High-throughput sequencing of mGluR signaling pathway genes reveals enrichment of rare variants in autism.

Identification of common molecular pathways affected by genetic variation in autism is important for understanding disease pathogenesis and devising effective therapies. Here, we test the hypothesis that rare genetic variation in the metabotropic glutamate-receptor (mGluR) signaling pathway contributes to autism susceptibility. Single-nucleotide variants in genes encoding components of the mGluR signaling pathway were identified by high-throughput multiplex sequencing of pooled samples from 290 non-syndromic autism cases and 300 ethnically matched controls on two independent next-generation platforms. This analysis revealed significant enrichment of rare functional variants in the mGluR pathway in autism cases. Higher burdens of rare, potentially deleterious variants were identified in autism cases for three pathway genes previously implicated in syndromic autism spectrum disorder, TSC1, TSC2, and SHANK3, suggesting that genetic variation in these genes also contributes to risk for non-syndromic autism. In addition, our analysis identified HOMER1, which encodes a postsynaptic density-localized scaffolding protein that interacts with Shank3 to regulate mGluR activity, as a novel autism-risk gene. Rare, potentially deleterious HOMER1 variants identified uniquely in the autism population affected functionally important protein regions or regulatory sequences and co-segregated closely with autism among children of affected families. We also identified rare ASD-associated coding variants predicted to have damaging effects on components of the Ras/MAPK cascade. Collectively, these findings suggest that altered signaling downstream of mGluRs contributes to the pathogenesis of non-syndromic autism.

Standardization of HER2 immunohistochemistry in breast cancer by automated quantitative analysis.

CONTEXT: There is critical need for standardization of HER2 immunohistochemistry testing in the clinical laboratory setting. Recently, the American Society of Clinical Oncology and the College of American Pathologists have submitted guidelines recommending that laboratories achieve 95% concordance between assays and observers for HER2 testing. OBJECTIVE: As a potential aid to pathologists for achieving these new guidelines, we have conducted an examination using automated quantitative analysis (AQUA analysis) to provide a standardized HER2 immunohistochemistry expression score across instruments (sites), operators, and staining runs. DESIGN: We analyzed HER2 expression by immunohistochemistry in a cohort (n = 669) of invasive breast cancers in tissue microarray format across different instruments (n = 3), operators (n = 3), and staining runs (n = 3). Using light source, instrument calibration techniques, and a new generation of image analysis software, we produced normalized AQUA scores for each parameter and examined their reproducibility. RESULTS: The average percent coefficients of variation across instruments, operators, and staining runs were 1.8%, 2.0%, and 5.1%, respectively. For positive/negative classification between parameters, concordance rates ranged from 94.5% to 99.3% for all cases. Differentially classified cases only occurred around the determined cut point, not over the entire distribution. CONCLUSIONS: These data demonstrate that AQUA analysis can provide a standardized HER2 immunohistochemistry test that can meet current guidelines by the American Society of Clinical Oncology/College of American Pathologists. The use of AQUA analysis could allow for standardized and objective HER2 testing in clinical laboratories.

Development of an unsupervised pixel-based clustering algorithm for compartmentalization of immunohistochemical expression using Automated QUantitative Analysis.

Inherent to most tissue image analysis routines are user-defined steps whereby specific pixel intensity thresholds must be set manually to differentiate background from signal-specific pixels within multiple images. To reduce operator time, remove operator-to-operator variability, and to obtain objective and optimal pixel separation for each image, we have developed an unsupervised pixel-based clustering algorithm allowing for the objective and unsupervised differentiation of signal from background, and differentiation of compartment-specific pixels on an image-by-image basis. We used the Automated QUantitative Analysis (AQUA) platform, a well-established automated fluorescence-based immunohistochemistry image analysis platform used for quantification of protein expression in specific cellular compartments to demonstrate utility of this methodology. As a metric for cellular compartmentalization, we examined correlation of percentage nuclear volume with histologic grade in 3 serial sections of a large cohort (n=669) of invasive breast cancer samples. We observed a significant (P=0.002, 0.006, and 0.08) difference in mean percentage nuclear volume between low and high-grade tumors. Reproducibility of percentage nuclear volume was also significant (P<0.001) across 3 serial sections. We then quantified compartment-specific expression of 5 biomarkers in 3 cancer types for association with outcome: estrogen receptor (nuclear), progesterone receptor (nuclear), HER2 (membrane/cytoplasm), ERCC1 (nuclear), and PTEN (cytoplasm). All 5 markers showed an expected and significant (P<0.05) association with survival. This new clustering algorithm thus produces accurate and precise compartmentalization for assessment of target gene expression, and will enhance the efficiency and objectivity of the current Automated QUantitative Analysis and other image analysis platform.

