programs are used to produce accurate isoform expression levels.
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Mangul, Serghei. "Algorithms for Transcriptome Quantification and Reconstruction from RNA-Seq Data." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/cs_diss/71.

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Massively parallel whole transcriptome sequencing and its ability to generate full transcriptome data at the single transcript level provides a powerful tool with multiple interrelated applications, including transcriptome reconstruction, gene/isoform expression estimation, also known as transcriptome quantification. As a result, whole transcriptome sequencing has become the technology of choice for performing transcriptome analysis, rapidly replacing array-based technologies. The most commonly used transcriptome sequencing protocol, referred to as RNA-Seq, generates short (single or paired) sequencing tags from the ends of randomly generated cDNA fragments. RNA-Seq protocol reduces the sequencing cost and significantly increases data throughput, but is computationally challenging to reconstruct full-length transcripts and accurately estimate their abundances across all cell types. We focus on two main problems in transcriptome data analysis, namely, transcriptome reconstruction and quantification. Transcriptome reconstruction, also referred to as novel isoform discovery, is the problem of reconstructing the transcript sequences from the sequencing data. Reconstruction can be done de novo or it can be assisted by existing genome and transcriptome annotations. Transcriptome quantification refers to the problem of estimating the expression level of each transcript. We present a genome-guided and annotation-guided transcriptome reconstruction methods as well as methods for transcript and gene expression level estimation. Empirical results on both synthetic and real RNA-seq datasets show that the proposed methods improve transcriptome quantification and reconstruction accuracy compared to previous methods.
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Kelly, Robert Noel. "Towards the absolute quantification of protein isoforms through the use of stable-isotope dilution mass spectrometry." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4401/.

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While the existence of protein was first described by Berzelius and Mulder back in 1838 and a single empirical formula noted (C400H620N100O120P1S1) (Vickery, 1950, Brand, 1946), early protein-based research was limited to the analysis of proteins which could be easily purified in large quantities, such as those obtained from blood, egg whites and those obtainable from slaughterhouses, such as digestive and metabolic enzymes (Chapman, 2005). Indeed, despite the development of recombinant deoxyribonucleic acid technologies in the 1970s (enabling protein expression) and the increasing sensitivity of techniques which enable the identification and sequencing of proteins separated by gel electrophoresis (Patterson and Aebersold, 2003), it was not until the late 1980s, with the description of soft biomolecule ionisation that large scale proteomic analyses were undertaken, based upon the use of mass spectrometry (Guerrera and Kleiner, 2005). While early mass spectrometry-based proteomic analyses focussed on the systematic identification of a great number of proteins within a single organism, the field of proteomics is now becoming increasingly quantitative (Baak et al., 2005), enabling the relative comparison of protein expression patterns between phenotypes, but also the targeted absolute quantification of specific proteins. During this project, a stable isotopically labelled internal standard based absolute quantitative technique, first described by Gerber and co-workers in 2003 (S. A. Gerber et al., 2003), was applied to the absolute quantification of three families of multiple protein isoforms. This area of research is of particular scientific interest as it is thought that up to 95% of human multi-exon genes may be subject to alternative splicing, making alternative splicing the rule, not the exception (Pan et al., 2008a). Indeed alternative splicing has also been implicated as both a cause and a consequence of disease. This technique should therefore enable both the confirmation of disease, based upon the identification of a set of phenotype specific protein biomarkers, but also the mapping of a disease’s progression (Venables, 2004). During this study, stable isotopically labelled internal standard peptides were selected for the absolute quantification of 11 confirmed protein isoforms, and two predicted protein isoforms. In addition, a separate MRM based LC-MS acquisition method was developed for the absolute quantification of each of the three families of protein isoforms (A-Raf, PDE4B and SERCA2) within a single analysis, and finally, these acquisition methods were applied to the absolute quantification of a range of immunoprecipitated, exogenously expressed protein isoforms. This project was, however, hindered by the sensitivity of the mass spectrometers available for use, preventing these acquisition methods from being applied to the absolute quantification of the endogenous levels of protein expression. While beyond the scope of this project, the further development of this quantitative technique should enable future researchers to: (i) Quantify each endogenously expressed protein isoform within a family of multiple protein isoforms. (ii) Assess any changes in the expression of each isoform in a range of cellular states, and (iii) Assess how a targeted drug treatment may affect the expression ratio of these protein isoforms.
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Bhatla, Sunetra. "Quantification and RNAi knockdown phenotype of rnp-4f isoforms during CNS development in Drosophila." Miami University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=miami1154706798.

