Quantification Of Isoforms Research Articles

Differential splicing analysis based on isoforms expression with NBSplice.

Alternative splicing alterations have been widely related to several human diseases revealing the importance of their study for the success of translational medicine. Differential splicing (DS) occurrence has been mainly analyzed through exon-based approaches over RNA-seq data. Although these strategies allow identifying differentially spliced genes, they ignore the identity of the affected gene isoforms which is crucial to understand the underlying pathological processes behind alternative splicing changes. Moreover, despite several isoform quantification tools for RNA-seq data have been recently developed, DS tools have not taken advantage of them. Here, the NBSplice R package for differential splicing analysis by means of isoform expression data is presented. It estimates differences on relative expressions of gene transcripts between experimental conditions to infer changes in gene alternative splicing patterns. The developed tool was evaluated using a synthetic RNA-seq dataset with controlled differential splicing. NBSplice accurately predicted DS occurrence, outperforming current methods in terms of accuracy, sensitivity, F-score, and false discovery rate control. The usefulness of our development was demonstrated by the analysis of a real cancer dataset, revealing new differentially spliced genes that could be studied pursuing new colorectal cancer biomarkers discovery.

Platform-integrated mRNA isoform quantification.

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. 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. Source code is available at: https://github.com/CompbioLabUcf/IntMTQ. Supplementary data are available at Bioinformatics online.

Critical Steps to be Taken into Consideration Before Quantification of β-Amyloid and Tau Isoforms in Blood can be Implemented in a Clinical Environment.

This review aims to document difficulties, limitations, and pitfalls when considering protein analysis in blood samples. It proposes an improved workflow for design, development, and validation of (immuno)assays for blood proteins, without providing reflections on a potential hypothesis of the origin of protein mismetabolism and deposition. There is a special focus on assay development for quantification of β-amyloid (Aβ) and tau in blood for diagnostic use or for integration in clinical trials in the field of Alzheimer’s disease (AD).

AIDE: annotation-assisted isoform discovery with high precision.

Genome-wide accurate identification and quantification of full-length mRNA isoforms is crucial for investigating transcriptional and posttranscriptional regulatory mechanisms of biological phenomena. Despite continuing efforts in developing effective computational tools to identify or assemble full-length mRNA isoforms from second-generation RNA-seq data, it remains a challenge to accurately identify mRNA isoforms from short sequence reads owing to the substantial information loss in RNA-seq experiments. Here, we introduce a novel statistical method, annotation-assisted isoform discovery (AIDE), the first approach that directly controls false isoform discoveries by implementing the testing-based model selection principle. Solving the isoform discovery problem in a stepwise and conservative manner, AIDE prioritizes the annotated isoforms and precisely identifies novel isoforms whose addition significantly improves the explanation of observed RNA-seq reads. We evaluate the performance of AIDE based on multiple simulated and real RNA-seq data sets followed by PCR-Sanger sequencing validation. Our results show that AIDE effectively leverages the annotation information to compensate the information loss owing to short read lengths. AIDE achieves the highest precision in isoform discovery and the lowest error rates in isoform abundance estimation, compared with three state-of-the-art methods Cufflinks, SLIDE, and StringTie. As a robust bioinformatics tool for transcriptome analysis, AIDE enables researchers to discover novel transcripts with high confidence.

Alternating EM algorithm for a bilinear model in isoform quantification from RNA-seq data.

Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform read distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide bias correction step(s), which is based on biological considerations-such as GC content-and applied in single samples separately. The main problem is that not all biases are known. We have developed a novel method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and is computed based on the simplifying assumptions. In contrast XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by a simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. We use an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes. In a differential-expression analysis of a real single-cell RNA-seq dataset, XAEM achieves substantially better rediscovery rates in independent validation sets. The method and pipeline are implemented as a tool and freely available for use at http://fafner.meb.ki.se/biostatwiki/xaem/. Supplementary data are available at Bioinformatics online.

Multiplexed primer extension sequencing: A targeted RNA-seq method that enables high-precision quantitation of mRNA splicing isoforms and rare pre-mRNA splicing intermediates.

