Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions.

SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.

timsTOF HT Improves Protein Identification and Quantitative Reproducibility for Deep Unbiased Plasma Protein Biomarker Discovery.

Mass spectrometry (MS) is a valuable tool for plasma proteome profiling and disease biomarker discovery. However, wide-ranging plasma protein concentrations, along with technical and biological variabilities, present significant challenges for deep and reproducible protein quantitation. Here, we evaluated the qualitative and quantitative performance of timsTOF HT and timsTOF Pro 2 mass spectrometers for analysis of neat plasma samples (unfractionated) and plasma samples processed using the Proteograph Product Suite (Proteograph) that enables robust deep proteomics sampling prior to mass spectrometry. Samples were evaluated across a wide range of peptide loading masses and liquid chromatography (LC) gradients. We observed up to a 76% increase in total plasma peptide precursors identified and a >2-fold boost in quantifiable plasma peptide precursors (CV < 20%) with timsTOF HT compared to Pro 2. Additionally, approximately 4.5 fold more plasma peptide precursors were detected by both timsTOF HT and timsTOF Pro 2 in the Proteograph analyzed plasma vs neat plasma. In an exploratory analysis of 20 late-stage lung cancer and 20 control plasma samples with the Proteograph, which were expected to exhibit distinct proteomes, an approximate 50% increase in total and statistically significant plasma peptide precursors (q < 0.05) was observed with timsTOF HT compared to Pro 2. Our data demonstrate the superior performance of timsTOF HT for identifying and quantifying differences between biologically diverse samples, allowing for improved disease biomarker discovery in large cohort studies. Moreover, researchers can leverage data sets from this study to optimize their liquid chromatography-mass spectrometry (LC-MS) workflows for plasma protein profiling and biomarker discovery. (ProteomeXchange identifier: PXD047854 and PXD047839).

Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects.

BACKGROUND: The aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format-electrochemiluminescence immunoassays-to quantify protein concentrations. The aim was achieved by building and validating a CRC classifier using concentration measures from a large sample set representing a true intent-to-test (ITT) symptomatic population. METHODS: 4435 patient samples were drawn from the Endoscopy II sample set. Samples were collected at seven hospitals across Denmark between 2010 and 2012 from subjects with symptoms of colorectal neoplasia. Colonoscopies revealed the presence or absence of CRC. 27 blood plasma proteins were selected as candidate biomarkers based on previous studies. Multiplexed electrochemiluminescence assays were used to measure the concentrations of these 27 proteins in all 4435 samples. 3066 patients were randomly assigned to the Discovery set, in which machine learning was used to build candidate classifiers. Some classifiers were refined by allowing up to a 25% indeterminate score range. The classifier with the best Discovery set performance was successfully validated in the separate Validation set, consisting of 1336 samples. RESULTS: The final classifier was a logistic regression using ten predictors: eight proteins (A1AG, CEA, CO9, DPPIV, MIF, PKM2, SAA, TFRC), age, and gender. In validation, the indeterminate rate of the new panel was 23.2%, sensitivity/specificity was 0.80/0.83, PPV was 36.5%, and NPV was 97.1%. CONCLUSIONS: The validated classifier serves as the basis of a new blood-based CRC test for symptomatic patients. The improved performance, resulting from robust concentration measures across a large sample set mirroring the ITT population, renders the new test the best available for this population. Results from a test using this classifier can help assess symptomatic patients' CRC risk, increase their colonoscopy compliance, and manage next steps in their care.

HITS-CLIP yields genome-wide insights into brain alternative RNA processing.

Protein-RNA interactions have critical roles in all aspects of gene expression. However, applying biochemical methods to understand such interactions in living tissues has been challenging. Here we develop a genome-wide means of mapping protein-RNA binding sites in vivo, by high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP). HITS-CLIP analysis of the neuron-specific splicing factor Nova revealed extremely reproducible RNA-binding maps in multiple mouse brains. These maps provide genome-wide in vivo biochemical footprints confirming the previous prediction that the position of Nova binding determines the outcome of alternative splicing; moreover, they are sufficiently powerful to predict Nova action de novo. HITS-CLIP revealed a large number of Nova-RNA interactions in 3' untranslated regions, leading to the discovery that Nova regulates alternative polyadenylation in the brain. HITS-CLIP, therefore, provides a robust, unbiased means to identify functional protein-RNA interactions in vivo.