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Strazielle, Nathalie. "Apport de l'analyse de l'ARN messager dans l'étude des variations d'expression de la gamma-glutamyltransferase et des cytochromes P-450 chez le rat : application aux phénomènes d'induction hépatique et d'ontogénèse dans le cerveau." Vandoeuvre-les-Nancy, INPL, 1991. http://www.theses.fr/1991INPL124N.

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Au sein d'un organisme eucaryote, la plupart des gènes sont activés ou inhibés à un stade précis de l'ontogénèse, dans un tissu ou une cellule particulière, ou en réponse à des molécules exogènes. De très nombreux mécanismes de régulation sont pré-traductionnels et se traduisent par une modification du taux d'ARN messager. Dans une première partie, nous avons développé et optimisé un protocole de quantification précise des taux d'ARNm, en étudiant plus particulièrement la limite de détection de la méthode et le protocole de dépôt des ARN sur slot blot. Nous avons appliqué cette technique à l'étude des phénomènes et mécanismes d'induction hépatique chez le rat. Nous avons caractérisé les effets de deux inducteurs, le RP 52028 et la dantrolène sur les taux d'ARNm codant pour différentes isoformes de cytochrome p-450. Nous avons confronté ces variations de taux de messagers avec celles observées pour les activités enzymatiques correspondantes, afin de préciser le ou les mécanismes impliqués. Nous avons déterminé les effets des mêmes molécules sur le taux d'ARNm codant pour la gamma-glutamyltransferase, et mis en évidence une corrélation entre cette enzyme et les isoformes P-450 2b1/2 après traitement par le RP 52028. Dans une seconde partie, nous avons analysé l'expression de l'ARN GGT dans le cerveau lors du développement, en parallèle avec la mesure de son activité enzymatique et observé une évolution différente pour les deux paramètres. Enfin, nous avons précisé la structure de l'extrémité 5 de l'ARN et montré que le messager exprimé dans le cerveau est diffèrent de l’ARN transcrit spécifiquement dans le rein
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Chen, Yi-Yuan, and 陳奕源. "Quantification of MxA mRNA isoform and regulation of MxA gene by Herpes Simplex Virus type I." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/29651544841057609447.

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碩士
臺灣大學
免疫學研究所
98
Herpes simplex virus 1 (HSV-1) is a member of human alphaherpesviruses which has evolved different strategies to evade type I interferon (IFN) response. Mammalian Mx proteins are dynamin-like GTPases that are induced by interferon (IFN) α/β and have antiviral activity against RNA viruses. Our previous studies have found that HSV-1 induces an alternatively spliced MxA isoform (varMxA) to enhance viral replication in primary human fibroblast in the absence of IFN triggering. In this study experiments have been designed to investigate expression of MxA isoforms in IFN-treated versus HSV-1 infected fibroblasts as well as the effect of HSV-1 on MxA promoter activity in luciferase reporter system. MxA isoform-specific primers were designed and used to measure the expression of MxA and varMxA transcripts in IFN-treated or HSV-1 infected human fibroblasts by real-time PCR analysis. The results showed that IFN-α treatment induced both MxA and varMxA expression at least 100 folds and remained stable over the 24h-course of treatment. Whereas HSV-1 infection resulted in degradation of housekeeping genes such as β-actin and GAPDH, expression of MxA and varMxA transcripts remained stable and increased slightly over an interval of at least 10h and started to decline at 24h after infection. These data suggested that either IFN-α or HSV-1 stimulated the expression of MxA and varMxA mRNA. The importance that MxA isoforms were not degraded but rather selectively remained expression in HSV-1 infected cells is deserved for further investigation. HSV-1 mediated MxA promoter activity was evaluated by transient transfection of melanoma cells with a luciferase reporter plasmid containing MxA promoter region (-533 to -1). HSV-1 infection result in the activation of MxA promoter by 5 folds was not dependent on ISRE (IFN-stimulated response element) binding since disruption of ISRE1 and ISRE2 binding sites did not eliminate MxA promoter activity after HSV-1 infection. However, HSV-1 mediated luciferase activity from MxA promoter mutant constructs with deletion in the frangment from -533 to -250 was significantly reduced to basal level. Site-directed mutagenesis at ICP4/TFIID putative binding site at -317 to -306 also showed a reduced luciferase activity either by HSV-1 infection or by co-transfection with a plasmid expressing ICP4. These experiments have demonstrated that ICP4 was able to trans activate MxA gene. Whether the effect requires the coorperation with cellular transcription factor TFIID remains to be elucidated.
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Too, Heng-Phon, and Winnie Kar Yee Fung. "Quantification and signaling of alternatively spliced GFRα2 isoforms." 2003. http://hdl.handle.net/1721.1/3789.

