Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems™ Axiom™ array genotyping calls: Retrospective evaluation of UK Biobank array data

The UK Biobank genotyped about 500k participants using Applied Biosystems Axiom microarrays. Participants were subsequently sequenced by the UK Biobank Exome Sequencing Consortium. Axiom genotyping was highly accurate in comparison to sequencing results, for almost 100,000 variants both directly genotyped on the UK Biobank Axiom array and via whole exome sequencing. However, in a study using the exome sequencing results of the first 50k individuals as reference (truth), it was observed that the positive predictive value (PPV) decreased along with the number of heterozygous array calls per variant. We developed a novel addition to the genotyping algorithm, Rare Heterozygous Adjusted (RHA), to significantly improve PPV in variants with minor allele frequency below 0.01%. The improvement in PPV was roughly equal when comparing to the exome sequencing of 50k individuals, or to the more recent ~200k individuals. Sensitivity was higher in the 200k data. The improved calling algorithm, along with enhanced quality control of array probesets, significantly improved the positive predictive value and the sensitivity of array data, making it suitable for the detection of ultra-rare variants.

MicroRNA polymorphisms and risk of colorectal cancer

BACKGROUND

miRNAs act as post-transcriptional regulators of gene expression. Genetic variation in miRNA-encoding sequences or their corresponding binding sites may affect the fidelity of the miRNA-mRNA interaction and subsequently alter the risk of cancer development.

METHODS

This study expanded the search for miRNA-related polymorphisms contributing to the etiology of colorectal cancer across the genome using a novel platform, the Axiom miRNA Target Site Genotyping Array (237,858 markers). After quality control, the study included 596 cases and 429 controls from the Molecular Epidemiology of Colorectal Cancer study, a population-based case-control study of colorectal cancer in northern Israel. The association between each marker and colorectal cancer status was examined assuming a log-additive genetic model using logistic regression adjusted for sex, age, and two principal components.

RESULTS

Twenty-three markers had P values less than 5.0E-04, and the most statistically significant association involved rs2985 (chr6:34845648; intronic of UHRF1BP1; OR = 0.66; P = 3.7E-05). Furthermore, this study replicated a previously published risk locus, rs1051690, in the 3'-untranslated region of the insulin receptor gene INSR (OR = 1.38; P = 0.03), with strong evidence of differences in INSR gene expression by genotype.

CONCLUSIONS

This study is the first to examine associations between genetic variation in miRNA target sites and colorectal cancer using a genome-wide approach. Functional studies to identify allele-specific effects on miRNA binding are needed to confirm the regulatory capacity of genetic variation to influence risk of colorectal cancer.

IMPACT

This study demonstrates the potential for an miRNA-targeted genome-wide association study to identify candidate susceptibility loci and prioritize them for functional characterization.

Abstract 2560: MicroRNA target site polymorphisms and colorectal cancer risk in the Ashkenazi Jewish population

MicroRNAs (miRNAs) act as key post-transcriptional regulators of gene expression via binding to the 3’ untranslated regions (UTRs) of mRNAs. Single nucleotide polymorphisms (SNPs) found in the miRNA sequence and/or corresponding binding sites can affect the fidelity of this interaction, and evidence from candidate miRNA studies suggests that such SNPs may increase or decrease risk of tumor development. This study was designed to expand the search for miRNA-related polymorphisms important in cancer etiology across the genome and to investigate the association between thousands of genetic variants in miRNA target sites and colorectal cancer (CRC) risk using a novel genotyping platform, the Axiom® miRNA Target Site Genotyping Array (237,858 markers). The final study sample after quality control filtering included 605 cases and 615 controls from the Molecular Epidemiology of Colorectal Cancer (MECC) study, a population-based case-control study of incident CRC cases in a geographically-defined area of northern Israel. The marginal association between each marker with minor allele frequency >=1% and CRC risk was examined assuming a log-additive genetic model using logistic regression adjusted for sex, age, and the first two principal components (PC) to capture fine-scale population structure. There were 11 markers with p-values less than 3E-4, and the most statistically significant association involved rs12130051 (chr1:19545053; 3’-UTR of KIAA0090) with an OR of 2.24 (1.52,3.31) and p=4.48E-5. In addition, rs1051690 (chr5:142605172; 3’-UTR of ARHGAP26), was statistically significantly associated with decreased CRC risk (OR (95% CI): 0.71 (0.59, 0.85); p = 2.03E-4). Further, this study provided evidence for replication of a previously published locus, rs1051690 in the 3’UTR region of the insulin receptor gene, INSR (OR (95% CI): 1.27 (0.96,1.67); p = 0.09). A fixed-effects meta-analysis of sample-size weighted p-values from a recent publication in Carcinogenesis describing the INSR variant (Landi et al., 2012) and from the current MECC study yielded a combined p-value of 0.01. To our knowledge, this is the first study to examine the association between genetic variation in miRNA target sites and cancer risk using a genome-wide approach. Work is ongoing to replicate findings from this study and to characterize the functional impact of prioritized polymorphisms.