The study of pre-mRNA splicing has been greatly aided by the advent of RNA sequencing (RNA-seq), which enables the genome-wide detection of discrete splice isoforms. Quantification of these splice isoforms requires analysis of splicing informative sequencing reads, those that unambiguously map to a single splice isoform, including exon-intron spanning alignments corresponding to retained introns, as well as exon-exon junction spanning alignments corresponding to either canonically- or alternatively-spliced isoforms. Because most RNA-seq experiments are designed to produce sequencing alignments that uniformly cover the entirety of transcripts, only a comparatively small number of splicing informative alignments are generated for any given splice site, leading to a decreased ability to detect and/or robustly quantify many splice isoforms. To address this problem, we have recently described a method termed Multiplexed Primer Extension sequencing, or MPE-seq, which uses pools of reverse transcription primers to target sequencing to user selected loci. By targeting reverse transcription to pre-mRNA splice junctions, this approach enables a dramatic enrichment in the fraction of splicing informative alignments generated per splicing event, yielding an increase in both the precision with which splicing efficiency can be measured, and in the detection of splice isoforms including rare splicing intermediates. Here we provide a brief review of the shortcomings associated with RNA-seq that drove our development of MPE-seq, as well as a detailed protocol for implementation of MPE-seq.

Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase ( Khk).

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.

Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase ( Khk)

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.

Abstract MP32: Mid-Life Fitness and Plasma Markers of Alzheimer’s Pathology

Introduction: Motor function in older adults is known to correlate with neurodegenerative changes and Alzheimer’s Disease (AD) pathology in the brain, however the relationship between mid-life fitness and AD pathology is unknown. AD pathology accumulates early and is difficult to measure; precise estimation requires brain imaging not accessible beyond research settings. Plasma Amyloid and Tau, on the other hand are easy to measure, and are markers of AD pathology and neuronal loss. We tested the association between physical fitness measures in mid-life (gait speed, grip strength and chair stand speed) and plasma markers of AD in the Framingham Heart Study (FHS) Offspring cohort. If these measures correlate with and predict plasma measures of AD burden, these could potentially be used to screen for risk of dementia. Hypothesis: We hypothesized that superior physical fitness will be cross-sectionally associated with higher plasma Amyloid Aβ42 and lower Tau; also, that physical fitness measures will be longitudinally associated with Tau measured at a later exam. Methods: The FHS Offspring cohort had plasma Aβ40 and Aβ42 measured at their 7th clinic exam (1998-01) and plasma total Tau measured at Exam 8 (2005-08). They had grip strength, gait speed and chair stand speed measured at Exam 7, and grip strength and gait speed measured at Exam 8. Grip strength was measured using the Jamar dynamometer, fast gait speed was measured over a 4-meter walkway and chair stand speed was assessed by asking the participants to stand up and down five times, as quickly as they can with their hands folded across their chest. Quantification of Aβ isoforms in plasma was performed using INNO-BIA assays and tau using Single Molecule Array technology.We used linear regression models to examine the association between physical fitness measures and plasma markers of AD adjusting for known confounders (diabetes, cardiovascular disease, atrial fibrillation, smoking, APOE4, systolic blood pressure, waist-to-hip ratio, total cholesterol level, physical activity index, and plasma homocysteine). Results: In this sample of 1886 community living adults (mean age 61, 54% women), hand grip strength was independently associated with plasma Aβ40 (Beta coefficient -0.28; SD 0.10; p value 0.003) and plasma Tau measured 5 years later (Beta coefficient -0.003; SD 0.001; p value 0.001). Gait speed and chair stand speed demonstrated associations with Aβ40 and total Tau which were attenuated by vascular risk factors. Conclusions: Hand grip strength is associated with AD pathology. Grip strength measurement could be a valid screening tool for identifying individuals at a higher risk for AD alongside other validated markers. Future research should examine the correlation between grip strength and AD burden measured by PET imaging.