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Neurturin (NTN) belongs to the glial cell-line derived neurotrophic factor (GDNF) family of growth factors. Both NTN and GDNF have been shown to potently prevent the degeneration of dopaminergic neuron in vitro and in vivo. The GDNF family receptor alpha 2 (GFRα-2) is the preferred receptor for NTN. In addition to the known full-length isoform (GFRα-2a), we have previously reported the isolation of two novel alternatively spliced isoforms (GFRα-2b and GFRα-2c). The expression levels of these isoforms have yet to be quantified and the functional properties determined. In this report, we have developed a real time polymerase chain reaction (PCR) using SYBR Green I to detect the expression levels of the three splice variants (GFRα-2a, GFRα-2b and GFRα-2c) in murine tissues. Both GFRα-2a and GFRα-2c were expressed at similar levels in all tissues examined. GFRα-2b was found to be 10 fold lower in expression. All three isoforms activated MAPK (ERK1/2) and Akt. Transcriptional profiling with DNA microarrays demonstrated that the spliced isoforms do not share similar profiles. In conclusion, we have now shown the expression levels of the spliced variants. All three isoforms are functional. However, each isoform appeared to have unique transcriptional profiles when activated.
Singapore-MIT Alliance (SMA)
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Divelbiss, Michelle. "Developing MenaCalc: an assay to predict risk of breast cancer tumor metastasis through quantification of Mena protein isoforms." Thesis, 2016. https://hdl.handle.net/2144/16749.