Nova regulates brain-specific splicing to shape the synapse.

Alternative RNA splicing greatly increases proteome diversity and may thereby contribute to tissue-specific functions. We carried out genome-wide quantitative analysis of alternative splicing using a custom Affymetrix microarray to assess the role of the neuronal splicing factor Nova in the brain. We used a stringent algorithm to identify 591 exons that were differentially spliced in the brain relative to immune tissues, and 6.6% of these showed major splicing defects in the neocortex of Nova2-/- mice. We tested 49 exons with the largest predicted Nova-dependent splicing changes and validated all 49 by RT-PCR. We analyzed the encoded proteins and found that all those with defined brain functions acted in the synapse (34 of 40, including neurotransmitter receptors, cation channels, adhesion and scaffold proteins) or in axon guidance (8 of 40). Moreover, of the 35 proteins with known interaction partners, 74% (26) interact with each other. Validating a large set of Nova RNA targets has led us to identify a multi-tiered network in which Nova regulates the exon content of RNAs encoding proteins that interact in the synapse.

Alternative splicing regulates mouse embryonic stem cell pluripotency and differentiation.

Two major goals of regenerative medicine are to reproducibly transform adult somatic cells into a pluripotent state and to control their differentiation into specific cell fates. Progress toward these goals would be greatly helped by obtaining a complete picture of the RNA isoforms produced by these cells due to alternative splicing (AS) and alternative promoter selection (APS). To investigate the roles of AS and APS, reciprocal exon-exon junctions were interrogated on a genome-wide scale in differentiating mouse embryonic stem (ES) cells with a prototype Affymetrix microarray. Using a recently released open-source software package named AltAnalyze, we identified 144 genes for 170 putative isoform variants, the majority (67%) of which were predicted to alter protein sequence and domain composition. Verified alternative exons were largely associated with pathways of Wnt signaling and cell-cycle control, and most were conserved between mouse and human. To examine the functional impact of AS, we characterized isoforms for two genes. As predicted by AltAnalyze, we found that alternative isoforms of the gene Serca2 were targeted by distinct microRNAs (miRNA-200b, miRNA-214), suggesting a critical role for AS in cardiac development. Analysis of the Wnt transcription factor Tcf3, using selective knockdown of an ES cell-enriched and characterized isoform, revealed several distinct targets for transcriptional repression (Stmn2, Ccnd2, Atf3, Klf4, Nodal, and Jun) as well as distinct differentiation outcomes in ES cells. The findings herein illustrate a critical role for AS in the specification of ES cells with differentiation, and highlight the utility of global functional analyses of AS.

Functionally distinct BMP1 isoforms show an opposite pattern of abundance in plasma from non-small cell lung cancer subjects and controls.

Advancements in deep plasma proteomics are enabling high-resolution measurement of plasma proteoforms, which may reveal a rich source of novel biomarkers previously concealed by aggregated protein methods. Here, we analyze 188 plasma proteomes from non-small cell lung cancer subjects (NSCLC) and controls to identify NSCLC-associated protein isoforms by examining differentially abundant peptides as a proxy for isoform-specific exon usage. We find four proteins comprised of peptides with opposite patterns of abundance between cancer and control subjects. One of these proteins, BMP1, has known isoforms that can explain this differential pattern, for which the abundance of the NSCLC-associated isoform increases with stage of NSCLC progression. The presence of cancer and control-associated isoforms suggests differential regulation of BMP1 isoforms. The identified BMP1 isoforms have known functional differences, which may reveal insights into mechanisms impacting NSCLC disease progression.

Evaluation of genetic variation contributing to differences in gene expression between populations.

