Karl Kornacker

Gene expression in papillary thyroid carcinoma reveals highly consistent profiles

Papillary thyroid carcinoma (PTC) is clinically heterogeneous. Apart from an association with ionizing radiation, the etiology and molecular biology of PTC is poorly understood. We used oligo-based DNA arrays to study the expression profiles of eight matched pairs of normal thyroid and PTC tissues. Additional PTC tumors and other tissues were studied by reverse transcriptase–PCR and immunohistochemistry. The PTCs showed concordant expression of many genes and distinct clustered profiles. Genes with increased expression in PTC included many encoding adhesion and extracellular matrix proteins. Expression was increased in 8/8 tumors for 24 genes and in 7/8 tumors for 22 genes. Among these genes were several previously known to be overexpressed in PTC, such as MET, LGALS3, KRT19, DPP4, MDK, TIMP1, and FN1. The numerous additional genes include CITED1, CHI3L1, ODZ1, N33, SFTPB, and SCEL. Reverse transcriptase–PCR showed high expression of CITED1, CHI3L1, ODZ1, and SCEL in 6/6 additional PTCs. Immunohistochemical analysis detected CITED1 and SFTPB in 49/52 and 39/52 PTCs, respectively, but not in follicular thyroid carcinoma and normal thyroid tissue. Genes underexpressed in PTC included tumor suppressors, thyroid function-related proteins, and fatty acid binding proteins. Expression was decreased in 7/8 tumors for eight genes and decreased in 6/8 tumors for 19 genes. We conclude that, despite its clinical heterogeneity, PTC is characterized by consistent and specific molecular changes. These findings reveal clues to the molecular pathways involved in PTC and may provide biomarkers for clinical use.

JTK_CYCLE: An Efficient Nonparametric Algorithm for Detecting Rhythmic Components in Genome-Scale Data Sets

Circadian rhythms are oscillations of physiology, behavior, and metabolism that have period lengths near 24 hours. In several model organisms and humans, circadian clock genes have been characterized and found to be transcription factors. Because of this, researchers have used microarrays to characterize global regulation of gene expression and algorithmic approaches to detect cycling. This article presents a new algorithm, JTK_CYCLE, designed to efficiently identify and characterize cycling variables in large data sets. Compared with COSOPT and the Fisher’s G test, two commonly used methods for detecting cycling transcripts, JTK_CYCLE distinguishes between rhythmic and nonrhythmic transcripts more reliably and efficiently. JTK_CYCLE’s increased resistance to outliers results in considerably greater sensitivity and specificity. Moreover, JTK_CYCLE accurately measures the period, phase, and amplitude of cycling transcripts, facilitating downstream analyses. Finally, JTK_CYCLE is several orders of magnitude faster than COSOPT, making it ideal for large-scale data sets. JTK_CYCLE was used to analyze legacy data sets including NIH3T3 cells, which have comparatively low amplitude oscillations. JTK_CYCLE’s improved power led to the identification of a novel cluster of RNA-interacting genes whose abundance is under clear circadian regulation. These data suggest that JTK_CYCLE is an ideal tool for identifying and characterizing oscillations in genome-scale data sets.

Chipping away at the chip bias: RNA degradation in microarray analysis

Measurement of gene expression is based on the assumption that an analyzed RNA sample closely represents the amount of transcripts in vivo. Transcripts show stability differences of up to two orders of magnitude in vivo1, raising the possibility that partial degradation during cell lysis could cause a variable extent of bias in quantification of different transcripts. One of the most effective tools for characterizing RNA integrity is capillary electrophoresis, in which RNA degradation is indicated by an altered 28S/18S rRNA signal ratio2. In the software of the commonly used system (Bioanalyzer 2100, Agilent), quantification of 18S and 28S rRNA is compromised by the fact that this calculation is based on area measurements that are heavily dependent on definitions of start and end points of peaks (Fig. 1a). Even accurate determination of this ratio is not sufficient to detect degradation efficiently (Fig. 1b). We developed a mathematical model that results in an objective number for quantitative characterization of RNA degradation. Aside from three prominent peaks (small RNAs, 18S and 28S rRNA), a chromatogram of the size distribution of cellular RNAs shows a broad range of molecular weights with much weaker signals. With increasing degradation, heights of 18S and 28S peaks gradually decrease and additional ‘degradation peak signals’ appear in a molecular weight range between small RNAs and the 18S peak (Fig. 1b). The ratio of the average degradation peak signal to the 18S peak signal multiplied by 100 will hereafter be referred to as the degradation factor. This analysis has been tested on 19 tissues of seven organisms, and it is a reproducible parameter for degradation of mammalian RNA (Supplementary Table 1 online). As an example, 12 repeated measurements of the same sample yielded an average degradation factor of 27.14 with a standard deviation of 1.06. Degradometer software for calculation of the degradation factor can be downloaded from http://www.dnaarrays.org. If one RNA sample was intact and the other was degraded during isolation, up to three-quarters of the differential gene expression measured was due solely to differences in RNA integrity between two samples (Fig. 1d). Supplementary Figure 1 online shows changes in mRNA levels caused by alteration of RNA integrity. This effect was independent of the algorithm applied to raw data analysis (Supplementary Tables 2, 3 and 4 online). For GAPD and ACTB, two transcripts for which signal intensities from 3′ and 5′ portions are frequently measured in microarray analysis, there is a positive correlation between the 3′/5′ ratio and the degradation factor of samples (Fig. 1c). This correlation is tissue-dependent (Supplementary Fig. 2 online).The smaller the difference in degradation factors between samples, the more closely the measured expression differences reflect biological differences (Fig. 1d). Aside from general RNase activity by members of the RNase A family3, RNase L, an enzyme activated in apoptotic Chipping away at the chip bias: RNA degradation in microarray analysis C O R R E S P O N D E N C E