Citation Format: Stephanie L. Stenzel, Jeremy Gollub, Michael Shapero, Andrea Finn, Gad Rennert, Stephen B. Gruber. MicroRNA target site polymorphisms and colorectal cancer risk in the Ashkenazi Jewish population. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2560. doi:10.1158/1538-7445.AM2013-2560

Genome-wide maps of circulating miRNA biomarkers for ulcerative colitis

Inflammatory Bowel Disease--comprised of Crohn's Disease and Ulcerative Colitis (UC)--is a complex, multi-factorial inflammatory disorder of the gastrointestinal tract. In this study we have explored the utility of naturally occurring circulating miRNAs as potential blood-based biomarkers for non-invasive prediction of UC incidences. Whole genome maps of circulating miRNAs in micro-vesicles, Peripheral Blood Mononuclear Cells and platelets have been constructed from a cohort of 20 UC patients and 20 normal individuals. Through Significance Analysis of Microarrays, a signature of 31 differentially expressed platelet-derived miRNAs has been identified and biomarker performance estimated through a non-probabilistic binary linear classification using Support Vector Machines. Through this approach, classifier measurements reveal a predictive score of 92.8% accuracy, 96.2% specificity and 89.5% sensitivity in distinguishing UC patients from normal individuals. Additionally, the platelet-derived biomarker signature can be validated at 88% accuracy through qPCR assays, and a majority of the miRNAs in this panel can be demonstrated to sub-stratify into 4 highly correlated intensity based clusters. Analysis of predicted targets of these biomarkers reveal an enrichment of pathways associated with cytoskeleton assembly, transport, membrane permeability and regulation of transcription factors engaged in a variety of regulatory cascades that are consistent with a cell-mediated immune response model of intestinal inflammation. Interestingly, comparison of the miRNA biomarker panel and genetic loci implicated in IBD through genome-wide association studies identifies a physical linkage between hsa-miR-941 and a UC susceptibility loci located on Chr 20. Taken together, analysis of these expression maps outlines a promising catalog of novel platelet-derived miRNA biomarkers of clinical utility and provides insight into the potential biological function of these candidates in disease pathogenesis.

Impact of cellular miRNAs on circulating miRNA biomarker signatures

Effective diagnosis and surveillance of complex multi-factorial disorders such as cancer can be improved by screening of easily accessible biomarkers. Highly stable cell free Circulating Nucleic Acids (CNA) present as both RNA and DNA species have been discovered in the blood and plasma of humans. Correlations between tumor-associated genomic/epigenetic/transcriptional changes and alterations in CNA levels are strong predictors of the utility of this biomarker class as promising clinical indicators. Towards this goal microRNAs (miRNAs) representing a class of naturally occurring small non-coding RNAs of 19-25 nt in length have emerged as an important set of markers that can associate their specific expression profiles with cancer development. In this study we investigate some of the pre-analytic considerations for isolating plasma fractions for the study of miRNA biomarkers. We find that measurement of circulating miRNA levels are frequently confounded by varying levels of cellular miRNAs of different hematopoietic origins. In order to assess the relative proportions of this cell-derived class, we have fractionated whole blood into plasma and its ensuing sub-fractions. Cellular miRNA signatures in cohorts of normal individuals are catalogued and the abundance and gender specific expression of bona fide circulating markers explored after calibrating the signal for this interfering class. A map of differentially expressed profiles is presented and the intrinsic variability of circulating miRNA species investigated in subsets of healthy males and females.

Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array

The success of genome-wide association studies has paralleled the development of efficient genotyping technologies. We describe the development of a next-generation microarray based on the new highly-efficient Affymetrix Axiom genotyping technology that we are using to genotype individuals of European ancestry from the Kaiser Permanente Research Program on Genes, Environment and Health (RPGEH). The array contains 674,517 SNPs, and provides excellent genome-wide as well as gene-based and candidate-SNP coverage. Coverage was calculated using an approach based on imputation and cross validation. Preliminary results for the first 80,301 saliva-derived DNA samples from the RPGEH demonstrate very high quality genotypes, with sample success rates above 94% and over 98% of successful samples having SNP call rates exceeding 98%. At steady state, we have produced 462 million genotypes per week for each Axiom system. The new array provides a valuable addition to the repertoire of tools for large scale genome-wide association studies.

Erratum to "Prediction of non-genotoxic carcinogenesis in rats using changes in gene expression following acute dosing"

Carcinogenicity of chemicals can currently only be evaluated in 2-year rodent bioassays. Therefore, the development of early biomarkers for carcinogenesis would result in substantial savings in time and expense. The current study investigates whether early changes in gene expression may be developed as markers for cancer. Animals were treated for 1 or 5 days with either non-genotoxic carcinogens or non-carcinogens and gene expression was analyzed by quantitative PCR (qPCR).We tested two gene signatures previously reported to detect non-genotoxic carcinogens. Using one gene signature it was confirmed that 3/3 nongenotoxic carcinogens and 2/2 non-carcinogens are correctly identified with data from 1 or 5 days of dosing. In contrast an alternative signature correctly identified 0/3 and 2/3 nongenotoxic carcinogens at 1 and 5 days of treatment, respectively and 2/2 non-carcinogens at both time-points. Additionally, we evaluated a novel panel of putative biomarker genes, from the literature, many of which have roles in cell growth and division, including myc, cdc2 and mcm6. These genes were significantly induced by non-genotoxic carcinogens and not by non-carcinogens. Using the average fold-induction across this panel, 2/3 non-genotoxic carcinogens were detected on both day 1 and day 5. These data support the idea that acute changes in gene expression may provide biomarkers for non-genotoxic carcinogenesis but also highlight interesting differences in the sensitivities of distinct gene signatures.

Interlaboratory evaluation of genomic signatures for predicting carcinogenicity in the rat

The Critical Path Institute recently established the Predictive Safety Testing Consortium, a collaboration between several companies and the U.S. Food and Drug Administration, aimed at evaluating and qualifying biomarkers for a variety of toxicological endpoints. The Carcinogenicity Working Group of the Predictive Safety Testing Consortium has concentrated on sharing data to test the predictivity of two published hepatic gene expression signatures, including the signature by Fielden et al. (2007, Toxicol. Sci. 99, 90-100) for predicting nongenotoxic hepatocarcinogens, and the signature by Nie et al. (2006, Mol. Carcinog. 45, 914-933) for predicting nongenotoxic carcinogens. Although not a rigorous prospective validation exercise, the consortium approach created an opportunity to perform a meta-analysis to evaluate microarray data from short-term rat studies on over 150 compounds. Despite significant differences in study designs and microarray platforms between laboratories, the signatures proved to be relatively robust and more accurate than expected by chance. The accuracy of the Fielden et al. signature was between 63 and 69%, whereas the accuracy of the Nie et al. signature was between 55 and 64%. As expected, the predictivity was reduced relative to internal validation estimates reported under identical test conditions. Although the signatures were not deemed suitable for use in regulatory decision making, they were deemed worthwhile in the early assessment of drugs to aid decision making in drug development. These results have prompted additional efforts to rederive and evaluate a QPCR-based signature using these samples. When combined with a standardized test procedure and prospective interlaboratory validation, the accuracy and potential utility in preclinical applications can be ascertained.

Radiogenomic analysis to identify imaging phenotypes associated with drug response gene expression programs in hepatocellular carcinoma

PURPOSE

To determine whether conventional contrast-enhanced computed tomography (CT) could be used to identify imaging phenotypes associated with a doxorubicin drug response gene expression program in hepatocellular carcinoma (HCC) by using an integrated imaging-genomic approach.

MATERIALS AND METHODS

Thirty HCCs were analyzed and scored individually across six predefined imaging phenotypes. Unsupervised and supervised bioinformatics analyses were performed to correlate the imaging scores with the corresponding tumor microarray data (each microarray contained gene expression measurements across approximately 18,000 genes) to identify relationships between the imaging traits and underlying tumor gene expression. Enrichment for a predefined doxorubicin-response gene expression program was then performed against the imaging phenotype-associated genes and enrichment determined.