Gene expression is a complex quantitative trait partially regulated by genetic variation in DNA sequence. Population differences in gene expression could contribute to some of the observed differences in susceptibility to common diseases and response to drug treatments. We characterized gene expression in the full set of HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry for 9156 transcript clusters (gene-level) evaluated with the Affymetrix GeneChip Human Exon 1.0 ST Array. Gene expression was found to differ significantly between these samples for 383 transcript clusters. Biological processes including ribosome biogenesis and antimicrobial humoral response were found to be enriched in these differential genes, suggesting their possible roles in contributing to the population differences at a higher level than that of mRNA expression and in response to environmental information. Genome-wide association studies for local or distant genetic variants that correlate with the differentially expressed genes enabled identification of significant associations with one or more single-nucleotide polymorphisms (SNPs), consistent with the hypothesis that genetic factors and not simply population identity or other characteristics (age of cell lines, length of culture, etc.) contribute to differences in gene expression in these samples. Our results provide a comprehensive view of the genes differentially expressed between populations and the enriched biological processes involved in these genes. We also provide an evaluation of the contributions of genetic variation and nongenetic factors to the population differences in gene expression.

Genetic architecture of transcript-level variation in humans.

We report here the results of testing the pairwise association of 12,747 transcriptional gene-expression values with more than two million single-nucleotide polymorphisms (SNPs) in samples of European (CEPH from Utah; CEU) and African (Yoruba from Ibadan; YRI) ancestry. We found 4,677 and 5,125 significant associations between expression quantitative nucleotides (eQTNs) and transcript clusters in the CEU and the YRI samples, respectively. The physical distance between an eQTN and its associated transcript cluster was referred to as the intrapair distance. An association with 4 Mb or less intrapair distance was defined as local; otherwise, it was defined as distant. The enrichment analysis of functional categories shows that genes harboring the local eQTNs are enriched in the categories related to nucleosome and chromatin assembly; the genes harboring the distant eQTNs are enriched in the categories related to transmembrane signal transduction, suggesting that these biological pathways are likely to play a significant role in regulation of gene expression. We highlight in the EPHX1 gene a deleterious nonsynonymous SNP that is distantly associated with gene expression of ORMDL3, a susceptibility gene for asthma.

Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona.

Large-scale, unbiased proteomics studies are constrained by the complexity of the plasma proteome. Here we report a highly parallel protein quantitation platform integrating nanoparticle (NP) protein coronas with liquid chromatography-mass spectrometry for efficient proteomic profiling. A protein corona is a protein layer adsorbed onto NPs upon contact with biofluids. Varying the physicochemical properties of engineered NPs translates to distinct protein corona patterns enabling differential and reproducible interrogation of biological samples, including deep sampling of the plasma proteome. Spike experiments confirm a linear signal response. The median coefficient of variation was 22%. We screened 43 NPs and selected a panel of 5, which detect more than 2,000 proteins from 141 plasma samples using a 96-well automated workflow in a pilot non-small cell lung cancer classification study. Our streamlined workflow combines depth of coverage and throughput with precise quantification based on unique interactions between proteins and NPs engineered for deep and scalable quantitative proteomic studies.

Identification of common genetic variants that account for transcript isoform variation between human populations.

In addition to the differences between populations in transcriptional and translational regulation of genes, alternative pre-mRNA splicing (AS) is also likely to play an important role in regulating gene expression and generating variation in mRNA and protein isoforms. Recently, the genetic contribution to transcript isoform variation has been reported in individuals of recent European descent. We report here results of an investigation of the differences in AS patterns between human populations. AS patterns in 176 HapMap lymphoblastoid cell lines derived from individuals of European and African ancestry were evaluated using the Affymetrix GeneChip Human Exon 1.0 ST Array. A variety of biological processes such as response to stimulus and transcription were found to be enriched among the differentially spliced genes. The differentially spliced genes also include some involved in human diseases that have different prevalence or susceptibility between populations. The genetic contribution to the population differences in transcript isoform variation was then evaluated by a genome-wide association using the HapMap genotypic data on single nucleotide polymorphisms (SNPs). The results suggest that local and distant genetic variants account for a substantial fraction of the observed transcript isoform variation between human populations. Our findings provide new insights into the complexity of the human genome as well as the health disparities between the two populations.