Synergistic function of E2F7 and E2F8 is essential for cell survival and embryonic development.

The E2f7 and E2f8 family members are thought to function as transcriptional repressors important for the control of cell proliferation. Here, we have analyzed the consequences of inactivating E2f7 and E2f8 in mice and show that their individual loss had no significant effect on development. Their combined ablation, however, resulted in massive apoptosis and dilation of blood vessels, culminating in lethality by embryonic day E11.5. A deficiency in E2f7 and E2f8 led to an increase in E2f1 and p53, as well as in many stress-related genes. Homo- and heterodimers of E2F7 and E2F8 were found on target promoters, including E2f1. Importantly, loss of either E2f1 or p53 suppressed the massive apoptosis in double-mutant embryos. These results identify E2F7 and E2F8 as a unique repressive arm of the E2F transcriptional network that is critical for embryonic development and control of the E2F1-p53 apoptotic axis.

Excitatory/Inhibitory Synaptic Imbalance Leads to Hippocampal Hyperexcitability in Mouse Models of Tuberous Sclerosis

Neural circuits are regulated by activity-dependent feedback systems that tightly control network excitability and which are thought to be crucial for proper brain development. Defects in the ability to establish and maintain network homeostasis may be central to the pathogenesis of neurodevelopmental disorders. Here, we examine the function of the tuberous sclerosis complex (TSC)-mTOR signaling pathway, a common target of mutations associated with epilepsy and autism spectrum disorder, in regulating activity-dependent processes in the mouse hippocampus. We find that the TSC-mTOR pathway is a central component of a positive feedback loop that promotes network activity by repressing inhibitory synapses onto excitatory neurons. In Tsc1 KO neurons, weakened inhibition caused by deregulated mTOR alters the balance of excitatory and inhibitory synaptic transmission, leading to hippocampal hyperexcitability. These findings identify the TSC-mTOR pathway as a regulator of neural network activity and have implications for the neurological dysfunction in disorders exhibiting deregulated mTOR signaling.

RNA-Seq and molecular docking reveal multi-level pesticide resistance in the bed bug

BackgroundBed bugs (Cimex lectularius) are hematophagous nocturnal parasites of humans that have attained high impact status due to their worldwide resurgence. The sudden and rampant resurgence of C. lectularius has been attributed to numerous factors including frequent international travel, narrower pest management practices, and insecticide resistance.ResultsWe performed a next-generation RNA sequencing (RNA-Seq) experiment to find differentially expressed genes between pesticide-resistant (PR) and pesticide-susceptible (PS) strains of C. lectularius. A reference transcriptome database of 51,492 expressed sequence tags (ESTs) was created by combining the databases derived from de novo assembled mRNA-Seq tags (30,404 ESTs) and our previous 454 pyrosequenced database (21,088 ESTs). The two-way GLMseq analysis revealed ~15,000 highly significant differentially expressed ESTs between the PR and PS strains. Among the top 5,000 differentially expressed ESTs, 109 putative defense genes (cuticular proteins, cytochrome P450s, antioxidant genes, ABC transporters, glutathione S-transferases, carboxylesterases and acetyl cholinesterase) involved in penetration resistance and metabolic resistance were identified. Tissue and development-specific expression of P450 CYP3 clan members showed high mRNA levels in the cuticle, Malpighian tubules, and midgut; and in early instar nymphs, respectively. Lastly, molecular modeling and docking of a candidate cytochrome P450 (CYP397A1V2) revealed the flexibility of the deduced protein to metabolize a broad range of insecticide substrates including DDT, deltamethrin, permethrin, and imidacloprid.ConclusionsWe developed significant molecular resources for C. lectularius putatively involved in metabolic resistance as well as those participating in other modes of insecticide resistance. RNA-Seq profiles of PR strains combined with tissue-specific profiles and molecular docking revealed multi-level insecticide resistance in C. lectularius. Future research that is targeted towards RNA interference (RNAi) on the identified metabolic targets such as cytochrome P450s and cuticular proteins could lay the foundation for a better understanding of the genetic basis of insecticide resistance in C. lectularius.