RESULTS

An imaging phenotype related to tumor margins on arterial phase images demonstrated significant correlation with the doxorubicin-response transcriptional program (P < .05, q < 0.1). It was also significantly associated with HCC venous invasion and tumor stage (P < .05, q < 0.1). Tumors with higher tumor margin scores were more strongly associated with the doxorubicin resistance transcriptional program and had a greater prevalence of venous invasion and worse stage. Tumors with lower tumor margin scores, however, demonstrated a converse relationship.

CONCLUSIONS

It is possible to identify HCC imaging phenotypes at CT that correlate with a doxorubicin drug response gene expression program. Given the role of doxorubicin in regional therapies for HCC management, it is possible that such an approach could be used to guide HCC therapy on a tumor-by-tumor basis on the basis of underlying tumor gene expression patterns.

A gene expression biomarker provides early prediction and mechanistic assessment of hepatic tumor induction by nongenotoxic chemicals

There are currently no accurate and well-validated short-term tests to identify nongenotoxic hepatic tumorigens, thus necessitating an expensive 2-year rodent bioassay before a risk assessment can begin. Using hepatic gene expression data from rats treated for 5 days with one of 100 structurally and mechanistically diverse nongenotoxic hepatocarcinogens and nonhepatocarcinogens, a novel multigenebiomarker (i.e., signature) was derived to predict the likelihood of nongenotoxic chemicals to induce liver tumors in longer term studies. Independent validation of the signature on 47 test chemicals indicates an assay sensitivity and specificity of 86% and 81%, respectively. Alternate short-term in vivo pathological and genomic biomarkers were evaluated in parallel for comparison, including liver weight, hepatocellular hypertrophy, hepatic necrosis, serum alanine aminotransferase activity, induction of cytochrome P450 genes, and repression of Tsc-22 or alpha2-macroglobulin messenger RNA. In contrast to these biomarkers, the gene expression-based signature was more accurate. Unlike existing tests, an understanding of potential modes of action for hepatic tumorigenicity can be derived by comparison of the signature profile of test chemicals to hepatic tumorigens of known mechanism, including regenerative proliferation, proliferation associated with xenobiotic receptor activation, peroxisome proliferation, and steroid hormone-mediated mechanisms. This signature is not only more accurate than current methods, but also facilitates the identification of mode of action to aid in the early assessment of human cancer risk.

Decoding global gene expression programs in liver cancer by noninvasive imaging

Paralleling the diversity of genetic and protein activities, pathologic human tissues also exhibit diverse radiographic features. Here we show that dynamic imaging traits in non-invasive computed tomography (CT) systematically correlate with the global gene expression programs of primary human liver cancer. Combinations of twenty-eight imaging traits can reconstruct 78% of the global gene expression profiles, revealing cell proliferation, liver synthetic function, and patient prognosis. Thus, genomic activity of human liver cancers can be decoded by noninvasive imaging, thereby enabling noninvasive, serial and frequent molecular profiling for personalized medicine.

The Stanford Microarray Database: implementation of new analysis tools and open source release of software

The Stanford Microarray Database (SMD; ) is a research tool and archive that allows hundreds of researchers worldwide to store, annotate, analyze and share data generated by microarray technology. SMD supports most major microarray platforms, and is MIAME-supportive and can export or import MAGE-ML. The primary mission of SMD is to be a research tool that supports researchers from the point of data generation to data publication and dissemination, but it also provides unrestricted access to analysis tools and public data from 300 publications. In addition to supporting ongoing research, SMD makes its source code fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD. In this article, we describe several data analysis tools implemented in SMD and we discuss features of our software release.

The Stanford Microarray Database: a user's guide

The Stanford Microarray Database (SMD) is a DNA microarray research database that provides a large amount of data for public use. This chapter describes the use of the primary tools for searching, browsing, retrieving, and analyzing data available for SMD. With this introduction, researchers and students will be able to examine and analyze a large body of gene expression and other experiments. Additional tools for depositing, annotating, sharing, and analyzing data, available only to registered users, are also described. SMD is available for installation as a local database.