A correlation with exon expression approach to identify cis-regulatory elements for tissue-specific alternative splicing.

Correlation of motif occurrences with gene expression intensity is an effective strategy for elucidating transcriptional cis-regulatory logic. Here we demonstrate that this approach can also identify cis-regulatory elements for alternative pre-mRNA splicing. Using data from a human exon microarray, we identified 56 cassette exons that exhibited higher transcript-normalized expression in muscle than in other normal adult tissues. Intron sequences flanking these exons were then analyzed to identify candidate regulatory motifs for muscle-specific alternative splicing. Correlation of motif parameters with gene-normalized exon expression levels was examined using linear regression and linear splines on RNA words and degenerate weight matrices, respectively. Our unbiased analysis uncovered multiple candidate regulatory motifs for muscle-specific splicing, many of which are phylogenetically conserved among vertebrate genomes. The most prominent downstream motifs were binding sites for Fox1- and CELF-related splicing factors, and a branchpoint-like element acuaac; pyrimidine-rich elements resembling PTB-binding sites were most significant in upstream introns. Intriguingly, our systematic study indicates a paucity of novel muscle-specific elements that are dominant in short proximal intronic regions. We propose that Fox and CELF proteins play major roles in enforcing the muscle-specific alternative splicing program, facilitating expression of unique isoforms of cytoskeletal proteins critical to muscle cell function.

A large-scale and robust dynamic MRM study of colorectal cancer biomarkers.

Over the past 20 years, mass spectrometry (MS) has emerged as a dynamic tool for proteomics biomarker discovery. However, published MS biomarker candidates often do not translate to the clinic, failing during attempts at independent replication. The cause can be shortcomings in study design, sample quality, assay quantitation, and/or quality/process control. To address these shortcomings, we developed an MS workflow in accordance with Tier 2 measurement requirements for targeted peptides, defined by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) "fit-for-purpose" approach, using dynamic multiple reaction monitoring (dMRM), which measures specific peptide transitions during predefined retention time (RT) windows. We describe the development of a robust multipex dMRM assay measuring 641 proteotypic peptides from 392 colorectal cancer (CRC) related proteins, and the procedures to track and handle sample processing and instrument variation over a four-month study, during which the assay measured blood samples from 1045 patients with CRC symptoms. After data collection, transitions were filtered by signal quality metrics before entering receiver operating characteristic (ROC) analysis. The results demonstrated CRC signal carried by 127 proteins in the symptomatic population. The workflow might be further developed to build Tier 1 assays for clinical tests identifying symptomatic individuals at elevated risk of CRC. SIGNIFICANCE: We developed a dMRM MS method with the rigor of a Tier 2 assay as defined by the CPTAC 'fit for purpose approach' [1]. Using quality and process control procedures, the assay was used to quantify 641 proteotypic peptides representing 392 CRC-related proteins in plasma from 1045 CRC-symptomatic patients. To our knowledge, this is the largest MRM method applied to the largest study to date. The results showed that 127 of the proteins carried univariate CRC signal in the symptomatic population. This large number of single biomarkers bodes well for future development of multivariate classifiers to distinguish CRC in the symptomatic population.

Unusual intron conservation near tissue-regulated exons found by splicing microarrays.