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Metastasis is the leading cause of poor prognosis for individuals diagnosed with cancer. Breast cancer is particularly prevalent with 1 in 10 women receiving a breast cancer diagnosis in her lifetime. There are various types of breast cancers that are distinguished by molecular subtype as defined by specific biomarker expression profiles: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). The subtypes defined by the varying expression of these receptors respond differently to cancer treatments. For example, luminal A ([ER/PR+] HER2- KI67-) responds well to endocrine therapy and patients generally have a good prognosis, whereas triple negative breast cancer (TNBC) ([ER/PR-] HER2- basal marker+) has no specific targeted treatment available and the prognosis is usually poor. Patients with the HER2 subtype often develop resistance to the treatment specific to the breast cancer molecular subtype. Since 90% of all cancer-related deaths are due to metastatic disease, effectively treating all of these types of breast cancers before metastasis is an important factor in achieving a more positive outcome, In order for metastasis to occur, a tumor cell must have the ability to mobilize, intravasate into the vasculature, and then extravasate and proliferate into a tumor at a distant site. Numerous biological and environmental factors must facilitate each of these steps in order for metastasis to occur. One biomarker of metastasis is a tumor microenvironment of metastasis (TMEM). A TMEM is the physical apposition of a Mena-expressing tumor cell, a macrophage (a type of white blood cell), and an endothelial cell (a blood vessel cell). Each TMEM component plays a key role in breast cancer biology. The automated clinical assay MetaSite BreastTM was developed by MetaStat, Inc. to quantify TMEMs. The MetaSiteTM score directly correlates with risk of developing metastasis. The Mena protein is involved in cell motility and expressed isoforms can either promote metastasis (for example, MenaINV), or protect and prevent metastasis (for example, Mena11a). These isoforms are not expressed in a binary manner and studies have shown that the ratio of MenaINV to Mena11a can give insight into the pro-metastatic/anti-metastatic biology of the cell. To indirectly measure the amount of MenaINV, the Z-score of Mena11a is subtracted from the Z-score of pan-Mena (all Mena isoforms), yielding a theoretical maximum amount of MenaINV, called Menacalc. This process is performed by quantitative analysis of multiplexed immunofluorescence staining through the MenaCalcTM assay developed by MetaStat, Inc. The results of this study demonstrated that MenaCalcTM is a high-performing, high-throughput assay that was clinically validated under CLIA-approved protocol in January 2016. The assay surpassed all benchmark goals for precision and performance. For both day-to-day and run-to-run operations, precision and reproducibility were analyzed using Pearson’s R and slope. The day-to-day reproducibility yielded Pearson’s R values of 0.879 and 0.853 comparing Day 1 vs. Day 2 and Day 2 vs. Day 3, respectively. The slopes for the same comparisons were 0.985 and 0.982, respectively. The analysis of run-to-run precision had Pearson’s R values of 0.999 and 0.994 comparing Day 1 vs. Day 2 and Day 2 vs. Day 3, respectively. The slopes were 0.999 for both comparisons. The development of such an assay brings new elements of precision and reproducibility to the current market of breast cancer biomarker tests. Statistical analysis revealed a wide range of MenaCalcTM scores that were independent of total Mena expression. Individual images showed a range of MenaCalcTM values from a low of only 2.9% of cells with a high MenaCalcTM score to a high of 97.4% of cells with a high MenaCalcTM score. Regions of high MenaCalcTM scores correlated with areas of invasive tumor. Preliminary data assessing the synergistic use of both the MetaSite BreastTM and the MenaCalcTM assays were promising. These data suggests that both physical MetaSiteTM structures and protein expression levels can be used to more thoroughly understand the biology of breast cancer and the path to metastasis. Three clusters of combined MetaSiteTM/MenaCalcTM scores were observed: MetaSiteTM low/MenaCalcTM low, MetaSiteTM low/MenaCalcTM high, MetaSiteTM high/MenaCalcTM high. Because a MetaSiteTM High/MenaCalcTM Low score combination was not observed, a high MenaCalcTM score may be necessary for TMEM formation. Studies are ongoing to further evaluate the synergy of the MetaSite BreastTM and the MenaCalcTM in order to bring more power to the assessment of metastatic risk.
2016-12-16T00:00:00Z
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Liu, X., L. Hu, G. Ge, B. Yang, J. Ning, S. Sun, L. Yang, Klaus Pors, and J. Gu. "Quantitative analysis of cytochrome P450 isoforms in human liver microsomes by the combination of proteomics and chemical probe-based assay." 2014. http://hdl.handle.net/10454/10502.

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Cytochrome P450 (CYP) is one of the most important drug-metabolizing enzyme families, which participates in the biotransformation of many endogenous and exogenous compounds. Quantitative analysis of CYP expression levels is important when studying the efficacy of new drug molecules and assessing drug-drug interactions in drug development. At present, chemical probe-based assay is the most widely used approach for the evaluation of CYP activity although there are cross-reactions between the isoforms with high sequence homologies. Therefore, quantification of each isozyme is highly desired in regard to meeting the ever-increasing requirements for carrying out pharmacokinetics and personalized medicine in the academic, pharmaceutical, and clinical setting. Herein, an absolute quantification method was employed for the analysis of the seven isoforms CYP1A2, 2B6, 3A4, 3A5, 2C9, 2C19, and 2E1 using a proteome-derived approach in combination with stable isotope dilution assay. The average absolute amount measured from twelve human liver microsomes samples were 39.3, 4.3, 54.0, 4.6, 10.3, 3.0, and 9.3 (pmol/mg protein) for 1A2, 2B6, 3A4, 3A5, 2C9, 2C19, and 2E1, respectively. Importantly, the expression level of CYP3A4 showed high correlation (r = 0.943, p < 0.0001) with the functional activity, which was measured using bufalin-a highly selective chemical probe we have developed. The combination of MRM identification and analysis of the functional activity, as in the case of CYP3A4, provides a protocol which can be extended to other functional enzyme studies with wide application in pharmaceutical research.
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Book chapters on the topic "Isoform quantification"

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Gamini, Ramya, Reiko Nakashima, Wen He, Chi Zhang, Ying Huang, Ying Zhang, Baohong Zhang, and Shanrong Zhao. "QuickIsoSeq for Isoform Quantification in Large-Scale RNA Sequencing." In Methods in Molecular Biology, 135–45. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1307-8_8.