[10] Clustering Microarray Data

Even a simple, small-scale, microarray experiment generates thousands to millions of data points. Clearly, spreadsheets or plotting programs do not suffice for analysis of such large volumes of data, and comprehensive analysis requires systematic methods for selection and organization of data. This chapter focuses on the concepts and algorithms of hierarchical clustering and the most commonly employed methods of partitioning or organizing microarray data, and freely available software that implements these algorithms.

The Stanford Microarray Database accommodates additional microarray platforms and data formats

The Stanford Microarray Database (SMD) (http://smd.stanford.edu) is a research tool for hundreds of Stanford researchers and their collaborators. In addition, SMD functions as a resource for the entire biological research community by providing unrestricted access to microarray data published by SMD users and by disseminating its source code. In addition to storing GenePix (Axon Instruments) and ScanAlyze output from spotted microarrays, SMD has recently added the ability to store, retrieve, display and analyze the complete raw data produced by several additional microarray platforms and image analysis software packages, so that we can also now accept data from Affymetrix GeneChips (MAS5/GCOS or dChip), Agilent Catalog or Custom arrays (using Agilent's Feature Extraction software) or data created by SpotReader (Niles Scientific). We have implemented software that allows us to accept MAGE-ML documents from array manufacturers and to submit MIAME-compliant data in MAGE-ML format directly to ArrayExpress and GEO, greatly increasing the ease with which data from SMD can be published adhering to accepted standards and also increasing the accessibility of published microarray data to the general public. We have introduced a new tool to facilitate data sharing among our users, so that datasets can be shared during, before or after the completion of data analysis. The latest version of the source code for the complete database package was released in November 2004 (http://smd.stanford.edu/download/), allowing researchers around the world to deploy their own installations of SMD.

GO::TermFinder--open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes

SUMMARY

GO::TermFinder comprises a set of object-oriented Perl modules for accessing Gene Ontology (GO) information and evaluating and visualizing the collective annotation of a list of genes to GO terms. It can be used to draw conclusions from microarray and other biological data, calculating the statistical significance of each annotation. GO::TermFinder can be used on any system on which Perl can be run, either as a command line application, in single or batch mode, or as a web-based CGI script.

AVAILABILITY

The full source code and documentation for GO::TermFinder are freely available from http://search.cpan.org/dist/GO-TermFinder/.

Primary systemic treatment of advanced Hodgkin's disease with EVA (etoposide, vinblastine, doxorubicin): 10-year follow-up

BACKGROUND

The most commonly used regimen for the treatment of advanced Hodgkin's disease (HD) is ABVD (doxorubicin, bleomycin, vinblastine and dacarbazine). Two of these components, bleomycin and dacarbazine, have defined toxicities such as pulmonary fibrosis and nausea/vomiting, and also uncertain single-drug activity. The EVA regimen (etoposide, vinblastine, doxorubicin) is an attempt to substitute a known active agent, etoposide, for bleomycin and dacarbazine.

PATIENTS AND METHODS

A series of 51 patients with advanced HD without prior systemic therapy were treated. The series included 12 stage II patients with bulky (>10 cm) mediastinal tumors, 10 of whom received complementary radiation therapy. The remaining patients received EVA only. Response, duration of response, survival, toxicity and the efficacy of salvage therapy were evaluated in all patients. The median follow-up time was 111 months and permitted an assessment of the long-term effects of treatment and natural history of a cohort of treated patients.

RESULTS

EVA achieved a complete response (or clinical complete response) in 48/51 patients (94%). Of these 48 responders, 16 relapsed in a median of 11 months (range 3-48 months). In follow-up, 32/51 patients had no evidence of relapsed HD, although three died from other causes (two from vascular events and one from large cell lymphoma), resulting in progression-free survival for the entire group of 57% at 111 months. Eight of the 16 were alive and free from disease at follow-up at 111 months. In the entire series, only seven patients (14%) died of HD. 37 patients (73%) continued free from disease. There was no pulmonary toxicity.

CONCLUSIONS

The EVA regimen appears to have an overall survival (OS) outcome comparable to ABVD, but without the lung toxicity. The high salvage rate of second-line therapy, in most instances at conventional dosage, suggests an absence of cross-resistance to alkylating agents in patients treated with EVA.