Transferrin glycosylation analysis from dried blood spot cards and capillary blood samples

BackgroundCongenital disorders of glycosylation (CDG) are a growing group of inherited diseases causing manifold symptoms. Routine diagnostic procedures are high performance liquid chromatography (HPLC) or isoelectric focusing (IEF) of serum transferrin. MethodsWe introduce a modified method to screen for glycosylation abnormalities from dried blood spot (DBS) samples based on isoelectric focusing. In PGM1-CDG, glycosylation analysis and enzyme activity measurement were performed from a single DBS sample. Furthermore, we present the possibility to use capillary blood samples for quantification of transferrin isoforms. ResultsIEF from DBS samples is possible and results are identical to the ones obtained in serum samples. Gel analysis using the ImageJ software allows quantification of IEF results. Storage at −20 °C ensures stable samples for more than six months. Capillary blood samples are equally suitable for glycosylation analysis and show no inferiority to serum samples. ConclusionIn view of a growing number of treatable CDG subtypes, the proposed methods allow reliable diagnosis and therapy control of CDG while being easily applicable. Capillary blood samples can be taken at home and sent in for follow-up. DBS are widely used in new-born screening programs and have the potential to broaden the knowledge of glycosylation abnormalities in early infancy. By its possible application in the context of alcohol abuse, the proposed method bears the potential for widespread use in a non-metabolic context.

Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase (Khk)

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.

Guided Reconstruction of Full-Length Isoforms from Short Reads by CIDANE.

Alternative splicing allows genes to express isoforms with different coding or regulatory functions on demand. While short read deep sequencing technologies (RNA-seq) provide an immediate measurement of local splicing events, the phasing of these events along full-length isoforms requires the computational inference of long-range dependencies from short-range data points. We introduce CIDANE, a tool for the assembly and quantification of full-length isoforms from short read RNA-seq data. CIDANE bridges the gap between RNA quantification methods that rely on a complete annotation of a species' transcriptome, and transcript assembly methods that will detect novel isoforms at the cost of a lower accuracy.

Simulation-based benchmarking of isoform quantification in single-cell RNA-seq

Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. However, best practice for using existing quantification methods has not been established. We carry out a benchmark for five popular isoform quantification tools. Performance is generally good for simulated data based on SMARTer and SMART-seq2 data. The reduction in performance compared with bulk RNA-seq is small. An important biological insight comes from our analysis of real data which shows that genes that express two isoforms in bulk RNA-seq predominantly express one or neither isoform in individual cells.

Detection and Quantification of Carbohydrate-Deficient Transferrin by MALDI-Compatible Protein Chips Prepared by Ambient Ion Soft Landing.

Transferrin is synthetized in the liver and is the most important iron-transport carrier in the human body. Severe alcohol consumption leads to alterations in glycosylation of transferrin. Mass spectrometry can provide fast detection and quantification of transferrin isoforms because they have different molecular masses. In this study, we used antibody chips in combination with MALDI-TOF MS for the detection and quantification of transferrin isoforms. Protein chips were prepared by functionalization of indium tin oxide glass using ambient ion soft landing of electrosprayed antitransferrin antibody. Two microliters of patient serum was applied on the antibody-modified spots, and after incubation, washing, and matrix deposition, transferrin isoforms were detected by MALDI-TOF MS. Peak intensities of each transferrin form were used to calculate total carbohydrate-deficient transferrin (CDT). The CDT values obtained by the MALDI chip method were compared with the results obtained by a standard capillary electrophoresis (CE). The chip-based MALDI-TOF MS method was used for enrichment and detection of CDT from human serum. A sample cohort from 186 patients was analyzed. Of these samples, 44 were positively identified as belonging to alcoholic patients, whereas 142 were negative by the MALDI chip approach. The correlation of the data obtained by the CE and the chip-based MALDI was r = 0.986, 95% CI. Functionalized MALDI chips modified by antitransferrin antibody prepared by ambient ion soft landing were successfully used for detection and quantification of CDT from human sera.

Simultaneous quantification of lipopeptide isoforms by UPLC-MS in the fermentation broth from Bacillus subtilis CNPMS22.