Alternative splicing contributes to both gene regulation and protein diversity. To discover broad relationships between regulation of alternative splicing and sequence conservation, we applied a systems approach, using oligonucleotide microarrays designed to capture splicing information across the mouse genome. In a set of 22 adult tissues, we observe differential expression of RNA containing at least two alternative splice junctions for about 40% of the 6,216 alternative events we could detect. Statistical comparisons identify 171 cassette exons whose inclusion or skipping is different in brain relative to other tissues and another 28 exons whose splicing is different in muscle. A subset of these exons is associated with unusual blocks of intron sequence whose conservation in vertebrates rivals that of protein-coding exons. By focusing on sets of exons with similar regulatory patterns, we have identified new sequence motifs implicated in brain and muscle splicing regulation. Of note is a motif that is strikingly similar to the branchpoint consensus but is located downstream of the 5' splice site of exons included in muscle. Analysis of three paralogous membrane-associated guanylate kinase genes reveals that each contains a paralogous tissue-regulated exon with a similar tissue inclusion pattern. While the intron sequences flanking these exons remain highly conserved among mammalian orthologs, the paralogous flanking intron sequences have diverged considerably, suggesting unusually complex evolution of the regulation of alternative splicing in multigene families.

Matrix metalloproteinases contribute to insulin insufficiency in Zucker diabetic fatty rats.

To assess the molecular changes associated with pancreatic beta-cell dysfunction occurring during the onset of type 2 diabetes, we profiled pancreatic islet mRNAs from diabetic male and high-fat-fed female Zucker diabetic fatty (ZDF) rats and their nondiabetic lean counterparts on custom islet-specific oligonucleotide arrays. The most prominent changes in both the male and female models of type 2 diabetes were increases in the mRNAs encoding proteases and extracellular matrix components that are associated with tissue remodeling and fibrosis. The mRNAs for metalloproteinase (MMP)-2, -12, and -14 were sharply increased with the onset of islet dysfunction and diabetes. Zymography of islet extracts revealed a concurrent, >10-fold increase in MMP-2 protease activity in islets from 9-week-old male ZDF rats. Treatment of female ZDF rats receiving a diabetogenic diet with PD166793, a broad-spectrum MMP inhibitor, substantially prevented diabetes. The effect of this compound was due in part to marked beta-cell expansion. These studies indicate that MMPs contribute to islet fibrosis and insulin insufficiency in ZDF rats. Class-targeted protease inhibitors should be explored for their potential therapeutic utility in preservation of beta-cell mass in type 2 diabetes.

Discovery and Validation of Plasma-Protein Biomarker Panels for the Detection of Colorectal Cancer and Advanced Adenoma in a Danish Collection of Samples from Patients Referred for Diagnostic Colonoscopy.

BACKGROUND: Well-collected and well-documented sample repositories are necessary for disease biomarker development. The availability of significant numbers of samples with the associated patient information enables biomarker validation to proceed with maximum efficacy and minimum bias. The creation and utilization of such a resource is an important step in the development of blood-based biomarker tests for colorectal cancer. METHODS: We have created a subject data and biological sample resource, Endoscopy II, which is based on 4698 individuals referred for diagnostic colonoscopy in Denmark between May 2010 and November 2012. Of the patients referred based on 1 or more clinical symptoms of colorectal neoplasia, 512 were confirmed by pathology to have colorectal cancer and 399 were confirmed to have advanced adenoma. Using subsets of these sample groups in case-control study designs (300 patients for colorectal cancer, 302 patients for advanced adenoma), 2 panels of plasma-based proteins for colorectal cancer and 1 panel for advanced adenoma were identified and validated based on ELISA data obtained for 28 proteins from the samples. RESULTS: One of the validated colorectal cancer panels was comprised of 8 proteins (CATD, CEA, CO3, CO9, SEPR, AACT, MIF, and PSGL) and had a validation ROC curve area under the curve (AUC) of 0.82 (CI 0.75-0.88). There was no significant difference in the performance between early- and late-stage cancer. The advanced adenoma panel was comprised of 4 proteins (CATD, CLUS, GDF15, SAA1) and had a validation ROC curve AUC of 0.65 (CI 0.56-0.74). CONCLUSIONS: These results suggest that the development of blood-based aids to colorectal cancer detection and diagnosis is feasible.

A Plasma-Based Protein Marker Panel for Colorectal Cancer Detection Identified by Multiplex Targeted Mass Spectrometry.