The Stanford Microarray Database: data access and quality assessment tools

The Stanford Microarray Database (SMD; http://genome-www.stanford.edu/microarray/) serves as a microarray research database for Stanford investigators and their collaborators. In addition, SMD functions as a resource for the entire scientific community, by making freely available all of its source code and providing full public access to data published by SMD users, along with many tools to explore and analyze those data. SMD currently provides public access to data from 3500 microarrays, including data from 85 publications, and this total is increasing rapidly. In this article, we describe some of SMD's newer tools for accessing public data, assessing data quality and for data analysis.

Microarray data quality analysis: lessons from the AFGC project. Arabidopsis Functional Genomics Consortium

Genome-wide expression profiling with DNA microarrays has and will provide a great deal of data to the plant scientific community. However, reliability concerns have required the development data quality tests for common systematic biases. Fortunately, most large-scale systematic biases are detectable and some are correctable by normalization. Technical replication experiments and statistical surveys indicate that these biases vary widely in severity and appearance. As a result, no single normalization or correction method currently available is able to address all the issues. However, careful sequence selection, array design, experimental design and experimental annotation can substantially improve the quality and biological of microarray data. In this review, we discuss these issues with reference to examples from the Arabidopsis Functional Genomics Consortium (AFGC) microarray project.

Phosphorylation regulates the ADP-induced rotation of the light chain domain of smooth muscle myosin

We have observed the effects of MgADP and thiophosphorylation on the conformational state of the light chain domain of myosin in skinned smooth muscle. Electron paramagnetic resonance (EPR) spectroscopy was used to monitor the orientation of spin probes attached to the myosin regulatory light chain (RLC). Two spectral states were seen, termed here "intermediate" and "final", that are distinguished by a approximately 24 degrees axial rotation of spin probes attached to the RLC. The two observed conformations are similar to those found previously for smooth muscle myosin S1; the final state corresponds to the major conformation of S1 in the absence of ADP, while the intermediate state corresponds to the conformation of S1 with ADP bound. Light chain domain orientation was observed as a function of the MgADP concentration and the extent of RLC thiophosphorylation. In rigor (no MgADP), LC domains were distributed equally between the intermediate state and the final state; upon addition of saturating (3.5 mM) MgADP, about one-third of the LC domains in the final state rotated approximately 20 degrees axially to the intermediate state. The progression of the change in populations was fit to a simple binding equation, yielding an apparent dissociation constant of approximately 110 microM for skinned smooth muscle fibers and approximately 730 microM for thiophosphorylated, skinned smooth muscle fibers. These observations suggest a model that explains the behavior of "latch bridges" in smooth muscle.

ADP release produces a rotation of the neck region of smooth myosin but not skeletal myosin

Current theories of muscle cross-bridge function suggest that force is generated by a change in the orientation of the myosin neck region. We attached a paramagnetic probe to a subunit in the neck region and measured the orientation of the probe using electron paramagnetic resonance spectroscopy. The angle of the probes on smooth myosin S1 were changed by 20 degrees +/- 4 degrees on addition of ADP (50% effect at 5 +/- 2 microM), but ADP produced little effect on skeletal S1. The orientation of smooth myosin, +ADP, resembled that of skeletal myosin, +/- ADP, suggesting that the release of ADP generates an extra rotation of the neck region in smooth muscle at the end of its power stroke.

Orientation of paramagnetic probes attached to gizzard regulatory light chain bound to myosin heads in rabbit skeletal muscle

The orientation of the myosin neck was monitored using electron paramagnetic resonance (EPR) spectroscopy. Gizzard regulatory light chain was labeled with a nitroxide spin probe and exchanged for the native subunit, located in the myosin neck, in rabbit psoas muscle fibers. The EPR spectra of rigor fibers indicated a substantial degree of probe immobilization and showed a strong dependence on the orientation of the fiber axis relative to the magnetic field, indicating that the neck was ordered in this state. Spectra of relaxed fibers at 24 degrees C showed that the neck was disordered, but the spectra of relaxed fibers at 4 degrees C indicated that the neck was partially ordered. Active fibers at the two temperatures produced spectra identical to relaxed fibers, indicating that no novel angles could be seen in the neck during the powerstroke. Proteolytic fragments of myosin, S1 and HMM, were exchanged with labeled light chains and bound to thin filaments in unlabeled fibers. The distribution of probe orientations for HMM was identical to that of labeled rigor fibers, while S1 showed a slightly different distribution, suggesting that the neck is distorted (by a few degrees) by the interactions of the two heads of myosin when bound to actin.