The rapid and accurate quantification of lipopeptide families in biological samples are challenging. We present the development and validation of a method for simultaneous quantification of three families of lipopeptides (iturins, fengycins, and surfactins) and their isoforms, as well as the homologous series. The method was optimized in UPLC-MS for a column temperature at 65°C, injection volume of 5μL, and sample temperature of 10°C. The SIM mode was used for detection and quantification of lipopeptides exhibiting ions [M + H]+ and [M + 2H]2+. Since the maximum mass detection threshold of the equipment is 1250Da and the fengycins have ions between 1435 and 1505Da, the ions [M + 2H]2+ were chosen for fengycin identification. The monitored ions were as follows: m/z 1043.5, 1057.5, 1071.5, 718.3, 725.4, 739.4, 732.4, 746.4, 753.4, 1008.6, 1022.6, and 1036.6. The compounds were separated by reverse-phase chromatography using a C18 analytical column in a total time of 19min. Standard curves were linear with rw 0.99 for all analytes. Intra- and inter-day precision for samples (50, 250, and 750μgL-1) were within recommended limits. The proposed analytical method was capable of simultaneously quantifying 12 isoforms and homologous series of lipopeptide families in biological samples, thus making it an important industrial tool in the evaluation of lipopeptide production processes. Graphical abstract ᅟ.

Phenotyping and relative quantification of vitamin D binding protein in a paediatric population by using liquid chromatography-tandem mass spectrometry.

Adequate concentrations of vitamin D are required to ensure bone health and minimize the incidence of multiple extraskeletal diseases. Although total 25-hydroxyvitamin D (25OHD) remains the recommended biomarker for assessing vitamin D status, it has been speculated that free 25OHD correlates better with clinical outcomes. The calculation of free 25OHD depends on the concentrations of vitamin D binding protein (DBP), the determination of which involves different immunoassays and has led to varying results and conclusions. We developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for simultaneous identification and relative quantification of DBP isoforms. We used serum samples from healthy children ( n = 79), mainly Caucasian (88%). Proteins were denatured, reduced, alkylated and digested with trypsin. Purified peptides were analysed by LC-MS/MS. The DBP phenotype was established by using the combinations of tryptic peptides associated with each of the three isoforms and one peptide common to all of them to perform relative quantification. The genotyping of volunteers ( n = 7) facilitated verification of the ability of our method to correctly identify the DBP phenotype. The DBP phenotype was correctly established in all samples from volunteers, based on the 100% correlation observed with the genotype. The most common DBP phenotype in Caucasian children was 2/1S (34%) and the rarest 1F/1F (2%). The relative quantification of DBP concentrations did not show statistically significant differences between phenotypes ( P = 0.11). LC-MS/MS enabled simultaneous phenotyping and relative quantification of DBP, while avoiding the analytical limitations of immunoassays and confirming similar concentrations of DBP in all phenotypes.

SpliceRCA: in Situ Single-Cell Analysis of mRNA Splicing Variants

Immune cell heterogeneity due to the differential expression of RNA splicing variants still remains unexplored. This is mainly because single-cell imaging technologies of splicing variants with precise sequence or base resolution are now not readily available. Herein, we design a splice-junction anchored padlock-probe-mediated rolling circle amplification assay (SpliceRCA) for single-cell imaging of splice isoforms of essential regulatory immune gene (CD45) upon T-cell activation. Two recognition regions in the padlock probe can target the splice-junction sequence, resulting in a close proximity for triggering in situ one-target-one-amplicon amplification. With the read length of ∼30 nucleotides, this method allows discrimination of isoforms with single-base precision and quantification of isoforms with single-molecule resolution. We applied SpliceRCA to single-cell image splice variants of essential regulatory immune gene (CD45) upon T-cell activation. It is found that CD45RO isoform presents a distal nuclear spatial distribution and is coregulated with CD45RB upon activation. Our strategy provides a single-cell analysis platform to investigate the mechanism of complex immune responses and may further guide immunotherapy.

Cellulose Synthase Stoichiometry in Aspen Differs from Arabidopsis and Norway Spruce.