HOXB4's road map to stem cell expansion

Homeodomain-containing transcription factors are important regulators of stem cell behavior. HOXB4 mediates expansion of adult and embryo-derived hematopoietic stem cells (HSCs) when expressed ectopically. To define the underlying molecular mechanisms, we performed gene expression profiling in combination with subsequent functional analysis with enriched adult HSCs and embryonic derivatives expressing inducible HOXB4. Thereby, we identified a set of overlapping genes that likely represent “universal” targets of HOXB4. A substantial number of loci are involved in signaling pathways important for controlling self-renewal, maintenance, and differentiation of stem cells. Functional assays performed on selected pathways confirmed the biological coherence of the array results. HOXB4 activity protected adult HSCs from the detrimental effects mediated by the proinflammatory cytokine TNF-α. This protection likely contributes to the competitive repopulation advantage of HOXB4-expressing HSCs observed in vivo. The concept of TNF-α inhibition may also prove beneficial for patients undergoing bone marrow transplantation. Furthermore, we demonstrate that HOXB4 activity and FGF signaling are intertwined. HOXB4-mediated expansion of adult and ES cell-derived HSCs was enhanced by specific and complete inhibition of FGF receptors. In contrast, the expanding activity of HOXB4 on hematopoietic progenitors in day 4–6 embryoid bodies was blunted in the presence of basic FGF (FGF2), indicating a dominant negative effect of FGF signaling on the earliest hematopoietic cells. In summary, our results strongly suggest that HOXB4 modulates the response of HSCs to multiple extrinsic signals in a concerted manner, thereby shifting the balance toward stem cell self-renewal.

Accurate quantification of DNA methylation using combined bisulfite restriction analysis coupled with the Agilent 2100 Bioanalyzer platform

DNA methylation is the best-studied epigenetic modification and describes the conversion of cytosine to 5-methylcytosine. The importance of this phenomenon is that aberrant promoter hypermethylation is a common occurrence in cancer and is frequently associated with gene silencing. Various techniques are currently available for the analysis of DNA methylation. However, accurate and reproducible quantification of DNA methylation remains challenging. In this report, we describe Bio-COBRA (combined bisulfite restriction analysis coupled with the Agilent 2100 Bioanalyzer platform), as a novel approach to quantitative DNA methylation analysis. The combination of a well-established method, COBRA, which interrogates DNA methylation via the restriction enzyme analysis of PCR-amplified bisulfite treated DNAs, with the Bioanalyzer platform allows for the rapid and quantitative assessment of DNA methylation patterns in large sample sets. The sensitivity and reproducibility of Bio-COBRA make it a valuable tool for the analysis of DNA methylation in clinical samples, which could aid in the development of diagnostic and prognostic parameters with respect to disease detection and management.

Accurate Expression Profiling of Very Small Cell Populations

Background Expression profiling, the measurement of all transcripts of a cell or tissue type, is currently the most comprehensive method to describe their physiological states. Given that accurate profiling methods currently available require RNA amounts found in thousands to millions of cells, many fields of biology working with specialized cell types cannot use these techniques because available cell numbers are limited. Currently available alternative methods for expression profiling from nanograms of RNA or from very small cell populations lack a broad validation of results to provide accurate information about the measured transcripts. Methods and Findings We provide evidence that currently available methods for expression profiling of very small cell populations are prone to technical noise and therefore cannot be used efficiently as discovery tools. Furthermore, we present Pico Profiling, a new expression profiling method from as few as ten cells, and we show that this approach is as informative as standard techniques from thousands to millions of cells. The central component of Pico Profiling is Whole Transcriptome Amplification (WTA), which generates expression profiles that are highly comparable to those produced by others, at different times, by standard protocols or by Real-time PCR. We provide a complete workflow from RNA isolation to analysis of expression profiles. Conclusions Pico Profiling, as presented here, allows generating an accurate expression profile from cell populations as small as ten cells.

DNA copy number gains in head and neck squamous cell carcinoma

Gene amplification, a common mechanism for oncogene activation in cancer, has been used as a tag for the identification of novel oncogenes. DNA amplification is frequently observed in head and neck squamous cell carcinoma (HNSCC) and potential oncogenes have already been reported. We applied restriction landmark genome scanning (RLGS) to study gene amplifications and low-level copy number changes in HNSCC in order to locate previously uncharacterized regions with copy number gains in primary tumor samples. A total of 63 enhanced RLGS fragments, indicative of DNA copy number changes, including gains of single alleles, were scored. Enhanced sequences were identified from 33 different chromosomal regions including those previously reported (e.g. 3q26.3 and 11q13.3) as well as novel regions (e.g. 3q29, 8q13.1, 8q22.3, 9q32, 10q24.32, 14q32.32, 17q25.1 and 20q13.33). Furthermore, our data suggest that amplicons 11q13.3 and 3q26.3–q29 may be divided into possibly two and three independent amplicons, respectively, an observation supported by published microarray expression data.