Gene expression profiling reveals putative HOXA10 downstream targets in the periimplantation mouse uterus.

HOXA10 encodes a transcription factor required for endometrial receptivity and embryo implantation. The objective of this study was to identify and to characterize those molecular markers regulated by HOXA10 expression. The authors have identified putative HOXA10 target genes identified by microarray analysis employing a murine model of transient HOXA10 expression during the anticipated implantation window. Microarray analysis identified 40 statistically significant genes regulated by HOXA10 overexpression of which 31 genes were downregulated greater than 2-fold over control and 9 genes were upregulated. Cellular ontogenies of differentially expressed genes include cell adhesion molecules, signal transduction factors, and metabolic regulators. Semiquantitative real-time reverse transcriptase polymerase chain reaction confirmed regulation of selected candidate genes. Examples included clusterin (Clu), phoshoglycerate 3-dehydrogenase (3-Pgdh), and tumor-associated calcium signal transducer 2 (Tacstd2). Elucidation of these pathways will allow further characterization of the molecular mechanisms governing endometrial development, which also may function to enhance uterine receptivity.

Assessment of whole genome amplification-induced bias through high-throughput, massively parallel whole genome sequencing.

BACKGROUND: Whole genome amplification is an increasingly common technique through which minute amounts of DNA can be multiplied to generate quantities suitable for genetic testing and analysis. Questions of amplification-induced error and template bias generated by these methods have previously been addressed through either small scale (SNPs) or large scale (CGH array, FISH) methodologies. Here we utilized whole genome sequencing to assess amplification-induced bias in both coding and non-coding regions of two bacterial genomes. Halobacterium species NRC-1 DNA and Campylobacter jejuni were amplified by several common, commercially available protocols: multiple displacement amplification, primer extension pre-amplification and degenerate oligonucleotide primed PCR. The amplification-induced bias of each method was assessed by sequencing both genomes in their entirety using the 454 Sequencing System technology and comparing the results with those obtained from unamplified controls. RESULTS: All amplification methodologies induced statistically significant bias relative to the unamplified control. For the Halobacterium species NRC-1 genome, assessed at 100 base resolution, the D-statistics from GenomiPhi-amplified material were 119 times greater than those from unamplified material, 164.0 times greater for Repli-G, 165.0 times greater for PEP-PCR and 252.0 times greater than the unamplified controls for DOP-PCR. For Campylobacter jejuni, also analyzed at 100 base resolution, the D-statistics from GenomiPhi-amplified material were 15 times greater than those from unamplified material, 19.8 times greater for Repli-G, 61.8 times greater for PEP-PCR and 220.5 times greater than the unamplified controls for DOP-PCR. CONCLUSION: Of the amplification methodologies examined in this paper, the multiple displacement amplification products generated the least bias, and produced significantly higher yields of amplified DNA.

Modifications and deletions of helices within the hairpin ribozyme-substrate complex: an active ribozyme lacking helix 1.

Within the hairpin ribozyme, structural elements required for formation of the active tertiary structure are localized in two independently folding domains, each consisting of an internal loop flanked by helical elements. Here, we present results of a systematic examination of the relationship between the structure of the helical elements and the ability of the RNA to form the catalytically active tertiary structure. Deletions and mutational analyses indicate that helix 1 (H1) in domain A can be entirely eliminated, while segments of helices 2, 3, and 4 can also be deleted. From these results, we derive a new active minimal ribozyme that contains three helical elements, an internal loop, and a terminal loop. A three-dimensional model of this truncated ribozyme was generated using MC-SYM, and confirms that the catalytic core of the minimized construct can adopt a tertiary structure that is very similar to that of the nontruncated version. A new strategy is described to study the functional importance of various residues and chemical groups and to identify specific interdomain interactions. This approach uses two physically separated and truncated domains derived from the minimal motif.