Cellulose is synthesized at the plasma membrane by cellulose synthase complexes (CSCs) containing cellulose synthases (CESAs). Genetic analysis and CESA isoform quantification indicate that cellulose in the secondary cell walls of Arabidopsis (Arabidopsis thaliana) is synthesized by isoforms CESA4, CESA7, and CESA8 in equimolar amounts. Here, we used quantitative proteomics to investigate whether the CSC model based on Arabidopsis secondary cell wall CESA stoichiometry can be applied to the angiosperm tree aspen (Populus tremula) and the gymnosperm tree Norway spruce (Picea abies). In the developing xylem of aspen, the secondary cell wall CESA stoichiometry was 3:2:1 for PtCESA8a/b:PtCESA4:PtCESA7a/b, while in Norway spruce, the stoichiometry was 1:1:1, as observed previously in Arabidopsis. Furthermore, in aspen tension wood, the secondary cell wall CESA stoichiometry changed to 8:3:1 for PtCESA8a/b:PtCESA4:PtCESA7a/b. PtCESA8b represented 73% of the total secondary cell wall CESA pool, and quantitative polymerase chain reaction analysis of CESA transcripts in cryosectioned tension wood revealed increased PtCESA8b expression during the formation of the cellulose-enriched gelatinous layer, while the transcripts of PtCESA4, PtCESA7a/b, and PtCESA8a decreased. A wide-angle x-ray scattering analysis showed that the shift in CESA stoichiometry in tension wood coincided with an increase in crystalline cellulose microfibril diameter, suggesting that the CSC CESA composition influences microfibril properties. The aspen CESA stoichiometry results raise the possibility of alternative CSC models and suggest that homomeric PtCESA8b complexes are responsible for cellulose biosynthesis in the gelatinous layer in tension wood.

Simultaneous Detection of Human C-Terminal p53 Isoforms by Single Template Molecularly Imprinted Polymers (MIPs) Coupled with Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)-Based Targeted Proteomics.

Abnormal expression of C-terminal p53 isoforms α, β, and γ can cause the development of cancers including breast cancer. To date, much evidence has demonstrated that these isoforms can differentially regulate target genes and modulate their expression. Thus, quantification of individual isoforms may help to link clinical outcome to p53 status and to improve cancer patient treatment. However, there are few studies on accurate determination of p53 isoforms, probably due to sequence homology of these isoforms and also their low abundance. In this study, a targeted proteomics assay combining molecularly imprinted polymers (MIPs) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed for simultaneous quantification of C-terminal p53 isoforms. Isoform-specific surrogate peptides (i.e., KPLDGEYFTLQIR (peptide-α) for isoform α, KPLDGEYFTLQDQTSFQK (peptide-β) for isoform β, and KPLDGEYFTLQMLLDLR (peptide-γ) for isoform γ) were first selected and used in both MIPs enrichment and mass spectrometric detection. The common sequence KPLDGEYFTLQ of these three surrogate peptides was used as single template in MIPs. In addition to optimization of imprinting conditions and characterization of the prepared MIPs, binding affinity and cross-reactivity of the MIPs for each surrogate peptide were also evaluated. As a result, a LOQ of 5 nM was achieved, which was >15-fold more sensitive than that without MIPs. Finally, the assay was validated and applied to simultaneous quantitative analysis of C-terminal p53 isoforms α, β, and γ in several human breast cell lines (i.e., MCF-10A normal cells, MCF-7 and MDA-MB-231 cancer cells, and drug-resistant MCF-7/ADR cancer cells). This study is among the first to employ single template MIPs and cross-reactivity phenomenon to select isoform-specific surrogate peptides and enable simultaneous quantification of protein isoforms in LC-MS/MS-based targeted proteomics.

Current and Future Methods for mRNA Analysis: A Drive Toward Single Molecule Sequencing.

The transcriptome encompasses a range of species including messenger RNA, and other noncoding RNA such as rRNA, tRNA, and short and long noncoding RNAs. Due to the huge role played by mRNA in development and disease, several methods have been developed to sequence and characterize mRNA, with RNA sequencing (RNA-Seq) emerging as the current method of choice particularly for large high-throughput studies. Short-read RNA-Seq which involves sequencing of short cDNA fragments and computationally assembling them to reconstruct the transcriptome, or aligning them to a reference is the most widely used approach. However, due to inherent limitations of this approach in de novo transcriptome assembly and isoform quantification, long-read RNA-Seq approaches, which also happen to be single molecule sequencing approaches, are increasingly becoming the standard for de novo transcriptome assembly and isoform quantification. In this chapter, we review the technical aspects of the current methods of RNA-Seq, both short and long-read approaches, and data analysis methods available. We discuss recent advances in single-cell RNA-Seq and direct RNA-Seq approaches, which perhaps will dominate the future of RNA-Seq.