INTRODUCTION: Colorectal cancer (CRC) testing programs reduce mortality; however, approximately 40% of the recommended population who should undergo CRC testing does not. Early colon cancer detection in patient populations ineligible for testing, such as the elderly or those with significant comorbidities, could have clinical benefit. Despite many attempts to identify individual protein markers of this disease, little progress has been made. Targeted mass spectrometry, using multiple reaction monitoring (MRM) technology, enables the simultaneous assessment of groups of candidates for improved detection performance. MATERIALS AND METHODS: A multiplex assay was developed for 187 candidate marker proteins, using 337 peptides monitored through 674 simultaneously measured MRM transitions in a 30-minute liquid chromatography-mass spectrometry analysis of immunodepleted blood plasma. To evaluate the combined candidate marker performance, the present study used 274 individual patient blood plasma samples, 137 with biopsy-confirmed colorectal cancer and 137 age- and gender-matched controls. Using 2 well-matched platforms running 5 days each week, all 274 samples were analyzed in 52 days. RESULTS: Using one half of the data as a discovery set (69 disease cases and 69 control cases), the elastic net feature selection and random forest classifier assembly were used in cross-validation to identify a 15-transition classifier. The mean training receiver operating characteristic area under the curve was 0.82. After final classifier assembly using the entire discovery set, the 136-sample (68 disease cases and 68 control cases) validation set was evaluated. The validation area under the curve was 0.91. At the point of maximum accuracy (84%), the sensitivity was 87% and the specificity was 81%. CONCLUSION: These results have demonstrated the ability of simultaneous assessment of candidate marker proteins using high-multiplex, targeted-mass spectrometry to identify a subset group of CRC markers with significant and meaningful performance.

Of Atkins and men: deviations from clinical definitions of mental retardation in death penalty cases.

Under Atkins v. Virginia, the Eighth Amendment exempts from execution individuals who meet the clinical definitions of mental retardation set forth by the American Association on Intellectual and Developmental Disabilities and the American Psychiatric Association. Both define mental retardation as significantly subaverage intellectual functioning accompanied by significant limitations in adaptive functioning, originating before the age of 18. Since Atkins, most jurisdictions have adopted definitions of mental retardation that conform to those definitions. But some states, looking often to stereotypes of persons with mental retardation, apply exclusion criteria that deviate from and are more restrictive than the accepted scientific and clinical definitions. These state deviations have the effect of excluding from Atkins's reach some individuals who plainly fall within the class it protects. This article focuses on the cases of Roger Cherry, Jeffrey Williams, Michael Stallings, and others, who represent an ever-growing number of individuals inappropriately excluded from Atkins. Left unaddressed, the state deviations discussed herein permit what Atkins does not: the death-sentencing and execution of some capital defendants who have mental retardation.

Integrated detection and population-genetic analysis of SNPs and copy number variation.

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.

Discovery of tissue-specific exons using comprehensive human exon microarrays.

BACKGROUND: Higher eukaryotes express a diverse population of messenger RNAs generated by alternative splicing. Large-scale methods for monitoring gene expression must adapt in order to accurately detect the transcript variation generated by this splicing. RESULTS: We have designed a high-density oligonucleotide microarray with probesets for more than one million annotated and predicted exons in the human genome. Using these arrays and a simple algorithm that normalizes exon signal to signal from the gene as a whole, we have identified tissue-specific exons from a panel of 16 different normal adult tissues. RT-PCR validation confirms approximately 86% of the predicted tissue-enriched probesets. Pair-wise comparisons between the tissues suggest that as many as 73% of detected genes are differentially alternatively spliced. We also demonstrate how an inclusive exon microarray can be used to discover novel alternative splicing events. As examples, 17 new tissue-specific exons from 11 genes were validated by RT-PCR and sequencing. CONCLUSION: In conjunction with a conceptually simple algorithm, comprehensive exon microarrays can detect tissue-specific alternative splicing events. Our data suggest significant expression outside of known exons and well annotated genes and a high frequency of alternative splicing events. In addition, we identified and validated a number of novel exons with tissue-specific splicing patterns. The tissue map data will likely serve as a valuable source of information on the regulation of alternative splicing.