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Vernes, Jean-Michel, and Y. Gloria Meng. "Detection and Quantification of VEGF Isoforms by ELISA." In Methods in Molecular Biology, 25–37. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2917-7_2.

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Bru-Martínez, Roque, Ascensión Martínez-Márquez, Jaime Morante-Carriel, Susana Sellés-Marchart, María José Martínez-Esteso, José Luis Pineda-Lucas, and Ignacio Luque. "Targeted Quantification of Isoforms of a Thylakoid-Bound Protein: MRM Method Development." In Methods in Molecular Biology, 147–62. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7411-5_10.

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Lin, Yen-Yi, Phuong Dao, Faraz Hach, Marzieh Bakhshi, Fan Mo, Anna Lapuk, Colin Collins, and S. Cenk Sahinalp. "CLIIQ: Accurate Comparative Detection and Quantification of Expressed Isoforms in a Population." In Lecture Notes in Computer Science, 178–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33122-0_14.

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5

Eis, Peggy S., and Mariano A. Garcia-Blanco. "Quantification of MicroRNAs, Splicing Isoforms, and Homologous mRNAs With the Invader Assay." In Methods in Molecular Biology, 279–318. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-60327-475-3_20.

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Koelsch, Kristi A. "Single-Cell High-Resolution Detection and Quantification of Protein Isoforms Differing by a Single Charge Unit." In Methods in Molecular Biology, 501–9. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8793-1_44.

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Zmuidinaite, Raminta, Ray K. Iles, Ricardo J. Pais, and Stephen A. Butler. "Detection and quantification of hCG and its isoforms with MALDI-ToF mass spectrometry." In 100 Years of Human Chorionic Gonadotropin, 75–85. Elsevier, 2020. http://dx.doi.org/10.1016/b978-0-12-820050-6.00008-4.

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Conference papers on the topic "Isoform quantification"

1

Howard, Brian E., and Steffen Heber. "Towards Reliable Isoform Quantification Using RNA-Seq Data." In 2009 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2009. http://dx.doi.org/10.1109/bibm.2009.70.

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Howard, Brian E., Paola Veronese, and Steffen Heber. "Improved RNA-Seq Partitions in Linear Models for Isoform Quantification." In 2011 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2011. http://dx.doi.org/10.1109/bibm.2011.102.

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Herrick, William G., Casey L. Kilpatrick, Melinda Hollingshead, James H. Doroshow, Ralph E. Parchment, and Apurva K. Srivastava. "Abstract B081: Elucidating the pharmacodynamics of PI3K and Ras-Raf signaling through isoform-specific multiplexed quantification of downstream effector phosphorylation." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; October 26-30, 2017; Philadelphia, PA. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1535-7163.targ-17-b081.

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Bergquist, Maria, Javier Sanchez, and Göran Hedenstierna. "Subcellular Visualization And Quantification Of Glucocorticoid Receptor Isoforms Alpha And Beta In Human Leucocytes." In American Thoracic Society 2010 International Conference, May 14-19, 2010 • New Orleans. American Thoracic Society, 2010. http://dx.doi.org/10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a5721.

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Fan, Alice C., Jessica L. Dermody, Christina Kong, Nancy Zhang, Mathias W. Orban, Reetesh Pai, Liwen Xu, et al. "Abstract B178: Nanoscale quantification of phosphorylated and unphosphorylated ERK and MEK isoforms differentiates tumor and nontumor clinical specimens." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics--Nov 15-19, 2009; Boston, MA. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/1535-7163.targ-09-b178.

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Ke, Zhiyuan, Sifang Wang, Vithya Manoharan, Susmitha Vuddagiri, Esther Ong, Sharon Lim, Sin Tiong Ong, et al. "Abstract 3819: Identification and quantification of isoforms of eukaryotic initiation factor 4E as biomarker in Mnk inhibitor-treated mouse model by capillary-based immunoassay platform." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-3819.

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